JordanSwindenLibraryLibrary "JordanSwindenLibrary"
TODO: add library description here
getDecimals()
Calculates how many decimals are on the quote price of the current market
Returns: The current decimal places on the market quote price
getPipSize(multiplier)
Calculates the pip size of the current market
Parameters:
multiplier (int) : The mintick point multiplier (1 by default, 10 for FX/Crypto/CFD but can be used to override when certain markets require)
Returns: The pip size for the current market
truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places
Parameters:
number (float) : The number to truncate
decimalPlaces (simple float) : (default=2) The number of decimal places to truncate to
Returns: The given number truncated to the given decimalPlaces
toWhole(number)
Converts pips into whole numbers
Parameters:
number (float) : The pip number to convert into a whole number
Returns: The converted number
toPips(number)
Converts whole numbers back into pips
Parameters:
number (float) : The whole number to convert into pips
Returns: The converted number
getPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period
Parameters:
value1 (float) : The first value to reference
value2 (float) : The second value to reference
lookback (int) : The lookback period to analyze
Returns: The percent change over the two values and lookback period
random(minRange, maxRange)
Wichmann–Hill Pseudo-Random Number Generator
Parameters:
minRange (float) : The smallest possible number (default: 0)
maxRange (float) : The largest possible number (default: 1)
Returns: A random number between minRange and maxRange
bullFib(priceLow, priceHigh, fibRatio)
Calculates a bullish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
bearFib(priceLow, priceHigh, fibRatio)
Calculates a bearish fibonacci value
Parameters:
priceLow (float) : The lowest price point
priceHigh (float) : The highest price point
fibRatio (float) : The fibonacci % ratio to calculate
Returns: The fibonacci value of the given ratio between the two price points
getMA(length, maType)
Gets a Moving Average based on type (! MUST BE CALLED ON EVERY TICK TO BE ACCURATE, don't place in scopes)
Parameters:
length (simple int) : The MA period
maType (string) : The type of MA
Returns: A moving average with the given parameters
barsAboveMA(lookback, ma)
Counts how many candles are above the MA
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to check
Returns: The bar count of how many recent bars are above the MA
barsBelowMA(lookback, ma)
Counts how many candles are below the MA
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to reference
Returns: The bar count of how many recent bars are below the EMA
barsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently (based on closing prices)
Parameters:
lookback (int) : The lookback period to look back over
ma (float) : The moving average to reference
Returns: The bar count of how many times price recently crossed the EMA (based on closing prices)
getPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count)
Parameters:
lookback (int) : The lookback period to look back over
direction (int) : The color of the bar to count (1 = Green, -1 = Red)
Returns: The bar count of how many candles have retraced over the given lookback & direction
getBodySize()
Gets the current candle's body size (in POINTS, divide by 10 to get pips)
Returns: The current candle's body size in POINTS
getTopWickSize()
Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's top wick size in POINTS
getBottomWickSize()
Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's bottom wick size in POINTS
getBodyPercent()
Gets the current candle's body size as a percentage of its entire size including its wicks
Returns: The current candle's body size percentage
isHammer(fib, colorMatch)
Checks if the current bar is a hammer candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=false) Does the candle need to be green? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a hammer candle
isStar(fib, colorMatch)
Checks if the current bar is a shooting star candle based on the given parameters
Parameters:
fib (float) : (default=0.382) The fib to base candle body on
colorMatch (bool) : (default=false) Does the candle need to be red? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a shooting star candle
isDoji(wickSize, bodySize)
Checks if the current bar is a doji candle based on the given parameters
Parameters:
wickSize (float) : (default=2) The maximum top wick size compared to the bottom (and vice versa)
bodySize (float) : (default=0.05) The maximum body size as a percentage compared to the entire candle size
Returns: A boolean - true if the current bar matches the requirements of a doji candle
isBullishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bullish engulfing candle
Parameters:
allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage
engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle
isBearishEC(allowance, rejectionWickSize, engulfWick)
Checks if the current bar is a bearish engulfing candle
Parameters:
allowance (float) : (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
rejectionWickSize (float) : (default=disabled) The maximum rejection wick size compared to the body as a percentage
engulfWick (bool) : (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle
isInsideBar()
Detects inside bars
Returns: Returns true if the current bar is an inside bar
isOutsideBar()
Detects outside bars
Returns: Returns true if the current bar is an outside bar
barInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session
Parameters:
sess (simple string) : The session to check
useFilter (bool) : (default=true) Whether or not to actually use this filter
Returns: A boolean - true if the current bar falls within the given time session
barOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session
Parameters:
sess (simple string) : The session to check
useFilter (bool) : (default=true) Whether or not to actually use this filter
Returns: A boolean - true if the current bar falls outside the given time session
dateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range
Parameters:
startTime (int) : The UNIX date timestamp to begin searching from
endTime (int) : the UNIX date timestamp to stop searching from
Returns: A boolean - true if the current bar falls within the given dates
dayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze
Parameters:
monday (bool) : Should the script analyze this day? (true/false)
tuesday (bool) : Should the script analyze this day? (true/false)
wednesday (bool) : Should the script analyze this day? (true/false)
thursday (bool) : Should the script analyze this day? (true/false)
friday (bool) : Should the script analyze this day? (true/false)
saturday (bool) : Should the script analyze this day? (true/false)
sunday (bool) : Should the script analyze this day? (true/false)
Returns: A boolean - true if the current bar's day is one of the given days
atrFilter(atrValue, maxSize)
Parameters:
atrValue (float)
maxSize (float)
tradeCount()
Calculate total trade count
Returns: Total closed trade count
isLong()
Check if we're currently in a long trade
Returns: True if our position size is positive
isShort()
Check if we're currently in a short trade
Returns: True if our position size is negative
isFlat()
Check if we're currentlyflat
Returns: True if our position size is zero
wonTrade()
Check if this bar falls after a winning trade
Returns: True if we just won a trade
lostTrade()
Check if this bar falls after a losing trade
Returns: True if we just lost a trade
maxDrawdownRealized()
Gets the max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).
Returns: The max drawdown based on closed trades (ie. realized P&L). The strategy tester displays max drawdown as open P&L (unrealized).
totalPipReturn()
Gets the total amount of pips won/lost (as a whole number)
Returns: Total amount of pips won/lost (as a whole number)
longWinCount()
Count how many winning long trades we've had
Returns: Long win count
shortWinCount()
Count how many winning short trades we've had
Returns: Short win count
longLossCount()
Count how many losing long trades we've had
Returns: Long loss count
shortLossCount()
Count how many losing short trades we've had
Returns: Short loss count
breakEvenCount(allowanceTicks)
Count how many break-even trades we've had
Parameters:
allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)
Returns: Break-even count
longCount()
Count how many long trades we've taken
Returns: Long trade count
shortCount()
Count how many short trades we've taken
Returns: Short trade count
longWinPercent()
Calculate win rate of long trades
Returns: Long win rate (0-100)
shortWinPercent()
Calculate win rate of short trades
Returns: Short win rate (0-100)
breakEvenPercent(allowanceTicks)
Calculate break even rate of all trades
Parameters:
allowanceTicks (float) : Optional - how many ticks to allow between entry & exit price (default 0)
Returns: Break-even win rate (0-100)
averageRR()
Calculate average risk:reward
Returns: Average winning trade divided by average losing trade
unitsToLots(units)
(Forex) Convert the given unit count to lots (multiples of 100,000)
Parameters:
units (float) : The units to convert into lots
Returns: Units converted to nearest lot size (as float)
getFxPositionSize(balance, risk, stopLossPips, fxRate, lots)
(Forex) Calculate fixed-fractional position size based on given parameters
Parameters:
balance (float) : The account balance
risk (float) : The % risk (whole number)
stopLossPips (float) : Pip distance to base risk on
fxRate (float) : The conversion currency rate (more info below in library documentation)
lots (bool) : Whether or not to return the position size in lots rather than units (true by default)
Returns: Units/lots to enter into "qty=" parameter of strategy entry function
EXAMPLE USAGE:
string conversionCurrencyPair = (strategy.account_currency == syminfo.currency ? syminfo.tickerid : strategy.account_currency + syminfo.currency)
float fx_rate = request.security(conversionCurrencyPair, timeframe.period, close )
if (longCondition)
strategy.entry("Long", strategy.long, qty=zen.getFxPositionSize(strategy.equity, 1, stopLossPipsWholeNumber, fx_rate, true))
skipTradeMonteCarlo(chance, debug)
Checks to see if trade should be skipped to emulate rudimentary Monte Carlo simulation
Parameters:
chance (float) : The chance to skip a trade (0-1 or 0-100, function will normalize to 0-1)
debug (bool) : Whether or not to display a label informing of the trade skip
Returns: True if the trade is skipped, false if it's not skipped (idea being to include this function in entry condition validation checks)
fillCell(tableID, column, row, title, value, bgcolor, txtcolor, tooltip)
This updates the given table's cell with the given values
Parameters:
tableID (table) : The table ID to update
column (int) : The column to update
row (int) : The row to update
title (string) : The title of this cell
value (string) : The value of this cell
bgcolor (color) : The background color of this cell
txtcolor (color) : The text color of this cell
tooltip (string)
Returns: Nothing.
"bar"に関するスクリプトを検索
Auto Volume Spread Analysis (VSA) [TANHEF]Auto Volume Spread Analysis (visible volume and spread bars auto-scaled): Understanding Market Intentions through the Interpretation of Volume and Price Movements.
All the sections below contain the same descriptions as my other indicator "Volume Spread Analysis" with the exception of 'Auto Scaling'.
█ Auto-Scaling
This indicator auto-scales spread bars to match the visible volume bars, unlike the previous "Volume Spread Analysis " version which limited the number of visible spread bars to a fixed count. The auto-scaling feature allows for easier navigation through historical data, enabling both more historical spread bars to be viewed and more historical VSA pattern labels being displayed without requiring using the bar replay tool. Please note that this indicator’s auto-scaling feature recalculates the visible bars on the chart, causing the indicator to reload whenever the chart is moved.
Auto-scaled spread bars have two display options (set via 'Spread Bars Method' setting):
Lines: a bar lookback limit of 500 bars.
Polylines: no bar lookback limit as only plotted on visible bars on chart, which uses multiple polylines are used.
█ Simple Explanation:
The Volume Spread Analysis (VSA) indicator is a comprehensive tool that helps traders identify key market patterns and trends based on volume and spread data. This indicator highlights significant VSA patterns and provides insights into market behavior through color-coded volume/spread bars and identification of bars indicating strength, weakness, and neutrality between buyers and sellers. It also includes powerful volume and spread forecasting capabilities.
█ Laws of Volume Spread Analysis (VSA):
The origin of VSA begins with Richard Wyckoff, a pivotal figure in its development. Wyckoff made significant contributions to trading theory, including the formulation of three basic laws:
The Law of Supply and Demand: This fundamental law states that supply and demand balance each other over time. High demand and low supply lead to rising prices until demand falls to a level where supply can meet it. Conversely, low demand and high supply cause prices to fall until demand increases enough to absorb the excess supply.
The Law of Cause and Effect: This law assumes that a 'cause' will result in an 'effect' proportional to the 'cause'. A strong 'cause' will lead to a strong trend (effect), while a weak 'cause' will lead to a weak trend.
The Law of Effort vs. Result: This law asserts that the result should reflect the effort exerted. In trading terms, a large volume should result in a significant price move (spread). If the spread is small, the volume should also be small. Any deviation from this pattern is considered an anomaly.
█ Volume and Spread Analysis Bars:
Display: Volume and spread bars that consist of color coded levels, with the spread bars scaled to match the volume bars. A displayable table (Legend) of bar colors and levels can give context and clarify to each volume/spread bar.
Calculation: Levels are calculated using multipliers applied to moving averages to represent key levels based on historical data: low, normal, high, ultra. This method smooths out short-term fluctuations and focuses on longer-term trends.
Low Level: Indicates reduced volatility and market interest.
Normal Level: Reflects typical market activity and volatility.
High Level: Indicates increased activity and volatility.
Ultra Level: Identifies extreme levels of activity and volatility.
This illustrates the appearance of Volume and Spread bars when scaled and plotted together:
█ Forecasting Capabilities:
Display: Forecasted volume and spread levels using predictive models.
Calculation: Volume and Spread prediction calculations differ as volume is linear and spread is non-linear.
Volume Forecast (Linear Forecasting): Predicts future volume based on current volume rate and bar time till close.
Spread Forecast (Non-Linear Dynamic Forecasting): Predicts future spread using a dynamic multiplier, less near midpoint (consolidation) and more near low or high (trending), reflecting non-linear expansion.
Moving Averages: In forecasting, moving averages utilize forecasted levels instead of actual levels to ensure the correct level is forecasted (low, normal, high, or ultra).
The following compares forecasted volume with actual resulting volume, highlighting the power of early identifying increased volume through forecasted levels:
█ VSA Patterns:
Criteria and descriptions for each VSA pattern are available as tooltips beside them within the indicator’s settings. These tooltips provide explanations of potential developments based on the volume and spread data.
Signs of Strength (🟢): Patterns indicating strong buying pressure and potential market upturns.
Down Thrust
Selling Climax
No Effort ➤ Bearish Result
Bearish Effort ➤ No Result
Inverse Down Thrust
Failed Selling Climax
Bull Outside Reversal
End of Falling Market (Bag Holder)
Pseudo Down Thrust
No Supply
Signs of Weakness (🔴): Patterns indicating strong selling pressure and potential market downturns.
Up Thrust
Buying Climax
No Effort ➤ Bullish Result
Bullish Effort ➤ No Result
Inverse Up Thrust
Failed Buying Climax
Bear Outside Reversal
End of Rising Market (Bag Seller)
Pseudo Up Thrust
No Demand
Neutral Patterns (🔵): Patterns indicating market indecision and potential for continuation or reversal.
Quiet Doji
Balanced Doji
Strong Doji
Quiet Spinning Top
Balanced Spinning Top
Strong Spinning Top
Quiet High Wave
Balanced High Wave
Strong High Wave
Consolidation
Bar Patterns (🟡): Common candlestick patterns that offer insights into market sentiment. These are required in some VSA patterns and can also be displayed independently.
Bull Pin Bar
Bear Pin Bar
Doji
Spinning Top
High Wave
Consolidation
This demonstrates the acronym and descriptive options for displaying bar patterns, with the ability to hover over text to reveal the descriptive text along with what type of pattern:
█ Alerts:
VSA Pattern Alerts: Notifications for identified VSA patterns at bar close.
Volume and Spread Alerts: Alerts for confirmed and forecasted volume/spread levels (Low, High, Ultra).
Forecasted Volume and Spread Alerts: Alerts for forecasted volume/spread levels (High, Ultra) include a minimum percent time elapsed input to reduce false early signals by ensuring sufficient bar time has passed.
█ Inputs and Settings:
Indicator Bar Color: Select color schemes for bars (Normal, Detail, Levels).
Indicator Moving Average Color: Select schemes for bars (Fill, Lines, None).
Price Bar Colors: Options to color price bars based on VSA patterns and volume levels.
Legend: Display a table of bar colors and levels for context and clarity of volume/spread bars.
Forecast: Configure forecast display and prediction details for volume and spread.
Average Multipliers: Define multipliers for different levels (Low, High, Ultra) to refine the analysis.
Moving Average: Set volume and spread moving average settings.
VSA: Select the VSA patterns to be calculated and displayed (Strength, Weakness, Neutral).
Bar Patterns: Criteria for bar patterns used in VSA (Doji, Bull Pin Bar, Bear Pin Bar, Spinning Top, Consolidation, High Wave).
Colors: Set exact colors used for indicator bars, indicator moving averages, and price bars.
More Display Options: Specify how VSA pattern text is displayed (Acronym, Descriptive), positioning, and sizes.
Alerts: Configure alerts for VSA patterns, volume, and spread levels, including forecasted levels.
█ Usage:
The Volume Spread Analysis indicator is a helpful tool for leveraging volume spread analysis to make informed trading decisions. It offers comprehensive visual and textual cues on the chart, making it easier to identify market conditions, potential reversals, and continuations. Whether analyzing historical data or forecasting future trends, this indicator provides insights into the underlying factors driving market movements.
CandleAnalysisLibrary "CandleAnalysis"
A collection of frequently used candle analysis functions in my scripts.
isBullish(barsBack)
Checks if a specific bar is bullish.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is bullish, otherwise returns false.
isBearish(barsBack)
Checks if a specific bar is bearish.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is bearish, otherwise returns false.
isBE(barsBack)
Checks if a specific bar is break even.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is break even, otherwise returns false.
getBodySize(barsBack, inPriceChg)
Calculates a specific candle's body size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the body size as a price change value. The default is false (in points).
Returns: The candle's body size in points.
getTopWickSize(barsBack, inPriceChg)
Calculates a specific candle's top wick size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).
Returns: The candle's top wick size in points.
getBottomWickSize(barsBack, inPriceChg)
Calculates a specific candle's bottom wick size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).
Returns: The candle's bottom wick size in points.
getBodyPercent(barsBack)
Calculates a specific candle's body size as a percentage of its entire size including its wicks.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: The candle's body size percentage.
isHammer(fib, bullish, barsBack)
Checks if a specific bar is a hammer candle based on a given fibonacci level.
Parameters:
fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.
bullish (bool) : (bool) True if the candle must to be green. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a hammer candle, otherwise returns false.
isShootingStar(fib, bearish, barsBack)
Checks if a specific bar is a shooting star candle based on a given fibonacci level.
Parameters:
fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.
bearish (bool) : (bool) True if the candle must to be red. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a shooting star candle, otherwise returns false.
isDoji(wickSize, bodySize, barsBack)
Checks if a specific bar is a doji candle based on a given wick and body size.
Parameters:
wickSize (float) : (float) The maximum top wick size compared to the bottom and vice versa. The default is 1.5.
bodySize (float) : (bool) The maximum body size as a percentage compared to the entire candle size. The default is 5.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a doji candle.
isBullishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)
Checks if a specific bar is a bullish engulfing candle.
Parameters:
gapTolerance (int)
rejectionWickSize (int) : (int) The maximum top wick size compared to the body as a percentage. The default is 10.
engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a bullish engulfing candle.
isBearishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)
Checks if a specific bar is a bearish engulfing candle.
Parameters:
gapTolerance (int)
rejectionWickSize (int) : (int) The maximum bottom wick size compared to the body as a percentage. The default is 10.
engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a bearish engulfing candle.
MarcosLibraryLibrary "MarcosLibrary"
A colection of frequently used functions in my scripts.
bullFibRet(priceLow, priceHigh, fibLevel)
Calculates a bullish fibonacci retracement value.
Parameters:
priceLow (float) : (float) The lowest price point.
priceHigh (float) : (float) The highest price point.
fibLevel (float) : (float) The fibonacci level to calculate.
Returns: The fibonacci value of the given retracement level.
bearFibRet(priceLow, priceHigh, fibLevel)
Calculates a bearish fibonacci retracement value.
Parameters:
priceLow (float) : (float) The lowest price point.
priceHigh (float) : (float) The highest price point.
fibLevel (float) : (float) The fibonacci level to calculate.
Returns: The fibonacci value of the given retracement level.
bullFibExt(priceLow, priceHigh, thirdPivot, fibLevel)
Calculates a bullish fibonacci extension value.
Parameters:
priceLow (float) : (float) The lowest price point.
priceHigh (float) : (float) The highest price point.
thirdPivot (float) : (float) The third price point.
fibLevel (float) : (float) The fibonacci level to calculate.
Returns: The fibonacci value of the given extension level.
bearFibExt(priceLow, priceHigh, thirdPivot, fibLevel)
Calculates a bearish fibonacci extension value.
Parameters:
priceLow (float) : (float) The lowest price point.
priceHigh (float) : (float) The highest price point.
thirdPivot (float) : (float) The third price point.
fibLevel (float) : (float) The fibonacci level to calculate.
Returns: The fibonacci value of the given extension level.
isBullish(barsBack)
Checks if a specific bar is bullish.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is bullish, otherwise returns false.
isBearish(barsBack)
Checks if a specific bar is bearish.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is bearish, otherwise returns false.
isBE(barsBack)
Checks if a specific bar is break even.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar is break even, otherwise returns false.
getBodySize(barsBack, inPriceChg)
Calculates a specific candle's body size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the body size as a price change value. The default is false (in points).
Returns: The candle's body size in points.
getTopWickSize(barsBack, inPriceChg)
Calculates a specific candle's top wick size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).
Returns: The candle's top wick size in points.
getBottomWickSize(barsBack, inPriceChg)
Calculates a specific candle's bottom wick size.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
inPriceChg (bool) : (bool) True to return the wick size as a price change value. The default is false (in points).
Returns: The candle's bottom wick size in points.
getBodyPercent(barsBack)
Calculates a specific candle's body size as a percentage of its entire size including its wicks.
Parameters:
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: The candle's body size percentage.
isHammer(fib, bullish, barsBack)
Checks if a specific bar is a hammer candle based on a given fibonacci level.
Parameters:
fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.
bullish (bool) : (bool) True if the candle must to be green. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a hammer candle, otherwise returns false.
isShootingStar(fib, bearish, barsBack)
Checks if a specific bar is a shooting star candle based on a given fibonacci level.
Parameters:
fib (float) : (float) The fibonacci level to base candle's body on. The default is 0.382.
bearish (bool) : (bool) True if the candle must to be red. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a shooting star candle, otherwise returns false.
isDoji(wickSize, bodySize, barsBack)
Checks if a specific bar is a doji candle based on a given wick and body size.
Parameters:
wickSize (float) : (float) The maximum top wick size compared to the bottom and vice versa. The default is 1.5.
bodySize (float) : (bool) The maximum body size as a percentage compared to the entire candle size. The default is 5.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a doji candle.
isBullishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)
Checks if a specific bar is a bullish engulfing candle.
Parameters:
gapTolerance (int)
rejectionWickSize (int) : (int) The maximum top wick size compared to the body as a percentage. The default is 10.
engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a bullish engulfing candle.
isBearishEC(gapTolerance, rejectionWickSize, engulfWick, barsBack)
Checks if a specific bar is a bearish engulfing candle.
Parameters:
gapTolerance (int)
rejectionWickSize (int) : (int) The maximum bottom wick size compared to the body as a percentage. The default is 10.
engulfWick (bool) : (bool) True if the engulfed candle's wick requires to be engulfed as well. The default is false.
barsBack (int) : (int) The number of bars to look back. The default is 0 (current bar).
Returns: True if the bar matches the requirements of a bearish engulfing candle.
CNTLibraryLibrary "CNTLibrary"
Custom Functions To Help Code In Pinescript V5
Coded By Christian Nataliano
First Coded In 10/06/2023
Last Edited In 22/06/2023
Huge Shout Out To © ZenAndTheArtOfTrading and his ZenLibrary V5, Some Of The Custom Functions Were Heavily Inspired By Matt's Work & His Pine Script Mastery Course
Another Shout Out To The TradingView's Team Library ta V5
//====================================================================================================================================================
// Custom Indicator Functions
//====================================================================================================================================================
GetKAMA(KAMA_lenght, Fast_KAMA, Slow_KAMA)
Calculates An Adaptive Moving Average Based On Perry J Kaufman's Calculations
Parameters:
KAMA_lenght (int) : Is The KAMA Lenght
Fast_KAMA (int) : Is The KAMA's Fastes Moving Average
Slow_KAMA (int) : Is The KAMA's Slowest Moving Average
Returns: Float Of The KAMA's Current Calculations
GetMovingAverage(Source, Lenght, Type)
Get Custom Moving Averages Values
Parameters:
Source (float) : Of The Moving Average, Defval = close
Lenght (simple int) : Of The Moving Average, Defval = 50
Type (string) : Of The Moving Average, Defval = Exponential Moving Average
Returns: The Moving Average Calculation Based On Its Given Source, Lenght & Calculation Type (Please Call Function On Global Scope)
GetDecimals()
Calculates how many decimals are on the quote price of the current market © ZenAndTheArtOfTrading
Returns: The current decimal places on the market quote price
Truncate(number, decimalPlaces)
Truncates (cuts) excess decimal places © ZenAndTheArtOfTrading
Parameters:
number (float)
decimalPlaces (simple float)
Returns: The given number truncated to the given decimalPlaces
ToWhole(number)
Converts pips into whole numbers © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
ToPips(number)
Converts whole numbers back into pips © ZenAndTheArtOfTrading
Parameters:
number (float)
Returns: The converted number
GetPctChange(value1, value2, lookback)
Gets the percentage change between 2 float values over a given lookback period © ZenAndTheArtOfTrading
Parameters:
value1 (float)
value2 (float)
lookback (int)
BarsAboveMA(lookback, ma)
Counts how many candles are above the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are above the MA
BarsBelowMA(lookback, ma)
Counts how many candles are below the MA © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many recent bars are below the EMA
BarsCrossedMA(lookback, ma)
Counts how many times the EMA was crossed recently © ZenAndTheArtOfTrading
Parameters:
lookback (int)
ma (float)
Returns: The bar count of how many times price recently crossed the EMA
GetPullbackBarCount(lookback, direction)
Counts how many green & red bars have printed recently (ie. pullback count) © ZenAndTheArtOfTrading
Parameters:
lookback (int)
direction (int)
Returns: The bar count of how many candles have retraced over the given lookback & direction
GetSwingHigh(Lookback, SwingType)
Check If Price Has Made A Recent Swing High
Parameters:
Lookback (int) : Is For The Swing High Lookback Period, Defval = 7
SwingType (int) : Is For The Swing High Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing High
GetSwingLow(Lookback, SwingType)
Check If Price Has Made A Recent Swing Low
Parameters:
Lookback (int) : Is For The Swing Low Lookback Period, Defval = 7
SwingType (int) : Is For The Swing Low Type Of Identification, Defval = 1
Returns: A Bool - True If Price Has Made A Recent Swing Low
//====================================================================================================================================================
// Custom Risk Management Functions
//====================================================================================================================================================
CalculateStopLossLevel(OrderType, Entry, StopLoss)
Calculate StopLoss Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLoss (float) : Is The Custom StopLoss Distance, Defval = 2x ATR Below Close
Returns: Float - The StopLoss Level In Actual Price As A
CalculateStopLossDistance(OrderType, Entry, StopLoss)
Calculate StopLoss Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
StopLoss (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The StopLoss Value In Pips
CalculateTakeProfitLevel(OrderType, Entry, StopLossDistance, RiskReward)
Calculate TakeProfit Level
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, Defval = na
StopLossDistance (float)
RiskReward (float)
Returns: Float - The TakeProfit Level In Actual Price
CalculateTakeProfitDistance(OrderType, Entry, TakeProfit)
Get TakeProfit Distance In Pips
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
Entry (float) : Is The Entry Level Of The Order, NEED TO INPUT PARAM
TakeProfit (float) : Level Based On Previous Calculation, NEED TO INPUT PARAM
Returns: Float - The TakeProfit Value In Pips
CalculateConversionCurrency(AccountCurrency, SymbolCurrency, BaseCurrency)
Get The Conversion Currecny Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
AccountCurrency (simple string) : Is For The Account Currency Used
SymbolCurrency (simple string) : Is For The Current Symbol Currency (Front Symbol)
BaseCurrency (simple string) : Is For The Current Symbol Base Currency (Back Symbol)
Returns: Tuple Of A Bollean (Convert The Currency ?) And A String (Converted Currency)
CalculateConversionRate(ConvertCurrency, ConversionRate)
Get The Conversion Rate Between Current Account Currency & Current Pair's Quoted Currency (FOR FOREX ONLY)
Parameters:
ConvertCurrency (bool) : Is To Check If The Current Symbol Needs To Be Converted Or Not
ConversionRate (float) : Is The Quoted Price Of The Conversion Currency (Input The request.security Function Here)
Returns: Float Price Of Conversion Rate (If In The Same Currency Than Return Value Will Be 1.0)
LotSize(LotSizeSimple, Balance, Risk, SLDistance, ConversionRate)
Get Current Lot Size
Parameters:
LotSizeSimple (bool) : Is To Toggle Lot Sizing Calculation (Simple Is Good Enough For Stocks & Crypto, Whilst Complex Is For Forex)
Balance (float) : Is For The Current Account Balance To Calculate The Lot Sizing Based Off
Risk (float) : Is For The Current Risk Per Trade To Calculate The Lot Sizing Based Off
SLDistance (float) : Is The Current Position StopLoss Distance From Its Entry Price
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - Position Size In Units
ToLots(Units)
Converts Units To Lots
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots
ToUnits(Lots)
Converts Lots To Units
Parameters:
Lots (float) : Is For How Many Lots Need To Be Converted Into Units (Minimun 0.01 Units)
Returns: Int - Position Size In Units
ToLotsInUnits(Units)
Converts Units To Lots Than Back To Units
Parameters:
Units (float) : Is For How Many Units Need To Be Converted Into Lots (Minimun 1000 Units)
Returns: Float - Position Size In Lots That Were Rounded To Units
ATRTrail(OrderType, SourceType, ATRPeriod, ATRMultiplyer, SwingLookback)
Calculate ATR Trailing Stop
Parameters:
OrderType (int) : Is To Determine A Long / Short Position, Defval = 1
SourceType (int) : Is To Determine Where To Calculate The ATR Trailing From, Defval = close
ATRPeriod (simple int) : Is To Change Its ATR Period, Defval = 20
ATRMultiplyer (float) : Is To Change Its ATR Trailing Distance, Defval = 1
SwingLookback (int) : Is To Change Its Swing HiLo Lookback (Only From Source Type 5), Defval = 7
Returns: Float - Number Of The Current ATR Trailing
DangerZone(WinRate, AvgRRR, Filter)
Calculate Danger Zone Of A Given Strategy
Parameters:
WinRate (float) : Is The Strategy WinRate
AvgRRR (float) : Is The Strategy Avg RRR
Filter (float) : Is The Minimum Profit It Needs To Be Out Of BE Zone, Defval = 3
Returns: Int - Value, 1 If Out Of Danger Zone, 0 If BE, -1 If In Danger Zone
IsQuestionableTrades(TradeTP, TradeSL)
Checks For Questionable Trades (Which Are Trades That Its TP & SL Level Got Hit At The Same Candle)
Parameters:
TradeTP (float) : Is The Trade In Question Take Profit Level
TradeSL (float) : Is The Trade In Question Stop Loss Level
Returns: Bool - True If The Last Trade Was A "Questionable Trade"
//====================================================================================================================================================
// Custom Strategy Functions
//====================================================================================================================================================
OpenLong(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Long Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Long"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Long Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
OpenShort(EntryID, LotSize, LimitPrice, StopPrice, Comment, CommentValue)
Open A Short Order Based On The Given Params
Parameters:
EntryID (string) : Is The Trade Entry ID, Defval = "Short"
LotSize (float) : Is The Lot Size Of The Trade, Defval = 1
LimitPrice (float) : Is The Limit Order Price To Set The Order At, Defval = Na / Market Order Execution
StopPrice (float) : Is The Stop Order Price To Set The Order At, Defval = Na / Market Order Execution
Comment (string) : Is The Order Comment, Defval = Short Entry Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
TP_SLExit(FromID, TPLevel, SLLevel, PercentageClose, Comment, CommentValue)
Exits Based On Predetermined TP & SL Levels
Parameters:
FromID (string) : Is The Trade ID That The TP & SL Levels Be Palced
TPLevel (float) : Is The Take Profit Level
SLLevel (float) : Is The StopLoss Level
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Returns: Void
CloseLong(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Long Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Long"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
CloseShort(ExitID, PercentageClose, Comment, CommentValue, Instant)
Exits A Short Order Based On A Specified Condition
Parameters:
ExitID (string) : Is The Trade ID That Will Be Closed, Defval = "Short"
PercentageClose (float) : Is The Amount To Close The Order At (In Percentage) Defval = 100
Comment (string) : Is The Order Comment, Defval = Exit Order
CommentValue (string) : Is For Custom Values In The Order Comment, Defval = Na
Instant (bool) : Is For Exit Execution Type, Defval = false
Returns: Void
BrokerCheck(Broker)
Checks Traded Broker With Current Loaded Chart Broker
Parameters:
Broker (string) : Is The Current Broker That Is Traded
Returns: Bool - True If Current Traded Broker Is Same As Loaded Chart Broker
OpenPC(LicenseID, OrderType, UseLimit, LimitPrice, SymbolPrefix, Symbol, SymbolSuffix, Risk, SL, TP, OrderComment, Spread)
Compiles Given Parameters Into An Alert String Format To Open Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Open
UseLimit (bool) : Is If We Want To Enter The Position At Exactly The Previous Closing Price
LimitPrice (float) : Is The Limit Price Of The Trade (Only For Pending Orders)
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Risk (float) : Is The Trade Risk Per Trade / Fixed Lot Sizing
SL (float) : Is The Trade SL In Price / In Pips
TP (float) : Is The Trade TP In Price / In Pips
OrderComment (string) : Is The Executed Trade Comment
Spread (float) : is The Maximum Spread For Execution
Returns: String - Pine Connector Order Syntax Alert Message
ClosePC(LicenseID, OrderType, SymbolPrefix, Symbol, SymbolSuffix)
Compiles Given Parameters Into An Alert String Format To Close Trades Using Pine Connector
Parameters:
LicenseID (string) : Is The Users PineConnector LicenseID
OrderType (int) : Is The Desired OrderType To Close
SymbolPrefix (string) : Is The Current Symbol Prefix (If Any)
Symbol (string) : Is The Traded Symbol
SymbolSuffix (string) : Is The Current Symbol Suffix (If Any)
Returns: String - Pine Connector Order Syntax Alert Message
//====================================================================================================================================================
// Custom Backtesting Calculation Functions
//====================================================================================================================================================
CalculatePNL(EntryPrice, ExitPrice, LotSize, ConversionRate)
Calculates Trade PNL Based On Entry, Eixt & Lot Size
Parameters:
EntryPrice (float) : Is The Trade Entry
ExitPrice (float) : Is The Trade Exit
LotSize (float) : Is The Trade Sizing
ConversionRate (float) : Is The Currency Conversion Rate (Used For Complex Lot Sizing Only)
Returns: Float - The Current Trade PNL
UpdateBalance(PrevBalance, PNL)
Updates The Previous Ginve Balance To The Next PNL
Parameters:
PrevBalance (float) : Is The Previous Balance To Be Updated
PNL (float) : Is The Current Trade PNL To Be Added
Returns: Float - The Current Updated PNL
CalculateSlpComm(PNL, MaxRate)
Calculates Random Slippage & Commisions Fees Based On The Parameters
Parameters:
PNL (float) : Is The Current Trade PNL
MaxRate (float) : Is The Upper Limit (In Percentage) Of The Randomized Fee
Returns: Float - A Percentage Fee Of The Current Trade PNL
UpdateDD(MaxBalance, Balance)
Calculates & Updates The DD Based On Its Given Parameters
Parameters:
MaxBalance (float) : Is The Maximum Balance Ever Recorded
Balance (float) : Is The Current Account Balance
Returns: Float - The Current Strategy DD
CalculateWR(TotalTrades, LongID, ShortID)
Calculate The Total, Long & Short Trades Win Rate
Parameters:
TotalTrades (int) : Are The Current Total Trades That The Strategy Has Taken
LongID (string) : Is The Order ID Of The Long Trades Of The Strategy
ShortID (string) : Is The Order ID Of The Short Trades Of The Strategy
Returns: Tuple Of Long WR%, Short WR%, Total WR%, Total Winning Trades, Total Losing Trades, Total Long Trades & Total Short Trades
CalculateAvgRRR(WinTrades, LossTrades)
Calculates The Overall Strategy Avg Risk Reward Ratio
Parameters:
WinTrades (int) : Are The Strategy Winning Trades
LossTrades (int) : Are The Strategy Losing Trades
Returns: Float - The Average RRR Values
CAGR(StartTime, StartPrice, EndTime, EndPrice)
Calculates The CAGR Over The Given Time Period © TradingView
Parameters:
StartTime (int) : Is The Starting Time Of The Calculation
StartPrice (float) : Is The Starting Price Of The Calculation
EndTime (int) : Is The Ending Time Of The Calculation
EndPrice (float) : Is The Ending Price Of The Calculation
Returns: Float - The CAGR Values
//====================================================================================================================================================
// Custom Plot Functions
//====================================================================================================================================================
EditLabels(LabelID, X1, Y1, Text, Color, TextColor, EditCondition, DeleteCondition)
Edit / Delete Labels
Parameters:
LabelID (label) : Is The ID Of The Selected Label
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
Text (string) : Is The Text Than Wants To Be Written In The Label
Color (color) : Is The Color Value Change Of The Label Text
TextColor (color)
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
EditLine(LineID, X1, Y1, X2, Y2, Color, EditCondition, DeleteCondition)
Edit / Delete Lines
Parameters:
LineID (line) : Is The ID Of The Selected Line
X1 (int) : Is The X1 Coordinate IN BARINDEX Xloc
Y1 (float) : Is The Y1 Coordinate IN PRICE Yloc
X2 (int) : Is The X2 Coordinate IN BARINDEX Xloc
Y2 (float) : Is The Y2 Coordinate IN PRICE Yloc
Color (color) : Is The Color Value Change Of The Line
EditCondition (int) : Is The Edit Condition of The Line (Setting Location / Color)
DeleteCondition (bool) : Is The Delete Condition Of The Line If Ture Deletes The Prev Itteration Of The Line
Returns: Void
//====================================================================================================================================================
// Custom Display Functions (Using Tables)
//====================================================================================================================================================
FillTable(TableID, Column, Row, Title, Value, BgColor, TextColor, ToolTip)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
Column (int) : Is The Current Column Of The Table That Wants To Be Edited
Row (int) : Is The Current Row Of The Table That Wants To Be Edited
Title (string) : Is The String Title Of The Current Cell Table
Value (string) : Is The String Value Of The Current Cell Table
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
ToolTip (string) : Is The ToolTip Of The Current Cell In The Table
Returns: Void
DisplayBTResults(TableID, BgColor, TextColor, StartingBalance, Balance, DollarReturn, TotalPips, MaxDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
StartingBalance (float) : Is The Account Starting Balance
Balance (float)
DollarReturn (float) : Is The Account Dollar Reture
TotalPips (float) : Is The Total Pips Gained / loss
MaxDD (float) : Is The Maximum Drawdown Over The Backtesting Period
Returns: Void
DisplayBTResultsV2(TableID, BgColor, TextColor, TotalWR, QTCount, LongWR, ShortWR, InitialCapital, CumProfit, CumFee, AvgRRR, MaxDD, CAGR, MeanDD)
Filling The Selected Table With The Inputed Information
Parameters:
TableID (table) : Is The Table ID That Wants To Be Edited
BgColor (color) : Is The Selected Color For The Current Table
TextColor (color) : Is The Selected Color For The Current Table
TotalWR (float) : Is The Strategy Total WR In %
QTCount (int) : Is The Strategy Questionable Trades Count
LongWR (float) : Is The Strategy Total WR In %
ShortWR (float) : Is The Strategy Total WR In %
InitialCapital (float) : Is The Strategy Initial Starting Capital
CumProfit (float) : Is The Strategy Ending Cumulative Profit
CumFee (float) : Is The Strategy Ending Cumulative Fee (Based On Randomized Fee Assumptions)
AvgRRR (float) : Is The Strategy Average Risk Reward Ratio
MaxDD (float) : Is The Strategy Maximum DrawDown In Its Backtesting Period
CAGR (float) : Is The Strategy Compounded Average GRowth In %
MeanDD (float) : Is The Strategy Mean / Average Drawdown In The Backtesting Period
Returns: Void
//====================================================================================================================================================
// Custom Pattern Detection Functions
//====================================================================================================================================================
BullFib(priceLow, priceHigh, fibRatio)
Calculates A Bullish Fibonacci Value (From Swing Low To High) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
BearFib(priceLow, priceHigh, fibRatio)
Calculates A Bearish Fibonacci Value (From Swing High To Low) © ZenAndTheArtOfTrading
Parameters:
priceLow (float)
priceHigh (float)
fibRatio (float)
Returns: The Fibonacci Value Of The Given Ratio Between The Two Price Points
GetBodySize()
Gets The Current Candle Body Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN POINTS
GetTopWickSize()
Gets The Current Candle Top Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Top Wick Size IN POINTS
GetBottomWickSize()
Gets The Current Candle Bottom Wick Size IN POINTS © ZenAndTheArtOfTrading
Returns: The Current Candle Bottom Wick Size IN POINTS
GetBodyPercent()
Gets The Current Candle Body Size As A Percentage Of Its Entire Size Including Its Wicks © ZenAndTheArtOfTrading
Returns: The Current Candle Body Size IN PERCENTAGE
GetTopWickPercent()
Gets The Current Top Wick Size As A Percentage Of Its Entire Body Size
Returns: Float - The Current Candle Top Wick Size IN PERCENTAGE
GetBottomWickPercent()
Gets The Current Bottom Wick Size As A Percentage Of Its Entire Bodu Size
Returns: Float - The Current Candle Bottom Size IN PERCENTAGE
BullishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Engulfing Candle
BearishEC(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bearish Engulfing Candle
Parameters:
Allowance (int) : To Give Flexibility Of Engulfing Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Engulfing Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Engulfing Candle
Hammer(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Star(Fib, ColorMatch, NearSwings, SwingLookBack, ATRFilterCheck, ATRPeriod)
Checks If The Current Bar Is A Hammer Candle
Parameters:
Fib (float) : To Specify Which Fibonacci Ratio To Use When Determining The Hammer Candle, Defval = 0.382 Ratio
ColorMatch (bool) : To Filter Only Bullish Closed Hammer Candle Pattern, Defval = false
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
ATRFilterCheck (float) : To Filter Smaller Hammer Candles That Might Be Better Classified As A Doji Candle, Defval = 1
ATRPeriod (simple int) : To Change ATR Period Of The ATR Filter, Defval = 20
Returns: Bool - True If The Current Bar Matches The Requirements of a Hammer Candle
Doji(MaxWickSize, MaxBodySize, DojiType, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Doji Candle
Parameters:
MaxWickSize (float) : To Specify The Maximum Lenght Of Its Upper & Lower Wick, Defval = 2
MaxBodySize (float) : To Specify The Maximum Lenght Of Its Candle Body IN PERCENT, Defval = 0.05
DojiType (int)
NearSwings (bool) : To Specify If We Want The Doji To Be Near A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High / Low (Only In Dragonlyf / Gravestone Mode), Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Doji Candle
BullishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bullsih Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing Low, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing Low, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bullish Harami Candle
BearishIB(Allowance, RejectionWickSize, EngulfWick, NearSwings, SwingLookBack)
Checks If The Current Bar Is A Bullish Harami Candle
Parameters:
Allowance (int) : To Give Flexibility Of Harami Pattern Detection In Markets That Have Micro Gaps, Defval = 0
RejectionWickSize (float) : To Filter Out long (Upper And Lower) Wick From The Bearish Harami Pattern, Defval = na
EngulfWick (bool) : To Specify If We Want The Pattern To Also Engulf Its Upper & Lower Previous Wicks, Defval = false
NearSwings (bool) : To Specify If We Want The Pattern To Be Near A Recent Swing High, Defval = true
SwingLookBack (int) : To Specify How Many Bars Back To Detect A Recent Swing High, Defval = 10
Returns: Bool - True If The Current Bar Matches The Requirements of a Bearish Harami Candle
//====================================================================================================================================================
// Custom Time Functions
//====================================================================================================================================================
BarInSession(sess, useFilter)
Determines if the current price bar falls inside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls within the given time session
BarOutSession(sess, useFilter)
Determines if the current price bar falls outside the specified session © ZenAndTheArtOfTrading
Parameters:
sess (simple string)
useFilter (bool)
Returns: A boolean - true if the current bar falls outside the given time session
DateFilter(startTime, endTime)
Determines if this bar's time falls within date filter range © ZenAndTheArtOfTrading
Parameters:
startTime (int)
endTime (int)
Returns: A boolean - true if the current bar falls within the given dates
DayFilter(monday, tuesday, wednesday, thursday, friday, saturday, sunday)
Checks if the current bar's day is in the list of given days to analyze © ZenAndTheArtOfTrading
Parameters:
monday (bool)
tuesday (bool)
wednesday (bool)
thursday (bool)
friday (bool)
saturday (bool)
sunday (bool)
Returns: A boolean - true if the current bar's day is one of the given days
AUSSess()
Checks If The Current Australian Forex Session In Running
Returns: Bool - True If Currently The Australian Session Is Running
ASIASess()
Checks If The Current Asian Forex Session In Running
Returns: Bool - True If Currently The Asian Session Is Running
EURSess()
Checks If The Current European Forex Session In Running
Returns: Bool - True If Currently The European Session Is Running
USSess()
Checks If The Current US Forex Session In Running
Returns: Bool - True If Currently The US Session Is Running
UNIXToDate(Time, ConversionType, TimeZone)
Converts UNIX Time To Datetime
Parameters:
Time (int) : Is The UNIX Time Input
ConversionType (int) : Is The Datetime Output Format, Defval = DD-MM-YYYY
TimeZone (string) : Is To Convert The Outputed Datetime Into The Specified Time Zone, Defval = Exchange Time Zone
Returns: String - String Of Datetime
LineWrapperLibrary "LineWrapper"
Wrapper Type for Line. Useful when you want to store the line details without drawing them. Can also be used in scnearios where you collect lines to be drawn and draw together towards the end.
draw(this)
draws line as per the wrapper object contents
Parameters:
this : (series Line) Line object.
Returns: current Line object
draw(this)
draws lines as per the wrapper object array
Parameters:
this : (series array) Array of Line object.
Returns: current Array of Line objects
update(this)
updates or redraws line as per the wrapper object contents
Parameters:
this : (series Line) Line object.
Returns: current Line object
update(this)
updates or redraws lines as per the wrapper object array
Parameters:
this : (series array) Array of Line object.
Returns: current Array of Line objects
get_price(this, bar)
get line price based on bar
Parameters:
this : (series Line) Line object.
bar : (series/int) bar at which line price need to be calculated
Returns: line price at given bar.
get_x1(this)
Returns UNIX time or bar index (depending on the last xloc value set) of the first point of the line.
Parameters:
this : (series Line) Line object.
Returns: UNIX timestamp (in milliseconds) or bar index.
get_x2(this)
Returns UNIX time or bar index (depending on the last xloc value set) of the second point of the line.
Parameters:
this : (series Line) Line object.
Returns: UNIX timestamp (in milliseconds) or bar index.
get_y1(this)
Returns price of the first point of the line.
Parameters:
this : (series Line) Line object.
Returns: Price value.
get_y2(this)
Returns price of the second point of the line.
Parameters:
this : (series Line) Line object.
Returns: Price value.
set_x1(this, x, draw, update)
Sets bar index or bar time (depending on the xloc) of the first point.
Parameters:
this : (series Line) Line object.
x : (series int) Bar index or bar time. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_x2(this, x, draw, update)
Sets bar index or bar time (depending on the xloc) of the second point.
Parameters:
this : (series Line) Line object.
x : (series int) Bar index or bar time. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_y1(this, y, draw, update)
Sets price of the first point
Parameters:
this : (series Line) Line object.
y : (series int/float) Price.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_y2(this, y, draw, update)
Sets price of the second point
Parameters:
this : (series Line) Line object.
y : (series int/float) Price.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_color(this, color, draw, update)
Sets the line color
Parameters:
this : (series Line) Line object.
color : (series color) New line color
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_extend(this, extend, draw, update)
Sets extending type of this line object. If extend=extend.none, draws segment starting at point (x1, y1) and ending at point (x2, y2). If extend is equal to extend.right or extend.left, draws a ray starting at point (x1, y1) or (x2, y2), respectively. If extend=extend.both, draws a straight line that goes through these points.
Parameters:
this : (series Line) Line object.
extend : (series string) New extending type.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_style(this, style, draw, update)
Sets the line style
Parameters:
this : (series Line) Line object.
style : (series string) New line style.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_width(this, width, draw, update)
Sets the line width.
Parameters:
this : (series Line) Line object.
width : (series int) New line width in pixels.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_xloc(this, x1, x2, xloc, draw, update)
Sets x-location and new bar index/time values.
Parameters:
this : (series Line) Line object.
x1 : (series int) Bar index or bar time of the first point.
x2 : (series int) Bar index or bar time of the second point.
xloc : (series string) New x-location value.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_xy1(this, x, y, draw, update)
Sets bar index/time and price of the first point.
Parameters:
this : (series Line) Line object.
x : (series int) Bar index or bar time. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
y : (series int/float) Price.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
set_xy2(this, x, y, draw, update)
Sets bar index/time and price of the second point
Parameters:
this : (series Line) Line object.
x : (series int) Bar index or bar time. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
y : (series int/float) Price.
draw : (series bool) draw line after setting attribute
update : (series bool) update line instead of redraw. Only valid if draw is set.
Returns: Current Line object
delete(this)
Deletes the underlying line drawing object
Parameters:
this : (series Line) Line object.
Returns: Current Line object
Line
Line Wrapper object
Fields:
x1 : (series int) Bar index (if xloc = xloc.bar_index) or bar UNIX time (if xloc = xloc.bar_time) of the first point of the line. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
y1 : (series int/float) Price of the first point of the line.
x2 : (series int) Bar index (if xloc = xloc.bar_index) or bar UNIX time (if xloc = xloc.bar_time) of the second point of the line. Note that objects positioned using xloc.bar_index cannot be drawn further than 500 bars into the future.
y2 : (series int/float) Price of the second point of the line.
xloc : (series string) See description of x1 argument. Possible values: xloc.bar_index and xloc.bar_time. Default is xloc.bar_index.
extend : (series string) If extend=extend.none, draws segment starting at point (x1, y1) and ending at point (x2, y2). If extend is equal to extend.right or extend.left, draws a ray starting at point (x1, y1) or (x2, y2), respectively. If extend=extend.both, draws a straight line that goes through these points. Default value is extend.none.
color : (series color) Line color.
style : (series string) Line style. Possible values: line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_left, line.style_arrow_right, line.style_arrow_both.
width : (series int) Line width in pixels.
obj : line object
Delta Volume Channels [LucF]█ OVERVIEW
This indicator displays on-chart visuals aimed at making the most of delta volume information. It can color bars and display two channels: one for delta volume, another calculated from the price levels of bars where delta volume divergences occur. Markers and alerts can also be configured using key conditions, and filtered in many different ways. The indicator caters to traders who prefer chart visuals over raw values. It will work on historical bars and in real time, using intrabar analysis to calculate delta volume in both conditions.
█ CONCEPTS
Delta Volume
The volume delta concept divides a bar's volume in "up" and "down" volumes. The delta is calculated by subtracting down volume from up volume. Many calculation techniques exist to isolate up and down volume within a bar. The simplest techniques use the polarity of interbar price changes to assign their volume to up or down slots, e.g., On Balance Volume or the Klinger Oscillator . Others such as Chaikin Money Flow use assumptions based on a bar's OHLC values. The most precise calculation method uses tick data and assigns the volume of each tick to the up or down slot depending on whether the transaction occurs at the bid or ask price. While this technique is ideal, it requires huge amounts of data on historical bars, which usually limits the historical depth of charts and the number of symbols for which tick data is available.
This indicator uses intrabar analysis to achieve a compromise between the simplest and most precise methods of calculating volume delta. In the context where historical tick data is not yet available on TradingView, intrabar analysis is the most precise technique to calculate volume delta on historical bars on our charts. TradingView's Volume Profile built-in indicators use it, as do the CVD - Cumulative Volume Delta Candles and CVD - Cumulative Volume Delta (Chart) indicators published from the TradingView account . My Volume Delta Columns Pro indicator also uses intrabar analysis. Other volume delta indicators such as my Realtime 5D Profile use realtime chart updates to achieve more precise volume delta calculations. Indicators of that type cannot be used on historical bars however; they only work in real time.
This is the logic I use to assign intrabar volume to up or down slots:
• If the intrabar's open and close values are different, their relative position is used.
• If the intrabar's open and close values are the same, the difference between the intrabar's close and the previous intrabar's close is used.
• As a last resort, when there is no movement during an intrabar and it closes at the same price as the previous intrabar, the last known polarity is used.
Once all intrabars making up a chart bar have been analyzed and the up or down property of each intrabar's volume determined, the up volumes are added and the down volumes subtracted. The resulting value is volume delta for that chart bar, which can be used as an estimate of the buying/selling pressure on an instrument.
Delta Volume Percent (DV%)
This value is the proportion that delta volume represents of the total intrabar volume in the chart bar. Note that on some symbols/timeframes, the total intrabar volume may differ from the chart's volume for a bar, but that will not affect our calculations since we use the total intrabar volume.
Delta Volume Channel
The DV channel is the space between two moving averages: the reference line and a DV%-weighted version of that reference. The reference line is a moving average of a type, source and length which you select. The DV%-weighted line uses the same settings, but it averages the DV%-weighted price source.
The weight applied to the source of the reference line is calculated from two values, which are multiplied: DV% and the relative size of the bar's volume in relation to previous bars. The effect of this is that DV% values on bars with higher total volume will carry greater weight than those with lesser volume.
The DV channel can be in one of four states, each having its corresponding color:
• Bull (teal): The DV%-weighted line is above the reference line.
• Strong bull (lime): The bull condition is fulfilled and the bar's close is above the reference line and both the reference and the DV%-weighted lines are rising.
• Bear (maroon): The DV%-weighted line is below the reference line.
• Strong bear (pink): The bear condition is fulfilled and the bar's close is below the reference line and both the reference and the DV%-weighted lines are falling.
Divergences
In the context of this indicator, a divergence is any bar where the slope of the reference line does not match that of the DV%-weighted line. No directional bias is assigned to divergences when they occur.
Divergence Channel
The divergence channel is the space between two levels (by default, the bar's low and high ) saved when divergences occur. When price has breached a channel and a new divergence occurs, a new channel is created. Until that new channel is breached, bars where additional divergences occur will expand the channel's levels if the bar's price points are outside the channel.
Prices breaches of the divergence channel will change its state. Divergence channels can be in one of five different states:
• Bull (teal): Price has breached the channel to the upside.
• Strong bull (lime): The bull condition is fulfilled and the DV channel is in the strong bull state.
• Bear (maroon): Price has breached the channel to the downside.
• Strong bear (pink): The bear condition is fulfilled and the DV channel is in the strong bear state.
• Neutral (gray): The channel has not been breached.
█ HOW TO USE THE INDICATOR
Load the indicator on an active chart (see here if you don't know how).
The default configuration displays:
• The DV channel, without the reference or DV%-weighted lines.
• The Divergence channel, without its level lines.
• Bar colors using the state of the DV channel.
The default settings use an Arnaud-Legoux moving average on the close and a length of 20 bars. The DV%-weighted version of it uses a combination of DV% and relative volume to calculate the ultimate weight applied to the reference. The DV%-weighted line is capped to 5 standard deviations of the reference. The lower timeframe used to access intrabars automatically adjusts to the chart's timeframe and achieves optimal balance between the number of intrabars inspected in each chart bar, and the number of chart bars covered by the script's calculations.
The Divergence channel's levels are determined using the high and low of the bars where divergences occur. Breaches of the channel require a bar's low to move above the top of the channel, and the bar's high to move below the channel's bottom.
No markers appear on the chart; if you want to create alerts from this script, you will need first to define the conditions that will trigger the markers, then create the alert, which will trigger on those same conditions.
To learn more about how to use this indicator, you must understand the concepts it uses and the information it displays, which requires reading this description. There are no videos to explain it.
█ FEATURES
The script's inputs are divided in four sections: "DV channel", "Divergence channel", "Other Visuals" and "Marker/Alert Conditions". The first setting is the selection method used to determine the intrabar precision, i.e., how many lower timeframe bars (intrabars) are examined in each chart bar. The more intrabars you analyze, the more precise the calculation of DV% results will be, but the less chart coverage can be covered by the script's calculations.
DV Channel
Here, you control the visibility and colors of the reference line, its weighted version, and the DV channel between them.
You also specify what type of moving average you want to use as a reference line, its source and length. This acts as the DV channel's baseline. The DV%-weighted line is also a moving average of the same type and length as the reference line, except that it will be calculated from the DV%-weighted source used in the reference line. By default, the DV%-weighted line is capped to five standard deviations of the reference line. You can change that value here. This section is also where you can disable the relative volume component of the weight.
Divergence Channel
This is where you control the appearance of the divergence channel and the key price values used in determining the channel's levels and breaching conditions. These choices have an impact on the behavior of the channel. More generous level prices like the default low and high selection will produce more conservative channels, as will the default choice for breach prices.
In this section, you can also enable a mode where an attempt is made to estimate the channel's bias before price breaches the channel. When it is enabled, successive increases/decreases of the channel's top and bottom levels are counted as new divergences occur. When one count is greater than the other, a bull/bear bias is inferred from it.
Other Visuals
You specify here:
• The method used to color chart bars, if you choose to do so.
• The display of a mark appearing above or below bars when a divergence occurs.
• If you want raw values to appear in tooltips when you hover above chart bars. The default setting does not display them, which makes the script faster.
• If you want to display an information box which by default appears in the lower left of the chart.
It shows which lower timeframe is used for intrabars, and the average number of intrabars per chart bar.
Marker/Alert Conditions
Here, you specify the conditions that will trigger up or down markers. The trigger conditions can include a combination of state transitions of the DV and the divergence channels. The triggering conditions can be filtered using a variety of conditions.
Configuring the marker conditions is necessary before creating an alert from this script, as the alert will use the marker conditions to trigger.
Markers only appear on bar closes, so they will not repaint. Keep in mind, when looking at markers on historical bars, that they are positioned on the bar when it closes — NOT when it opens.
Raw values
The raw values calculated by this script can be inspected using a tooltip and the Data Window. The tooltip is visible when you hover over the top of chart bars. It will display on the last 500 bars of the chart, and shows the values of DV, DV%, the combined weight, and the intermediary values used to calculate them.
█ INTERPRETATION
The aim of the DV channel is to provide a visual representation of the buying/selling pressure calculated using delta volume. The simplest characteristic of the channel is its bull/bear state. One can then distinguish between its bull and strong bull states, as transitions from strong bull to bull states will generally happen when buyers are losing steam. While one should not infer a reversal from such transitions, they can be a good place to tighten stops. Only time will tell if a reversal will occur. One or more divergences will often occur before reversals.
The nature of the divergence channel's design makes it particularly adept at identifying consolidation areas if its settings are kept on the conservative side. A gray divergence channel should usually be considered a no-trade zone. More adventurous traders can use the DV channel to orient their trade entries if they accept the risk of trading in a neutral divergence channel, which by definition will not have been breached by price.
If your charts are already busy with other stuff you want to hold on to, you could consider using only the chart bar coloring component of this indicator:
At its simplest, one way to use this indicator would be to look for overlaps of the strong bull/bear colors in both the DV channel and a divergence channel, as these identify points where price is breaching the divergence channel when buy/sell pressure is consistent with the direction of the breach. I have highlighted all those points in the chart below. Not all of them would have produced profitable trades, but nothing is perfect in the markets. Also, keep in mind that the circles identify the visual you would be looking for — not the trade's entry level.
█ LIMITATIONS
• The script will not work on symbols where no volume is available. An error will appear when that is the case.
• Because a maximum of 100K intrabars can be analyzed by a script, a compromise is necessary between the number of intrabars analyzed per chart bar
and chart coverage. The more intrabars you analyze per chart bar, the less coverage you will obtain.
The setting of the "Intrabar precision" field in the "DV channel" section of the script's inputs
is where you control how the lower timeframe is calculated from the chart's timeframe.
█ NOTES
Volume Quality
If you use volume, it's important to understand its nature and quality, as it varies with sectors and instruments. My Volume X-ray indicator is one way you can appraise the quality of an instrument's intraday volume.
For Pine Script™ Coders
• This script uses the new overload of the fill() function which now makes it possible to do vertical gradients in Pine. I use it for both channels displayed by this script.
• I use the new arguments for plot() 's `display` parameter to control where the script plots some of its values,
namely those I only want to appear in the script's status line and in the Data Window.
• I wrote my script using the revised recommendations in the Style Guide from the Pine v5 User Manual.
█ THANKS
To PineCoders . I have used their lower_tf library in this script, to manage the calculation of the LTF and intrabar stats, and their Time library to convert a timeframe in seconds to a printable form for its display in the Information box.
To TradingView's Pine Script™ team. Their innovations and improvements, big and small, constantly expand the boundaries of the language. What this script does would not have been possible just a few months back.
And finally, thanks to all the users of my scripts who take the time to comment on my publications and suggest improvements. I do not reply to all but I do read your comments and do my best to implement your suggestions with the limited time that I have.
AdxlLibrary "Adxl"
Functions to calculate the Average Directional Index
getDirectionUp(bar, lookback)
Bar high changed from open for bar
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getDirectionDown(bar, lookback)
Bar low changed from open for bar
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getPositiveDirectionalMovement(bar, lookback)
Positive directional movement for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getNegativeDirectionalMovement(bar, lookback)
Negative directional movement for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : series int The lookback period
Returns: series float
getTrueRangeMovingAverage(bar, lookback)
True range moving average for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getDirectionUpIndex(bar, lookback)
Direction up index for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getDirectionDownIndex(bar, lookback)
Direction down index for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getTotalDirectionIndex(bar, lookback)
Total direction index for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
getAverageDirectionalIndex(bar, lookback)
Average Directional Index (ADX) for bar during lookback
Parameters:
bar : series int The bar to calculate at
lookback : simple int The lookback period
Returns: series int
HighTimeframeTimingLibrary "HighTimeframeTiming"
@description Library for sampling high timeframe (HTF) historical data at an arbitrary number of HTF bars back, using a single security() call.
The data is fixed and does not alter over the course of the HTF bar. It also behaves consistently on historical and elapsed realtime bars.
‼ LIMITATIONS: This library function depends on there being a consistent number of chart timeframe bars within the HTF bar. This is almost always true in 24/7 markets like crypto.
This might not be true if the chart doesn't produce an update when expected, for example because the asset is thinly traded and there is no volume or price update from the feed at that time.
To mitigate this risk, use this function on liquid assets and at chart timeframes high enough to reliably produce updates at least once per bar period.
The consistent ratio of bars might also break down in markets with irregular sessions and hours. I'm not sure if or how one could mitigate this.
Another limitation is that because we're accessing a multiplied number of chart bars, you will run out of chart bars faster than you would HTF bars. This is only a problem if you use a large historical operator.
If you call a function from this library, you should probably reproduce these limitations in your script description.
However, all of this doesn't mean that this function might not still be the best available solution, depending what your needs are.
If a single chart bar is skipped, for example, the calculation will be off by 1 until the next HTF bar opens. This is certainly inconsistent, but potentially still usable.
@function f_offset_synch(float _HTF_X, int _HTF_H, int _openChartBarsIn, bool _updateEarly)
Returns the number of chart bars that you need to go back in order to get a stable HTF value from a given number of HTF bars ago.
@param float _HTF_X is the timeframe multiplier, i.e. how much bigger the selected timeframe is than the chart timeframe. The script shows a way to calculate this using another of my libraries without using up a security() call.
@param int _HTF_H is the historical operator on the HTF, i.e. how many bars back you want to go on the higher timeframe. If omitted, defaults to zero.
@param int _openChartBarsIn is how many chart bars have been opened within the current HTF bar. An example of calculating this is given below.
@param bool _updateEarly defines whether you want to update the value at the closing calculation of the last chart bar in the HTF bar or at the open of the first one.
@returns an integer that you can use as a historical operator to retrieve the value for the appropriate HTF bar.
🙏 Credits: This library is an attempt at a solution of the problems in using HTF data that were laid out by Pinecoders in "security() revisited" -
Thanks are due to the authors of that work for an understanding of HTF issues. In addition, the current script also includes some of its code.
Specifically, this script reuses the main function recommended in "security() revisited", for the purposes of comparison. And it extends that function to access historical data, again just for comparison.
All the rest of the code, and in particular all of the code in the exported function, is my own.
Special thanks to LucF for pointing out the limitations of my approach.
~~~~~~~~~~~~~~~~|
EXPLANATION
~~~~~~~~~~~~~~~~|
Problems with live HTF data: Many problems with using live HTF data from security() have been clearly explained by Pinecoders in "security() revisited"
In short, its behaviour is inconsistent between historical and elapsed realtime bars, and it changes in realtime, which can cause calculations and alerts to misbehave.
Various unsatisfactory solutions are discussed in "security() revisited", and understanding that script is a prerequisite to understanding this library.
PineCoders give their own solution, which is to fix the data by essentially using the previous HTF bar's data. Importantly, that solution is consistent between historical and realtime bars.
This library is an attempt to provide an alternative to that solution.
Problems with historical HTF data: In addition to the problems with live HTF data, there are different issues when trying to access historical HTF data.
Why use historical HTF data? Maybe you want to do custom calculations that involve previous HTF bars. Or to use HTF data in a function that has mutable variables and so can't be done in a security() call.
Most obviously, using the historical operator (in this description, represented using { } because the square brackets don't render) on variables already retrieved from a security() call, e.g. HTF_Close{1}, is not very useful:
it retrieves the value from the previous *chart* bar, not the previous HTF bar.
Using {1} directly in the security() call instead does get data from the previous HTF bar, but it behaves inconsistently, as we shall see.
This library addresses these concerns as well.
Housekeeping: To follow what's going on with the example and comparisons, turn line labels on: Settings > Scales > Indicator Name Label.
The following explanation assumes "close" as the source, but you can change it if you want.
To quickly see the difference between historical and realtime bars, set the HTF to something like 3 minutes on a 15s chart.
The bars at the top of the screen show the status. Historical bars are grey, elapsed realtime bars are red, and the realtime bar is green. A white vertical line shows the open of a HTF bar.
A: This library function f_offset_synch(): When supplied with an input offset of 0, it plots a stable value of the close of the *previous* HTF bar. This value is thus safe to use for calculations and alerts.
For a historical operator of {1}, it gives the close of the *last-but-one* bar. Sounds simple enough. Let's look at the other options to see its advantages.
B: Live HTF data: Represented on the line label as "security(){0}". Note: this is the source that f_offset_synch() samples.
The raw HTF data is very different on historical and realtime bars:
+ On historical bars, it uses a flat value from the end of the previous HTF bar. It updates at the close of the HTF bar.
+ On realtime bars, it varies between and within each chart bar.
There might be occasions where you want to use live data, in full knowledge of its drawbacks described above. For example, to show simple live conditions that are reversible after a chart bar close.
This library transforms live data to get the fixed data, thus giving you access to both live and fixed data with only one security() call.
C: Historical data using security(){H}: To see how this behaves, set the {H} value in the settings to 1 and show options A, B, and C.
+ On historical bars, this option matches option A, this library function, exactly. It behaves just like security(){0} but one HTF bar behind, as you would expect.
+ On realtime bars, this option takes the value of security(){0} at the end of a HTF bar, but it takes it from the previous *chart* bar, and then persists that.
The easiest way to see this inconsistency is on the first realtime bar (marked red at the top of the screen). This option suddenly jumps, even if it's in the middle of a HTF bar.
Contrast this with option A, which is always constant, until it updates, once per HTF bar.
D: PineCoders' original function: To see how this behaves, show options A, B, and D. Set the {H} value in the settings to 0, then 1.
The PineCoders' original function (D) and extended function (E) do not have the same limitations as this library, described in the Limitations section.
This option has all of the same advantages that this library function, option A, does, with the following differences:
+ It cannot access historical data. The {H} setting makes no difference.
+ It always updates at the open of the first chart bar in a new HTF bar.
By contrast, this library function, option A, is configured by default to update at the close of the last chart bar in a HTF bar.
This little frontrunning is only a few seconds but could be significant in trading. E.g. on a 1D HTF with a 4H chart, an alert that involves a HTF change set to trigger ON CLOSE would trigger 4 hours later using this method -
but use exactly the same value. It depends on the market and timeframe as to whether you could actually trade this. E.g. at the very end of a tradfi day your order won't get executed.
This behaviour mimics how security() itself updates, as is easy to see on the chart. If you don't want it, just set in_updateEarly to false. Then it matches option D exactly.
E: PineCoders' function, extended to get history: To see how this behaves, show options A and E. Set the {H} value in the settings to 0, then 1.
I modified the original function to be able to get historical values. In all other respects it is the same.
Apart from not having the option to update earlier, the only disadvantage of this method vs this library function is that it requires one security() call for each historical operator.
For example, if you wanted live data, and fixed data, and fixed data one bar back, you would need 3 security() calls. My library function requires just one.
This is the essential tradeoff: extra complexity and less robustness in certain circumstances (the PineCoders function is simple and universal by comparison) for more flexibility with fewer security() calls.
taLibrary "ta"
█ OVERVIEW
This library holds technical analysis functions calculating values for which no Pine built-in exists.
Look first. Then leap.
█ FUNCTIONS
cagr(entryTime, entryPrice, exitTime, exitPrice)
It calculates the "Compound Annual Growth Rate" between two points in time. The CAGR is a notional, annualized growth rate that assumes all profits are reinvested. It only takes into account the prices of the two end points — not drawdowns, so it does not calculate risk. It can be used as a yardstick to compare the performance of two instruments. Because it annualizes values, the function requires a minimum of one day between the two end points (annualizing returns over smaller periods of times doesn't produce very meaningful figures).
Parameters:
entryTime : The starting timestamp.
entryPrice : The starting point's price.
exitTime : The ending timestamp.
exitPrice : The ending point's price.
Returns: CAGR in % (50 is 50%). Returns `na` if there is not >=1D between `entryTime` and `exitTime`, or until the two time points have not been reached by the script.
█ v2, Mar. 8, 2022
Added functions `allTimeHigh()` and `allTimeLow()` to find the highest or lowest value of a source from the first historical bar to the current bar. These functions will not look ahead; they will only return new highs/lows on the bar where they occur.
allTimeHigh(src)
Tracks the highest value of `src` from the first historical bar to the current bar.
Parameters:
src : (series int/float) Series to track. Optional. The default is `high`.
Returns: (float) The highest value tracked.
allTimeLow(src)
Tracks the lowest value of `src` from the first historical bar to the current bar.
Parameters:
src : (series int/float) Series to track. Optional. The default is `low`.
Returns: (float) The lowest value tracked.
█ v3, Sept. 27, 2022
This version includes the following new functions:
aroon(length)
Calculates the values of the Aroon indicator.
Parameters:
length (simple int) : (simple int) Number of bars (length).
Returns: ( [float, float ]) A tuple of the Aroon-Up and Aroon-Down values.
coppock(source, longLength, shortLength, smoothLength)
Calculates the value of the Coppock Curve indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
longLength (simple int) : (simple int) Number of bars for the fast ROC value (length).
shortLength (simple int) : (simple int) Number of bars for the slow ROC value (length).
smoothLength (simple int) : (simple int) Number of bars for the weigted moving average value (length).
Returns: (float) The oscillator value.
dema(source, length)
Calculates the value of the Double Exponential Moving Average (DEMA).
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The double exponentially weighted moving average of the `source`.
dema2(src, length)
An alternate Double Exponential Moving Average (Dema) function to `dema()`, which allows a "series float" length argument.
Parameters:
src : (series int/float) Series of values to process.
length : (series int/float) Length for the smoothing parameter calculation.
Returns: (float) The double exponentially weighted moving average of the `src`.
dm(length)
Calculates the value of the "Demarker" indicator.
Parameters:
length (simple int) : (simple int) Number of bars (length).
Returns: (float) The oscillator value.
donchian(length)
Calculates the values of a Donchian Channel using `high` and `low` over a given `length`.
Parameters:
length (int) : (series int) Number of bars (length).
Returns: ( [float, float, float ]) A tuple containing the channel high, low, and median, respectively.
ema2(src, length)
An alternate ema function to the `ta.ema()` built-in, which allows a "series float" length argument.
Parameters:
src : (series int/float) Series of values to process.
length : (series int/float) Number of bars (length).
Returns: (float) The exponentially weighted moving average of the `src`.
eom(length, div)
Calculates the value of the Ease of Movement indicator.
Parameters:
length (simple int) : (simple int) Number of bars (length).
div (simple int) : (simple int) Divisor used for normalzing values. Optional. The default is 10000.
Returns: (float) The oscillator value.
frama(source, length)
The Fractal Adaptive Moving Average (FRAMA), developed by John Ehlers, is an adaptive moving average that dynamically adjusts its lookback period based on fractal geometry.
Parameters:
source (float) : (series int/float) Series of values to process.
length (int) : (series int) Number of bars (length).
Returns: (float) The fractal adaptive moving average of the `source`.
ft(source, length)
Calculates the value of the Fisher Transform indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Number of bars (length).
Returns: (float) The oscillator value.
ht(source)
Calculates the value of the Hilbert Transform indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
Returns: (float) The oscillator value.
ichimoku(conLength, baseLength, senkouLength)
Calculates values of the Ichimoku Cloud indicator, including tenkan, kijun, senkouSpan1, senkouSpan2, and chikou. NOTE: offsets forward or backward can be done using the `offset` argument in `plot()`.
Parameters:
conLength (int) : (series int) Length for the Conversion Line (Tenkan). The default is 9 periods, which returns the mid-point of the 9 period Donchian Channel.
baseLength (int) : (series int) Length for the Base Line (Kijun-sen). The default is 26 periods, which returns the mid-point of the 26 period Donchian Channel.
senkouLength (int) : (series int) Length for the Senkou Span 2 (Leading Span B). The default is 52 periods, which returns the mid-point of the 52 period Donchian Channel.
Returns: ( [float, float, float, float, float ]) A tuple of the Tenkan, Kijun, Senkou Span 1, Senkou Span 2, and Chikou Span values. NOTE: by default, the senkouSpan1 and senkouSpan2 should be plotted 26 periods in the future, and the Chikou Span plotted 26 days in the past.
ift(source)
Calculates the value of the Inverse Fisher Transform indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
Returns: (float) The oscillator value.
kvo(fastLen, slowLen, trigLen)
Calculates the values of the Klinger Volume Oscillator.
Parameters:
fastLen (simple int) : (simple int) Length for the fast moving average smoothing parameter calculation.
slowLen (simple int) : (simple int) Length for the slow moving average smoothing parameter calculation.
trigLen (simple int) : (simple int) Length for the trigger moving average smoothing parameter calculation.
Returns: ( [float, float ]) A tuple of the KVO value, and the trigger value.
pzo(length)
Calculates the value of the Price Zone Oscillator.
Parameters:
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The oscillator value.
rms(source, length)
Calculates the Root Mean Square of the `source` over the `length`.
Parameters:
source (float) : (series int/float) Series of values to process.
length (int) : (series int) Number of bars (length).
Returns: (float) The RMS value.
rwi(length)
Calculates the values of the Random Walk Index.
Parameters:
length (simple int) : (simple int) Lookback and ATR smoothing parameter length.
Returns: ( [float, float ]) A tuple of the `rwiHigh` and `rwiLow` values.
stc(source, fast, slow, cycle, d1, d2)
Calculates the value of the Schaff Trend Cycle indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
fast (simple int) : (simple int) Length for the MACD fast smoothing parameter calculation.
slow (simple int) : (simple int) Length for the MACD slow smoothing parameter calculation.
cycle (simple int) : (simple int) Number of bars for the Stochastic values (length).
d1 (simple int) : (simple int) Length for the initial %D smoothing parameter calculation.
d2 (simple int) : (simple int) Length for the final %D smoothing parameter calculation.
Returns: (float) The oscillator value.
stochFull(periodK, smoothK, periodD)
Calculates the %K and %D values of the Full Stochastic indicator.
Parameters:
periodK (simple int) : (simple int) Number of bars for Stochastic calculation. (length).
smoothK (simple int) : (simple int) Number of bars for smoothing of the %K value (length).
periodD (simple int) : (simple int) Number of bars for smoothing of the %D value (length).
Returns: ( [float, float ]) A tuple of the slow %K and the %D moving average values.
stochRsi(lengthRsi, periodK, smoothK, periodD, source)
Calculates the %K and %D values of the Stochastic RSI indicator.
Parameters:
lengthRsi (simple int) : (simple int) Length for the RSI smoothing parameter calculation.
periodK (simple int) : (simple int) Number of bars for Stochastic calculation. (length).
smoothK (simple int) : (simple int) Number of bars for smoothing of the %K value (length).
periodD (simple int) : (simple int) Number of bars for smoothing of the %D value (length).
source (float) : (series int/float) Series of values to process. Optional. The default is `close`.
Returns: ( [float, float ]) A tuple of the slow %K and the %D moving average values.
supertrend(factor, atrLength, wicks)
Calculates the values of the SuperTrend indicator with the ability to take candle wicks into account, rather than only the closing price.
Parameters:
factor (float) : (series int/float) Multiplier for the ATR value.
atrLength (simple int) : (simple int) Length for the ATR smoothing parameter calculation.
wicks (simple bool) : (simple bool) Condition to determine whether to take candle wicks into account when reversing trend, or to use the close price. Optional. Default is false.
Returns: ( [float, int ]) A tuple of the superTrend value and trend direction.
szo(source, length)
Calculates the value of the Sentiment Zone Oscillator.
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The oscillator value.
t3(source, length, vf)
Calculates the value of the Tilson Moving Average (T3).
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
vf (simple float) : (simple float) Volume factor. Affects the responsiveness.
Returns: (float) The Tilson moving average of the `source`.
t3Alt(source, length, vf)
An alternate Tilson Moving Average (T3) function to `t3()`, which allows a "series float" `length` argument.
Parameters:
source (float) : (series int/float) Series of values to process.
length (float) : (series int/float) Length for the smoothing parameter calculation.
vf (simple float) : (simple float) Volume factor. Affects the responsiveness.
Returns: (float) The Tilson moving average of the `source`.
tema(source, length)
Calculates the value of the Triple Exponential Moving Average (TEMA).
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The triple exponentially weighted moving average of the `source`.
tema2(source, length)
An alternate Triple Exponential Moving Average (TEMA) function to `tema()`, which allows a "series float" `length` argument.
Parameters:
source (float) : (series int/float) Series of values to process.
length (float) : (series int/float) Length for the smoothing parameter calculation.
Returns: (float) The triple exponentially weighted moving average of the `source`.
trima(source, length)
Calculates the value of the Triangular Moving Average (TRIMA).
Parameters:
source (float) : (series int/float) Series of values to process.
length (int) : (series int) Number of bars (length).
Returns: (float) The triangular moving average of the `source`.
trima2(src, length)
An alternate Triangular Moving Average (TRIMA) function to `trima()`, which allows a "series int" length argument.
Parameters:
src : (series int/float) Series of values to process.
length : (series int) Number of bars (length).
Returns: (float) The triangular moving average of the `src`.
trix(source, length, signalLength, exponential)
Calculates the values of the TRIX indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
signalLength (simple int) : (simple int) Length for smoothing the signal line.
exponential (simple bool) : (simple bool) Condition to determine whether exponential or simple smoothing is used. Optional. The default is `true` (exponential smoothing).
Returns: ( [float, float, float ]) A tuple of the TRIX value, the signal value, and the histogram.
uo(fastLen, midLen, slowLen)
Calculates the value of the Ultimate Oscillator.
Parameters:
fastLen (simple int) : (series int) Number of bars for the fast smoothing average (length).
midLen (simple int) : (series int) Number of bars for the middle smoothing average (length).
slowLen (simple int) : (series int) Number of bars for the slow smoothing average (length).
Returns: (float) The oscillator value.
vhf(source, length)
Calculates the value of the Vertical Horizontal Filter.
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Number of bars (length).
Returns: (float) The oscillator value.
vi(length)
Calculates the values of the Vortex Indicator.
Parameters:
length (simple int) : (simple int) Number of bars (length).
Returns: ( [float, float ]) A tuple of the viPlus and viMinus values.
vzo(length)
Calculates the value of the Volume Zone Oscillator.
Parameters:
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The oscillator value.
williamsFractal(period)
Detects Williams Fractals.
Parameters:
period (int) : (series int) Number of bars (length).
Returns: ( [bool, bool ]) A tuple of an up fractal and down fractal. Variables are true when detected.
wpo(length)
Calculates the value of the Wave Period Oscillator.
Parameters:
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The oscillator value.
█ v7, Nov. 2, 2023
This version includes the following new and updated functions:
atr2(length)
An alternate ATR function to the `ta.atr()` built-in, which allows a "series float" `length` argument.
Parameters:
length (float) : (series int/float) Length for the smoothing parameter calculation.
Returns: (float) The ATR value.
changePercent(newValue, oldValue)
Calculates the percentage difference between two distinct values.
Parameters:
newValue (float) : (series int/float) The current value.
oldValue (float) : (series int/float) The previous value.
Returns: (float) The percentage change from the `oldValue` to the `newValue`.
donchian(length)
Calculates the values of a Donchian Channel using `high` and `low` over a given `length`.
Parameters:
length (int) : (series int) Number of bars (length).
Returns: ( [float, float, float ]) A tuple containing the channel high, low, and median, respectively.
highestSince(cond, source)
Tracks the highest value of a series since the last occurrence of a condition.
Parameters:
cond (bool) : (series bool) A condition which, when `true`, resets the tracking of the highest `source`.
source (float) : (series int/float) Series of values to process. Optional. The default is `high`.
Returns: (float) The highest `source` value since the last time the `cond` was `true`.
lowestSince(cond, source)
Tracks the lowest value of a series since the last occurrence of a condition.
Parameters:
cond (bool) : (series bool) A condition which, when `true`, resets the tracking of the lowest `source`.
source (float) : (series int/float) Series of values to process. Optional. The default is `low`.
Returns: (float) The lowest `source` value since the last time the `cond` was `true`.
relativeVolume(length, anchorTimeframe, isCumulative, adjustRealtime)
Calculates the volume since the last change in the time value from the `anchorTimeframe`, the historical average volume using bars from past periods that have the same relative time offset as the current bar from the start of its period, and the ratio of these volumes. The volume values are cumulative by default, but can be adjusted to non-accumulated with the `isCumulative` parameter.
Parameters:
length (simple int) : (simple int) The number of periods to use for the historical average calculation.
anchorTimeframe (simple string) : (simple string) The anchor timeframe used in the calculation. Optional. Default is "D".
isCumulative (simple bool) : (simple bool) If `true`, the volume values will be accumulated since the start of the last `anchorTimeframe`. If `false`, values will be used without accumulation. Optional. The default is `true`.
adjustRealtime (simple bool) : (simple bool) If `true`, estimates the cumulative value on unclosed bars based on the data since the last `anchor` condition. Optional. The default is `false`.
Returns: ( [float, float, float ]) A tuple of three float values. The first element is the current volume. The second is the average of volumes at equivalent time offsets from past anchors over the specified number of periods. The third is the ratio of the current volume to the historical average volume.
rma2(source, length)
An alternate RMA function to the `ta.rma()` built-in, which allows a "series float" `length` argument.
Parameters:
source (float) : (series int/float) Series of values to process.
length (float) : (series int/float) Length for the smoothing parameter calculation.
Returns: (float) The rolling moving average of the `source`.
supertrend2(factor, atrLength, wicks)
An alternate SuperTrend function to `supertrend()`, which allows a "series float" `atrLength` argument.
Parameters:
factor (float) : (series int/float) Multiplier for the ATR value.
atrLength (float) : (series int/float) Length for the ATR smoothing parameter calculation.
wicks (simple bool) : (simple bool) Condition to determine whether to take candle wicks into account when reversing trend, or to use the close price. Optional. Default is `false`.
Returns: ( [float, int ]) A tuple of the superTrend value and trend direction.
vStop(source, atrLength, atrFactor)
Calculates an ATR-based stop value that trails behind the `source`. Can serve as a possible stop-loss guide and trend identifier.
Parameters:
source (float) : (series int/float) Series of values that the stop trails behind.
atrLength (simple int) : (simple int) Length for the ATR smoothing parameter calculation.
atrFactor (float) : (series int/float) The multiplier of the ATR value. Affects the maximum distance between the stop and the `source` value. A value of 1 means the maximum distance is 100% of the ATR value. Optional. The default is 1.
Returns: ( [float, bool ]) A tuple of the volatility stop value and the trend direction as a "bool".
vStop2(source, atrLength, atrFactor)
An alternate Volatility Stop function to `vStop()`, which allows a "series float" `atrLength` argument.
Parameters:
source (float) : (series int/float) Series of values that the stop trails behind.
atrLength (float) : (series int/float) Length for the ATR smoothing parameter calculation.
atrFactor (float) : (series int/float) The multiplier of the ATR value. Affects the maximum distance between the stop and the `source` value. A value of 1 means the maximum distance is 100% of the ATR value. Optional. The default is 1.
Returns: ( [float, bool ]) A tuple of the volatility stop value and the trend direction as a "bool".
Removed Functions:
allTimeHigh(src)
Tracks the highest value of `src` from the first historical bar to the current bar.
allTimeLow(src)
Tracks the lowest value of `src` from the first historical bar to the current bar.
trima2(src, length)
An alternate Triangular Moving Average (TRIMA) function to `trima()`, which allows a
"series int" length argument.
Realtime Delta Volume Action [LucF]█ OVERVIEW
This indicator displays on-chart, realtime, delta volume and delta ticks information for each bar. It aims to provide traders who trade price action on small timeframes with volume and tick information gathered as updates come in the chart's feed. It builds its own candles, which are optimized to display volume delta information. It only works in realtime.
█ WARNING
This script is intended for traders who can already profitably trade discretionary on small timeframes. The high cost in fees and the excitement of trading at small timeframes have ruined many newcomers to trading. While trading at small timeframes can work magic for adrenaline junkies in search of thrills rather than profits, I DO NOT recommend it to most traders. Only seasoned discretionary traders able to factor in the relatively high cost of such a trading practice can ever hope to take money out of markets in that type of environment, and I would venture they account for an infinitesimal percentage of traders. If you are a newcomer to trading, AVOID THIS TOOL AT ALL COSTS — unless you are interested in experimenting with the interpretation of volume delta combined with price action. No tool currently available on TradingView provides this type of close monitoring of volume delta information, but if you are not already trading small timeframes profitably, please do not let yourself become convinced that it is the missing piece you needed. Avoid becoming a sucker who only contributes by providing liquidity to markets.
The information calculated by the indicator cannot be saved on charts, nor can it be recalculated from historical bars.
If you refresh the chart or restart the script, the accumulated information will be lost.
█ FEATURES
Key values
The script displays the following key values:
• Above the bar: ticks delta (DT), the total ticks for the bar, the percentage of total ticks that DT represents (DT%)
• Below the bar: volume delta (DV), the total volume for the bar, the percentage of total volume that DV represents (DV%).
Candles
Candles are composed of four components:
1. A top shaped like this: ┴, and a bottom shaped like this: ┬ (picture a normal Japanese candle without a body outline; the values used are the same).
2. The candle bodies are filled with the bull/bear color representing the polarity of DV. The intensity of the body's color is determined by the DV% value.
When DV% is 100, the intensity of the fill is brightest. This plays well in interpreting the body colors, as the smaller, less significant DV% values will produce less vivid colors.
3. The bright-colored borders of the candle bodies occur on "strong bars", i.e., bars meeting the criteria selected in the script's inputs, which you can configure.
4. The POC line is a small horizontal line that appears to the left of the candle. It is the volume-weighted average of all price updates during the bar.
Calculations
This script monitors each realtime update of the chart's feed. It first determines if price has moved up or down since the last update. The polarity of the price change, in turn, determines the polarity of the volume and tick for that specific update. If price does not move between consecutive updates, then the last known polarity is used. Using this method, we can calculate a running volume delta and ticks delta for the bar, which becomes the bar's final delta values when the bar closes (you can inspect values of elapsed realtime bars in the Data Window or the indicator's values). Note that these values will all reset if the script re-executes because of a change in inputs or a chart refresh.
While this method of calculating is not perfect, it is by far the most precise way of calculating volume delta available on TradingView at the moment. Calculating more precise results would require scripts to have access to tick data from any chart timeframe. Charts at seconds timeframes do use exchange/broker ticks when the feeds you are using allow for it, and this indicator will run on them, but tick data is not yet available from higher timeframes. Also, note that the method used in this script is far superior to the intrabar inspection technique used on historical bars in my other "Delta Volume" indicators. This is because volume and ticks delta here are calculated from many more realtime updates than the available intrabars in history. Unfortunately, the calculation method used here cannot be used on historical bars, where intrabar inspection remains, in my opinion, the optimal method.
Inputs
The script's inputs provide many ways to personalize all the components: what is displayed, the colors used to display the information, and the marker conditions. Tooltips provide details for many of the inputs; I leave their exploration to you.
Markers
Markers provide a way for you to identify the points of interest of your choice on the chart. You control the set of conditions that trigger each of the five available markers.
You select conditions by entering, in the field for each marker, the number of each condition you want to include, separated by a comma. The conditions are:
1 — The bar's polarity is up/dn.
2 — `close` rises/falls ("rises" means it is higher than its value on the previous bar).
3 — DV's polarity is +/–.
4 — DV% rises (↕).
5 — POC rises/falls.
6 — The quantity of realtime updates rises (↕).
7 — DV > limit (You specify the limit in the inputs. Since DV can be +/–, DV– must be less than `–limit` for a short marker).
8 — DV% > limit (↕).
9 — DV+ rises for a long marker, DV– falls for a short.
10 — Consecutive DV+/DV– on two bars.
11 — Total volume rises (↕).
12 — DT's polarity is +/–.
13 — DT% rises (↕).
14 — DT+ rises for a long marker, DT– falls for a short.
Conditions showing the (↕) symbol do not have symmetrical states; they act more like filters. If you only include condition 4 in a marker's setup, for example, both long and short markers will trigger on bars where DV% rises. To trigger only long or short markers, you must add a condition providing directional differentiation, such as conditions 1 or 2. Accordingly, you would enter "1,4" or "2,4".
For a marker to trigger, ALL the conditions you specified for it must be met. Long markers appear on the chart as "Mx▲" signs under the values displayed below candles. Short markers display "Mx▼" over the number of updates displayed above candles. The marker's number will replace the "x" in "Mx▲". The script loads with five markers that will not trigger because no conditions are associated with them. To activate markers, you will need to select and enter the set of conditions you require for each one.
Alerts
You can configure alerts on this script. They will trigger whenever one of the configured markers triggers. Alerts do not repaint, so they trigger at the bar's close—which is also when the markers will appear.
█ HOW TO USE IT
As a rule, I do not prescribe expected use of my indicators, as traders have proved to be much more creative than me in using them. Additionally, I tend to think that if you expect detailed recommendations from me to be able to use my indicators, it's a sign you are in a precarious situation and should go back to the drawing board and master the necessary basics that will allow you to explore and decide for yourself if my indicators can be useful to you, and how you will use them. I will make an exception for this thing, as it presents fairly novel information. I will use simple logic to surmise potential uses, as contrary to most of my other indicators, I have NOT used this one to actually trade. Markets have a way of throwing wrenches in our seemingly bullet-proof rationalizing, so drive cautiously and please forgive me if the pointers I share here don't pan out.
The first thing to do is to disable your normal bars. You can do this by clicking on the eye icon that appears when you hover over the symbol's name in the upper-left corner of your chart.
The absolute value and polarity of DV mean little without perspective; that's why I include both total volume for the bar and the percentage that DV represents of that total volume. I interpret a low DV% value as indecision. If you share that opinion, you could, let's say, configure one of the markers on "DV% > 80%", for example (to do so you would enter "8" in the condition field of any marker, and "80" in the limit field for condition 8, below the marker conditions).
I also like to analyze price action on the bar with DV%. Small DV% values should often produce small candle bodies. If a small DV% value occurs on a bar with much movement and high volume, I'm thinking "tough battle with potential explosive power when one side wins". Conversely, large bodies with high DV% mean that large volume is breaching through multiple levels, or that nobody is suddenly willing to take the other side of a normal volume of trades.
I find the POC lines really interesting. First, they tell us the price point where the most significant action (taking into account both price occurrences AND volume) during the bar occurred. Second, they can be useful when compared against past values. Third, their color helps us in figuring out which ones are the most significant. Unsurprisingly, bunches of orange POCs tend to appear in consolidation zones, in pauses, and before reversals. It may be useful to often focus more on POC progression than on `close` values. This is not to say that OHLC values are not useful; looking, as is customary, for higher highs or lower lows, or for repeated tests of precise levels can of course still be useful. I do like how POCs add another dimension to chart readings.
What should you do with the ticks delta above bars? Old-time ticker tape readers paid attention to the sounds coming from it (the "ticker" moniker actually comes from the sound they made). They knew activity was picking up when the frequency of the "ticks" increased. My thinking is that the total number of ticks will help you in the same way, since increasing updates usually mean growing interest—and thus perhaps price movement, as increasing volatility or volume would lead us to surmise. Ticks delta can help you figure out when proportionally large, random orders come in from traders with other perspectives than the short-term price action you are typically working with when you use this tool. Just as volume delta, ticks delta are one more informational component that can help you confirm convergence when building your opinions on price action.
What are strong bars? They are an attempt to identify significance. They are like a default marker, except that instead of displaying "Mx▲/▼" below/above the bar, the candle's body is outlined in bright bull/bear color when one is detected. Strong bars require a respectable amount of conditions to be met (you can see and re-configure them in the inputs). Think of them as pushes rather than indications of an upcoming, strong and multi-bar move. Pushes do, for sure, often occur at the beginning of strong trends. You will often see a few strong bars occur at 2-3 bar intervals at the beginning or middle of trends. But they also tend to occur at tops/bottoms, which makes their interpretation problematic. Another pattern that you will see quite frequently is a final strong bar in the direction of the trend, followed a few bars later by another strong bar in the reverse direction. My summary analyses seemed to indicate these were perhaps good points where one could make a bet on an early, risky reversal entry.
The last piece of information displayed by the indicator is the color of the candle bodies. Three possible colors are used. Bull/bear is determined by the polarity of DV, but only when the bar's polarity matches that of DV. When it doesn't, the color is the divergence color (orange, by default). Whichever color is used for the body, its intensity is determined by the DV% value. Maximum intensity occurs when DV%=100, so the more significant DV% values generate more noticeable colors. Body colors can be useful when looking to confirm the convergence of other components. The visual effect this creates hopefully makes it easier to detect patterns on the chart.
One obvious methodology that comes to mind to trade with this tool would be to use another indicator like Technical Ratings at a higher timeframe to identify the larger context's trend, and then use this tool to identify entries for short-term trades in that direction.
█ NOTES AND RAMBLINGS
Instant Calculations
This indicator uses instant values calculated on the bar only. No moving averages or calculations involving historical periods are used. The only exception to this rule is in some of the marker conditions like "Two consecutive DV+ values", where information from the previous bar is used.
Trading Small vs Long Timeframes
I never trade discretionary at the 5sec–5min timeframes this indicator was designed to be used with; I trade discretionary at 1D, 1W and 1M timeframes, and let systems trade at smaller timeframes. The higher the timeframe you trade at, the fewer fees you will pay because you trade less and are not churning trading volume, as is inevitable at smaller timeframes. Trading at higher timeframes is also a good way to gain an instant edge on most of the trading crowd that has its nose to the ground and often tends to forget the big picture. It also makes for a much less demanding trading practice, where you have lots of time to research and build your long-term opinions on potential future outcomes. While the future is always uncertain, I believe trades riding on long-term trends have stronger underlying support from the reality outside markets.
To traders who will ask why I publish an indicator designed for small timeframes, let me say that my main purpose here is to showcase what can be done with Pine. I often see comments by coders who are obviously not aware of what Pine is capable of in 2021. Since its humble beginnings seven years ago, Pine has grown and become a serious programming language. TradingView's growing popularity and its ongoing commitment to keep Pine accessible to newcomers to programming is gradually making Pine more and more of a standard in indicator and strategy programming. The technical barriers to entry for traders interested in owning their trading practice by developing their personal tools to trade have never been so low. I am also publishing this script because I value volume delta information, and I present here what I think is an original way of analyzing it.
Performance
The script puts a heavy load on the Pine runtime and the charting engine. After running the script for a while, you will often notice your chart becoming less responsive, and your chart tab can take longer to activate when you go back to it after using other tabs. That is the reason I encourage you to set the number of historical values displayed on bars to the minimum that meets your needs. When your chart becomes less responsive because the script has been running on it for many hours, refreshing the browser tab will restart everything and bring the chart's speed back up. You will then lose the information displayed on elapsed bars.
Neutral Volume
This script represents a departure from the way I have previously calculated volume delta in my scripts. I used the notion of "neutral volume" when inspecting intrabar timeframes, for bars where price did not move. No longer. While this had little impact when using intrabar inspection because the minimum usable timeframe was 1min (where bars with zero movement are relatively infrequent), a more precise way was required to handle realtime updates, where multiple consecutive prices often have the same value. This will usually happen whenever orders are unable to move across the bid/ask levels, either because of slow action or because a large-volume bid/ask level is taking time to breach. In either case, the proper way to calculate the polarity of volume delta for those updates is to use the last known polarity, which is how I calculate now.
The Order Book
Without access to the order book's levels (the depth of market), we are limited to analyzing transactions that come in the TradingView feed for the chart. That does not mean the volume delta information calculated this way is irrelevant; on the contrary, much of the information calculated here is not available in trading consoles supplied by exchanges/brokers. Yet it's important to realize that without access to the order book, you are forfeiting the valuable information that can be gleaned from it. The order book's levels are always in movement, of course, and some of the information they contain is mere posturing, i.e., attempts to influence the behavior of other players in the market by traders/systems who will often remove their orders when price comes near their order levels. Nonetheless, the order book is an essential tool for serious traders operating at intraday timeframes. It can be used to time entries/exits, to explain the causes of particular price movements, to determine optimal stop levels, to get to know the traders/systems you are betting against (they tend to exhibit behavioral patterns only recognizable through the order book), etc. This tool in no way makes the order book less useful; I encourage all intraday traders to become familiar with it and avoid trading without one.
Delta Volume Candles [LucF]█ OVERVIEW
This indicator plots on-chart volume delta information using candles that can replace your normal candles, tops and bottoms appended to normal candles, optional MAs of those tops and bottoms levels, a divergence channel and a chart background. The indicator calculates volume delta using intrabar analysis, meaning that it uses the lower timeframe bars constituting each chart bar.
█ CONCEPTS
Volume Delta
The volume delta concept divides a bar's volume in "up" and "down" volumes. The delta is calculated by subtracting down volume from up volume. Many calculation techniques exist to isolate up and down volume within a bar. The simplest use the polarity of interbar price changes to assign their volume to up or down slots, e.g., On Balance Volume or the Klinger Oscillator . Others such as Chaikin Money Flow use assumptions based on a bar's OHLC values. The most precise calculation method uses tick data and assigns the volume of each tick to the up or down slot depending on whether the transaction occurs at the bid or ask price. While this technique is ideal, it requires huge amounts of data on historical bars, which considerably limits the historical depth of charts and the number of symbols for which tick data is available. Furthermore, historical tick data is not yet available on TradingView.
This indicator uses intrabar analysis to achieve a compromise between the simplest and most precise methods of calculating volume delta. It is currently the most precise method usable on TradingView charts. TradingView's Volume Profile built-in indicators use it, as do the CVD - Cumulative Volume Delta Candles and CVD - Cumulative Volume Delta (Chart) indicators published from the TradingView account . My Delta Volume Channels and Volume Delta Columns Pro indicators also use intrabar analysis. Other volume delta indicators such as my Realtime 5D Profile use realtime chart updates to calculate volume delta without intrabar analysis, but that type of indicator only works in real time; they cannot calculate on historical bars.
This is the logic I use to determine the polarity of intrabars, which determines the up or down slot where its volume is added:
• If the intrabar's open and close values are different, their relative position is used.
• If the intrabar's open and close values are the same, the difference between the intrabar's close and the previous intrabar's close is used.
• As a last resort, when there is no movement during an intrabar, and it closes at the same price as the previous intrabar, the last known polarity is used.
Once all intrabars making up a chart bar have been analyzed and the up or down property of each intrabar's volume determined, the up volumes are added, and the down volumes subtracted. The resulting value is volume delta for that chart bar, which can be used as an estimate of the buying/selling pressure on an instrument. Not all markets have volume information. Without it, this indicator is useless.
Intrabar analysis
Intrabars are chart bars at a lower timeframe than the chart's. The timeframe used to access intrabars determines the number of intrabars accessible for each chart bar. On a 1H chart, each chart bar of an active market will, for example, usually contain 60 bars at the lower timeframe of 1min, provided there was market activity during each minute of the hour.
This indicator automatically calculates an appropriate lower timeframe using the chart's timeframe and the settings you use in the script's "Intrabars" section of the inputs. As it can access lower timeframes as small as seconds when available, the indicator can be used on charts at relatively small timeframes such as 1min, provided the market is active enough to produce bars at second timeframes.
The quantity of intrabars analyzed in each chart bar determines:
• The precision of calculations (more intrabars yield more precise results).
• The chart coverage of calculations (there is a 100K limit to the quantity of intrabars that can be analyzed on any chart,
so the more intrabars you analyze per chart bar, the less chart bars can be calculated by the indicator).
The information box displayed at the bottom right of the chart shows the lower timeframe used for intrabars, as well as the average number of intrabars detected for chart bars and statistics on chart coverage.
Balances
This indicator calculates five balances from volume delta values. The balances are oscillators with a zero centerline; positive values are bullish, and negative values are bearish. It is important to understand the balances as they can be used to:
• Color candle bodies.
• Calculate body and top and bottom divergences.
• Color an EMA channel.
• Color the chart's background.
• Configure markers and alerts.
The five balances are:
1 — Bar Balance : This is the only balance using instant values; it is simply the subtraction of the down volume from the up volume on the bar, so the instant volume delta for that bar.
2 — Average Balance : Calculates a distinct EMA for both the up and down volumes, and subtracts the down EMA from the up EMA.
The result is akin to MACD's histogram because it is the subtraction of two moving averages.
3 — Momentum Balance : Starts by calculating, separately for both up and down volumes, the difference between the same EMAs used in "Average Balance" and
an SMA of twice the period used for the "Average Balance" EMAs. The difference for the up side is subtracted from the difference for the down side,
and an RSI of that value is calculated and brought over the −50/+50 scale.
4 — Relative Balance : The reference values used in the calculation are the up and down EMAs used in the "Average Balance".
From those, we calculate two intermediate values using how much the instant up and down volumes on the bar exceed their respective EMA — but with a twist.
If the bar's up volume does not exceed the EMA of up volume, a zero value is used. The same goes for the down volume with the EMA of down volume.
Once we have our two intermediate values for the up and down volumes exceeding their respective MA, we subtract them. The final value is an ALMA of that subtraction.
The rationale behind using zero values when the bar's up/down volume does not exceed its EMA is to only take into account the more significant volume.
If both instant volume values exceed their MA, then the difference between the two is the signal's value.
The signal is called "relative" because the intermediate values are the difference between the instant up/down volumes and their respective MA.
This balance flatlines when the bar's up/down volumes do not exceed their EMAs, which makes it useful to spot areas where trader interest dwindles, such as consolidations.
The smaller the period of the final value's ALMA, the more easily it will flatline. These flat zones should be considered no-trade zones.
5 — Percent Balance : This balance is the ALMA of the ratio of the "Bar Balance" over the total volume for that bar.
From the balances and marker conditions, two more values are calculated:
1 — Marker Bias : This sums the up/down (+1/‒1) occurrences of the markers 1 to 4 over a period you define, so it ranges from −4 to +4, times the period.
Its calculation will depend on the modes used to calculate markers 3 and 4.
2 — Combined Balances : This is the sum of the bull/bear (+1/−1) states of each of the five balances, so it ranges from −5 to +5.
The periods for all of these balances can be configured in the "Periods" section at the bottom of the script's inputs. As you cannot see the balances on the chart, you can use my Volume Delta Columns Pro indicator in a pane; it can plot the same balances, so you will be able to analyze them.
Divergences
In the context of this indicator, a divergence is any bar where the bear/bull state of a balance (above/below its zero centerline) diverges from the polarity of a chart bar. No directional bias is assigned to divergences when they occur. Candle bodies and tops/bottoms can each be colored differently on divergences detected from distinct balances.
Divergence Channel
The divergence channel is the space between two levels (by default, the bar's open and close ) saved when divergences occur. When price (by default the close ) has breached a channel and a new divergence occurs, a new channel is created. Until that new channel is breached, bars where additional divergences occur will expand the channel's levels if the bar's price points are outside the channel.
Prices breaches of the divergence channel will change its state. Divergence channels can be in one of three different states:
• Bull (green): Price has breached the channel to the upside.
• Bear (red): Price has breached the channel to the downside.
• Neutral (gray): The channel has not yet been breached.
█ HOW TO USE THE INDICATOR
I do not make videos to explain how to use my indicators. I do, however, try hard to include in their description everything one needs to understand what they do. From there, it's up to you to explore and figure out if they can be useful in your trading practice. Communicating in videos what this description and the script's tooltips contain would make for very long videos that would likely exceed the attention span of most people who find this description too long. There is no quick way to understand an indicator such as this one because it uses many different concepts and has quite a bit of settings one can use to modify its visuals and behavior — thus how one uses it. I will happily answer questions on the inner workings of the indicator, but I do not answer questions like "How do I trade using this indicator?" A useful answer to that question would require an in-depth analysis of who you are, your trading methodology and objectives, which I do not have time for. I do not teach trading.
Start by loading the indicator on an active chart containing volume information. See here if you need help.
The default configuration displays:
• Normal candles where the bodies are only colored if the bar's volume has increased since the last bar.
If you want to use this indicator's candles, you may want to disable your chart's candles by clicking the eye icon to the right of the symbol's name in the top left of the chart.
• A top or bottom appended to the normal candles. It represents the difference between up and down volume for that bar
and is positioned at the top or bottom, depending on its polarity. If up volume is greater than down volume, a top is displayed. If down volume is greater, a bottom is plotted.
The size of tops and bottoms is determined by calculating a factor which is the proportion of volume delta over the bar's total volume.
That factor is then used to calculate the top or bottom size relative to a baseline of the average candle body size of the last 100 bars.
• An information box in the bottom right displaying intrabar and chart coverage information.
• A light red background when the intrabar volume differs from the chart's volume by more than 1%.
The script's inputs contain tooltips explaining most of the fields. I will not repeat them here. Following is a brief description of each section of the indicator's inputs which will give you an idea of what the indicator can do:
Normal Candles is where you configure the replacement candles plotted by the script. You can choose from different coloring schemes for their bodies and specify a unique color for bodies where a divergence calculated using the method you choose occurs.
Volume Tops & Botttoms is where you configure the display of tops and bottoms, and their EMAs. The EMAs are calculated from the high point of tops and the low point of bottoms. They can act as a channel to evaluate price, and you can choose to color the channel using a gradient reflecting the advances/declines in the balance of your choice.
Divergence Channel is where you set up the appearance and behavior of the divergence channel. These areas represent levels where price and volume delta information do not converge. They can be interpreted as regions with no clear direction from where one will look for breaches. You can configure the channel to take into account one or both types of divergences you have configured for candle bodies and tops/bottoms.
Background allows you to configure a gradient background color that reflects the advances/declines in the balance of your choice. You can use this to provide context to the volume delta values from bars. You can also control the background color displayed on volume discrepancies between the intrabar and the chart's timeframe.
Intrabars is where you choose the calculation mode determining the lower timeframe used to access intrabars. The indicator uses the chart's timeframe and the type of market you are on to calculate the lower timeframe. Your setting there should reflect which compromise you prefer between the precision of calculations and chart coverage. This is also where you control the display of the information box in the lower right corner of the chart.
Markers allows you to control the plotting of chart markers on different conditions. Their configuration determines when alerts generated from the indicator will fire. Note that in order to generate alerts from this script, they must be created from your chart. See this Help Center page to learn how. Only the last 500 markers will be visible on the chart, but this will not affect the generation of alerts.
Periods is where you configure the periods for the balances and the EMAs used in the indicator.
The raw values calculated by this script can be inspected using the Data Window.
█ INTERPRETATION
Rightly or wrongly, volume delta is considered by many a useful complement to the interpretation of price action. I use it extensively in an attempt to find convergence between my read of volume delta and price movement — not so much as a predictor of future price movement. No system or person can predict the future. Accordingly, I consider people who speak or act as if they know the future with certainty to be dangerous to themselves and others; they are charlatans, imprudent or blissfully ignorant.
I try to avoid elaborate volume delta interpretation schemes involving too many variables and prefer to keep things simple:
• Trends that have more chances of continuing should be accompanied by VD of the same polarity.
In trends, I am looking for "slow and steady". I work from the assumption that traders and systems often overreact, which translates into unproductive volatility.
Wild trends are more susceptible to overreactions.
• I prefer steady VD values over wildly increasing ones, as large VD increases often come with increased price volatility, which can backfire.
Large VD values caused by stopping volume will also often occur on trend reversals with abnormally high candles.
• Prices escaping divergence channels may be leading a trend in that direction, although there is no telling how long that trend will last; could be just a few bars or hundreds.
When price is in a channel, shifts in VD balances can sometimes give us an idea of the direction where price has the most chance of breaking.
• Dwindling VD will often indicate trend exhaustion and predate reversals by many bars, but the problem is that mere pauses in a trend will often produce the same behavior in VD.
I think it is too perilous to infer rigidly from VD decreases.
Divergence Channel
Here I have configured the divergence channels to be visible. First, I set the bodies to display divergences on the default Bar Balance. They are indicated by yellow bodies. Then I activated the divergence channels by choosing to draw levels on body divergences and checked the "Fill" checkbox to fill the channel with the same color as the levels. The divergence channel is best understood as a direction-less area from where a breach can be acted on if other variables converge with the breach's direction:
Tops and Bottoms EMAs
I find these EMAs rather interesting. They have no equivalent elsewhere, as they are calculated from the top and bottom values this indicator plots. The only similarity they have with volume-weighted MAs, including VWAP, is that they use price and volume. This indicator's Tops and Bottoms EMAs, however, use the price and volume delta. While the channel differs from other channels in how it is calculated, it can be used like others, as a baseline from which to evaluate price movement or, alternatively, as stop levels. Remember that you can change the period used for the EMAs in the "Periods" section of the inputs.
This chart shows the EMAs in action, filled with a gradient representing the advances/decline from the Momentum balance. Notice the anomaly in the chart's latest bars where the Momentum balance gradient has been indicating a bullish bias for some time, during which price was mostly below the EMAs. Price has just broken above the channel on positive VD. My interpretation of this situation would be that it is a risky opportunity for a long trade in the larger context where the market has been in a downtrend since the 5th. Intrepid traders choosing to enter here could do so with a "make or break" tight stop that will minimize their losses should the market continue its downtrend while hopefully preserving the potential upside of price continuing on the longer-term uptrend prevalent since the 28th:
█ NOTES
Volume
If you use indicators such as this one which depends on volume information, it is important to realize that the volume data they consume comes from data feeds, and that all data feeds are NOT created equally. Those who create the data feeds we use must make decisions concerning the nature of the transactions they tally and the way they are tallied in each feed, and these decisions affect the nature of our volume data. My Volume X-ray publication discusses some of the reasons why volume information from different timeframes, brokers/exchanges or sectors may vary considerably. I encourage you to read it. This indicator's display of a warning through a background color on volume discrepancies between the timeframe used to access intrabars and the chart's timeframe is an attempt to help you realize these variations in feeds. Don't take things for granted, and understand that the quality of a given feed's volume information affects the quality of the results this indicator calculates.
Markets as ecosystems
I believe it is perilous to think that behavioral patterns you discover in one market through the lens of this or any other indicator will necessarily port to other markets. While this may sometimes be the case, it will often not. Why is that? Because each market is its own ecosystem. As cities do, all markets share some common characteristics, but they also all have their idiosyncrasies. A proportion of a city's inhabitants is always composed of outsiders who come and go, but a core population of regulars and systems is usually the force that actually defines most of the city's observable characteristics. I believe markets work somewhat the same way; they may look the same, but if you live there for a while and pay attention, you will notice the idiosyncrasies. Some things that work in some markets will, accordingly, not work in others. Please keep that in mind when you draw conclusions.
On Up/Down or Buy/Sell Volume
Buying or selling volume are misnomers, as every unit of volume transacted is both bought and sold by two different traders. While this does not keep me from using the terms, there is no such thing as “buy only” or “sell only” volume. Trader lingo is riddled with peculiarities. Without access to order book information, traders work with the assumption that when price moves up during a bar, there was more buying pressure than selling pressure, just as when buy market orders take out limit ask orders in the order book at successively higher levels. The built-in volume indicator available on TradingView uses this logic to color the volume columns green or red. While this script’s calculations are more precise because it analyses intrabars to calculate its information, it uses pretty much the same imperfect logic. Until Pine scripts can have access to how much volume was transacted at the bid/ask prices, our volume delta calculations will remain a mere proxy.
Repainting
• The values calculated on the realtime bar will update as new information comes from the feed.
• Historical values may recalculate if the historical feed is updated or when calculations start from a new point in history.
• Markers and alerts will not repaint as they only occur on a bar's close. Keep this in mind when viewing markers on historical bars,
where one could understandably and incorrectly assume they appear at the bar's open.
To learn more about repainting, see the Pine Script™ User Manual's page on the subject .
Superfluity
In "The Bed of Procrustes", Nassim Nicholas Taleb writes: To bankrupt a fool, give him information . This indicator can display a lot of information. The inevitable adaptation period you will need to figure out how to use it should help you eliminate all the visuals you do not need. The more you eliminate, the easier it will be to focus on those that are the most useful to your trading practice. Don't be a fool.
█ THANKS
Thanks to alexgrover for his Dekidaka-Ashi indicator. His volume plots on candles were the inspiration for my top/bottom plots.
Kudos to PineCoders for their libraries. I use two of them in this script: Time and lower_tf .
The first versions of this script used functionality that I would not have known about were it not for these two guys:
— A guy called Kuan who commented on a Backtest Rookies presentation of their Volume Profile indicator.
— theheirophant , my partner in the exploration of the sometimes weird abysses of request.security() ’s behavior at lower timeframes.
Great Expectations [LucF]Great Expectations helps traders answer the question: What is possible? It is a powerful question, yet exploration of the unknown always entails risk. A more complete set of questions better suited to traders could be:
What opportunity exists from any given point on a chart?
What portion of this opportunity can be realistically captured?
What risk will be incurred in trying to do so, and how long will it take?
Great Expectations is the result of an exploration of these questions. It is a trade simulator that generates visual and quantitative information to help strategy modelers visually identify and analyse areas of optimal expectation on charts, whether they are designing automated or discretionary strategies.
WARNING: Great Expectations is NOT an indicator that helps determine the current state of a market. It works by looking at points in the past from which the future is already known. It uses one definition of repainting extensively (i.e. it goes back in the past to print information that could not have been know at the time). Repainting understood that way is in fact almost all the indicator does! —albeit for what I hope is a noble cause. The indicator is of no use whatsoever in analyzing markets in real-time. If you do not understand what it does, please stay away!
This is an indicator—not a strategy that uses TradingView’s backtesting engine. It works by simulating trades, not unlike a backtest, but with the crucial difference that it assumes a trade (either long or short) is entered on all bars in the historic sample. It walks forward from each bar and determines possible outcomes, gathering individual trade statistics that in turn generate precious global statistics from all outcomes tested on the chart.
Great Expectations provides numbers summarizing trade results on all simulations run from the chart. Those numbers cannot be compared to backtest-produced numbers since all non-filtered bars are examined, even if an entry was taken on the bar immediately preceding the current one, which never happens in a backtest. This peculiarity does NOT invalidate Great Expectations calculations; it just entails that results be considered under a different light. Provided they are evaluated within the indicator’s context, they can be useful—sometimes even more than backtesting results, e.g. in evaluating the impact of parameter-fitting or variations in entry, exit or filtering strats.
Traders and strategy modelers are creatures of hope often suffering from blurred vision; my hope is that Great Expectations will help them appraise the validity of their setup and strat intuitions in a realistic fashion, preventing confirmation bias from obstructing perspective—and great expectations from turning into financial great deceptions.
USE CASES
You’ve identified what looks like a promising setup on other indicators. You load Great Expectations on the chart and evaluate if its high-expectation areas match locations where your setup’s conditions occur. Unless today is your lucky day, chances are the indicator will help you realize your setup is not as promising as you had hoped.
You want to get a rough estimate of the optimal trade duration for a chart and you don’t mind using the entry and exit strategies provided with the indicator. You use the trade length readouts of the indicator.
You’re experimenting with a new stop strategy and want to know how long it will keep you in trades, on average. You integrate your stop strategy in the indicator’s code and look at the average trade length it produces and the TST ratio to evaluate its performance.
You have put together your own entry and exit criteria and are looking for a filter that will help you improve backtesting results. You visually ascertain the suitability of your filter by looking at its results on the charts with great Expectations, to see if your filter is choosing its areas correctly.
You have a strategy that shows backtested trades on your chart. Great Expectations can help you evaluate how well your strategy is benefitting from high-opportunity areas while avoiding poor expectation spots.
You want more complete statistics on your set of strategies than what backtesting will provide. You use Great Expectations, knowing that it tests all bars in the sample that correspond to your criteria, as opposed to backtesting results which are limited to a subset of all possible entries.
You want to fool your friends into thinking you’ve designed the holy grail of indicators, something that identifies optimal opportunities on any chart; you show them the P&L cloud.
FEATURES
For one trade
At any given point on the chart, assuming a trade is entered there, Great Expectations shows you information specific to that trade simulation both on the chart and in the Data Window.
The chart can display:
the P & L Cloud which shows whether the trade ended profitably or not, and by how much,
the Opportunity & Risk Cloud which the maximum opportunity and risk the simulation encountered. When superimposed over the P & L cloud, you will see what I call the managed opportunity and risk, i.e the portion of maximum opportunity that was captured and the portion of the maximum risk that was incurred,
the target and if it was reached,
a background that uses a gradient to show different levels of trade length, P&L or how frequently the target was reached during simulation.
The Data Window displays more than 40 values on individual trades and global results. For any given trade you will know:
Entry/Exit levels, including slippage impact,
It’s outcome and duration,
P/L achieved,
The fraction of the maximum opportunity/risk managed by the trade.
For all trades
After going through all the possible trades on the chart, the indicator will provide you with a rare view of all outcomes expressed with the P&L cloud, which allows us to instantly see the most/least profitable areas of a chart using trade data as support, while also showing its relationship with the opportunity/risk encountered during the simulation. The difference between the two clouds is the managed opportunity and risk.
The Data Window will present you with numbers which we will go through later. Some of them are: average stop size, P/L, win rate, % opportunity managed, trade lengths for different types of trade outcomes and the TST (Target:Stop Travel) ratio.
Let’s see Great Expectations in action… and remember to open your Data Window!
INPUTS
Trade direction : You must first choose if you wish to look at long or short trades. Because of the way the indicator works and the amount of visual information on the chart, it is only practical to look at one type of trades at a time. The default is Longs.
Maximum trade Length (MaxL) : This is the maximum walk forward distance the simulator will go in analyzing outcomes from any given point in the past. It also determines the size of the dead zone among the chart’s last bars. A red background line identifies the beginning of the dead zone for which not enough bars have elapsed to analyze outcomes for the maximum trade length defined. If an ATR-based entry stop is used, that length is added to the wait time before beginning simulations, so that the first entry starts with a clean ATR value. On a sample of around 16000 bars, my tests show that the indicator runs into server errors at lengths of around 290, i.e. having completed ~4,6M simulation loop iterations. That is way too high a length anyways; 100 will usually be amply enough to ring out all the possibilities out of a simulation, and on shorter time frames, 30 can be enough. While making it unduly small will prevent simulations of expressing the market’s potential, the less you use, the faster the indicator will run. The default is 40.
Unrealized P&L base at End of Trade (EOT) : When a simulation ends and the trade is still open, we calculate unrealized P&L from an exit order executed from either the last in-trade stop on the previous bar, or the close of the last bar. You can readily see the impact of this selection on the chart, with the P&L cloud. The default is on the close.
Display : The check box besides the title does nothing.
Show target : Shows a green line displaying the trade’s target expressed as a multiple of X, i.e. the amplitude of the entry stop. I call this value “X” and use it as a unit to express profit and loss on a trade (some call it “R”). The line is highlighted for trades where the close reached the target during the trade, whether the trade ended in profit or loss. This is also where you specify the multiple of X you wish to use in calculating targets. The multiple is used even if targets are not displayed.
Show P&L Cloud : The cloud allows traders to see right away the profitable areas of the chart. The only line printed with the cloud is the “end of trade line” (EOT). The EOT line is the only way one can see the level where a trade ended on the chart (in the Data Window you can see it as the “Exit Fill” value). The EOT level for the trade determines if the trade ended in a profit or a loss. Its value represents one of the following:
- fill from order executed at close of bar where stop is breached during trade (which produces “Realized P/L”),
- simulation of a fill pseudo-fill at the user-defined EOT level (last close or stop level) if the trade runs its course through MaxL bars without getting stopped (producing Unrealized P/L).
The EOT line and the cloud fill print in green when the trade’s outcome is profitable and in red when it is not. If the trade was closed after breaching the stop, the line appears brighter.
Show Opportunity&Risk Cloud : Displays the maximum opportunity/risk that was present during the trade, i.e. the maximum and minimum prices reached.
Background Color Scheme : Allows you to choose between 3 different color schemes for the background gradients, to accommodate different types of chart background/candles. Select “None” if you don’t want a background.
Background source : Determines what value will be used to generate the different intensities of the gradient. You can choose trade length (brighter is shorter), Trade P&L (brighter is higher) or the number of times the target was reached during simulation (brighter is higher). The default is Trade Length.
Entry strat : The check box besides the title does nothing. The default strat is All bars, meaning a trade will be simulated from all bars not excluded by the filters where a MaxL bars future exists. For fun, I’ve included a pseudo-random entry strat (an indirect way of changing the seed is to vary the starting date of the simulation).
Show Filter State : Displays areas where the combination of filters you have selected are allowing entries. Filtering occurs as per your selection(s), whether the state is displayed or not. The effect of multiple selections is additive. The filters are:
1. Bar direction: Longs will only be entered if close>open and vice versa.
2. Rising Volume: Applies to both long and shorts.
3. Rising/falling MA of the length you choose over the number of bars you choose.
4. Custom indicator: You can feed your own filtering signal through this from another indicator. It must produce a signal of 1 to allow long entries and 0 to allow shorts.
Show Entry Stops :
1. Multiple of user-defined length ATR.
2. Fixed percentage.
3. Fixed value.
All entry stops are calculated using the entry fill price as a reference. The fill price is calculated from the current bar’s open, to which slippage is added if configured. This simulates the case where the strategy issued the entry signal on the previous bar for it to be executed at the next bar’s open.
The entry stop remains active until the in-trade stop becomes the more aggressive of the two stops. From then on, the entry stop will be ignored, unless a bar close breaches the in-trade stop, in which case the stop will be reset with a new entry stop and the process repeats.
Show In-trade stops : Displays in bright red the selected in-trade stop (be sure to read the note in this section about them).
1. ATR multiple: added/subtracted from the average of the two previous bars minimum/maximum of open/close.
2. A trailing stop with a deviation expressed as a multiple of entry stop (X).
3. A fixed percentage trailing stop.
Trailing stops deviations are measured from the highest/lowest high/low reached during the trade.
Note: There is a twist with the in-trade stops. It’s that for any given bar, its in-trade stop can hold multiple values, as each successive pass of the advancing simulation loops goes over it from a different entry points. What is printed is the stop from the loop that ended on that bar, which may have nothing to do with other instances of the trade’s in-trade stop for the same bar when visited from other starting points in previous simulations. There is just no practical way to print all stop values that were used for any given bar. While the printed entry stops are the actual ones used on each bar, the in-trade stops shown are merely the last instance used among many.
Include Slippage : if checked, slippage will be added/subtracted from order price to yield the fill price. Slippage is in percentage. If you choose to include slippage in the simulations, remember to adjust it by considering the liquidity of the markets and the time frame you’ll be analyzing.
Include Fees : if checked, fees will be subtracted/added to both realized an unrealized trade profits/losses. Fees are in percentage. The default fees work well for crypto markets but will need adjusting for others—especially in Forex. Remember to modify them accordingly as they can have a major impact on results. Both fees and slippage are included to remind us of their importance, even if the global numbers produced by the indicator are not representative of a real trading scenario composed of sequential trades.
Date Range filtering : the usual. Just note that the checkbox has to be selected for date filtering to activate.
DATA WINDOW
Most of the information produced by this indicator is made available in the Data Window, which you bring up by using the icon below the Watchlist and Alerts buttons at the right of the TV UI. Here’s what’s there.
Some of the information presented in the Data Window is standard trade data; other values are not so standard; e. g. the notions of managed opportunity and risk and Target:Stop Travel ratio. The interplay between all the values provided by Great Expectations is inherently complex, even for a static set of entry/filter/exit strats. During the constant updating which the habitual process of progressive refinement in building strategies that is the lot of strategy modelers entails, another level of complexity is no doubt added to the analysis of this indicator’s values. While I don’t want to sound like Wolfram presenting A New Kind of Science , I do believe that if you are a serious strategy modeler and spend the time required to get used to using all the information this indicator makes available, you may find it useful.
Trade Information
Entry Order : This is the open of the bar where simulation starts. We suppose that an entry signal was generated at the previous bar.
Entry Fill (including slip.) : The actual entry price, including slippage. This is the base price from which other values will be calculated.
Exit Order : When a stop is breached, an exit order is executed from the close of the bar that breached the stop. While there is no “In-trade stop” value included in the Data Window (other than the End of trade Stop previously discussed), this “Exit Order” value is how we can know the level where the trade was stopped during the simulation. The “Trade Length” value will then show the bar where the stop was breached.
Exit Fill (including slip.) : When the exit order is simulated, slippage is added to the order level to create the fill.
Chart: Target : This is the target calculated at the beginning of the simulation. This value also appear on the chart in teal. It is controlled by the multiple of X defined under the “Show Target” checkbox in the Inputs.
Chart: Entry Stop : This value also appears on the chart (the red dots under points where a trade was simulated). Its value is controlled by the Entry Strat chosen in the Inputs.
X (% Fill, including Fees) and X (currency) : This is the stop’s amplitude (Entry Fill – Entry Stop) + Fees. It represents the risk incurred upon entry and will be used to express P&L. We will show R expressed in both a percentage of the Entry Fill level (this value), and currency (the next value). This value represents the risk in the risk:reward ratio and is considered to be a unit of 1 so that RR can be expressed as a single value (i.e. “2” actually meaning “1:2”).
Trade Length : If trade was stopped, it’s the number of bars elapsed until then. The trade is then considered “Closed”. If the trade ends without being stopped (there is no profit-taking strat implemented, so the stop is the only exit strat), then the trade is “Open”, the length is MaxL and it will show in orange. Otherwise the value will print in green/red to reflect if the trade is winning/losing.
P&L (X) : The P&L of the trade, expressed as a multiple of X, which takes into account fees paid at entry and exit. Given our default target setting at 2 units of “X”, a trade that closes at its target will have produced a P&L of +2.0, i.e. twice the value of X (not counting fees paid at exit ). A trade that gets stopped late 50% further that the entry stop’s level will produce a P&L of -1.5X.
P&L (currency, including Fees) : same value as above, but expressed in currency.
Target first reached at bar : If price closed above the target during the trade (even if it occurs after the trade was stopped), this will show when. This value will be used in calculating our TST ratio.
Times Stop/Target reached in sim. : Includes all occurrences during the complete simulation loop.
Opportunity (X) : The highest/lowest price reached during a simulation, i.e. the maximum opportunity encountered, whether the trade was previously stopped or not, expressed as a multiple of X.
Risk (X) : The lowest/highest price reached during a simulation, i.e. the maximum risk encountered, whether the trade was previously stopped or not, expressed as a multiple of X.
Risk:Opportunity : The greater this ratio, the greater Opportunity is, compared to Risk.
Managed Opportunity (%) : The portion of Opportunity that was captured by the highest/low stop position, even if it occurred after a previous stop closed the trade.
Managed Risk (%) : The portion of risk that was protected by the lowest/highest stop position, even if it occurred after a previous stop closed the trade. When this value is greater than 100%, it means the trade’s stop is protecting more than the maximum risk, which is frequent. You will, however, never see close to those values for the Managed Opportunity value, since the stop would have to be higher than the Maximum opportunity. It is much easier to alleviate the risk than it is to lock in profits.
Managed Risk:Opportunity : The ratio of the two preceding values.
Managed Opp. vs. Risk : The Managed Opportunity minus the Managed Risk. When it is negative, which is most often is, it means your strat is protecting a greater portion of the risk than it captures opportunity.
Global Numbers
Win Rate(%) : Percentage of winning trades over all entries. Open trades are considered winning if their last stop/close (as per user selection) locks in profits.
Avg X%, Avg X (currency) : Averages of previously described values:.
Avg Profitability/Trade (APPT) : This measures expectation using: Average Profitability Per Trade = (Probability of Win × Average Win) − (Probability of Loss × Average Loss) . It quantifies the average expectation/trade, which RR alone can’t do, as the probabilities of each outcome (win/lose) must also be used to calculate expectancy. The APPT combine the RR with the win rate to yield the true expectancy of a strategy. In my usual way of expressing risk with X, APPT is the equivalent of the average P&L per trade expressed in X. An APPT of -1.5 means that we lose on average 1.5X/trade.
Equity (X), Equity (currency) : The cumulative result of all trade outcomes, expressed as a multiple of X. Multiplied by the Average X in currency, this yields the Equity in currency.
Risk:Opportunity, Managed Risk:Opportunity, Managed Opp. vs. Risk : The global values of the ones previously described.
Avg Trade Length (TL) : One of the most important values derived by going through all the simulations. Again, it is composed of either the length of stopped trades, or MaxL when the trade isn’t stopped (open). This value can help systems modelers shape the characteristics of the components they use to build their strategies.
Avg Closed Win TL and Avg Closed Lose TL : The average lengths of winning/losing trades that were stopped.
Target reached? Avg bars to Stop and Target reached? Avg bars to Target : For the trades where the target was reached at some point in the simulation, the number of bars to the first point where the stop was breached and where the target was reached, respectively. These two values are used to calculate the next value.
TST (Target:Stop Travel Ratio) : This tracks the ratio between the two preceding values (Bars to first stop/Bars to first target), but only for trades where the target was reached somewhere in the loop. A ratio of 2 means targets are reached twice as fast as stops.
The next values of this section are counts or percentages and are self-explanatory.
Chart Plots
Contains chart plots of values already describes.
NOTES
Optimization/Overfitting: There is a fine line between optimizing and overfitting. Tools like this indicator can lead unsuspecting modelers down a path of overfitting that often turns strategies into over-specialized beasts that do not perform elegantly when confronted to the real-world. Proven testing strategies like walk forward analysis will go a long way in helping modelers alleviate this risk.
Input tuning: Because the results generated by the indicator will vary with the parameters used in the active entry, filtering and exit strats, it’s important to realize that although it may be fun at first, just slapping the default settings on a chart and time frame will not yield optimal nor reliable results. While using ATR as often as possible (as I do in this indicator) is a good way to make strat parametrization adaptable, it is not a foolproof solution.
There is no data for the last MaxL bars of the chart, since not enough trade future has elapsed to run a simulation from MaxL bars back.
Modifying the code: I have tried to structure the code modularly, even if that entails a larger code base, so that you can adapt it to your needs. I’ve included a few token components in each of the placeholders designed for entry strategies, filters, entry stops and in-trade stops. This will hopefully make it easier to add your own. In the same spirit, I have also commented liberally.
You will find in the code many instances of standard trade management tasks that can be lifted to code TV strategies where, as I do in mine, you manage everything yourself and don’t rely on built-in Pine strategy functions to act on your trades.
Enjoy!
THANKS
To @scarf who showed me how plotchar() could be used to plot values without ruining scale.
To @glaz for the suggestion to include a Chandelier stop strat; I will.
To @simpelyfe for the idea of using an indicator input for the filters (if some day TV lets us use more than one, it will be useful in other modules of the indicator).
To @RicardoSantos for the random generator used in the random entry strat.
To all scripters publishing open source on TradingView; their code is the best way to learn.
To my trading buddies Irving and Bruno; who showed me way back how pro traders get it done.
Ultimate MACD [captainua]Ultimate MACD - Comprehensive MACD Trading System
Overview
This indicator combines traditional MACD calculations with advanced features including divergence detection, volume analysis, histogram analysis tools, regression forecasting, strong top/bottom detection, and multi-timeframe confirmation to provide a comprehensive MACD-based trading system. The script calculates MACD using configurable moving average types (EMA, SMA, RMA, WMA) and applies various smoothing methods to reduce noise while maintaining responsiveness. The combination of these features creates a multi-layered confirmation system that reduces false signals by requiring alignment across multiple indicators and timeframes.
Core Calculations
MACD Calculation:
The script calculates MACD using the standard formula: MACD Line = Fast MA - Slow MA, Signal Line = Moving Average of MACD Line, Histogram = MACD Line - Signal Line. The default parameters are Fast=12, Slow=26, Signal=9, matching the traditional MACD settings. The script supports four moving average types:
- EMA (Exponential Moving Average): Standard and most responsive, default choice
- SMA (Simple Moving Average): Equal weight to all periods
- RMA (Wilder's Moving Average): Smoother, less responsive
- WMA (Weighted Moving Average): Recent prices weighted more heavily
The price source can be configured as Close (standard), Open, High, Low, HL2, HLC3, or OHLC4. Alternative sources provide different sensitivity characteristics for various trading strategies.
Configuration Presets:
The script includes trading style presets that automatically configure MACD parameters:
- Scalping: Fast/Responsive settings (8,18,6 with minimal smoothing)
- Day Trading: Balanced settings (10,22,7 with minimal smoothing)
- Swing Trading: Standard settings (12,26,9 with moderate smoothing)
- Position Trading: Smooth/Conservative settings (15,35,12 with higher smoothing)
- Custom: Full manual control over all parameters
Histogram Smoothing:
The histogram can be smoothed using EMA to reduce noise and filter minor fluctuations. Smoothing length of 1 = raw histogram (no smoothing), higher values (3-5) = smoother histogram. Increased smoothing reduces noise but may delay signals slightly.
Percentage Mode:
MACD values can be converted to percentage of price (MACD/Close*100) for cross-instrument comparison. This is useful when comparing MACD signals across instruments with different price levels (e.g., BTC vs ETH). The percentage mode normalizes MACD values, making them comparable regardless of instrument price.
MACD Scale Factor:
A scale factor multiplier (default 1.0) allows adjusting MACD display size for better visibility. Use 0.3-0.5 if MACD appears too compressed, or 2.0-3.0 if too small.
Dynamic Overbought/Oversold Levels:
Overbought and oversold levels are calculated dynamically based on MACD's mean and standard deviation over a lookback period. The formula: OB = MACD Mean + (StdDev × OB Multiplier), OS = MACD Mean - (StdDev × OS Multiplier). This adapts to current market conditions, widening in volatile markets and narrowing in calm markets. The lookback period (default 20) controls how quickly the levels adapt: longer periods (30-50) = more stable levels, shorter (10-15) = more responsive.
OB/OS Background Coloring:
Optional background coloring can highlight the entire panel when MACD enters overbought or oversold territory, providing prominent visual indication of extreme conditions. The background colors are drawn on top of the main background to ensure visibility.
Divergence Detection
Regular Divergence:
The script uses the MACD line (not histogram) for divergence detection, which provides more reliable signals. Bullish divergence: Price makes a lower low while MACD line makes a higher low. Bearish divergence: Price makes a higher high while MACD line makes a lower high. Divergences often precede reversals and are powerful reversal signals.
Pivot-Based Divergence:
The divergence detection uses actual pivot points (pivotlow/pivothigh) instead of simple lowest/highest comparisons. This provides more accurate divergence detection by identifying significant pivot lows/highs in both price and MACD line. The pivot-based method compares two recent pivot points: for bullish divergence, price makes a lower low while MACD makes a higher low at the pivot points. This method reduces false divergences by requiring actual pivot points rather than just any low/high within a period.
The pivot lookback parameters (left and right) control how many bars on each side of a pivot are required for confirmation. Higher values = more conservative pivot detection.
Hidden Divergence:
Continuation patterns that signal trend continuation rather than reversal. Bullish hidden divergence: Price makes a higher low but MACD makes a lower low. Bearish hidden divergence: Price makes a lower high but MACD makes a higher high. These patterns indicate the trend is likely to continue in the current direction.
Zero-Line Filter:
The "Don't Touch Zero Line" option ensures divergences occur in proper context: for bullish divergence, MACD must stay below zero; for bearish divergence, MACD must stay above zero. This filters out divergences that occur in neutral zones.
Range Filtering:
Minimum and maximum lookback ranges control the time window between pivots to consider for divergence. This helps filter out divergences that are too close together (noise) or too far apart (less relevant).
Volume Confirmation System
Volume threshold filtering requires current volume to exceed the volume SMA multiplied by the threshold factor. The formula: Volume Confirmed = Volume > (Volume SMA × Threshold). If the threshold is set to 1.0 or lower, volume confirmation is effectively disabled (always returns true). This allows you to use the indicator without volume filtering if desired. Volume confirmation significantly increases divergence and signal reliability.
Volume Climax and Dry-Up Detection:
The script can mark bars with extremely high volume (volume climax) or extremely low volume (volume dry-up). Volume climax indicates potential reversal points or strong momentum continuation. Volume dry-up indicates low participation and may produce unreliable signals. These markers use standard deviation multipliers to identify extreme volume conditions.
Zero-Line Cross Detection
MACD zero-line crosses indicate momentum shifts: above zero = bullish momentum, below zero = bearish momentum. The script includes alert conditions for zero-line crosses with cooldown protection to prevent alert spam. Zero-line crosses can provide early warning signals before MACD crosses the signal line.
Histogram Analysis Tools
Histogram Moving Average:
A moving average applied to the histogram itself helps identify histogram trend direction and acts as a signal line for histogram movements. Supports EMA, SMA, RMA, and WMA types. Useful for identifying when histogram momentum is strengthening or weakening.
Histogram Bollinger Bands:
Bollinger Bands are applied to the MACD histogram instead of price. The calculation: Basis = SMA(Histogram, Period), StdDev = stdev(Histogram, Period), Upper = Basis + (StdDev × Deviation Multiplier), Lower = Basis - (StdDev × Deviation Multiplier). This creates dynamic zones around the histogram that adapt to histogram volatility. When the histogram touches or exceeds the bands, it indicates extreme conditions relative to recent histogram behavior.
Stochastic MACD (StochMACD):
Stochastic MACD applies the Stochastic oscillator formula to the MACD histogram instead of price. This normalizes the histogram to a 0-100 scale, making it easier to identify overbought/oversold conditions on the histogram itself. The calculation: %K = ((Histogram - Lowest Histogram) / (Highest Histogram - Lowest Histogram)) × 100. %K is smoothed, and %D is calculated as the moving average of smoothed %K. Standard thresholds are 80 (overbought) and 20 (oversold).
Regression Forecasting
The script includes advanced regression forecasting that predicts future MACD values using mathematical models. This helps anticipate potential MACD movements and provides forward-looking context for trading decisions.
Regression Types:
- Linear: Simple trend line (y = mx + b) - fastest, works well for steady trends
- Polynomial: Quadratic curve (y = ax² + bx + c) - captures curvature in MACD movement
- Exponential Smoothing: Weighted average with more weight on recent values - responsive to recent changes
- Moving Average: Uses difference between short and long MA to estimate trend - stable and smooth
Forecast Horizon:
Number of bars to forecast ahead (default 5, max 50 for linear/MA, max 20 for polynomial due to performance). Longer horizons predict further ahead but may be less accurate.
Confidence Bands:
Optional upper/lower bands around forecast show prediction uncertainty based on forecast error (standard deviation of prediction vs actual). Wider bands = higher uncertainty. The confidence level multiplier (default 1.5) controls band width.
Forecast Display:
Forecast appears as dotted lines extending forward from current bar, with optional confidence bands. All forecast values respect percentage mode and scale factor settings.
Strong Top/Bottom Signals
The script detects strong recovery from extreme MACD levels, generating "sBottom" and "sTop" signals. These identify significant reversal potential when MACD recovers substantially from overbought/oversold extremes.
Strong Bottom (sBottom):
Triggered when:
1. MACD was at or near its lowest point in the bottom period (default 10 bars)
2. MACD was in or near the oversold zone
3. MACD has recovered by at least the threshold amount (default 0.5) from the lowest point
4. Recovery persists for confirmation bars (default 2 consecutive bars)
5. MACD has moved out of the oversold zone
6. Volume is above average
7. All enabled filters pass
8. Minimum bars have passed since last signal (reset period, default 5 bars)
Strong Top (sTop):
Triggered when:
1. MACD was at or near its highest point in the top period (default 7 bars)
2. MACD was in or near the overbought zone
3. MACD has declined by at least the threshold amount (default 0.5) from the highest point
4. Decline persists for confirmation bars (default 2 consecutive bars)
5. MACD has moved out of the overbought zone
6. Volume is above average
7. All enabled filters pass
8. Minimum bars have passed since last signal (reset period, default 5 bars)
Label Placement:
sTop/sBottom labels appear on the historical bar where the actual extreme occurred (not on current bar), showing the exact MACD value at that extreme. Labels respect the unified distance checking system to prevent overlaps with Buy/Sell Strength labels.
Signal Strength Calculation
The script calculates a composite signal strength score (0-100) based on multiple factors:
- MACD distance from signal line (0-50 points): Larger separation indicates stronger signal
- Volume confirmation (0-15 points): Volume above average adds points
- Secondary timeframe alignment (0-15 points): Higher timeframe agreement adds points
- Distance from zero line (0-20 points): Closer to zero can indicate stronger reversal potential
Higher scores (70+) indicate stronger, more reliable signals. The signal strength is displayed in the statistics table and can be used as a filter to only accept signals above a threshold.
Smart Label Placement System
The script includes an advanced label placement system that tracks MACD extremes and places Buy/Sell Strength labels at optimal locations:
Label Placement Algorithm:
- Labels appear on the current bar at confirmation (not on historical extreme bars), ensuring they're visible when the signal is confirmed
- The system tracks pending signals when MACD enters OB/OS zones or crosses the signal line
- During tracking, the system continuously searches for the true extreme (lowest MACD for buys, highest MACD for sells) within a configurable historical lookback period
- Labels are only finalized when: (1) MACD exits the OB/OS zone, (2) sufficient bars have passed (2x minimum distance), (3) MACD has recovered/declined by a configurable percentage from the extreme (default 15%), and (4) tracking has stopped (no better extreme found)
Label Spacing and Overlap Prevention:
- Minimum Bars Between Labels: Base distance requirement (default 5 bars)
- Label Spacing Multiplier: Scales the base distance (default 1.5x) for better distribution. Higher values = more spacing between labels
- Effective distance = Base Distance × Spacing Multiplier (e.g., 5 × 1.5 = 7.5 bars minimum)
- Unified distance checking prevents overlaps between all label types (Buy Strength, Sell Strength, sTop, sBottom)
Strength-Based Filtering:
- Label Strength Minimum (%): Only labels with strength at or above this threshold are displayed (default 75%)
- When multiple potential labels are close together, the system automatically compares strengths and keeps only the strongest one
- This ensures only the most significant signals are displayed, reducing chart clutter
Zero Line Polarity Enforcement:
- Enforce Zero Line Polarity (default enabled): Ensures labels follow traditional MACD interpretation
- Buy Strength labels only appear when the tracked extreme MACD value was below zero (negative territory)
- Sell Strength labels only appear when the tracked extreme MACD value was above zero (positive territory)
- This prevents counter-intuitive labels (e.g., Buy labels above zero line) and aligns with standard MACD trading principles
Recovery/Decline Confirmation:
- Recovery/Decline Confirm (%): Percent move away from the extreme required before finalizing (default 15%)
- For Buy labels: MACD must recover by at least this percentage from the tracked bottom
- For Sell labels: MACD must decline by at least this percentage from the tracked top
- Higher values = more confirmation required, fewer but more reliable labels
Historical Lookback:
- Historical Lookback for Label Placement: Number of bars to search for true extremes (default 20)
- The system searches within this period to find the actual lowest/highest MACD value
- Higher values analyze more history but may be slower; lower values are faster but may miss some extremes
Cross Quality Score
The script calculates a MACD cross quality score (0-100) that rates crossover quality based on:
- Cross angle (0-50 points): Steeper crosses = stronger signals
- Volume confirmation (0-25 points): Volume above average adds points
- Distance from zero line (0-25 points): Crosses near zero line are stronger
This score helps identify high-quality crossovers and can be used as a filter to only accept signals meeting minimum quality threshold.
Filtering System
Histogram Filter:
Requires histogram to be above zero for buy signals, below zero for sell signals. Ensures momentum alignment before generating signals.
Signal Strength Filter:
Requires minimum signal strength score for signals. Higher threshold = only strongest signals pass. This combines multiple confirmation factors into a single filter.
Cross Quality Filter:
Requires minimum cross quality score for signals. Rates crossover quality based on angle, volume, momentum, and distance from zero. Only signals meeting minimum quality threshold will be generated.
All filters use the pattern: filterResult = not filterEnabled OR conditionMet. This means if a filter is disabled, it always passes (returns true). Filters can be combined, and all must pass for a signal to fire.
Multi-Timeframe Analysis
The script can display MACD from a secondary (higher) timeframe and use it for confirmation. When secondary timeframe confirmation is enabled, signals require the higher timeframe MACD to align (bullish/bearish) with the signal direction. This ensures signals align with the larger trend context, reducing counter-trend trades.
Secondary Timeframe MACD:
The secondary timeframe MACD uses the same calculation parameters (fast, slow, signal, MA type) as the main MACD but from a higher timeframe. This provides context for the current timeframe's MACD position relative to the larger trend. The secondary MACD lines are displayed on the chart when enabled.
Noise Filtering
Noise filtering hides small histogram movements below a threshold. This helps focus on significant moves and reduces chart clutter. When enabled, only histogram movements above the threshold are displayed. Typical threshold values are 0.1-0.5 for most instruments, depending on the instrument's price range and volatility.
Signal Debounce
Signal debounce prevents duplicate MACD cross signals within a short time period. Useful when MACD crosses back and forth quickly, creating multiple signals. Debounce ensures only one signal per period, reducing signal spam during choppy markets. This is separate from alert cooldown, which applies to all alert types.
Background Color Modes
The script offers three background color modes:
- Dynamic: Full MACD heatmap based on OB/OS conditions, confidence, and momentum. Provides rich visual feedback.
- Monotone: Soft neutral background but still allows overlays (OB/OS zones). Keeps the chart clean without overpowering candles.
- Off: No MACD background (only overlays and plots). Maximum chart cleanliness.
When OB/OS background colors are enabled, they are drawn on top of the main background to ensure visibility.
Statistics Table
A real-time statistics table displays current MACD values, signal strength, distance from zero line, secondary timeframe alignment, volume confirmation status, and all active filter statuses. The table dynamically adjusts to show only enabled features, keeping it clean and relevant. The table position can be configured (Top Left, Top Right, Bottom Left, Bottom Right).
Performance Statistics Table
An optional performance statistics table shows comprehensive filter diagnostics:
- Total buy/sell signals (raw crossover count before filters)
- Filtered buy/sell signals (signals that passed all filters)
- Overall pass rates (percentage of signals that passed filters)
- Rejected signals count
- Filter-by-filter rejection diagnostics showing which filters rejected how many signals
This table helps optimize filter settings by showing which filters are most restrictive and how they impact signal frequency. The diagnostics format shows rejections as "X B / Y S" (X buy signals rejected, Y sell signals rejected) or "Disabled" if the filter is not active.
Alert System
The script includes separate alert conditions for each signal type:
- MACD Cross: MACD line crosses above/below Signal line (with or without secondary confirmation)
- Zero-Line Cross: MACD crosses above/below zero
- Divergence: Regular and hidden divergence detections
- Secondary Timeframe: Higher timeframe MACD crosses
- Histogram MA Cross: Histogram crosses above/below its moving average
- Histogram Zero Cross: Histogram crosses above/below zero
- StochMACD: StochMACD overbought/oversold entries and %K/%D crosses
- Histogram BB: Histogram touches/breaks Bollinger Bands
- Volume Events: Volume climax and dry-up detections
- OB/OS: MACD entry/exit from overbought/oversold zones
- Strong Top/Bottom: sTop and sBottom signal detections
Each alert type has its own cooldown system to prevent alert spam. The cooldown requires a minimum number of bars between alerts of the same type, reducing duplicate alerts during volatile periods. Alert types can be filtered to only evaluate specific alert types (All, MACD Cross, Zero Line, Divergence, Secondary Timeframe, Histogram MA, Histogram Zero, StochMACD, Histogram BB, Volume Events, OB/OS, Strong Top/Bottom).
How Components Work Together
MACD crossovers provide the primary signal when the MACD line crosses the Signal line. Zero-line crosses indicate momentum shifts and can provide early warning signals. Divergences identify potential reversals before they occur.
Volume confirmation ensures signals occur with sufficient market participation, filtering out low-volume false breakouts. Histogram analysis tools (MA, Bollinger Bands, StochMACD) provide additional context for signal reliability and identify significant histogram zones.
Signal strength combines multiple confirmation factors into a single score, making it easy to filter for only the strongest signals. Cross quality score rates crossover quality to identify high-quality setups. Multi-timeframe confirmation ensures signals align with higher timeframe trends, reducing counter-trend trades.
Usage Instructions
Getting Started:
The default configuration shows MACD(12,26,9) with standard EMA calculations. Start with default settings and observe behavior, then customize settings to match your trading style. You can use configuration presets for quick setup based on your trading style.
Customizing MACD Parameters:
Adjust Fast Length (default 12), Slow Length (default 26), and Signal Length (default 9) based on your trading timeframe. Shorter periods (8,17,7) for faster signals, longer (15,30,12) for smoother signals. You can change the moving average type: EMA for responsiveness, RMA for smoothness, WMA for recent price emphasis.
Price Source Selection:
Choose Close (standard), or alternative sources (HL2, HLC3, OHLC4) for different sensitivity. HL2 uses the midpoint of the high-low range, HLC3 and OHLC4 incorporate more price information.
Histogram Smoothing:
Set smoothing to 1 for raw histogram (no smoothing), or increase (3-5) for smoother histogram that reduces noise. Higher smoothing reduces false signals but may delay signals slightly.
Percentage Mode:
Enable percentage mode when comparing MACD across instruments with different price levels. This normalizes MACD values, making them directly comparable.
Dynamic OB/OS Levels:
The dynamic thresholds automatically adapt to volatility. Adjust the multipliers (default 1.5) to fine-tune sensitivity: higher values (2.0-3.0) = more extreme thresholds (fewer signals), lower (1.0-1.5) = more frequent signals. Adjust the lookback period to control how quickly levels adapt. Enable OB/OS background colors for visual indication of extreme conditions.
Volume Confirmation:
Set volume threshold to 1.0 (default, effectively disabled) or higher (1.2-1.5) for standard confirmation. Higher values require more volume for confirmation. Set to 0.1 to completely disable volume filtering.
Filters:
Enable filters gradually to find your preferred balance. Start with histogram filter for basic momentum alignment, then add signal strength filter (threshold 50+) for moderate signals, then cross quality filter (threshold 50+) for high-quality crossovers. Combine filters for highest-quality signals but expect fewer signals.
Divergence:
Enable divergence detection and adjust pivot lookback parameters. Pivot-based divergence provides more accurate detection using actual pivot points. Hidden divergence is useful for trend-following strategies. Adjust range parameters to filter divergences by time window.
Zero-Line Crosses:
Zero-line cross alerts are automatically available when alerts are enabled. These provide early warning signals for momentum shifts.
Histogram Analysis Tools:
Enable Histogram Moving Average to see histogram trend direction. Enable Histogram Bollinger Bands to identify extreme histogram zones. Enable Stochastic MACD to normalize histogram to 0-100 scale for overbought/oversold identification.
Multi-Timeframe:
Enable secondary timeframe MACD to see higher timeframe context. Enable secondary confirmation to require higher timeframe alignment for signals.
Signal Strength:
Signal strength is automatically calculated and displayed in the statistics table. Use signal strength filter to only accept signals above a threshold (e.g., 50 for moderate, 70+ for strong signals only).
Smart Label Placement:
Configure label placement settings to control label appearance and quality:
- Label Strength Minimum (%): Set threshold (default 75%) to show only strong signals. Higher = fewer, stronger labels
- Label Spacing Multiplier: Adjust spacing (default 1.5x) for better distribution. Higher = more spacing between labels
- Recovery/Decline Confirm (%): Set confirmation requirement (default 15%). Higher = more confirmation, fewer labels
- Enforce Zero Line Polarity: Enable (default) to ensure Buy labels only appear when tracked extreme was below zero, Sell labels only when above zero
- Historical Lookback: Adjust search period (default 20 bars) for finding true extremes. Higher = more history analyzed
Cross Quality:
Cross quality score is automatically calculated for crossovers. Use cross quality filter to only accept high-quality crossovers (threshold 50+ for moderate, 70+ for high quality).
Alerts:
Set up alerts for your preferred signal types. Enable alert cooldown (default enabled, 5 bars) to prevent alert spam. Use alert type filter to only evaluate specific alert types (All, MACD Cross, Zero Line, Divergence, Secondary Timeframe, Histogram MA, Histogram Zero, StochMACD, Histogram BB, Volume Events, OB/OS, Strong Top/Bottom). Each signal type has its own alert condition, so you can be selective about which signals trigger alerts.
Visual Elements and Signal Markers
The script uses various visual markers to indicate signals and conditions:
- MACD Line: Green when above signal (bullish), red when below (bearish) if dynamic colors enabled. Optional black outline for enhanced visibility
- Signal Line: Orange line with optional black outline for enhanced visibility
- Histogram: Color-coded based on direction and momentum (green for bullish rising, lime for bullish falling, red for bearish falling, orange for bearish rising)
- Zero Line: Horizontal reference line at MACD = 0
- Fill to Zero: Green/red semi-transparent fill between MACD line and zero line showing bullish/bearish territory
- Fill Between OB/OS: Blue semi-transparent fill between overbought/oversold thresholds highlighting neutral zone
- OB/OS Background Colors: Background coloring when MACD enters overbought/oversold zones
- Background Colors: Dynamic or monotone backgrounds indicating MACD state, or custom chart background
- Divergence Labels: "🐂" for bullish, "🐻" for bearish, "H Bull" for hidden bullish, "H Bear" for hidden bearish
- Divergence Lines: Colored lines connecting pivot points when divergences are detected
- Volume Climax Markers: ⚡ symbol for extremely high volume
- Volume Dry-Up Markers: 💧 symbol for extremely low volume
- Buy/Sell Strength Labels: Show signal strength percentage (e.g., "Buy Strength: 75%")
- Strong Top/Bottom Labels: "sTop" and "sBottom" for extreme level recoveries
- Secondary MACD Lines: Purple lines showing higher timeframe MACD
- Histogram MA: Orange line showing histogram moving average
- Histogram BB: Blue bands around histogram showing extreme zones
- StochMACD Lines: %K and %D lines with overbought/oversold thresholds
- Regression Forecast: Dotted blue lines extending forward with optional confidence bands
Signal Priority and Interpretation
Signals are generated independently and can occur simultaneously. Higher-priority signals generally indicate stronger setups:
1. MACD Cross with Multiple Filters - Highest priority: Requires MACD crossover plus all enabled filters (histogram, signal strength, cross quality) and secondary timeframe confirmation if enabled. These are the most reliable signals.
2. Zero-Line Cross - High priority: Indicates momentum shift. Can provide early warning signals before MACD crosses the signal line.
3. Divergence Signals - Medium-High priority: Pivot-based divergence is more reliable than simple divergence. Hidden divergence indicates continuation rather than reversal.
4. MACD Cross with Basic Filters - Medium priority: MACD crosses signal line with basic histogram filter. Less reliable alone but useful when combined with other confirmations.
Best practice: Wait for multiple confirmations. For example, a MACD crossover combined with divergence, volume confirmation, and secondary timeframe alignment provides the strongest setup.
Chart Requirements
For proper script functionality and compliance with TradingView requirements, ensure your chart displays:
- Symbol name: The trading pair or instrument name should be visible
- Timeframe: The chart timeframe should be clearly displayed
- Script name: "Ultimate MACD " should be visible in the indicator title
These elements help traders understand what they're viewing and ensure proper script identification. The script automatically includes this information in the indicator title and chart labels.
Performance Considerations
The script is optimized for performance:
- Calculations use efficient Pine Script functions (ta.ema, ta.sma, etc.) which are optimized by TradingView
- Conditional execution: Features only calculate when enabled
- Label management: Old labels are automatically deleted to prevent accumulation
- Array management: Divergence label arrays are limited to prevent memory accumulation
The script should perform well on all timeframes. On very long historical data with many enabled features, performance may be slightly slower, but it remains usable.
Known Limitations and Considerations
- Dynamic OB/OS levels can vary significantly based on recent MACD volatility. In very volatile markets, levels may be wider; in calm markets, they may be narrower.
- Volume confirmation requires sufficient historical volume data. On new instruments or very short timeframes, volume calculations may be less reliable.
- Higher timeframe MACD uses request.security() which may have slight delays on some data feeds.
- Stochastic MACD requires the histogram to have sufficient history. Very short periods on new charts may produce less reliable StochMACD values initially.
- Divergence detection requires sufficient historical data to identify pivot points. Very short lookback periods may produce false positives.
Practical Use Cases
The indicator can be configured for different trading styles and timeframes:
Swing Trading:
Use MACD(12,26,9) with secondary timeframe confirmation. Enable divergence detection. Use signal strength filter (threshold 50+) and cross quality filter (threshold 50+) for higher-quality signals. Enable histogram analysis tools for additional context.
Day Trading:
Use MACD(8,17,7) or use "Day Trading" preset with minimal histogram smoothing for faster signals. Enable zero-line cross alerts for early signals. Use volume confirmation with threshold 1.2-1.5. Enable histogram MA for momentum tracking.
Trend Following:
Use MACD(12,26,9) or longer periods (15,30,12) for smoother signals. Enable secondary timeframe confirmation for trend alignment. Hidden divergence signals are useful for trend continuation entries. Use cross quality filter to identify high-quality crossovers.
Reversal Trading:
Focus on divergence detection (pivot-based for accuracy) combined with zero-line crosses. Enable volume confirmation. Use histogram Bollinger Bands to identify extreme histogram zones. Enable StochMACD for overbought/oversold identification.
Multi-Timeframe Analysis:
Enable secondary timeframe MACD to see context from larger timeframes. For example, use daily MACD on hourly charts to understand the larger trend context. Enable secondary confirmation to require higher timeframe alignment for signals.
Practical Tips and Best Practices
Getting Started:
Start with default settings and observe MACD behavior. The default configuration (MACD 12,26,9 with EMA) is balanced and works well across different markets. After observing behavior, customize settings to match your trading style. Consider using configuration presets for quick setup.
Reducing Repainting:
All signals are based on confirmed bars, minimizing repainting. The script uses confirmed bar data for all calculations to ensure backtesting accuracy.
Signal Quality:
MACD crosses with multiple filters provide the highest-quality signals because they require alignment across multiple indicators. These signals have lower frequency but higher reliability. Use signal strength scores to identify the strongest signals (70+). Use cross quality scores to identify high-quality crossovers (70+).
Filter Combinations:
Start with histogram filter for basic momentum alignment, then add signal strength filter for moderate signals, then cross quality filter for high-quality crossovers. Combining all filters significantly reduces false signals but also reduces signal frequency. Find your balance based on your risk tolerance.
Volume Filtering:
Set volume threshold to 1.0 (default, effectively disabled) or lower to effectively disable volume filtering if you trade instruments with unreliable volume data or want to test without volume confirmation. Standard confirmation uses 1.2-1.5 threshold.
MACD Period Selection:
Standard MACD(12,26,9) provides balanced signals suitable for most trading. Shorter periods (8,17,7) for faster signals, longer (15,30,12) for smoother signals. Adjust based on your timeframe and trading style. Consider using configuration presets for optimized settings.
Moving Average Type:
EMA provides balanced responsiveness with smoothness. RMA is smoother and less responsive. WMA gives more weight to recent prices. SMA gives equal weight to all periods. Choose based on your preference for responsiveness vs. smoothness.
Divergence:
Pivot-based divergence is more reliable than simple divergence because it uses actual pivot points. Hidden divergence indicates continuation rather than reversal, useful for trend-following strategies. Adjust pivot lookback parameters to control sensitivity.
Dynamic Thresholds:
Dynamic OB/OS thresholds automatically adapt to volatility. In volatile markets, thresholds widen; in calm markets, they narrow. Adjust the multipliers to fine-tune sensitivity. Enable OB/OS background colors for visual indication.
Zero-Line Crosses:
Zero-line crosses indicate momentum shifts and can provide early warning signals before MACD crosses the signal line. Enable alerts for zero-line crosses to catch these early signals.
Alert Management:
Enable alert cooldown (default enabled, 5 bars) to prevent alert spam. Use alert type filter to only evaluate specific alert types. Signal debounce (default enabled, 3 bars) prevents duplicate MACD cross signals during choppy markets.
Technical Specifications
- Pine Script Version: v6
- Indicator Type: Non-overlay (displays in separate panel below price chart)
- Repainting Behavior: Minimal - all signals are based on confirmed bars, ensuring accurate backtesting results
- Performance: Optimized with conditional execution. Features only calculate when enabled.
- Compatibility: Works on all timeframes (1 minute to 1 month) and all instruments (stocks, forex, crypto, futures, etc.)
- Edge Case Handling: All calculations include safety checks for division by zero, NA values, and boundary conditions. Alert cooldowns and signal debounce handle edge cases where conditions never occurred or values are NA.
Technical Notes
- All MACD values respect percentage mode conversion when enabled
- Volume confirmation uses cached volume SMA for performance
- Label arrays (divergence) are automatically limited to prevent memory accumulation
- Background coloring: OB/OS backgrounds are drawn on top of main background to ensure visibility
- All calculations are optimized with conditional execution - features only calculate when enabled (performance optimization)
- Signal strength calculation combines multiple factors into a single score for easy filtering
- Cross quality calculation rates crossover quality based on angle, volume, and distance from zero
- Secondary timeframe MACD uses request.security() for higher timeframe data access
- Histogram analysis features (Bollinger Bands, MA, StochMACD) provide additional context beyond basic MACD signals
- Statistics table dynamically adjusts to show only enabled features, keeping it clean and relevant
- Divergence detection uses MACD line (not histogram) for more reliable signals
- Configuration presets automatically optimize MACD parameters for different trading styles
- Smart label placement: Labels appear on current bar at confirmation, using strength from tracked extreme point
- Label spacing uses effective distance (base distance × spacing multiplier) for better distribution
- Zero line polarity enforcement ensures Buy labels only appear when tracked extreme MACD < 0, Sell labels only when tracked extreme MACD > 0
- Label finalization requires MACD exit from OB/OS zone, sufficient bars passed, and recovery/decline percentage confirmation
- Strength-based filtering automatically compares and keeps only the strongest label when multiple signals are close together
- Enhanced visualization: Line outlines drawn behind main lines for superior visibility (black default, configurable)
- Enhanced visualization: Fill between MACD and zero line provides instant visual feedback (green above, red below)
- Enhanced visualization: Fill between OB/OS thresholds highlights neutral zone when dynamic levels are active
- Custom chart background overrides background mode when enabled, allowing theme-consistent indicator panels
Iridescent Liquidity Prism [JOAT]Iridescent Liquidity Prism | Peer Momentum HUD
A multi-layered order-flow indicator that combines microstructure analysis, smart-money footprint detection, and intermarket momentum signals. The script uses dynamic color-shifting themes to visualize liquidity patterns, structure, and peer momentum data directly on the chart.
There is so much to choose from inside the settings, if you think it's a mess on the chart it's because you have to personally customize it based on your needs...
Core Functionality
The indicator calculates and displays several analytical layers simultaneously:
Order-Flow Imbalance (OFI): Calculates buy vs. sell volume pressure using volume-weighted price distribution within each bar. Uses an EMA filter (default: 55 periods) to smooth the signal. Values are normalized using standard deviation to identify significant imbalances.
Smart Money Footprints: Detects accumulation and distribution zones by comparing volume rate of change (ROC) against price ROC. When volume ROC exceeds a threshold (default: 65%) and price ROC is positive, accumulation is detected. When volume ROC is high but price ROC is negative, distribution is detected.
Fractal Structure Mapping: Identifies pivot highs and lows using a fractal detection algorithm (default: 5-bar period). Maintains a rolling window of recent structure points (default: 4 levels) and draws connecting lines to show trend structure.
Fair Value Gap (FVG) Detection: Automatically detects price gaps where three consecutive candles create an imbalance. Bullish FVGs occur when the current low exceeds the high two bars ago. Bearish FVGs occur when the current high is below the low two bars ago. Gaps persist for a configurable duration (default: 320 bars) and fade when price fills the gap.
Liquidity Void Detection: Identifies candles where the high-low range exceeds an ATR threshold (default: 1.7x ATR) while volume is below average (default: 65% of 20-bar average). These conditions suggest areas where liquidity may be thin.
Price/Volume Divergence: Uses linear regression to detect when price trend direction disagrees with volume trend direction. A divergence alert appears when price is trending up while volume is trending down, or vice versa.
Peer Momentum Heatmap (PMH): Calculates composite momentum scores for up to 6 symbols across 4 timeframes. Each score combines RSI (default: 14 periods) and StochRSI (default: 14 periods, 3-bar smooth) to create a momentum composite between -1 and +1. The highest absolute momentum score across all combinations is displayed in the HUD.
Custom settings using Fractal Pivots, Skeleton Structure, Pulse Liquidity Voids, Bottom Colorful HeatMaps, and Iridescent Field.
---
Visual Components
Spectrum Aura Glow: ATR-weighted bands (default: 0.25x ATR) that expand and contract around price action, indicating volatility conditions. The thickness adapts to market volatility.
Chromatic Flow Trail: A blended line combining EMA and WMA of price (default: 8-period EMA blended with WMA at 65% ratio). The trail uses gradient colors that shift based on a phase oscillator, creating an iridescent effect.
Volume Heat Projection: Creates horizontal volume profile bands at price levels (default: 14 levels). Scans recent bars (default: 150 bars) to calculate volume concentration. Each level is colored based on its volume density relative to the maximum volume level.
Structure Skeleton: Dashed lines connecting fractal pivot points. Uses two layers: a primary line (2-3px width) and an optional glow overlay (4-5px width) for enhanced visibility.
Fractal Markers: Diamond shapes placed at pivot high and low points. Color-coded: primary color for highs, secondary color for lows.
Iridescent Color Themes: Five color themes available: Iridescent (default), Pearlescent, Prismatic, ColorShift, and Metallic. Colors shift dynamically using a phase oscillator that cycles through the color spectrum based on bar index and a speed multiplier (default: 0.35).
---
HUD Console Metrics
The right-side HUD displays seven key metrics:
Flow: Shows OFI status: ▲ FLOW BUY when normalized OFI exceeds imbalance threshold (default: 2.2), ▼ FLOW SELL when below -2.2, or ◆ FLOW BAL when balanced.
Struct: Structure trend bias: ▲ STRUCT BULL when microtrend > 2, ▼ STRUCT BEAR when < -2, or ◆ STRUCT RANGE when neutral.
Smart$: Institutional activity: ◈ ACCUM when smart money index = 1, ◈ DISTRIB when = -1, or ○ IDLE when inactive.
Liquid: Liquidity state: ⚡ VOID when a liquidity void is detected, or ● NORMAL otherwise.
Diverg: Divergence status: ⚠ ALERT when price/volume divergence detected, or ✓ CLEAR when aligned.
PMH: Peer Momentum Heatmap status: Shows dominant timeframe and momentum score. Displays 🪩 for bull surge (above 0.55 threshold) or 🧨 for bear surge (below -0.55).
FVG: Fair Value Gap status: Shows active gap count or CLEAR when no gaps exist. Displays GAP LONG when bullish gap detected, GAP SHORT when bearish gap detected.
Pearlscent Color with Volume Heatmap.
Parameters and Settings
Microstructure Engine:
Analysis Depth: 20-250 bars (default: 55) - Controls OFI smoothing period
Liquidity Threshold ATR: 1.0-4.0 (default: 1.7) - Multiplier for void detection
Imbalance Ratio: 1.5-6.0 (default: 2.2) - Standard deviations for OFI significance
Smart Money Layer:
Smart Money Window: 10-150 bars (default: 24) - Period for ROC calculations
Accumulation Threshold: 40-95% (default: 65%) - Volume ROC threshold
Structural Mapping:
Fractal Pivot Period: 3-15 bars (default: 5) - Period for pivot detection
Structure Memory: 2-8 levels (default: 4) - Number of structure points to track
Volume Heat Projection:
Heat Map Lookback: 60-400 bars (default: 150) - Bars to analyze for volume profile
Heat Map Levels: 5-30 levels (default: 14) - Number of price level bands
Heat Map Opacity: 40-100% (default: 92%) - Transparency of heat map boxes
Heat Map Width Limit: 6-80 bars (default: 26) - Maximum width of heat map boxes
Heat Map Visibility Threshold: 0.0-0.5 (default: 0.08) - Minimum density to display
Iridescent Enhancements:
Visual Theme: Iridescent, Pearlescent, Prismatic, ColorShift, or Metallic
Color Shift Speed: 0.05-1.00 (default: 0.35) - Speed of color phase oscillation
Aura Thickness (ATR): 0.05-1.0 (default: 0.25) - Multiplier for aura band width
Chromatic Trail Length: 2-50 bars (default: 8) - Period for trail calculation
Trail Blend Ratio: 0.1-0.95 (default: 0.65) - EMA/WMA blend percentage
FVG Persistence: 50-600 bars (default: 320) - Bars to keep FVG boxes active
Max Active FVG Boxes: 10-200 (default: 40) - Maximum boxes on chart
FVG Base Opacity: 20-95% (default: 80%) - Transparency of FVG boxes
Peer Momentum Heatmap:
Peer Symbols: Comma-separated list of up to 6 symbols (e.g., "BTCUSD,ETHUSD")
Peer Timeframes: Comma-separated list of up to 4 timeframes (default: "60,240,D")
PMH RSI Length: 5-50 periods (default: 14)
PMH StochRSI Length: 5-50 periods (default: 14)
PMH StochRSI Smooth: 1-10 periods (default: 3)
Super Momentum Threshold: 0.2-0.95 (default: 0.55) - Threshold for surge detection
Clarity & Readability:
Liquidity Void Opacity: 5-90% (default: 30%)
Smart Money Footprint Opacity: 5-90% (default: 35%)
HUD Background Opacity: 40-95% (default: 70%)
Iridescent Field:
Field Opacity: 20-100% (default: 86%) - Background color intensity
Field Smooth Length: 10-200 bars (default: 34) - Smoothing for background gradient
---
Alerts
The indicator provides seven alert conditions:
Liquidity Void Detected - Triggers when void conditions are met
Strong Order Flow - Triggers when normalized OFI exceeds imbalance ratio
Smart Money Activity - Triggers when accumulation or distribution detected
Price/Volume Divergence - Triggers when divergence conditions occur
Structure Shift - Triggers when structure polarity changes significantly
PMH Bull Surge - Triggers when PMH exceeds positive threshold (if enabled)
PMH Bear Surge - Triggers when PMH exceeds negative threshold (if enabled)
Bull/Bear Prismatic FVG - Triggers when new FVG is detected (if FVG display enabled)
---
Usage Considerations
Performance may vary on lower timeframes due to the volume heat map calculations scanning multiple bars. Consider reducing heat map lookback or levels if experiencing slowdowns.
The PMH feature requires data requests to other symbols/timeframes, which may impact performance. Limit the number of peer symbols and timeframes for optimal performance.
FVG boxes automatically expire after the persistence period to prevent chart clutter. The maximum box limit (default: 40) prevents excessive memory usage.
Color themes affect all visual elements. Choose a theme that provides good contrast with your chart background.
The indicator is designed for overlay display. All visual elements are positioned relative to price action.
Structure lines are drawn dynamically as new pivots form. On fast-moving markets, structure may update frequently.
Volume calculations assume typical volume data availability. Symbols without volume may show incomplete data for volume-dependent features.
---
Technical Notes
Built on Pine Script v6 with dynamic request capability for PMH functionality.
Uses exponential moving averages (EMA) and weighted moving averages (WMA) for trail calculations to balance responsiveness and smoothness.
Volume profile calculation uses price level buckets. Higher levels provide finer granularity but require more computation.
Iridescent color engine uses a phase oscillator with sine wave calculations for smooth color transitions.
Box management includes automatic cleanup of expired boxes to maintain performance.
All visual elements use color gradients and transparency for smooth blending with price action.
---
Customization Examples
Intraday Scalping Setup:
Analysis Depth: 30 bars
Heat Map Lookback: 100 bars
FVG Persistence: 150 bars
PMH Window: 15 bars
Fast color shift speed: 0.5+
Macro Structure Tracking:
Analysis Depth: 100+ bars
Heat Map Lookback: 300+ bars
FVG Persistence: 500+ bars
Structure Memory: 6-8 levels
Slower color shift speed: 0.2
---
Limitations
Volume heat map calculations may be computationally intensive on lower timeframes with high lookback values.
PMH requires valid symbol names and accessible timeframes. Invalid symbols or timeframes will return no data.
FVG detection requires at least 3 bars of history. Early bars may not show FVG boxes.
Structure lines connect points but do not predict future structure. They reflect historical pivot relationships.
Color themes are aesthetic choices and do not affect calculation logic.
The indicator does not provide trading signals. All visual elements are analytical tools that require interpretation in context of market conditions.
Open Source
This indicator is open source and available for modification and distribution. The code is published with Pine Script v6 compliance. Users are free to customize parameters, modify calculations, and adapt the visual elements to their trading needs.
For questions, suggestions, or anything please talk to me in private messages or comments below!
Would love to help!
- officialjackofalltrades
On Balance Volume [BrightSideTrading]
# On Balance Volume - Complete User Guide
## Overview
This enhanced OBV indicator provides clean, actionable volume analysis with intelligent signal filtering. It combines On-Balance Volume (OBV) with a smoothed signal line to identify shifts in buying and selling pressure without chart clutter.
**Key Features:**
- Real-time OBV and signal line visualization
- Smart crossover detection with confirmation filtering
- Z-Score momentum analysis
- Customizable signal alerts with V-shaped markers
- Window-normalized option for detrended analysis
---
## What is On-Balance Volume (OBV)?
OBV is a volume-based momentum indicator that accumulates volume on up days and subtracts volume on down days. It answers a fundamental question: **Is volume flowing in (buying) or out (selling)?**
**Formula:**
- If Close > Previous Close: OBV = Previous OBV + Volume
- If Close < Previous Close: OBV = Previous OBV - Volume
- If Close = Previous Close: OBV = Previous OBV (unchanged)
**What it tells you:**
- **Rising OBV** = Accumulation (smart money buying)
- **Falling OBV** = Distribution (smart money selling)
- **OBV above zero line** = Net positive buying pressure
- **OBV below zero line** = Net negative selling pressure
---
## Interface & Settings
### **MAIN VISUALIZATION**
**OBV Line (Green/Red Ribbon)**
- Green when OBV is above the signal line (bullish trend)
- Red when OBV is below the signal line (bearish trend)
- Toggles between window-normalized (detrended) and raw values
**Signal Line (Orange)**
- Smoothed average of OBV
- Crossovers with OBV generate buy/sell signals
- Default: 21-period SMA
**V-Shaped Markers**
- Green upward V = Bullish crossover (buy signal)
- Red downward V = Bearish crossover (sell signal)
- Appears at the OBV value when signal is triggered
**Zero Line (Yellow)**
- Center equilibrium point for volume balance
- Acts as support/resistance for OBV
- Separates buying pressure (above) from selling pressure (below)
---
### **SOURCE GROUP**
**Source**
- **Default:** Close
- **Options:** Open, High, Low, or any custom value
- Controls which price value triggers OBV direction changes
- Most traders use Close for standard OBV calculation
---
### **SIGNAL SMOOTHING GROUP**
**Show Signal?**
- **Default:** ON
- Toggle visibility of the signal line
- Disable if you prefer to see raw OBV only
**Smoothing Type**
- **SMA (Simple Moving Average)** - Default, standard smoothing
- **EMA (Exponential Moving Average)** - Faster response, weights recent bars more heavily
- **Choose SMA** for consistent, traditional OBV signals
- **Choose EMA** for faster trend identification (more whipsaws possible)
**Smoothing Length**
- **Default:** 21 bars
- **Range:** 1-200 bars
- **Lower values** (5-14): Faster signals, more noise
- **Higher values** (30-50): Slower signals, fewer false alarms
- **Recommendation:** Use 21-25 for most timeframes
---
### **SIGNAL FILTERING GROUP**
This is your primary control for signal quality and frequency.
**Show Signal Markers?**
- **Default:** ON
- Toggle the V-shaped buy/sell markers on/off
- Disable if markers distract from your analysis
**Signal Filter Type**
- **None** - Shows every single crossover (noisy, best for skilled traders)
- **Confirmation Bars** - Waits N bars before confirming signal (recommended)
- **Strength-Based** - Only signals during strong momentum (filters weakest moves)
#### **CONFIRMATION BARS MODE** (Recommended)
Best for reducing false signals while staying responsive to real moves.
**Confirmation Bars**
- **Default:** 2 bars
- **Range:** 1-10 bars
- Waits for the signal to hold for N consecutive bars after crossover
- **Setting 1:** Every crossover (same as "None")
- **Setting 2:** Wait 1 bar confirmation (good balance)
- **Setting 3:** Wait 2 bars confirmation (filters 50% of noise)
- **Setting 4+:** Very selective, misses quick reversals
**How it works:**
1. OBV crosses signal line → Confirmation counter starts
2. If OBV stays on correct side for 2 bars → V-marker appears
3. If OBV crosses back → Counter resets, no signal
#### **STRENGTH-BASED MODE**
Only signals when momentum is statistically significant.
**Min Z-Score Strength**
- **Default:** 0.3
- **Range:** 0.0-3.0
- Requires OBV deviation from its mean to reach this threshold
- **Setting 0.1-0.3:** More signals, lower quality
- **Setting 0.5-0.8:** Moderate signals, good quality
- **Setting 1.0+:** Only the strongest momentum shifts
**How it works:**
- Calculates how far OBV is from its 50-bar average (Z-score)
- Only shows signals when this distance is meaningful
- Automatically avoids weak, choppy market conditions
---
### **VISUALS & COLORS GROUP**
**Highlight Crossovers?**
- **Default:** ON
- Master toggle for all signal markers
- Turn OFF to see only the OBV/signal lines
**Apply Ribbon Filling?**
- **Default:** ON
- Colors the space between OBV and signal line
- Green fill = OBV above signal (bullish)
- Red fill = OBV below signal (bearish)
- Provides clear visual trend confirmation
- Turn OFF for minimal chart clutter
---
### **STATS & ZONES GROUP**
**Use Window-Normalized OBV (visual only)?**
- **Default:** ON
- Removes long-term trend from OBV for clearer short-term signals
- Detrends the indicator to highlight recent momentum changes
- **ON:** Better for swing trading and identifying reversals
- **OFF:** Better for trend-following strategies
- Note: Z-Score always uses raw OBV for statistical accuracy
**OBV Normalize Window**
- **Default:** 200 bars
- Lookback period for detrending calculation
- Larger values = more aggressive detrending
- Adjust if you want OBV to oscillate more/less around zero
**Show Z-Score (OBV)?**
- **Default:** ON
- Displays statistical momentum indicator below main chart
- Ranges from -3 to +3 (most data within -2 to +2)
- High Z-Score = Strong buying momentum
- Low Z-Score = Strong selling momentum
**Z-Score Lookback**
- **Default:** 50 bars
- Period for calculating Z-Score mean and standard deviation
- Larger = smoother Z-Score, slower response
- Smaller = noisier Z-Score, faster response
**Show ROC (OBV Momentum)?**
- **Default:** OFF
- Rate of Change indicator for OBV velocity
- Useful for identifying momentum turning points
- Enable if you want to see speed of volume changes
**ROC Lookback**
- **Default:** 14 bars
- Period for ROC calculation
**Show Z-Score StdDev Zones?**
- **Default:** ON
- Shaded regions around zero line showing statistical boundaries
- Inner Zone (±1 Z) = Normal variation
- Outer Zone (±2 Z) = Extreme moves, potential reversals
- Helps identify overbought/oversold volume conditions
**Inner Zone (±Z)**
- **Default:** 1.0
- First boundary for standard deviation zones
- Most normal trading occurs within ±1
**Outer Zone (±Z)**
- **Default:** 2.0
- Second boundary for extreme conditions
- Crossing these zones indicates significant momentum shift
---
## Trading Strategy Examples
### **Strategy 1: Signal Line Crossovers (Beginner)**
**Setup:**
- Signal Filter Type: **Confirmation Bars**
- Confirmation Bars: **2-3**
- Show Signal Markers: **ON**
**Rules:**
1. **BUY signal** (green V): When OBV crosses above signal line and holds for 2-3 bars
- Confirms buying pressure is building
- Look for price to follow within 1-3 bars
2. **SELL signal** (red V): When OBV crosses below signal line and holds for 2-3 bars
- Confirms selling pressure is increasing
- Expect price decline
3. **Exit:** Take profits at next signal or use price support/resistance
**Best For:** Swing trading, intraday reversals, timeframes 5m-1h
---
### **Strategy 2: Zero Line Bounce (Intermediate)**
**Setup:**
- Signal Filter Type: **Strength-Based**
- Min Z-Score Strength: **0.5**
- Show Z-Score StdDev Zones: **ON**
**Rules:**
1. **Watch OBV approach zero line** during established trends
- OBV bouncing repeatedly off zero = trend is healthy
- OBV breaking through zero = trend reversal imminent
2. **Enter on bounce:** Buy when OBV bounces from zero line in uptrend
3. **Exit on break:** Close position when OBV breaks below zero line
4. **Confirm with Z-Score:** Only take trades when Z-Score shows momentum (|Z| > 0.5)
**Best For:** Trend traders, identifying trend strength, medium timeframes 15m-4h
---
### **Strategy 3: Momentum Extremes (Advanced)**
**Setup:**
- Signal Filter Type: **None**
- Show Z-Score StdDev Zones: **ON**
- Outer Zone: **2.0**
**Rules:**
1. **Identify extremes:** When Z-Score breaks outer zone (±2.0)
- Indicator is in extreme territory
- Likely overextended
2. **Fade extremes:** Take opposite position when Z-Score hits extreme
- High Z (>2.0) = OBV overbought, expect pullback
- Low Z (<-2.0) = OBV oversold, expect bounce
3. **Confirm:** Wait for crossover signal to enter
4. **Target:** Outer zone of opposite side or zero line
**Best For:** Range trading, mean reversion, experienced traders only
---
## Reading the Indicator in Different Markets
### **Strong Uptrend**
- OBV consistently above signal line (green)
- OBV well above zero line, rising higher lows
- Z-Score positive, trending upward
- **Action:** Buy dips to signal line, sell at resistance
### **Strong Downtrend**
- OBV consistently below signal line (red)
- OBV well below zero line, making lower highs
- Z-Score negative, trending downward
- **Action:** Sell rallies to signal line, cover at support
### **Consolidation/Choppy Market**
- OBV whipsaws around signal line frequently
- Crossovers occur every few bars
- Z-Score oscillating between -1 and +1
- **Action:** Increase confirmation bars to 3-4, or switch to strength-based filter
### **Accumulation (Bottom Formation)**
- OBV rising while price is flat or falling
- Volume flowing in despite downtrend (bullish divergence)
- Z-Score climbing while price lows hold
- **Action:** Expect breakout up; prepare buy near support
### **Distribution (Top Formation)**
- OBV falling while price is flat or rising
- Volume flowing out despite uptrend (bearish divergence)
- Z-Score falling while price continues higher
- **Action:** Expect breakdown down; prepare short near resistance
---
## Parameter Tuning Guide
### **Aggressive Settings (More Signals)**
- Smoothing Length: 14
- Signal Filter: None or Confirmation Bars: 1
- Min Z-Score: 0.1
- Best for: Day trading, high volatility stocks
- Risk: More false signals
### **Balanced Settings (Recommended)**
- Smoothing Length: 21
- Signal Filter: Confirmation Bars: 2
- Min Z-Score: 0.3
- Best for: Swing trading, most market conditions
- Risk/Reward: Moderate
### **Conservative Settings (Fewer Signals)**
- Smoothing Length: 30-40
- Signal Filter: Confirmation Bars: 3-4 or Strength-Based: 0.7+
- Min Z-Score: 0.8
- Best for: Position trading, high-conviction trades only
- Risk: May miss some moves
---
## Common Questions & Troubleshooting
**Q: Why are there more sell signals than buy signals?**
A: This reflects the actual market action. Markets often decline faster than they rise (fear > greed). Confirm signals with price action and support/resistance.
**Q: The indicator keeps whipsawing, should I hide it?**
A: Increase Confirmation Bars to 3-4 or switch to Strength-Based filter. Market conditions matter—choppy markets require stricter filters.
**Q: What's the difference between normalized and raw OBV?**
A: Normalized (detrended) shows shorter-term momentum by removing long-term trends. Raw OBV shows absolute accumulation/distribution over the full period. Use normalized for swing signals, raw for trend confirmation.
**Q: My signals come too late. How do I get faster entry?**
A: Reduce Smoothing Length (try 14 instead of 21), use EMA instead of SMA, or set Confirmation Bars to 1. Trade-off: More false signals.
**Q: Can I use this for day trading?**
A: Yes, on 1m-5m charts with aggressive settings. Use Confirmation Bars: 1 and focus on Z-Score > 0.5 entries only.
**Q: Should I trade every signal?**
A: No. Filter signals using: price near support/resistance, multiple indicators confirming, and Z-Score showing momentum. Best signals occur at key levels.
---
## Best Practices
1. **Always confirm with price action:** OBV signals work best when price is near support, resistance, or moving average. Don't trade signals in a vacuum.
2. **Use volume context:** Check if volume is increasing or decreasing on the signal. Strong signals have volume confirmation (increasing volume on OBV spikes).
3. **Adjust settings per timeframe:**
- 1m-5m: Smoothing 12, Confirmation 1, Z-Score 0.2
- 15m-1h: Smoothing 20, Confirmation 2, Z-Score 0.3
- 4h-1d: Smoothing 25, Confirmation 3, Z-Score 0.5
4. **Watch the zero line:** It's your friend. OBV behavior at the zero line reveals trend strength. Bounces = healthy trend. Breaks = reversal.
5. **Risk management:** No indicator is perfect. Use proper position sizing and stop losses. OBV should confirm your thesis, not be the only reason to trade.
6. **Combine with other indicators:**
- Price moving averages for trend confirmation
- RSI or Stochastic for overbought/oversold levels
- Support/resistance for entry/exit zones
- MACD for momentum divergences
---
## Disclaimer
This indicator is for educational and informational purposes only. It is not financial advice. Past performance does not guarantee future results. Always conduct your own research and consult with a financial advisor before making trading decisions. Trading carries risk, including potential loss of principal.
---
## Version History
**Version 1.0** - Initial release with enhanced signal filtering, Z-Score analysis, and customizable parameters.
Luxy VWAP Magic - MTF Projection EngineThis indicator transforms the classic VWAP into a comprehensive trading system. Instead of switching between multiple indicators, you get everything in one place: multi-timeframe analysis, statistical bands, momentum detection, volume profiling, session tracking, and divergence signals.
What Makes This Different
Traditional VWAP indicators show a single line. This tool treats VWAP as a foundation for complete market analysis. The indicator automatically detects your asset type (stocks, crypto, forex, futures) and adjusts its behavior accordingly. Crypto traders get 24/7 session tracking. Stock traders get proper market hours handling. Everyone gets institutional-grade analytics.
Anchor Period Options
The anchor period determines when VWAP resets and recalculates. You have three categories of options:
Time-Based Anchors:
Session - Resets at market open. Best for intraday stock trading where you want fresh VWAP each day.
Day - Resets at midnight UTC. Standard option for most traders.
Week / Month / Quarter / Year - Longer reset periods for swing traders and position traders who want broader context.
Rolling Window Anchors:
Rolling 5D - A sliding 5-day window that never resets. Solves the Monday problem where weekly VWAP equals daily VWAP on first day of week.
Rolling 21D - Approximately one month of trading data in continuous calculation. Excellent for crypto and forex markets that trade 24/7 without clear session breaks.
Event-Based Anchors:
Dividends - Resets on ex-dividend dates. Track institutional cost basis from dividend events.
Splits - Resets on stock split dates. Useful for analyzing post-split trading behavior.
Earnings - Resets on earnings report dates. See where volume-weighted trading occurred since last quarterly report.
Standard Deviation Bands
Three sets of bands surround the main VWAP line:
Band 1 (Aqua) - Plus and minus one standard deviation. Approximately 68% of price action occurs within this range under normal distribution. Touches suggest minor extension.
Band 2 (Fuchsia) - Plus and minus two standard deviations. Only 5% of trading should occur outside this range statistically. Touches here indicate significant overextension and high probability of mean reversion.
Band 3 (Purple) - Plus and minus three standard deviations. Touches are rare (0.3% probability) and represent extreme conditions. Often marks climax moves or panic selling/buying.
Each band can be toggled independently. Most traders show Band 1 by default and add Band 2 and 3 for specific setups or volatile instruments.
Multi-Timeframe VWAP System
The MTF section plots previous period VWAPs as horizontal support and resistance levels:
Daily VWAP - Previous day's final VWAP value. Key intraday reference level.
Weekly VWAP - Previous week's final VWAP. Important for swing traders.
Monthly VWAP - Previous month's final VWAP. Institutional benchmark level.
Quarterly VWAP - Previous quarter's final VWAP. Major support/resistance for position traders.
Previous Day VWAP - Yesterday's closing VWAP specifically, separate from current daily calculation.
The Confluence Zone percentage setting determines how close multiple VWAPs must be to trigger a confluence alert. When two or more timeframe VWAPs converge within this threshold, you get a high-probability support/resistance zone.
Session VWAPs for Global Markets
For forex, crypto, and futures traders who operate in 24/7 markets, the indicator tracks three major global sessions:
Asia Session - UTC 21:00 to 08:00. Gold colored line. Typically lower volatility, range-bound action that sets overnight levels.
London Session - UTC 08:00 to 17:00. Orange colored line. Often determines daily direction with high volume European participation.
New York Session - UTC 13:00 to 22:00. Blue colored line. Highest volume session globally. Sharp directional moves common.
Previous session VWAP values display as horizontal lines when each session closes, acting as intraday support and resistance. The table shows which sessions are currently active with checkmarks.
On-Chart Labels and Signals
The indicator plots several types of labels directly on price action when significant events occur:
Volume Spike Labels
Fire when current bar volume exceeds configurable thresholds relative to both the previous bar and the 20-bar average. Default settings require 300% of previous bar AND 200% of average volume. Green labels indicate bullish candles. Red labels indicate bearish candles. These spikes often mark institutional entry points.
Momentum Shift Labels
Appear when VWAP acceleration changes direction. The Slowing label warns when an active trend loses steam, often preceding reversal. The Accelerating label confirms trend continuation or potential bottom during downtrends. Filters available to show only reversal signals in existing trends.
VWAP Squeeze Labels
Detect when standard deviation bands contract relative to ATR (Average True Range). Low volatility compression often precedes explosive breakout moves. When the squeeze fires (releases), a label appears with directional prediction based on VWAP slope.
Divergence Labels
Mark price/volume divergences using CVD (Cumulative Volume Delta) analysis:
Bullish divergence: Price makes lower low, but CVD makes higher low. Hidden accumulation despite price weakness.
Bearish divergence: Price makes higher high, but CVD makes lower high. Hidden distribution despite price strength.
Dynamic VWAP Coloring
The main VWAP line changes color based on its slope direction:
Green - VWAP is rising. Institutional buying pressure. Volume-weighted price increasing.
Red - VWAP is falling. Institutional selling pressure. Volume-weighted price decreasing.
Gray - VWAP is flat. Consolidation or balance between buyers and sellers.
This coloring can be disabled for a static blue line if you prefer cleaner visuals. The VWAP label next to the line shows the current trend direction and delta percentage.
Calculated Projection Cone
One of the most powerful features is the Calculated Projection Cone. Unlike traditional extrapolation methods that simply extend a trend line forward, this system analyzes what actually happened in similar market conditions throughout the chart's history.
How It Works:
The system classifies each bar into one of 27 unique market states:
Z-Score Level - LOW (oversold), MID (fair value), or HIGH (overbought) based on configurable thresholds
Trend Direction - DOWN, FLAT, or UP based on VWAP slope
Volume Profile - LOW (below 80%), NORMAL (80-150%), or HIGH (above 150%) relative volume
When you look at the current bar, the indicator:
1. Identifies the current market state (e.g., LOW Z-Score + UP Trend + HIGH Volume)
2. Searches through all historical bars on the chart that had the same state
3. Calculates what happened in those bars X bars later (where X is your projection horizon)
4. Shows you the probability of up/down and the average move size
Visual Elements:
Probability Cone - Colored green (bullish probability above 55%), red (bearish below 45%), or gold (neutral). The cone width represents the historical range of outcomes (roughly the 20th to 80th percentile).
Center Line - Shows the average expected price based on historical outcomes in similar conditions.
Probability Label - Displays direction probability and average move. Example: "67% UP (+0.8%)" means 67% of similar past cases moved up, averaging 0.8% gain.
Fallback System:
When the exact 27-state match has insufficient historical data:
First fallback: Uses Z-Score plus Trend only (9 broader states, ignoring volume)
Second fallback: Uses Z-Score only (3 states)
When fallback is active, confidence automatically adjusts
Settings:
Projection Horizon - How many bars forward to analyze outcomes (5, 10, 15, or 20 bars, default 10)
Lookback Period - Historical data window in days (30-252, default 60)
Minimum Samples - Cases needed before using fallback (5-30, default 10)
Z-Score Threshold - Bucket boundary for LOW/MID/HIGH classification (1.0, 1.5, or 2.0 sigma)
Cloud Transparency - Adjust visibility (50-95%)
Colors - Customize bullish, bearish, and neutral cone colors
Confidence Levels:
HIGH - 30 or more similar historical cases found
MEDIUM - 15-29 similar cases
LOW - Fewer than 15 cases (more uncertainty)
IMPORTANT DISCLAIMER:
The Calculated Projection is based on past patterns only. It is NOT a price prediction or financial advice. Similar market states in the past do not guarantee similar outcomes in the future. The probability shown is historical frequency, not a guarantee. Always combine with other analysis and never rely solely on projections for trading decisions.
Alert Conditions
The indicator includes over 20 pre-built alert conditions:
Price vs VWAP:
Price crosses above VWAP
Price crosses below VWAP
Band Touches:
Price touches plus or minus one sigma band
Price touches plus or minus two sigma band (extreme)
Price touches plus or minus three sigma band (very extreme)
Z-Score Extremes:
Z-Score crosses above plus two (overbought extreme)
Z-Score crosses below minus two (oversold extreme)
Momentum and Trend:
Momentum slowing
Momentum accelerating
Trend turns bullish/bearish/neutral
Volume:
Volume spike detected
CVD Direction:
Buyers take control
Sellers take control
High Probability Signals:
Bullish reversal signal (oversold plus accelerating momentum)
Bearish reversal signal (overbought plus slowing momentum)
MTF and Special:
MTF confluence zone entry
VWAP squeeze fired
Bullish/Bearish divergence detected
Any significant signal (catch-all)
All signals use confirmed bar data to prevent false alerts from incomplete candles.
Settings Overview
Settings are organized into logical groups:
VWAP Settings
Anchor Period selection
Show/Hide VWAP line
Dynamic coloring toggle
VWAP label visibility
Bands Visibility
Toggle each of three bands independently
Info Table
Show/Hide table
Table position (9 options)
Text size
Volume spike label settings with adjustable thresholds
Momentum label settings with filters
Signal labels limited to 5 most recent (auto-managed)
Probability engine lookback period
Multi-Timeframe VWAP
Enable/Disable MTF system
Show MTF in table
Show MTF lines on chart
Individual timeframe toggles
Confluence zone threshold
Squeeze detection toggle
Session VWAPs
Enable/Disable session tracking
Apply to all assets option
Show session labels
Divergence Detection
Enable/Disable divergence
Pivot lookback period
Show divergence labels
Calculated Projection
Enable/Disable projection cone
Projection horizon (5, 10, 15, or 20 bars)
Lookback period in days (30-252)
Minimum samples threshold
Z-Score classification threshold (1.0, 1.5, or 2.0 sigma)
Cloud transparency adjustment
Bullish, bearish, and neutral colors
The Info Table - Your Trading Dashboard
The right side of your chart displays a compact table with up to twelve metrics.
Row-by-Row Breakdown:
Asset and Period - Shows what the indicator detected (US Stock, Crypto, Forex, etc.) and your selected anchor period. The detection happens automatically based on exchange data, so VWAP resets and calculations match your actual trading instrument.
Delta Percentage - How far current price sits from VWAP, expressed as a percentage. Positive means price trades above fair value. Negative means below. Large delta values (beyond 1-2%) often precede mean reversion moves. Day traders watch this for overextension.
Z-Score - Statistical deviation from VWAP measured in standard deviations. Unlike raw delta, Z-Score accounts for volatility. A 2% move in a volatile biotech stock differs from 2% in a stable utility. Z-Score normalizes this. Values beyond plus or minus two sigma occur only 5% of the time statistically.
Trend Direction - Whether VWAP itself is rising, falling, or flat. Rising VWAP means the volume-weighted average price is increasing, which indicates institutional accumulation. Falling VWAP suggests distribution. This differs from price trend since it weights by volume.
Momentum State - Is the trend accelerating or slowing down? This measures the rate of change in VWAP slope. When an uptrend shows slowing momentum, it often precedes reversal. Accelerating momentum in a downtrend can signal capitulation and potential bottom.
Relative Volume - Current bar volume compared to the 20-bar average, shown as percentage. Values above 150% indicate above-average activity. Spikes above 200-300% often mark institutional involvement. Low volume (below 80%) warns of potential fake moves.
MTF Bias - Four checkmarks or X marks showing whether price sits above or below Daily, Weekly, Monthly, and Quarterly VWAP. Four checkmarks means strong bullish alignment across all timeframes. Four X marks indicates bearish alignment. Mixed readings suggest consolidation or transition.
Band Probabilities - Historical statistics showing how often price touched each standard deviation band over your lookback period. This helps you understand if mean reversion or trend following works better for your specific instrument.
Session Status - Which global trading sessions are currently active (Asia, London, New York). Shows checkmarks for active sessions. Important for forex and crypto traders who need to know when major liquidity windows open and close.
Divergence State - Whether the indicator detects bullish or bearish divergence between price and cumulative volume delta. Bullish divergence occurs when price makes lower lows but buying pressure (CVD) makes higher lows, suggesting hidden accumulation.
Confidence Score - A weighted composite of all factors displayed as a progress bar and percentage. Combines MTF alignment, Z-Score, trend direction, volume delta, momentum, and relative volume into a single 0-100 score. Higher scores indicate stronger conviction setups.
Calculated Projection - When the Projection Cone is enabled, shows the historical probability of price direction and expected move. For example: "▲ 67% (+0.8%)" means in similar market states historically, price moved up 67% of the time with an average gain of 0.8%. The system analyzes 27 unique market states based on Z-Score, Trend, and Volume conditions.
Recommended Use Cases
Day Trading Stocks:
Use Session anchor with Band 1 visible. Watch for price returning to VWAP after morning move. Volume spikes near VWAP often mark institutional accumulation zones.
Swing Trading:
Use Weekly or Rolling 21D anchor. Enable MTF lines for Daily and Weekly levels. Trade pullbacks to these levels in direction of MTF bias.
Crypto and Forex:
Enable Session VWAPs. Use Rolling anchors to avoid artificial resets. Monitor session transitions for breakout opportunities.
Mean Reversion:
Focus on Z-Score reaching plus or minus two. Add Band 2 visibility. Combine with slowing momentum for highest probability reversals.
Trend Following:
Watch MTF bias alignment. Four checkmarks plus accelerating momentum plus high volume confirms trend continuation setups.
Projection Planning:
Enable the Calculated Projection to see what happened historically in similar market conditions. Use 5-10 bars for intraday setups, 15-20 bars for swing trade planning. Focus on high probability readings (above 60%) with HIGH confidence (30 or more samples). The cone shows the probable range of outcomes based on actual historical data. Combine with other factors like MTF alignment and volume for higher conviction setups.
Important Notes
The indicator does not repaint. MTF values use previous period's confirmed data.
Rolling VWAP works best on 15-minute timeframes and above due to bar lookback requirements.
Session VWAPs apply to global markets by default (forex, crypto, futures). Enable the all-assets option for stocks if desired.
Volume data for forex represents tick volume, not actual traded volume.
All alert conditions fire only on confirmed (closed) bars to prevent false signals.
The Calculated Projection updates each bar as market state changes. This is expected behavior. The projection shows probabilities based on similar past conditions, not a fixed prediction.
Q AND A
Q: Does this indicator repaint?
A: No. The main VWAP calculation uses standard TradingView VWAP methodology. Multi-timeframe values use previous period's confirmed data with appropriate lookahead settings. All alert signals require bar confirmation.
Q: Why does my Rolling VWAP look different on 1-minute versus 15-minute charts?
A: Rolling VWAP calculates across a fixed number of trading days. On very short timeframes, the bar lookback may hit TradingView limits. For best Rolling VWAP accuracy, use 15-minute or higher timeframes.
Q: Can I use this on any instrument?
A: Yes. The indicator automatically detects asset type and adjusts behavior. Stocks use standard market hours. Crypto uses 24/7 calculations. Forex uses tick volume. Everything adapts automatically.
Q: What does the Confidence Score actually measure?
A: The score combines six weighted factors: MTF alignment (25%), Z-Score position (20%), Trend direction (20%), CVD pressure (15%), Momentum state (10%), and Relative volume (10%). Higher scores indicate more factors aligned in one direction.
Q: Why are Session VWAPs not showing on my stock chart?
A: Session VWAPs apply to 24-hour markets by default (forex, crypto, futures). For stocks, enable the Use for All Assets option in Session VWAP settings.
Q: The Divergence labels appear delayed. Is this a bug?
A: Divergence detection requires pivot confirmation, which needs bars on both sides of the pivot point. The label appears at the actual pivot location (several bars back) once confirmed. This is intentional and prevents false signals.
Q: Can I change the band colors?
A: Yes. Each of the three bands has its own color input setting. You can customize Band 1, Band 2, and Band 3 colors to match your preferences. The defaults are Aqua, Fuchsia, and Purple. The main VWAP line color adapts dynamically based on slope direction or can be set to static blue.
Q: How do I set up alerts?
A: Right-click on the chart, select Add Alert, choose this indicator, and select your desired condition from the dropdown. All conditions include descriptive alert messages with relevant data.
Q: What is the Probability Engine lookback period?
A: This setting determines how many trading days the indicator analyzes to calculate band touch rates and mean reversion statistics. Default is 60 days (approximately 3 months). Longer periods provide more stable statistics but may miss recent behavior changes.
Q: Why do I see fewer labels than expected?
A: Signal labels (Volume, Momentum, Squeeze, Divergence) are limited to 5 most recent labels on the chart to keep it clean. When a new label appears, the oldest one is automatically removed. Additionally, momentum labels have several filters: check the slope multiplier setting (higher values require stronger trends) and the Only Reversal Signals option (when enabled, labels only appear for potential reversals, not trend confirmations).
Q: What is the Calculated Projection and how accurate is it?
A: The Calculated Projection analyzes what happened in past market conditions similar to the current state. It classifies each bar by Z-Score level, Trend direction, and Volume profile (27 unique states), then shows the historical probability of up vs down and the average move size. It is NOT a price prediction or guarantee. The probability shown is how often similar conditions led to up/down moves historically, not a future guarantee. Always use it as one input among many.
Q: Why does the Projection probability change?
A: The projection updates on each bar as market state changes. If Z-Score moves from LOW to MID, or trend shifts from UP to FLAT, the system looks up a different historical category. This is expected behavior. The projection shows what happened in similar past conditions to the current bar's state.
Q: The Projection shows LOW confidence. What does that mean?
A: Confidence levels indicate sample size: HIGH means 30 or more historical cases found, MEDIUM means 15-29 cases, LOW means fewer than 15 cases. When sample size is low, the system uses a fallback: first aggregating by Z-Score plus Trend only (ignoring volume), then by Z-Score only. LOW confidence means less statistical reliability, so weight other factors more heavily in your decision.
Q: Why does the cone sometimes show 50/50 probability?
A: A 50/50 reading means that in similar past market states, price moved up roughly half the time and down half the time. This indicates a neutral or balanced condition where historical patterns provide no directional edge. Consider waiting for a higher probability setup or using other analysis methods.
CREDITS AND ACKNOWLEDGMENTS
Methodology Foundation:
VWAP (Volume Weighted Average Price) - Standard institutional benchmark calculation, widely used since the 1980s for algorithmic execution and fair value assessment
Standard Deviation Bands - Statistical volatility measurement applying normal distribution principles to price deviation from mean
Z-Score Analysis - Classic statistical normalization technique for comparing values across different volatility regimes
Cumulative Volume Delta (CVD) - Order flow analysis concept measuring aggressive buying versus selling pressure
Concept Integration:
Mean reversion probability engine - Custom historical statistics tracking for band touch rates
Momentum acceleration detection - Second derivative analysis of VWAP slope changes
VWAP Squeeze - Volatility compression concept adapted from TTM Squeeze methodology applied to VWAP bands versus ATR
Confidence scoring system - Weighted composite scoring combining multiple technical factors
Calculated Projection Cone - Probability-based projection using 27-state market classification (Z-Score, Trend, Volume) with historical outcome analysis and weighted fallback system
All calculations use standard public domain formulas and TradingView built-in functions. No proprietary third-party code was used.
For questions, feedback, or feature requests, please comment below or send a private message.
Happy Trading!
ULTIMATE ORDER FLOW SYSTEM🔥 ULTIMATE ORDER FLOW SYSTEM
Overview
This comprehensive order flow analysis tool combines **Volume Profile**, **Cumulative Delta**, and **Large Order Detection** to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react.
📊 Core Components & Methodology
🔥 ULTIMATE ORDER FLOW SYSTEM
Overview
This comprehensive order flow analysis tool combines Volume Profile, Cumulative Delta, and Large Order Detection to identify high-probability trading setups. The script analyzes institutional order flow patterns and volume distribution to pinpoint key levels where price is likely to react.
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📊 Core Components & Methodology
1. Volume Profile Analysis
The script constructs a horizontal volume profile by:
• Dividing the price range into configurable rows (default: 20)
• Accumulating volume at each price level over a lookback period (default: 50 bars)
• Separating buy volume (green bars close > open) from sell volume (red bars)
• Identifying three critical levels:
o POC (Point of Control): Price level with highest traded volume - acts as a strong magnet
o VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone
o HVN (High Volume Nodes): Resistance zones where institutions accumulated positions
o LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets
Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance.
________________________________________
2. Cumulative Delta (Order Flow)
Tracks the running total of buying vs selling pressure:
• Bar Delta: Difference between buy and sell volume per candle
• Cumulative Delta: Sum of all bar deltas - shows net directional pressure
• Delta Moving Average: Smoothed delta (20-period) to identify trend
• Delta Divergences:
o Bullish: Price makes lower low, but delta makes higher low (absorption at bottom)
o Bearish: Price makes higher high, but delta makes lower high (exhaustion at top)
How It Works: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations.
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3. Large Order Detection
Identifies institutional-sized orders in real-time:
• Compares current bar volume to 20-period moving average
• Flags orders exceeding 2.5x average volume (configurable multiplier)
• Distinguishes bullish (green circles below) vs bearish (red circles above) large orders
Rationale: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals.
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🎯 Trading Signal Logic
Combined Setup Criteria
The script generates SHORT and LONG signals when multiple conditions align:
SHORT Signal Requirements:
1. Price reaches an HVN resistance zone (within 0.2%)
2. Large sell order detected (volume spike + red candle)
3. Cumulative delta is bearish OR bearish divergence present
4. 10-bar cooldown between signals (prevents overtrading)
LONG Signal Requirements:
1. Price reaches an HVN support zone
2. Large buy order detected (volume spike + green candle)
3. Cumulative delta is bullish OR bullish divergence present
4. 10-bar cooldown enforced
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🔧 Customization Options
Setting - Purpose - Recommendation
Volume Profile Rows - Granularity of level detection - 20 (balanced)
Lookback Period - Historical data analyzed - 50 bars (intraday), 200 (swing)
Large Order Multiplier - Sensitivity to volume spikes - 2.5x (standard), 3.5x (conservative)
HVN Threshold - Resistance zone detection - 1.3 (default)
LVN Threshold - Target zone identification - 0.6 (default)
Divergence Lookback - Pivot detection period - 5 bars (responsive)
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📈 Dashboard Indicators
The real-time panel displays:
• POC: Current Point of Control price
• Location: Whether price is at HVN resistance
• Orders: Current large buy/sell activity
• Cumulative Δ: Net order flow value + trend direction
• Divergence: Active bullish/bearish divergences
• Bar Strength: % of candle volume that's directional (>65% = strong)
• SETUP: Current trade signal (LONG/SHORT/WAIT)
________________________________________
🎨 Visual System
• Yellow POC Line: Highest volume level - primary pivot
• Blue Value Area Box: Fair value zone (VAH to VAL)
• Red HVN Zones: Resistance/support from institutional accumulation
• Green LVN Zones: Low-liquidity targets for quick moves
• Volume Bars: Green (buy pressure) vs Red (sell pressure) distribution
• Triangles: LONG (green up) and SHORT (red down) entry signals
• Diamonds: Divergence warnings (cyan=bullish, fuchsia=bearish)
________________________________________
💡 How This Script Is Unique
Unlike standalone volume profile or delta indicators, this script:
1. Synthesizes three complementary methods - volume structure, order flow momentum, and liquidity detection
2. Requires multi-factor confirmation - signals only trigger when price, volume, and delta align at key zones
3. Adapts to market regime - delta filters ensure you're trading with the dominant order flow direction
4. Provides context, not just signals - the dashboard helps you understand why a setup is forming
________________________________________
⚙️ Best Practices
Timeframes:
• 5-15 min: Scalping (use 30-50 bar lookback)
• 1-4 hour: Swing trading (use 100-200 bar lookback)
Risk Management:
• Enter on signal candle close
• Stop loss: Beyond nearest HVN/LVN zone
• Target 1: Next LVN level
• Target 2: Opposite value area boundary
Filters:
• Avoid signals during major news events
• Require bar delta strength >65% for aggressive entries
• Wait for delta MA cross confirmation in ranging markets
________________________________________
🚨 Alerts Available
• Long Setup Trigger
• Short Setup Trigger
• Bullish/Bearish Divergence Detection
• Large Buy/Sell Order Execution
________________________________________
📚 Educational Context
This methodology is based on principles used by professional order flow traders:
• Market Profile Theory: Volume distribution reveals fair value
• Tape Reading: Large orders show institutional intent
• Auction Theory: Price seeks areas of liquidity imbalance (LVN zones)
The script automates pattern recognition that discretionary traders spend years learning to identify manually.
________________________________________
⚠️ Disclaimer
This indicator is a trading tool, not a trading system. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results.
________________________________________
Version: 6 (Pine Script)
Type: Overlay + Separate Pane (Delta Panel)
Resource Usage: Moderate (500 bars history, 500 lines/boxes)
________________________________________
For questions or support, please comment below. If you find this script valuable, please boost and favorite! 🚀
1. Volume Profile Analysis
The script constructs a horizontal volume profile by:
- Dividing the price range into configurable rows (default: 20)
- Accumulating volume at each price level over a lookback period (default: 50 bars)
- Separating buy volume (green bars close > open) from sell volume (red bars)
- Identifying three critical levels:
- POC (Point of Control): Price level with highest traded volume - acts as a strong magnet
- VAH/VAL (Value Area High/Low): Contains 70% of total volume - defines fair value zone
- HVN (High Volume Nodes): Resistance zones where institutions accumulated positions
- LVN (Low Volume Nodes): Thin zones that price moves through quickly - ideal targets
Why This Matters: Institutional traders leave footprints through volume. HVN zones show where large players defended levels, making them reliable support/resistance.
---
2. Cumulative Delta (Order Flow)
Tracks the running total of buying vs selling pressure:
- **Bar Delta**: Difference between buy and sell volume per candle
- **Cumulative Delta**: Sum of all bar deltas - shows net directional pressure
- **Delta Moving Average**: Smoothed delta (20-period) to identify trend
- **Delta Divergences**:
- **Bullish**: Price makes lower low, but delta makes higher low (absorption at bottom)
- **Bearish**: Price makes higher high, but delta makes lower high (exhaustion at top)
**How It Works**: When cumulative delta trends up while price consolidates, it signals accumulation. Delta divergences reveal when smart money is positioned opposite to retail expectations.
---
### 3. **Large Order Detection**
Identifies **institutional-sized orders** in real-time:
- Compares current bar volume to 20-period moving average
- Flags orders exceeding 2.5x average volume (configurable multiplier)
- Distinguishes bullish (green circles below) vs bearish (red circles above) large orders
**Rationale**: Sudden volume spikes at key levels indicate institutional participation - the "fuel" needed for breakouts or reversals.
---
## 🎯 Trading Signal Logic
### Combined Setup Criteria
The script generates **SHORT** and **LONG** signals when multiple conditions align:
**SHORT Signal Requirements:**
1. Price reaches an HVN resistance zone (within 0.2%)
2. Large sell order detected (volume spike + red candle)
3. Cumulative delta is bearish OR bearish divergence present
4. 10-bar cooldown between signals (prevents overtrading)
**LONG Signal Requirements:**
1. Price reaches an HVN support zone
2. Large buy order detected (volume spike + green candle)
3. Cumulative delta is bullish OR bullish divergence present
4. 10-bar cooldown enforced
---
## 🔧 Customization Options
| Setting | Purpose | Recommendation |
|---------|---------|----------------|
| **Volume Profile Rows** | Granularity of level detection | 20 (balanced) |
| **Lookback Period** | Historical data analyzed | 50 bars (intraday), 200 (swing) |
| **Large Order Multiplier** | Sensitivity to volume spikes | 2.5x (standard), 3.5x (conservative) |
| **HVN Threshold** | Resistance zone detection | 1.3 (default) |
| **LVN Threshold** | Target zone identification | 0.6 (default) |
| **Divergence Lookback** | Pivot detection period | 5 bars (responsive) |
---
## 📈 Dashboard Indicators
The real-time panel displays:
- **POC**: Current Point of Control price
- **Location**: Whether price is at HVN resistance
- **Orders**: Current large buy/sell activity
- **Cumulative Δ**: Net order flow value + trend direction
- **Divergence**: Active bullish/bearish divergences
- **Bar Strength**: % of candle volume that's directional (>65% = strong)
- **SETUP**: Current trade signal (LONG/SHORT/WAIT)
---
## 🎨 Visual System
- **Yellow POC Line**: Highest volume level - primary pivot
- **Blue Value Area Box**: Fair value zone (VAH to VAL)
- **Red HVN Zones**: Resistance/support from institutional accumulation
- **Green LVN Zones**: Low-liquidity targets for quick moves
- **Volume Bars**: Green (buy pressure) vs Red (sell pressure) distribution
- **Triangles**: LONG (green up) and SHORT (red down) entry signals
- **Diamonds**: Divergence warnings (cyan=bullish, fuchsia=bearish)
---
## 💡 How This Script Is Unique
Unlike standalone volume profile or delta indicators, this script:
1. **Synthesizes three complementary methods** - volume structure, order flow momentum, and liquidity detection
2. **Requires multi-factor confirmation** - signals only trigger when price, volume, and delta align at key zones
3. **Adapts to market regime** - delta filters ensure you're trading with the dominant order flow direction
4. **Provides context, not just signals** - the dashboard helps you understand *why* a setup is forming
---
## ⚙️ Best Practices
**Timeframes:**
- 5-15 min: Scalping (use 30-50 bar lookback)
- 1-4 hour: Swing trading (use 100-200 bar lookback)
**Risk Management:**
- Enter on signal candle close
- Stop loss: Beyond nearest HVN/LVN zone
- Target 1: Next LVN level
- Target 2: Opposite value area boundary
**Filters:**
- Avoid signals during major news events
- Require bar delta strength >65% for aggressive entries
- Wait for delta MA cross confirmation in ranging markets
---
## 🚨 Alerts Available
- Long Setup Trigger
- Short Setup Trigger
- Bullish/Bearish Divergence Detection
- Large Buy/Sell Order Execution
---
## 📚 Educational Context
This methodology is based on principles used by professional order flow traders:
- **Market Profile Theory**: Volume distribution reveals fair value
- **Tape Reading**: Large orders show institutional intent
- **Auction Theory**: Price seeks areas of liquidity imbalance (LVN zones)
The script automates pattern recognition that discretionary traders spend years learning to identify manually.
---
## ⚠️ Disclaimer
This indicator is a **trading tool, not a trading system**. It identifies high-probability setups based on order flow analysis but requires proper risk management, market context, and trader discretion. Past performance does not guarantee future results.
---
**Version**: 6 (Pine Script)
**Type**: Overlay + Separate Pane (Delta Panel)
**Resource Usage**: Moderate (500 bars history, 500 lines/boxes)
---
*For questions or support, please comment below. If you find this script valuable, please boost and favorite!* 🚀
Mars Signals - Ultimate Institutional Suite v3.0(Joker)Comprehensive Trading Manual
Mars Signals – Ultimate Institutional Suite v3.0 (Joker)
## Chapter 1 – Philosophy & System Architecture
This script is not a simple “buy/sell” indicator.
Mars Signals – UIS v3.0 (Joker) is designed as an institutional-style analytical assistant that layers several methodologies into a single, coherent framework.
The system is built on four core pillars:
1. Smart Money Concepts (SMC)
- Detection of Order Blocks (professional demand/supply zones).
- Detection of Fair Value Gaps (FVGs) (price imbalances).
2. Smart DCA Strategy
- Combination of RSI and Bollinger Bands
- Identifies statistically discounted zones for scaling into spot positions or exiting shorts.
3. Volume Profile (Visible Range Simulation)
- Distribution of volume by price, not by time.
- Identification of POC (Point of Control) and high-/low-volume areas.
4. Wyckoff Helper – Spring
- Detection of bear traps, liquidity grabs, and sharp bullish reversals.
All four pillars feed into a Confluence Engine (Scoring System).
The final output is presented in the Dashboard, with a clear, human-readable signal:
- STRONG LONG 🚀
- WEAK LONG ↗
- NEUTRAL / WAIT
- WEAK SHORT ↘
- STRONG SHORT 🩸
This allows the trader to see *how many* and *which* layers of the system support a bullish or bearish bias at any given time.
## Chapter 2 – Settings Overview
### 2.1 General & Dashboard Group
- Show Dashboard Panel (`show_dash`)
Turns the dashboard table in the corner of the chart ON/OFF.
- Show Signal Recommendation (`show_rec`)
- If enabled, the textual signal (STRONG LONG, WEAK SHORT, etc.) is displayed.
- If disabled, you only see feature status (ON/OFF) and the current price.
- Dashboard Position (`dash_pos`)
Determines where the dashboard appears on the chart:
- `Top Right`
- `Bottom Right`
- `Top Left`
### 2.2 Smart Money (SMC) Group
- Enable SMC Strategy (`show_smc`)
Globally enables or disables the Order Block and FVG logic.
- Order Block Pivot Lookback (`ob_period`)
Main parameter for detecting key pivot highs/lows (swing points).
- Default value: 5
- Concept:
A bar is considered a pivot low if its low is lower than the lows of the previous 5 and the next 5 bars.
Similarly, a pivot high has a high higher than the previous 5 and the next 5 bars.
These pivots are used as anchors for Order Blocks.
- Increasing `ob_period`:
- Fewer levels.
- But levels tend to be more significant and reliable.
- In highly volatile markets (major news, war events, FOMC, etc.),
using values 7–10 is recommended to filter out weak levels.
- Show Fair Value Gaps (`show_fvg`)
Enables/disables the drawing of FVG zones (imbalances).
- Bullish OB Color (`c_ob_bull`)
- Color of Bullish Order Blocks (Demand Zones).
- Default: semi-transparent green (transparency ≈ 80).
- Bearish OB Color (`c_ob_bear`)
- Color of Bearish Order Blocks (Supply Zones).
- Default: semi-transparent red.
- Bullish FVG Color (`c_fvg_bull`)
- Color of Bullish FVG (upward imbalance), typically yellow.
- Bearish FVG Color (`c_fvg_bear`)
- Color of Bearish FVG (downward imbalance), typically purple.
### 2.3 Smart DCA Strategy Group
- Enable DCA Zones (`show_dca`)
Enables the Smart DCA logic and visual labels.
- RSI Length (`rsi_len`)
Lookback period for RSI (default: 14).
- Shorter → more sensitive, more noise.
- Longer → fewer signals, higher reliability.
- Bollinger Bands Length (`bb_len`)
Moving average period for Bollinger Bands (default: 20).
- BB Multiplier (`bb_mult`)
Standard deviation multiplier for Bollinger Bands (default: 2.0).
- For extremely volatile markets, values like 2.5–3.0 can be used so that only extreme deviations trigger a DCA signal.
### 2.4 Volume Profile (Visible Range Sim) Group
- Show Volume Profile (`show_vp`)
Enables the simulated Volume Profile bars on the right side of the chart.
- Volume Lookback Bars (`vp_lookback`)
Number of bars used to compute the Volume Profile (default: 150).
- Higher values → broader historical context, heavier computation.
- Row Count (`vp_rows`)
Number of vertical price segments (rows) to divide the total price range into (default: 30).
- Width (%) (`vp_width`)
Relative width of each volume bar as a percentage.
In the code, bar widths are scaled relative to the row with the maximum volume.
> Technical note: Volume Profile calculations are executed only on the last bar (`barstate.islast`) to keep the script performant even on higher timeframes.
### 2.5 Wyckoff Helper Group
- Show Wyckoff Events (`show_wyc`)
Enables detection and plotting of Wyckoff Spring events.
- Volume MA Length (`vol_ma_len`)
Length of the moving average on volume.
A bar is considered to have Ultra Volume if its volume is more than 2× the volume MA.
## Chapter 3 – Smart Money Strategy (Order Blocks & FVG)
### 3.1 What Is an Order Block?
An Order Block (OB) represents the footprint of large institutional orders:
- Bullish Order Block (Demand Zone)
The last selling region (bearish candle/cluster) before a strong upward move.
- Bearish Order Block (Supply Zone)
The last buying region (bullish candle/cluster) before a strong downward move.
Institutions and large players place heavy orders in these regions. Typical price behavior:
- Price moves away from the zone.
- Later returns to the same zone to fill unfilled orders.
- Then continues the larger trend.
In the script:
- If `pl` (pivot low) forms → a Bullish OB is created.
- If `ph` (pivot high) forms → a Bearish OB is created.
The box is drawn:
- From `bar_index ` to `bar_index`.
- Between `low ` and `high `.
- `extend=extend.right` extends the OB into the future, so it acts as a dynamic support/resistance zone.
- Only the last 4 OB boxes are kept to avoid clutter.
### 3.2 Order Block Color Guide
- Semi-transparent Green (`c_ob_bull`)
- Represents a Bullish Order Block (Demand Zone).
- Interpretation: a price region with a high probability of bullish reaction.
- Semi-transparent Red (`c_ob_bear`)
- Represents a Bearish Order Block (Supply Zone).
- Interpretation: a price region with a high probability of bearish reaction.
Overlap (Multiple OBs in the Same Area)
When two or more Order Blocks overlap:
- The shared area appears visually denser/stronger.
- This suggests higher order density.
- Such zones can be treated as high-priority levels for entries, exits, and stop-loss placement.
### 3.3 Demand/Supply Logic in the Scoring Engine
is_in_demand = low <= ta.lowest(low, 20)
is_in_supply = high >= ta.highest(high, 20)
- If current price is near the lowest lows of the last 20 bars, it is considered in a Demand Zone → positive impact on score.
- If current price is near the highest highs of the last 20 bars, it is considered in a Supply Zone → negative impact on score.
This logic complements Order Blocks and helps the Dashboard distinguish whether:
- Market is currently in a statistically cheap (long-friendly) area, or
- In a statistically expensive (short-friendly) area.
### 3.4 Fair Value Gaps (FVG)
#### Concept
When the market moves aggressively:
- Some price levels are skipped and never traded.
- A gap between wicks/shadows of consecutive candles appears.
- These regions are called Fair Value Gaps (FVGs) or Imbalances.
The market generally “dislikes” imbalance and often:
- Returns to these zones in the future.
- Fills the gap (rebalance).
- Then resumes its dominant direction.
#### Implementation in the Code
Bullish FVG (Yellow)
fvg_bull_cond = show_smc and show_fvg and low > high and close > high
if fvg_bull_cond
box.new(bar_index , high , bar_index, low, ...)
Core condition:
`low > high ` → the current low is above the high of two bars ago; the space between them is an untraded gap.
Bearish FVG (Purple)
fvg_bear_cond = show_smc and show_fvg and high < low and close < low
if fvg_bear_cond
box.new(bar_index , low , bar_index, high, ...)
Core condition:
`high < low ` → the current high is below the low of two bars ago; again a price gap exists.
#### FVG Color Guide
- Transparent Yellow (`c_fvg_bull`) – Bullish FVG
Often acts like a magnet for price:
- Price tends to retrace into this zone,
- Fill the imbalance,
- And then continue higher.
- Transparent Purple (`c_fvg_bear`) – Bearish FVG
Price tends to:
- Retrace upward into the purple area,
- Fill the imbalance,
- And then resume downward movement.
#### Trading with FVGs
- FVGs are *not* standalone entry signals.
They are best used as:
- Targets (take-profit zones), or
- Reaction areas where you expect a pause or reversal.
Examples:
- If you are long, a bearish FVG above is often an excellent take-profit zone.
- If you are short, a bullish FVG below is often a good cover/exit zone.
### 3.5 Core SMC Trading Templates
#### Reversal Long
1. Price trades down into a green Order Block (Demand Zone).
2. A bullish confirmation candle (Close > Open) forms inside or just above the OB.
3. If this zone is close to or aligned with a bullish FVG (yellow), the signal is reinforced.
4. Entry:
- At the close of the confirmation candle, or
- Using a limit order near the upper boundary of the OB.
5. Stop-loss:
- Slightly below the OB.
- If the OB is broken decisively and price consolidates below it, the zone loses validity.
6. Targets:
- The next FVG,
- Or the next red Order Block (Supply Zone) above.
#### Reversal Short
The mirror scenario:
- Price rallies into a red Order Block (Supply).
- A bearish confirmation candle forms (Close < Open).
- FVG/premium structure above can act as a confluence.
- Stop-loss goes above the OB.
- Targets: lower FVGs or subsequent green OBs below.
## Chapter 4 – Smart DCA Strategy (RSI + Bollinger Bands)
### 4.1 Smart DCA Concept
- Classic DCA = buying at fixed time intervals regardless of price.
- Smart DCA = scaling in only when:
- Price is statistically cheaper than usual, and
- The market is in a clear oversold condition.
Code logic:
rsi_val = ta.rsi(close, rsi_len)
= ta.bb(close, bb_len, bb_mult)
dca_buy = show_dca and rsi_val < 30 and close < bb_lower
dca_sell = show_dca and rsi_val > 70 and close > bb_upper
Conditions:
- DCA Buy – Smart Scale-In Zone
- RSI < 30 → oversold.
- Close < lower Bollinger Band → price has broken below its typical volatility envelope.
- DCA Sell – Overbought/Distribution Zone
- RSI > 70 → overbought.
- Close > upper Bollinger Band → price is extended far above the mean.
### 4.2 Visual Representation on the Chart
- Green “DCA” Label Below Candle
- Shape: `labelup`.
- Color: lime background, white text.
- Meaning: statistically attractive level for laddered spot entries or short exits.
- Red “SELL” Label Above Candle
- Warning that the market is in an extended, overbought condition.
- Suitable for profit-taking on longs or considering short entries (with proper confluence and risk management).
- Light Green Background (`bgcolor`)
- When `dca_buy` is true, the candle background turns very light green (high transparency).
- This helps visually identify DCA Zones across the chart at a glance.
### 4.3 Practical Use in Trading
#### Spot Trading
Used to build a better average entry price:
- Every time a DCA label appears, allocate a fixed portion of capital (e.g., 2–5%).
- Combining DCA signals with:
- Green OBs (Demand Zones), and/or
- The Volume Profile POC
makes the zone structurally more important.
#### Futures Trading
- Longs
- Use DCA Buy signals as low-risk zones for opening or adding to longs when:
- Price is inside a green OB, or
- The Dashboard already leans LONG.
- Shorts
- Use DCA Sell signals as:
- Exit zones for longs, or
- Areas to initiate shorts with stops above structural highs.
## Chapter 5 – Volume Profile (Visible Range Simulation)
### 5.1 Concept
Traditional volume (histogram under the chart) shows volume over time.
Volume Profile shows volume by price level:
- At which prices has the highest trading activity occurred?
- Where did buyers and sellers agree the most (High Volume Nodes – HVNs)?
- Where did price move quickly due to low participation (Low Volume Nodes – LVNs)?
### 5.2 Implementation in the Script
Executed only when `show_vp` is enabled and on the last bar:
1. The last `vp_lookback` bars (default 150) are processed.
2. The minimum low and maximum high over this window define the price range.
3. This price range is divided into `vp_rows` segments (e.g., 30 rows).
4. For each row:
- All bars are scanned.
- If the mid-price `(high + low ) / 2` falls inside a row, that bar’s volume is added to the row total.
5. The row with the greatest volume is stored as `max_vol_idx` (the POC row).
6. For each row, a volume box is drawn on the right side of the chart.
### 5.3 Color Scheme
- Semi-transparent Orange
- The row with the maximum volume – the Point of Control (POC).
- Represents the strongest support/resistance level from a volume perspective.
- Semi-transparent Blue
- Other volume rows.
- The taller the bar → the higher the volume → the stronger the interest at that price band.
### 5.4 Trading Applications
- If price is above POC and retraces back into it:
→ POC often acts as support, suitable for long setups.
- If price is below POC and rallies into it:
→ POC often acts as resistance, suitable for short setups or profit-taking.
HVNs (Tall Blue Bars)
- Represent areas of equilibrium where the market has spent time and traded heavily.
- Price tends to consolidate here before choosing a direction.
LVNs (Short or Nearly Empty Bars)
- Represent low participation zones.
- Price often moves quickly through these areas – useful for targeting fast moves.
## Chapter 6 – Wyckoff Helper – Spring
### 6.1 Spring Concept
In the Wyckoff framework:
- A Spring is a false break of support.
- The market briefly trades below a well-defined support level, triggers stop losses,
then sharply reverses upward as institutional buyers absorb liquidity.
This movement:
- Clears out weak hands (retail sellers).
- Provides large players with liquidity to enter long positions.
- Often initiates a new uptrend.
### 6.2 Code Logic
Conditions for a Spring:
1. The current low is lower than the lowest low of the previous 50 bars
→ apparent break of a long-standing support.
2. The bar closes bullish (Close > Open)
→ the breakdown was rejected.
3. Volume is significantly elevated:
→ `volume > 2 × volume_MA` (Ultra Volume).
When all conditions are met and `show_wyc` is enabled:
- A pink diamond is plotted below the bar,
- With the label “Spring” – one of the strongest long signals in this system.
### 6.3 Trading Use
- After a valid Spring, markets frequently enter a meaningful bullish phase.
- The highest quality setups occur when:
- The Spring forms inside a green Order Block, and
- Near or on the Volume Profile POC.
Entries:
- At the close of the Spring bar, or
- On the first pullback into the mid-range of the Spring candle.
Stop-loss:
- Slightly below the Spring’s lowest point (wick low plus a small buffer).
## Chapter 7 – Confluence Engine & Dashboard
### 7.1 Scoring Logic
For each bar, the script:
1. Resets `score` to 0.
2. Adjusts the score based on different signals.
SMC Contribution
if show_smc
if is_in_demand
score += 1
if is_in_supply
score -= 1
- Being in Demand → `+1`
- Being in Supply → `-1`
DCA Contribution
if show_dca
if dca_buy
score += 2
if dca_sell
score -= 2
- DCA Buy → `+2` (strong, statistically driven long signal)
- DCA Sell → `-2`
Wyckoff Spring Contribution
if show_wyc
if wyc_spring
score += 2
- Spring → `+2` (entry of strong money)
### 7.2 Mapping Score to Dashboard Signal
- score ≥ 2 → STRONG LONG 🚀
Multiple bullish conditions aligned.
- score = 1 → WEAK LONG ↗
Some bullish bias, but only one layer clearly positive.
- score = 0 → NEUTRAL / WAIT
Rough balance between buying and selling forces; staying flat is usually preferable.
- score = -1 → WEAK SHORT ↘
Mild bearish bias, suited for cautious or short-term plays.
- score ≤ -2 → STRONG SHORT 🩸
Convergence of several bearish signals.
### 7.3 Dashboard Structure
The dashboard is a two-column table:
- Row 0
- Column 0: `"Mars Signals"` – black background, white text.
- Column 1: `"UIS v3.0"` – black background, yellow text.
- Row 1
- Column 0: `"Price:"` (light grey background).
- Column 1: current closing price (`close`) with a semi-transparent blue background.
- Row 2
- Column 0: `"SMC:"`
- Column 1:
- `"ON"` (green) if `show_smc = true`
- `"OFF"` (grey) otherwise.
- Row 3
- Column 0: `"DCA:"`
- Column 1:
- `"ON"` (green) if `show_dca = true`
- `"OFF"` (grey) otherwise.
- Row 4
- Column 0: `"Signal:"`
- Column 1: signal text (`status_txt`) with background color `status_col`
(green, red, teal, maroon, etc.)
- If `show_rec = false`, these cells are cleared.
## Chapter 8 – Visual Legend (Colors, Shapes & Actions)
For quick reading inside TradingView, the visual elements are described line by line instead of a table.
Chart Element: Green Box
Color / Shape: Transparent green rectangle
Core Meaning: Bullish Order Block (Demand Zone)
Suggested Trader Response: Look for longs, Smart DCA adds, closing or reducing shorts.
Chart Element: Red Box
Color / Shape: Transparent red rectangle
Core Meaning: Bearish Order Block (Supply Zone)
Suggested Trader Response: Look for shorts, or take profit on existing longs.
Chart Element: Yellow Area
Color / Shape: Transparent yellow zone
Core Meaning: Bullish FVG / upside imbalance
Suggested Trader Response: Short take-profit zone or expected rebalance area.
Chart Element: Purple Area
Color / Shape: Transparent purple zone
Core Meaning: Bearish FVG / downside imbalance
Suggested Trader Response: Long take-profit zone or temporary supply region.
Chart Element: Green "DCA" Label
Color / Shape: Green label with white text, plotted below the candle
Core Meaning: Smart ladder-in buy zone, DCA buy opportunity
Suggested Trader Response: Spot DCA entry, partial short exit.
Chart Element: Red "SELL" Label
Color / Shape: Red label with white text, plotted above the candle
Core Meaning: Overbought / distribution zone
Suggested Trader Response: Take profit on longs, consider initiating shorts.
Chart Element: Light Green Background (bgcolor)
Color / Shape: Very transparent light-green background behind bars
Core Meaning: Active DCA Buy zone
Suggested Trader Response: Treat as a discount zone on the chart.
Chart Element: Orange Bar on Right
Color / Shape: Transparent orange horizontal bar in the volume profile
Core Meaning: POC – price with highest traded volume
Suggested Trader Response: Strong support or resistance; key reference level.
Chart Element: Blue Bars on Right
Color / Shape: Transparent blue horizontal bars in the volume profile
Core Meaning: Other volume levels, showing high-volume and low-volume nodes
Suggested Trader Response: Use to identify balance zones (HVN) and fast-move corridors (LVN).
Chart Element: Pink "Spring" Diamond
Color / Shape: Pink diamond with white text below the candle
Core Meaning: Wyckoff Spring – liquidity grab and potential major bullish reversal
Suggested Trader Response: One of the strongest long signals in the suite; look for high-quality long setups with tight risk.
Chart Element: STRONG LONG in Dashboard
Color / Shape: Green background, white text in the Signal row
Core Meaning: Multiple bullish layers in confluence
Suggested Trader Response: Consider initiating or increasing longs with strict risk management.
Chart Element: STRONG SHORT in Dashboard
Color / Shape: Red background, white text in the Signal row
Core Meaning: Multiple bearish layers in confluence
Suggested Trader Response: Consider initiating or increasing shorts with a logical, well-placed stop.
## Chapter 9 – Timeframe-Based Trading Playbook
### 9.1 Timeframe Selection
- Scalping
- Timeframes: 1M, 5M, 15M
- Objective: fast intraday moves (minutes to a few hours).
- Recommendation: focus on SMC + Wyckoff.
Smart DCA on very low timeframes may introduce excessive noise.
- Day Trading
- Timeframes: 15M, 1H, 4H
- Provides a good balance between signal quality and frequency.
- Recommendation: use the full stack – SMC + DCA + Volume Profile + Wyckoff + Dashboard.
- Swing Trading & Position Investing
- Timeframes: Daily, Weekly
- Emphasis on Smart DCA + Volume Profile.
- SMC and Wyckoff are used mainly to fine-tune swing entries within larger trends.
### 9.2 Scenario A – Scalping Long
Example: 5-Minute Chart
1. Price is declining into a green OB (Bullish Demand).
2. A candle with a long lower wick and bullish close (Pin Bar / Rejection) forms inside the OB.
3. A Spring diamond appears below the same candle → very strong confluence.
4. The Dashboard shows at least WEAK LONG ↗, ideally STRONG LONG 🚀.
5. Entry:
- On the close of the confirmation candle, or
- On the first pullback into the mid-range of that candle.
6. Stop-loss:
- Slightly below the OB.
7. Targets:
- Nearby bearish FVG above, and/or
- The next red OB.
### 9.3 Scenario B – Day-Trading Short
Recommended Timeframes: 1H or 4H
1. The market completes a strong impulsive move upward.
2. Price enters a red Order Block (Supply).
3. In the same zone, a purple FVG appears or remains unfilled.
4. On a lower timeframe (e.g., 15M), RSI enters overbought territory and a DCA Sell signal appears.
5. The main timeframe Dashboard (1H) shows WEAK SHORT ↘ or STRONG SHORT 🩸.
Trade Plan
- Open a short near the upper boundary of the red OB.
- Place the stop above the OB or above the last swing high.
- Targets:
- A yellow FVG lower on the chart, and/or
- The next green OB (Demand) below.
### 9.4 Scenario C – Swing / Investment with Smart DCA
Timeframes: Daily / Weekly
1. On the daily or weekly chart, each time a green “DCA” label appears:
- Allocate a fixed fraction of your capital (e.g., 3–5%) to that asset.
2. Check whether this DCA zone aligns with the orange POC of the Volume Profile:
- If yes → the quality of the entry zone is significantly higher.
3. If the DCA signal sits inside a daily green OB, the probability of a medium-term bottom increases.
4. Always build the position laddered, never all-in at a single price.
Exits for investors:
- Near weekly red OBs or large purple FVG zones.
- Ideally via partial profit-taking rather than closing 100% at once.
### 9.5 Case Study 1 – BTCUSDT (15-Minute)
- Context: Price has sold off down towards 65,000 USD.
- A green OB had previously formed at that level.
- Near the lower boundary of this OB, a partially filled yellow FVG is present.
- As price returns to this region, a Spring appears.
- The Dashboard shifts from NEUTRAL / WAIT to WEAK LONG ↗.
Plan
- Enter a long near the OB low.
- Place stop below the Spring low.
- First target: a purple FVG around 66,200.
- Second (optional) target: the first red OB above that level.
### 9.6 Case Study 2 – Meme Coin (PEPE – 4H)
- After a strong pump, price enters a corrective phase.
- On the 4H chart, RSI drops below 30; price breaks below the lower Bollinger Band → a DCA label prints.
- The Volume Profile shows the POC at approximately the same level.
- The Dashboard displays STRONG LONG 🚀.
Plan
- Execute laddered buys in the combined DCA + POC zone.
- Place a protective stop below the last significant swing low.
- Target: an expected 20–30% upside move towards the next red OB or purple FVG.
## Chapter 10 – Risk Management, Psychology & Advanced Tuning
### 10.1 Risk Management
No signal, regardless of its strength, replaces risk control.
Recommendations:
- In futures, do not expose more than 1–3% of account equity to risk per trade.
- Adjust leverage to the volatility of the instrument (lower leverage for highly volatile altcoins).
- Place stop-losses in zones where the idea is clearly invalidated:
- Below/above the relevant Order Block or Spring, not randomly in the middle of the structure.
### 10.2 Market-Specific Parameter Tuning
- Calmer Markets (e.g., major FX pairs)
- `ob_period`: 3–5.
- `bb_mult`: 2.0 is usually sufficient.
- Highly Volatile Markets (Crypto, news-driven assets)
- `ob_period`: 7–10 to highlight only the most robust OBs.
- `bb_mult`: 2.5–3.0 so that only extreme deviations trigger DCA.
- `vol_ma_len`: increase (e.g., to ~30) so that Spring triggers only on truly exceptional
volume spikes.
### 10.3 Trading Psychology
- STRONG LONG 🚀 does not mean “risk-free”.
It means the probability of a successful long, given the model’s logic, is higher than average.
- Treat Mars Signals as a confirmation and context system, not a full replacement for your own decision-making.
- Example of disciplined thinking:
- The Dashboard prints STRONG LONG,
- But price is simultaneously testing a multi-month macro resistance or a major negative news event is imminent,
- In such cases, trade smaller, widen stops appropriately, or skip the trade.
## Chapter 11 – Technical Notes & FAQ
### 11.1 Does the Script Repaint?
- Order Blocks and Springs are based on completed pivot structures and confirmed candles.
- Until a pivot is confirmed, an OB does not exist; after confirmation, behavior is stable under classic SMC assumptions.
- The script is designed to be structurally consistent rather than repainting signals arbitrarily.
### 11.2 Computational Load of Volume Profile
- On the last bar, the script processes up to `vp_lookback` bars × `vp_rows` rows.
- On very low timeframes with heavy zooming, this can become demanding.
- If you experience performance issues:
- Reduce `vp_lookback` or `vp_rows`, or
- Temporarily disable Volume Profile (`show_vp = false`).
### 11.3 Multi-Timeframe Behavior
- This version of the script is not internally multi-timeframe.
All logic (OB, DCA, Spring, Volume Profile) is computed on the active timeframe only.
- Practical workflow:
- Analyze overall structure and key zones on higher timeframes (4H / Daily).
- Use lower timeframes (15M / 1H) with the same tool for timing entries and exits.
## Conclusion
Mars Signals – Ultimate Institutional Suite v3.0 (Joker) is a multi-layer trading framework that unifies:
- Price structure (Order Blocks & FVG),
- Statistical behavior (Smart DCA via RSI + Bollinger),
- Volume distribution by price (Volume Profile with POC, HVN, LVN),
- Liquidity events (Wyckoff Spring),
into a single, coherent system driven by a transparent Confluence Scoring Engine.
The final output is presented in clear, actionable language:
> STRONG LONG / WEAK LONG / NEUTRAL / WEAK SHORT / STRONG SHORT
The system is designed to support professional decision-making, not to replace it.
Used together with strict risk management and disciplined execution,
Mars Signals – UIS v3.0 (Joker) can serve as a central reference manual and operational guide
for your trading workflow, from scalping to swing and investment positioning.
Time-Decay Liquidity Zones [BackQuant]Time-Decay Liquidity Zones
A dynamic liquidity map that turns single-bar exhaustion events into fading, color-graded zones, so you can see where trapped traders and unfinished business still matter, and when those areas have finally stopped pulling price.
What this is
This indicator detects unusually strong impulsive moves into wicks, converts them into supply or demand “zones,” then lets those zones decay over time. Each zone carries a strength score that fades bar by bar. Zones that stop attracting or rejecting price are gradually de-emphasized and eventually removed, while the most relevant areas stay bright and obvious.
Instead of static rectangles that live forever, you get a living liquidity map where:
Zones are born from objective criteria: volatility, wick size, and optional volume spikes.
Zones “age” using a configurable decay factor and maximum lifetime.
Zone color and opacity reflect current relative strength on a unified clear → green → red gradient.
Zones freeze when broken, so you can distinguish “active reaction areas” from “historical levels that have already given way”.
Conceptual idea
Large wicks with strong volatility often mark areas where aggressive orders met hidden liquidity and got absorbed. Price may revisit these areas to test leftover interest or to relieve trapped positions. However, not every wick matters for long. As time passes and more bars print, the market “forgets” some areas.
Time-Decay Liquidity Zones turns that idea into a rule-based system:
Find bars that likely reflect strong aggressive flows into liquidity.
Mark a zone around the wick using ATR-based thickness.
Assign a strength score of 1.0 at birth.
Each bar, reduce that score by a decay factor and remove zones that fall below a threshold or live too long.
Color all surviving zones from weak to strong using a single gradient scale and a visual legend.
How events are detected
Detection lives in the Event Detection group. The script combines range, wick size, and optional volume filters into simple rules.
Volatility filter
ATR Length — computes a rolling ATR over your chosen window. This is the volatility baseline.
Min range in ATRs — bar range (High–Low) must exceed this multiple of ATR for an event to be considered. This avoids tiny bars triggering zones.
Wick filters
For each bar, the script splits the candle into body and wicks:
Upper wick = High minus the max(Open, Close).
Lower wick = min(Open, Close) minus Low.
Then it tests:
Upper wick condition — upper wick must be larger than Min wick size in ATRs × ATR.
Lower wick condition — lower wick must be larger than Min wick size in ATRs × ATR.
Only bars with a sufficiently long wick relative to volatility qualify as candidate “liquidity events”.
Volume filter
Optionally, the script requires a volume spike:
Use volume filter — if enabled, volume must exceed a rolling volume SMA by a configurable multiplier.
Volume SMA length — period for the volume average.
Volume spike multiplier — how many times above the SMA current volume needs to be.
This lets you focus only on “heavy” tests of liquidity and ignore quiet bars.
Event types
Putting it together:
Upper event (potential supply / long liquidation, etc.)
Occurs when:
Upper wick is large in ATR terms.
Full bar range is large in ATR terms.
Volume is above the spike threshold (if enabled).
Lower event (potential demand / short liquidation, etc.)
Symmetric conditions using the lower wick.
How zones are constructed
Zone geometry lives in Zone Geometry .
When an event is detected, the script builds a rectangular box that anchors to the wick and extends in the appropriate direction by an ATR-based thickness.
For upper (supply-type) zones
Bottom of the zone = event bar high.
Top of the zone = event bar high + Zone thickness in ATRs × ATR.
The zone initially spans only the event bar on the x-axis, but is extended to the right as new bars appear while the zone is active.
For lower (demand-type) zones
Top of the zone = event bar low.
Bottom of the zone = event bar low − Zone thickness in ATRs × ATR.
Same extension logic: box starts on the event bar and grows rightward while alive.
The result is a band around the wick that scales with volatility. On high-ATR charts, zones are thicker. On calm charts, they are narrower and more precise.
Zone lifecycle, decay, and removal
All lifecycle logic is controlled by the Decay & Lifetime group.
Each zone carries:
Score — a floating-point “importance” measure, starting at 1.0 when created.
Direction — +1 for upper zones, −1 for lower zones.
Birth index — bar index at creation time.
Active flag — whether the zone is still considered unbroken and extendable.
1) Active vs broken
Each confirmed bar, the script checks:
For an upper zone , the zone is counted as “broken” when the close moves above the top of the zone.
For a lower zone , the zone is counted as “broken” when the close moves below the bottom of the zone.
When a zone breaks:
Its right edge is frozen at the previous bar (no further extension).
The zone remains on the chart, but is no longer updated by price interaction. It still decays in score until removal.
This lets you see where a major level was overrun, while naturally fading its influence over time.
2) Time decay
At each confirmed bar:
Score := Score × Score decay per bar .
A decay value close to 1.0 means very slow decay and long-lived zones.
Lower values (closer to 0.9) mean faster forgetting and more current-focused zones.
You are controlling how quickly the market “forgets” past events.
3) Age and score-based removal
Zones are removed when either:
Age in bars exceeds Max bars a zone can live .
This is a hard lifetime cap.
Score falls below Minimum score before removal .
This trims zones that have decayed into irrelevance even if their age is still within bounds.
When a zone is removed, its box is deleted and all associated state is freed to keep performance and visuals clean.
Unified gradient and color logic
Color control lives in Gradient & Color . The indicator uses a single continuous gradient for all zones, above and below price, so you can read strength at a glance without guessing what palette means what.
Base colors
You set:
Mid strength color (green) — used for mid-level strength zones and as the “anchor” in the gradient.
High strength color (red) — used for the strongest zones.
Max opacity — the maximum visual opacity for the solid part of the gradient. Lower values here mean more solid; higher values mean more transparent.
The script then defines three internal points:
Clear end — same as mid color, but with a high alpha (close to transparent).
Mid end — mid color at the strongest allowed opacity.
High end — high color at the strongest allowed opacity.
Strength normalization
Within each update:
The script finds the maximum score among all existing zones.
Each zone’s strength is computed as its score divided by this maximum.
Strength is clamped into .
This means a zone with strength 1.0 is currently the strongest zone on the chart. Other zones are colored relative to that.
Piecewise gradient
Color is assigned in two stages:
For strength between 0.0 and 0.5: interpolate from “clear” green to solid green.
Weak zones are barely visible, mid-strength zones appear as solid green.
For strength between 0.5 and 1.0: interpolate from solid green to solid red.
The strongest zones shift toward the red anchor, clearly separating them from everything else.
Strength scale legend
To make the gradient readable, the indicator draws a vertical legend on the right side of the chart:
About 15 cells from top (Strong) to bottom (Weak).
Each cell uses the same gradient function as the zones themselves.
Top cell is labeled “Strong”; bottom cell is labeled “Weak”.
This legend acts as a fixed reference so you can instantly map a zone’s color to its approximate strength rank.
What it plots
At a glance, the indicator produces:
Upper liquidity zones above price, built from large upper wick events.
Lower liquidity zones below price, built from large lower wick events.
All zones colored by relative strength using the same gradient.
Zones that freeze when price breaks them, then fade out via decay and removal.
A strength scale legend on the right to interpret the gradient.
There are no extra lines, labels, or clutter. The focus is the evolving structure of liquidity zones and their visual strength.
How to read the zones
Bright red / bright green zones
These are your current “major” liquidity areas. They have high scores relative to other zones and have not yet decayed. Expect meaningful reactions, absorption attempts, or spillover moves when price interacts with them.
Faded zones
Pale, nearly transparent zones are either old, decayed, or minor. They can still matter, but priority is lower. If these are in the middle of a long consolidation, they often become background noise.
Broken but still visible zones
Zones whose extension has stopped have been overrun by closing price. They show where a key level gave way. You can use them as context for regime shifts or failed attempts.
Absence of zones
A chart with few or no zones means that, under your current thresholds, there have not been strong enough liquidity events recently. Either tighten the filters or accept that recent price action has been relatively balanced.
Use cases
1) Intraday liquidity hunting
Run the indicator on lower timeframes (e.g., 1–15 minute) with moderately fast decay.
Use the upper zones as potential sell reaction areas, the lower zones as potential buy reaction areas.
Combine with order flow, CVD, or footprint tools to see whether price is absorbing or rejecting at each zone.
2) Swing trading context
Increase ATR length and range/wick multipliers to focus only on major spikes.
Set slower decay and higher max lifetime so zones persist across multiple sessions.
Use these zones as swing inflection areas for larger setups, for example anticipating re-tests after breakouts.
3) Stop placement and invalidation
For longs, place invalidation beyond a decaying lower zone rather than in the middle of noise.
For shorts, place invalidation beyond strong upper zones.
If price closes through a strong zone and it freezes, treat that as additional evidence your prior bias may be wrong.
4) Identifying trapped flows
Upper zones formed after violent spikes up that quickly fail can mark trapped longs.
Lower zones formed after violent spikes down that quickly reverse can mark trapped shorts.
Watching how price behaves on the next touch of those zones can hint at whether those participants are being rescued or squeezed.
Settings overview
Event Detection
Use volume filter — enable or disable the volume spike requirement.
Volume SMA length — rolling window for average volume.
Volume spike multiplier — how aggressive the volume spike filter is.
ATR length — period for ATR, used in all size comparisons.
Min wick size in ATRs — minimum wick size threshold.
Min range in ATRs — minimum bar range threshold.
Zone Geometry
Zone thickness in ATRs — vertical size of each liquidity zone, scaled by ATR.
Decay & Lifetime
Score decay per bar — multiplicative decay factor for each zone score per bar.
Max bars a zone can live — hard cap on lifetime.
Minimum score before removal — score cut-off at which zones are deleted.
Gradient & Color
Mid strength color (green) — base color for mid-level zones and the lower half of the gradient.
High strength color (red) — target color for the strongest zones.
Max opacity — controls the most solid end of the gradient (0 = fully solid, 100 = fully invisible).
Tuning guidance
Fast, session-only liquidity
Shorter ATR length (e.g., 20–50).
Higher wick and range multipliers to focus only on extreme events.
Decay per bar closer to 0.95–0.98 and moderate max lifetime.
Volume filter enabled with a decent multiplier (e.g., 1.5–2.0).
Slow, structural zones
Longer ATR length (e.g., 100+).
Moderate wick and range thresholds.
Decay per bar very close to 1.0 for slow fading.
Higher max lifetime and slightly higher min score threshold so only very weak zones disappear.
Noisy, high-volatility instruments
Increase wick and range ATR multipliers to avoid over-triggering.
Consider enabling the volume filter with stronger settings.
Keep decay moderate to avoid the chart getting overloaded with old zones.
Notes
This is a structural and contextual tool, not a complete trading system. It does not account for transaction costs, execution slippage, or your specific strategy rules. Use it to:
Highlight where liquidity has recently been tested hard.
Rank these areas by decaying strength.
Guide your attention when layering in separate entry signals, risk management, and higher-timeframe context.
Time-Decay Liquidity Zones is designed to keep your chart focused on where the market has most recently “cared” about price, and to gradually forget what no longer matters. Adjust the detection, geometry, decay, and gradient to fit your product and timeframe, and let the zones show you which parts of the tape still have unfinished business.
Liquidity Void Zone Detector [PhenLabs]📊 Liquidity Void Zone Detector
Version: PineScript™v6
📌 Description
The Liquidity Void Zone Detector is a sophisticated technical indicator designed to identify and visualize areas where price moved with abnormally low volume or rapid momentum, creating "voids" in market liquidity. These zones represent areas where insufficient trading activity occurred during price movement, often acting as magnets for future price action as the market seeks to fill these gaps.
Built on PineScript v6, this indicator employs a dual-detection methodology that analyzes both volume depletion patterns and price movement intensity relative to ATR. The revolutionary 3D visualization system uses three-layer polyline rendering with adaptive transparency and vertical offsets, creating genuine depth perception where low liquidity zones visually recede and high liquidity zones protrude forward. This makes critical market structure immediately apparent without cluttering your chart.
🚀 Points of Innovation
Dual detection algorithm combining volume threshold analysis and ATR-normalized price movement sensitivity for comprehensive void identification
Three-layer 3D visualization system with progressive transparency gradients (85%, 78%, 70%) and calculated vertical offsets for authentic depth perception
Intelligent state machine logic that tracks consecutive void bars and only renders zones meeting minimum qualification requirements
Dynamic strength scoring system (0-100 scale) that combines inverted volume ratios with movement intensity for accurate void characterization
Adaptive ATR-based spacing calculation that automatically adjusts 3D layering depth to match instrument volatility
Efficient memory management system supporting up to 100 simultaneous void visualizations with automatic array-based cleanup
🔧 Core Components
Volume Analysis Engine: Calculates rolling volume averages and compares current bar volume against dynamic thresholds to detect abnormally thin trading conditions
Price Movement Analyzer: Normalizes bar range against ATR to identify rapid price movements that indicate liquidity exhaustion regardless of instrument or timeframe
Void Tracking State Machine: Maintains persistent tracking of void start bars, price boundaries, consecutive bar counts, and cumulative strength across multiple bars
3D Polyline Renderer: Generates three-layer rectangular polylines with precise timestamp-to-bar index conversion and progressive offset calculations
Strength Calculation System: Combines volume component (inverted ratio capped at 100) with movement component (ATR intensity × 30) for comprehensive void scoring
🔥 Key Features
Automatic Void Detection: Continuously scans price action for low volume conditions or rapid movements, triggering void tracking when thresholds are exceeded
Real-Time Visualization: Creates 3D rectangular zones spanning from void initiation to termination, with color-coded depth indicating liquidity type
Adjustable Sensitivity: Configure volume threshold multiplier (0.1-2.0x), price movement sensitivity (0.5-5.0x), and minimum qualifying bars (1-10) for customized detection
Dual Color Coding: Separate visual treatment for low liquidity voids (receding red) and high liquidity zones (protruding green) based on 50-point strength threshold
Optional Compact Labels: Toggle LV (Low Volume) or HV (High Volume) circular labels at void centers for quick identification without visual clutter
Lookback Period Control: Adjust analysis window from 5 to 100 bars to match your trading timeframe and market volatility characteristics
Memory-Efficient Design: Automatically manages polyline and label arrays, deleting oldest elements when user-defined maximum is reached
Data Window Integration: Plots void detection binary, current strength score, and average volume for detailed analysis in TradingView's data window
🎨 Visualization
Three-Layer Depth System: Each void is rendered as three stacked polylines with progressive transparency (85%, 78%, 70%) and calculated vertical offsets creating authentic 3D appearance
Directional Depth Perception: Low liquidity zones recede with back layer most transparent; high liquidity zones protrude with front layer most transparent for instant visual differentiation
Adaptive Offset Spacing: Vertical separation between layers calculated as ATR(14) × 0.001, ensuring consistent 3D effect across different instruments and volatility regimes
Color Customization: Fully configurable base colors for both low liquidity zones (default: red with 80 transparency) and high liquidity zones (default: green with 80 transparency)
Minimal Chart Clutter: Closed polylines with matching line and fill colors create clean rectangular zones without unnecessary borders or visual noise
Background Highlight: Subtle yellow background (96% transparency) marks bars where void conditions are actively detected in real-time
Compact Labeling: Optional tiny circular labels with 60% transparent backgrounds positioned at void center points for quick reference
📖 Usage Guidelines
Detection Settings
Lookback Period: Default: 10 | Range: 5-100 | Number of bars analyzed for volume averaging and void detection. Lower values increase sensitivity to recent changes; higher values smooth detection across longer timeframes. Adjust based on your trading timeframe: short-term traders use 5-15, swing traders use 20-50, position traders use 50-100.
Volume Threshold: Default: 1.0 | Range: 0.1-2.0 (step 0.1) | Multiplier applied to average volume. Bars with volume below (average × threshold) trigger void conditions. Lower values detect only extreme volume depletion; higher values capture more moderate low-volume situations. Start with 1.0 and decrease to 0.5-0.7 for stricter detection.
Price Movement Sensitivity: Default: 1.5 | Range: 0.5-5.0 (step 0.1) | Multiplier for ATR-normalized price movement detection. Values above this threshold indicate rapid price changes suggesting liquidity voids. Increase to 2.0-3.0 for volatile instruments; decrease to 0.8-1.2 for ranging or low-volatility conditions.
Minimum Void Bars: Default: 10 | Range: 1-10 | Minimum consecutive bars exhibiting void conditions required before visualization is created. Filters out brief anomalies and ensures only sustained voids are displayed. Use 1-3 for scalping, 5-10 for intraday trading, 10+ for swing trading to match your time horizon.
Visual Settings
Low Liquidity Color: Default: Red (80% transparent) | Base color for zones where volume depletion or rapid movement indicates thin liquidity. These zones recede visually (back layer most transparent). Choose colors that contrast with your chart theme for optimal visibility.
High Liquidity Color: Default: Green (80% transparent) | Base color for zones with relatively higher liquidity compared to void threshold. These zones protrude visually (front layer most transparent). Ensure clear differentiation from low liquidity color.
Show Void Labels: Default: True | Toggle display of compact LV/HV labels at void centers. Disable for cleaner charts when trading; enable for analysis and review to quickly identify void types across your chart.
Max Visible Voids: Default: 50 | Range: 10-100 | Maximum number of void visualizations kept on chart. Each void uses 3 polylines, so setting of 50 maintains 150 total polylines. Higher values preserve more history but may impact performance on lower-end systems.
✅ Best Use Cases
Gap Fill Trading: Identify unfilled liquidity voids that price frequently returns to, providing high-probability retest and reversal opportunities when price approaches these zones
Breakout Validation: Distinguish genuine breakouts through established liquidity from false breaks into void zones that lack sustainable volume support
Support/Resistance Confluence: Layer void detection over key horizontal levels to validate structural integrity—levels within high liquidity zones are stronger than those in voids
Trend Continuation: Monitor for new void formation in trend direction as potential continuation zones where price may accelerate due to reduced resistance
Range Trading: Identify void zones within consolidation ranges that price tends to traverse quickly, helping to avoid getting caught in rapid moves through thin areas
Entry Timing: Wait for price to reach void boundaries rather than entering mid-void, as voids tend to be traversed quickly with limited profit-taking opportunities
⚠️ Limitations
Historical Pattern Indicator: Identifies past liquidity voids but cannot predict whether price will return to fill them or when filling might occur
No Volume on Forex: Indicator uses tick volume for forex pairs, which approximates but doesn't represent true trading volume, potentially affecting detection accuracy
Lagging Confirmation: Requires minimum consecutive bars (default 10) before void is visualized, meaning detection occurs after void formation begins
Trending Market Behavior: Strong trends driven by fundamental catalysts may create voids that remain unfilled for extended periods or permanently
Timeframe Dependency: Detection sensitivity varies significantly across timeframes; settings optimized for one timeframe may not perform well on others
No Directional Bias: Indicator identifies liquidity characteristics but provides no predictive signal for price direction after void detection
Performance Considerations: Higher max visible void settings combined with small minimum void bars can generate numerous visualizations impacting chart rendering speed
💡 What Makes This Unique
Industry-First 3D Visualization: Unlike flat volume or liquidity indicators, the three-layer rendering with directional depth perception provides instant visual hierarchy of liquidity quality
Dual-Mode Detection: Combines both volume-based and movement-based detection methodologies, capturing voids that single-approach indicators miss
Intelligent Qualification System: State machine logic prevents premature visualization by requiring sustained void conditions, reducing false signals and chart clutter
ATR-Normalized Analysis: All detection thresholds adapt to instrument volatility, ensuring consistent performance across stocks, forex, crypto, and futures without constant recalibration
Transparency-Based Depth: Uses progressive transparency gradients rather than colors or patterns to create depth, maintaining visual clarity while conveying information hierarchy
Comprehensive Strength Metrics: 0-100 void strength calculation considers both the degree of volume depletion and the magnitude of price movement for nuanced zone characterization
🔬 How It Works
Phase 1: Real-Time Detection
On each bar close, the indicator calculates average volume over the lookback period and compares current bar volume against the volume threshold multiplier
Simultaneously measures current bar's high-low range and normalizes it against ATR, comparing the result to price movement sensitivity parameter
If either volume falls below threshold OR movement exceeds sensitivity threshold, the bar is flagged as exhibiting void characteristics
Phase 2: Void Tracking & Qualification
When void conditions first appear, state machine initializes tracking variables: start bar index, initial top/bottom prices, consecutive bar counter, and cumulative strength accumulator
Each subsequent bar with void conditions extends the tracking, updating price boundaries to envelope all bars and accumulating strength scores
When void conditions cease, system checks if consecutive bar count meets minimum threshold; if yes, proceeds to visualization; if no, discards the tracking and resets
Phase 3: 3D Visualization Construction
Calculates average void strength by dividing cumulative strength by number of bars, then determines if void is low liquidity (>50 strength) or high liquidity (≤50 strength)
Generates three polyline layers spanning from start bar to end bar and from top price to bottom price, each with calculated vertical offset based on ATR
Applies progressive transparency (85%, 78%, 70%) with layer ordering creating recession effect for low liquidity zones and protrusion effect for high liquidity zones
Creates optional center label and pushes all visual elements into arrays for memory management
Phase 4: Memory Management & Display
Continuously monitors polyline array size (each void creates 3 polylines); when total exceeds max visible voids × 3, deletes oldest polylines via array.shift()
Similarly manages label array, removing oldest labels when count exceeds maximum to prevent memory accumulation over extended chart history
Plots diagnostic data to TradingView’s data window (void detection binary, current strength, average volume) for detailed analysis without cluttering main chart
💡 Note:
This indicator is designed to enhance your market structure analysis by revealing liquidity characteristics that aren’t visible through standard price and volume displays. For best results, combine void detection with your existing support/resistance analysis, trend identification, and risk management framework. Liquidity voids are descriptive of past market behavior and should inform positioning decisions rather than serve as standalone entry/exit signals. Experiment with detection parameters across different timeframes to find settings that align with your trading style and instrument characteristics.
Algorithm Predator - ML-liteAlgorithm Predator - ML-lite
This indicator combines four specialized trading agents with an adaptive multi-armed bandit selection system to identify high-probability trade setups. It is designed for swing and intraday traders who want systematic signal generation based on institutional order flow patterns , momentum exhaustion , liquidity dynamics , and statistical mean reversion .
Core Architecture
Why These Components Are Combined:
The script addresses a fundamental challenge in algorithmic trading: no single detection method works consistently across all market conditions. By deploying four independent agents and using reinforcement learning algorithms to select or blend their outputs, the system adapts to changing market regimes without manual intervention.
The Four Trading Agents
1. Spoofing Detector Agent 🎭
Detects iceberg orders through persistent volume at similar price levels over 5 bars
Identifies spoofing patterns via asymmetric wick analysis (wicks exceeding 60% of bar range with volume >1.8× average)
Monitors order clustering using simplified Hawkes process intensity tracking (exponential decay model)
Signal Logic: Contrarian—fades false breakouts caused by institutional manipulation
Best Markets: Consolidations, institutional trading windows, low-liquidity hours
2. Exhaustion Detector Agent ⚡
Calculates RSI divergence between price movement and momentum indicator over 5-bar window
Detects VWAP exhaustion (price at 2σ bands with declining volume)
Uses VPIN reversals (volume-based toxic flow dissipation) to identify momentum failure
Signal Logic: Counter-trend—enters when momentum extreme shows weakness
Best Markets: Trending markets reaching climax points, over-extended moves
3. Liquidity Void Detector Agent 💧
Measures Bollinger Band squeeze (width <60% of 50-period average)
Identifies stop hunts via 20-bar high/low penetration with immediate reversal and volume spike
Detects hidden liquidity absorption (volume >2× average with range <0.3× ATR)
Signal Logic: Breakout anticipation—enters after liquidity grab but before main move
Best Markets: Range-bound pre-breakout, volatility compression zones
4. Mean Reversion Agent 📊
Calculates price z-scores relative to 50-period SMA and standard deviation (triggers at ±2σ)
Implements Ornstein-Uhlenbeck process scoring (mean-reverting stochastic model)
Uses entropy analysis to detect algorithmic trading patterns (low entropy <0.25 = high predictability)
Signal Logic: Statistical reversion—enters when price deviates significantly from statistical equilibrium
Best Markets: Range-bound, low-volatility, algorithmically-dominated instruments
Adaptive Selection: Multi-Armed Bandit System
The script implements four reinforcement learning algorithms to dynamically select or blend agents based on performance:
Thompson Sampling (Default - Recommended):
Uses Bayesian inference with beta distributions (tracks alpha/beta parameters per agent)
Balances exploration (trying underused agents) vs. exploitation (using proven winners)
Each agent's win/loss history informs its selection probability
Lite Approximation: Uses pseudo-random sampling from price/volume noise instead of true random number generation
UCB1 (Upper Confidence Bound):
Calculates confidence intervals using: average_reward + sqrt(2 × ln(total_pulls) / agent_pulls)
Deterministic algorithm favoring agents with high uncertainty (potential upside)
More conservative than Thompson Sampling
Epsilon-Greedy:
Exploits best-performing agent (1-ε)% of the time
Explores randomly ε% of the time (default 10%, configurable 1-50%)
Simple, transparent, easily tuned via epsilon parameter
Gradient Bandit:
Uses softmax probability distribution over agent preference weights
Updates weights via gradient ascent based on rewards
Best for Blend mode where all agents contribute
Selection Modes:
Switch Mode: Uses only the selected agent's signal (clean, decisive)
Blend Mode: Combines all agents using exponentially weighted confidence scores controlled by temperature parameter (smooth, diversified)
Lock Agent Feature:
Optional manual override to force one specific agent
Useful after identifying which agent dominates your specific instrument
Only applies in Switch mode
Four choices: Spoofing Detector, Exhaustion Detector, Liquidity Void, Mean Reversion
Memory System
Dual-Layer Architecture:
Short-Term Memory: Stores last 20 trade outcomes per agent (configurable 10-50)
Long-Term Memory: Stores episode averages when short-term reaches transfer threshold (configurable 5-20 bars)
Memory Boost Mechanism: Recent performance modulates agent scores by up to ±20%
Episode Transfer: When an agent accumulates sufficient results, averages are condensed into long-term storage
Persistence: Manual restoration of learned parameters via input fields (alpha, beta, weights, microstructure thresholds)
How Memory Works:
Agent generates signal → outcome tracked after 8 bars (performance horizon)
Result stored in short-term memory (win = 1.0, loss = 0.0)
Short-term average influences agent's future scores (positive feedback loop)
After threshold met (default 10 results), episode averaged into long-term storage
Long-term patterns (weighted 30%) + short-term patterns (weighted 70%) = total memory boost
Market Microstructure Analysis
These advanced metrics quantify institutional order flow dynamics:
Order Flow Toxicity (Simplified VPIN):
Measures buy/sell volume imbalance over 20 bars: |buy_vol - sell_vol| / (buy_vol + sell_vol)
Detects informed trading activity (institutional players with non-public information)
Values >0.4 indicate "toxic flow" (informed traders active)
Lite Approximation: Uses simple open/close heuristic instead of tick-by-tick trade classification
Price Impact Analysis (Simplified Kyle's Lambda):
Measures market impact efficiency: |price_change_10| / sqrt(volume_sum_10)
Low values = large orders with minimal price impact ( stealth accumulation )
High values = retail-dominated moves with high slippage
Lite Approximation: Uses simplified denominator instead of regression-based signed order flow
Market Randomness (Entropy Analysis):
Counts unique price changes over 20 bars / 20
Measures market predictability
High entropy (>0.6) = human-driven, chaotic price action
Low entropy (<0.25) = algorithmic trading dominance (predictable patterns)
Lite Approximation: Simple ratio instead of true Shannon entropy H(X) = -Σ p(x)·log₂(p(x))
Order Clustering (Simplified Hawkes Process):
Tracks self-exciting event intensity (coordinated order activity)
Decays at 0.9× per bar, spikes +1.0 when volume >1.5× average
High intensity (>0.7) indicates clustering (potential spoofing/accumulation)
Lite Approximation: Simple exponential decay instead of full λ(t) = μ + Σ α·exp(-β(t-tᵢ)) with MLE
Signal Generation Process
Multi-Stage Validation:
Stage 1: Agent Scoring
Each agent calculates internal score based on its detection criteria
Scores must exceed agent-specific threshold (adjusted by sensitivity multiplier)
Agent outputs: Signal direction (+1/-1/0) and Confidence level (0.0-1.0)
Stage 2: Memory Boost
Agent scores multiplied by memory boost factor (0.8-1.2 based on recent performance)
Successful agents get amplified, failing agents get dampened
Stage 3: Bandit Selection/Blending
If Adaptive Mode ON:
Switch: Bandit selects single best agent, uses only its signal
Blend: All agents combined using softmax-weighted confidence scores
If Adaptive Mode OFF:
Traditional consensus voting with confidence-squared weighting
Signal fires when consensus exceeds threshold (default 70%)
Stage 4: Confirmation Filter
Raw signal must repeat for consecutive bars (default 3, configurable 2-4)
Minimum confidence threshold: 0.25 (25%) enforced regardless of mode
Trend alignment check: Long signals require trend_score ≥ -2, Short signals require trend_score ≤ 2
Stage 5: Cooldown Enforcement
Minimum bars between signals (default 10, configurable 5-15)
Prevents over-trading during choppy conditions
Stage 6: Performance Tracking
After 8 bars (performance horizon), signal outcome evaluated
Win = price moved in signal direction, Loss = price moved against
Results fed back into memory and bandit statistics
Trading Modes (Presets)
Pre-configured parameter sets:
Conservative: 85% consensus, 4 confirmations, 15-bar cooldown
Expected: 60-70% win rate, 3-8 signals/week
Best for: Swing trading, capital preservation, beginners
Balanced: 70% consensus, 3 confirmations, 10-bar cooldown
Expected: 55-65% win rate, 8-15 signals/week
Best for: Day trading, most traders, general use
Aggressive: 60% consensus, 2 confirmations, 5-bar cooldown
Expected: 50-58% win rate, 15-30 signals/week
Best for: Scalping, high-frequency trading, active management
Elite: 75% consensus, 3 confirmations, 12-bar cooldown
Expected: 58-68% win rate, 5-12 signals/week
Best for: Selective trading, high-conviction setups
Adaptive: 65% consensus, 2 confirmations, 8-bar cooldown
Expected: Varies based on learning
Best for: Experienced users leveraging bandit system
How to Use
1. Initial Setup (5 Minutes):
Select Trading Mode matching your style (start with Balanced)
Enable Adaptive Learning (recommended for automatic agent selection)
Choose Thompson Sampling algorithm (best all-around performance)
Keep Microstructure Metrics enabled for liquid instruments (>100k daily volume)
2. Agent Tuning (Optional):
Adjust Agent Sensitivity multipliers (0.5-2.0):
<0.8 = Highly selective (fewer signals, higher quality)
0.9-1.2 = Balanced (recommended starting point)
1.3 = Aggressive (more signals, lower individual quality)
Monitor dashboard for 20-30 signals to identify dominant agent
If one agent consistently outperforms, consider using Lock Agent feature
3. Bandit Configuration (Advanced):
Blend Temperature (0.1-2.0):
0.3 = Sharp decisions (best agent dominates)
0.5 = Balanced (default)
1.0+ = Smooth (equal weighting, democratic)
Memory Decay (0.8-0.99):
0.90 = Fast adaptation (volatile markets)
0.95 = Balanced (most instruments)
0.97+ = Long memory (stable trends)
4. Signal Interpretation:
Green triangle (▲): Long signal confirmed
Red triangle (▼): Short signal confirmed
Dashboard shows:
Active agent (highlighted row with ► marker)
Win rate per agent (green >60%, yellow 40-60%, red <40%)
Confidence bars (█████ = maximum confidence)
Memory size (short-term buffer count)
Colored zones display:
Entry level (current close)
Stop-loss (1.5× ATR)
Take-profit 1 (2.0× ATR)
Take-profit 2 (3.5× ATR)
5. Risk Management:
Never risk >1-2% per signal (use ATR-based stops)
Signals are entry triggers, not complete strategies
Combine with your own market context analysis
Consider fundamental catalysts and news events
Use "Confirming" status to prepare entries (not to enter early)
6. Memory Persistence (Optional):
After 50-100 trades, check Memory Export Panel
Record displayed alpha/beta/weight values for each agent
Record VPIN and Kyle threshold values
Enable "Restore From Memory" and input saved values to continue learning
Useful when switching timeframes or restarting indicator
Visual Components
On-Chart Elements:
Spectral Layers: EMA8 ± 0.5 ATR bands (dynamic support/resistance, colored by trend)
Energy Radiance: Multi-layer glow boxes at signal points (intensity scales with confidence, configurable 1-5 layers)
Probability Cones: Projected price paths with uncertainty wedges (15-bar projection, width = confidence × ATR)
Connection Lines: Links sequential signals (solid = same direction continuation, dotted = reversal)
Kill Zones: Risk/reward boxes showing entry, stop-loss, and dual take-profit targets
Signal Markers: Triangle up/down at validated entry points
Dashboard (Configurable Position & Size):
Regime Indicator: 4-level trend classification (Strong Bull/Bear, Weak Bull/Bear)
Mode Status: Shows active system (Adaptive Blend, Locked Agent, or Consensus)
Agent Performance Table: Real-time win%, confidence, and memory stats
Order Flow Metrics: Toxicity and impact indicators (when microstructure enabled)
Signal Status: Current state (Long/Short/Confirming/Waiting) with confirmation progress
Memory Panel (Configurable Position & Size):
Live Parameter Export: Alpha, beta, and weight values per agent
Adaptive Thresholds: Current VPIN sensitivity and Kyle threshold
Save Reminder: Visual indicator if parameters should be recorded
What Makes This Original
This script's originality lies in three key innovations:
1. Genuine Meta-Learning Framework:
Unlike traditional indicator mashups that simply display multiple signals, this implements authentic reinforcement learning (multi-armed bandits) to learn which detection method works best in current conditions. The Thompson Sampling implementation with beta distribution tracking (alpha for successes, beta for failures) is statistically rigorous and adapts continuously. This is not post-hoc optimization—it's real-time learning.
2. Episodic Memory Architecture with Transfer Learning:
The dual-layer memory system mimics human learning patterns:
Short-term memory captures recent performance (recency bias)
Long-term memory preserves historical patterns (experience)
Automatic transfer mechanism consolidates knowledge
Memory boost creates positive feedback loops (successful strategies become stronger)
This architecture allows the system to adapt without retraining , unlike static ML models that require batch updates.
3. Institutional Microstructure Integration:
Combines retail-focused technical analysis (RSI, Bollinger Bands, VWAP) with institutional-grade microstructure metrics (VPIN, Kyle's Lambda, Hawkes processes) typically found in academic finance literature and professional trading systems, not standard retail platforms. While simplified for Pine Script constraints, these metrics provide insight into informed vs. uninformed trading , a dimension entirely absent from traditional technical analysis.
Mashup Justification:
The four agents are combined specifically for risk diversification across failure modes:
Spoofing Detector: Prevents false breakout losses from manipulation
Exhaustion Detector: Prevents chasing extended trends into reversals
Liquidity Void: Exploits volatility compression (different regime than trending)
Mean Reversion: Provides mathematical anchoring when patterns fail
The bandit system ensures the optimal tool is automatically selected for each market situation, rather than requiring manual interpretation of conflicting signals.
Why "ML-lite"? Simplifications and Approximations
This is the "lite" version due to necessary simplifications for Pine Script execution:
1. Simplified VPIN Calculation:
Academic Implementation: True VPIN uses volume bucketing (fixed-volume bars) and tick-by-tick buy/sell classification via Lee-Ready algorithm or exchange-provided trade direction flags
This Implementation: 20-bar rolling window with simple open/close heuristic (close > open = buy volume)
Impact: May misclassify volume during ranging/choppy markets; works best in directional moves
2. Pseudo-Random Sampling:
Academic Implementation: Thompson Sampling requires true random number generation from beta distributions using inverse transform sampling or acceptance-rejection methods
This Implementation: Deterministic pseudo-randomness derived from price and volume decimal digits: (close × 100 - floor(close × 100)) + (volume % 100) / 100
Impact: Not cryptographically random; may have subtle biases in specific price ranges; provides sufficient variation for agent selection
3. Hawkes Process Approximation:
Academic Implementation: Full Hawkes process uses maximum likelihood estimation with exponential kernels: λ(t) = μ + Σ α·exp(-β(t-tᵢ)) fitted via iterative optimization
This Implementation: Simple exponential decay (0.9 multiplier) with binary event triggers (volume spike = event)
Impact: Captures self-exciting property but lacks parameter optimization; fixed decay rate may not suit all instruments
4. Kyle's Lambda Simplification:
Academic Implementation: Estimated via regression of price impact on signed order flow over multiple time intervals: Δp = λ × Δv + ε
This Implementation: Simplified ratio: price_change / sqrt(volume_sum) without proper signed order flow or regression
Impact: Provides directional indicator of impact but not true market depth measurement; no statistical confidence intervals
5. Entropy Calculation:
Academic Implementation: True Shannon entropy requires probability distribution: H(X) = -Σ p(x)·log₂(p(x)) where p(x) is probability of each price change magnitude
This Implementation: Simple ratio of unique price changes to total observations (variety measure)
Impact: Measures diversity but not true information entropy with probability weighting; less sensitive to distribution shape
6. Memory System Constraints:
Full ML Implementation: Neural networks with backpropagation, experience replay buffers (storing state-action-reward tuples), gradient descent optimization, and eligibility traces
This Implementation: Fixed-size array queues with simple averaging; no gradient-based learning, no state representation beyond raw scores
Impact: Cannot learn complex non-linear patterns; limited to linear performance tracking
7. Limited Feature Engineering:
Advanced Implementation: Dozens of engineered features, polynomial interactions (x², x³), dimensionality reduction (PCA, autoencoders), feature selection algorithms
This Implementation: Raw agent scores and basic market metrics (RSI, ATR, volume ratio); minimal transformation
Impact: May miss subtle cross-feature interactions; relies on agent-level intelligence rather than feature combinations
8. Single-Instrument Data:
Full Implementation: Multi-asset correlation analysis (sector ETFs, currency pairs, volatility indices like VIX), lead-lag relationships, risk-on/risk-off regimes
This Implementation: Only OHLCV data from displayed instrument
Impact: Cannot incorporate broader market context; vulnerable to correlated moves across assets
9. Fixed Performance Horizon:
Full Implementation: Adaptive horizon based on trade duration, volatility regime, or profit target achievement
This Implementation: Fixed 8-bar evaluation window
Impact: May evaluate too early in slow markets or too late in fast markets; one-size-fits-all approach
Performance Impact Summary:
These simplifications make the script:
✅ Faster: Executes in milliseconds vs. seconds (or minutes) for full academic implementations
✅ More Accessible: Runs on any TradingView plan without external data feeds, APIs, or compute servers
✅ More Transparent: All calculations visible in Pine Script (no black-box compiled models)
✅ Lower Resource Usage: <500 bars lookback, minimal memory footprint
⚠️ Less Precise: Approximations may reduce statistical edge by 5-15% vs. academic implementations
⚠️ Limited Scope: Cannot capture tick-level dynamics, multi-order-book interactions, or cross-asset flows
⚠️ Fixed Parameters: Some thresholds hardcoded rather than dynamically optimized
When to Upgrade to Full Implementation:
Consider professional Python/C++ versions with institutional data feeds if:
Trading with >$100K capital where precision differences materially impact returns
Operating in microsecond-competitive environments (HFT, market making)
Requiring regulatory-grade audit trails and reproducibility
Backtesting with tick-level precision for strategy validation
Need true real-time adaptation with neural network-based learning
For retail swing/day trading and position management, these approximations provide sufficient signal quality while maintaining usability, transparency, and accessibility. The core logic—multi-agent detection with adaptive selection—remains intact.
Technical Notes
All calculations use standard Pine Script built-in functions ( ta.ema, ta.atr, ta.rsi, ta.bb, ta.sma, ta.stdev, ta.vwap )
VPIN and Kyle's Lambda use simplified formulas optimized for OHLCV data (see "Lite" section above)
Thompson Sampling uses pseudo-random noise from price/volume decimal digits for beta distribution sampling
No repainting: All calculations use confirmed bar data (no forward-looking)
Maximum lookback: 500 bars (set via max_bars_back parameter)
Performance evaluation: 8-bar forward-looking window for reward calculation (clearly disclosed)
Confidence threshold: Minimum 0.25 (25%) enforced on all signals
Memory arrays: Dynamic sizing with FIFO queue management
Limitations and Disclaimers
Not Predictive: This indicator identifies patterns in historical data. It cannot predict future price movements with certainty.
Requires Human Judgment: Signals are entry triggers, not complete trading strategies. Must be confirmed with your own analysis, risk management rules, and market context.
Learning Period Required: The adaptive system requires 50-100 bars minimum to build statistically meaningful performance data for bandit algorithms.
Overfitting Risk: Restoring memory parameters from one market regime to a drastically different regime (e.g., low volatility to high volatility) may cause poor initial performance until system re-adapts.
Approximation Limitations: Simplified calculations (see "Lite" section) may underperform academic implementations by 5-15% in highly efficient markets.
No Guarantee of Profit: Past performance, whether backtested or live-traded, does not guarantee future performance. All trading involves risk of loss.
Forward-Looking Bias: Performance evaluation uses 8-bar forward window—this creates slight look-ahead for learning (though not for signals). Real-time performance may differ from indicator's internal statistics.
Single-Instrument Limitation: Does not account for correlations with related assets or broader market regime changes.
Recommended Settings
Timeframe: 15-minute to 4-hour charts (sufficient volatility for ATR-based stops; adequate bar volume for learning)
Assets: Liquid instruments with >100k daily volume (forex majors, large-cap stocks, BTC/ETH, major indices)
Not Recommended: Illiquid small-caps, penny stocks, low-volume altcoins (microstructure metrics unreliable)
Complementary Tools: Volume profile, order book depth, market breadth indicators, fundamental catalysts
Position Sizing: Risk no more than 1-2% of capital per signal using ATR-based stop-loss
Signal Filtering: Consider external confluence (support/resistance, trendlines, round numbers, session opens)
Start With: Balanced mode, Thompson Sampling, Blend mode, default agent sensitivities (1.0)
After 30+ Signals: Review agent win rates, consider increasing sensitivity of top performers or locking to dominant agent
Alert Configuration
The script includes built-in alert conditions:
Long Signal: Fires when validated long entry confirmed
Short Signal: Fires when validated short entry confirmed
Alerts fire once per bar (after confirmation requirements met)
Set alert to "Once Per Bar Close" for reliability
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
LibTmFrLibrary "LibTmFr"
This is a utility library for handling timeframes and
multi-timeframe (MTF) analysis in Pine Script. It provides a
collection of functions designed to handle common tasks related
to period detection, session alignment, timeframe construction,
and time calculations, forming a foundation for
MTF indicators.
Key Capabilities:
1. **MTF Period Engine:** The library includes functions for
managing higher-timeframe (HTF) periods.
- **Period Detection (`isNewPeriod`):** Detects the first bar
of a given timeframe. It includes custom logic to handle
multi-month and multi-year intervals where
`timeframe.change()` may not be sufficient.
- **Bar Counting (`sinceNewPeriod`):** Counts the number of
bars that have passed in the current HTF period or
returns the final count for a completed historical period.
2. **Automatic Timeframe Selection:** Offers functions for building
a top-down analysis framework:
- **Automatic HTF (`autoHTF`):** Suggests a higher timeframe
(HTF) for broader context based on the current timeframe.
- **Automatic LTF (`autoLTF`):** Suggests an appropriate lower
timeframe (LTF) for granular intra-bar analysis.
3. **Timeframe Manipulation and Comparison:** Includes tools for
working with timeframe strings:
- **Build & Split (`buildTF`, `splitTF`):** Functions to
programmatically construct valid Pine Script timeframe
strings (e.g., "4H") and parse them back into their
numeric and unit components.
- **Comparison (`isHigherTF`, `isActiveTF`, `isLowerTF`):**
A set of functions to check if a given timeframe is
higher, lower, or the same as the script's active timeframe.
- **Multiple Validation (`isMultipleTF`):** Checks if a
higher timeframe is a practical multiple of the current
timeframe. This is based on the assumption that checking
if recent, completed HTF periods contained more than one
bar is a valid proxy for preventing data gaps.
4. **Timestamp Interpolation:** Contains an `interpTimestamp()`
function that calculates an absolute timestamp by
interpolating at a given percentage across a specified
range of bars (e.g., 50% of the way through the last
20 bars), enabling time calculations at a resolution
finer than the chart's native bars.
---
**DISCLAIMER**
This library is provided "AS IS" and for informational and
educational purposes only. It does not constitute financial,
investment, or trading advice.
The author assumes no liability for any errors, inaccuracies,
or omissions in the code. Using this library to build
trading indicators or strategies is entirely at your own risk.
As a developer using this library, you are solely responsible
for the rigorous testing, validation, and performance of any
scripts you create based on these functions. The author shall
not be held liable for any financial losses incurred directly
or indirectly from the use of this library or any scripts
derived from it.
buildTF(quantity, unit)
Builds a Pine Script timeframe string from a numeric quantity and a unit enum.
The resulting string can be used with `request.security()` or `input.timeframe`.
Parameters:
quantity (int) : series int Number to specifie how many `unit` the timeframe spans.
unit (series TFUnit) : series TFUnit The size category for the bars.
Returns: series string A Pine-style timeframe identifier, e.g.
"5S" → 5-seconds bars
"30" → 30-minute bars
"120" → 2-hour bars
"1D" → daily bars
"3M" → 3-month bars
"24M" → 2-year bars
splitTF(tf)
Splits a Pine‑timeframe identifier into numeric quantity and unit (TFUnit).
Parameters:
tf (string) : series string Timeframe string, e.g.
"5S", "30", "120", "1D", "3M", "24M".
Returns:
quantity series int The numeric value of the timeframe (e.g., 15 for "15", 3 for "3M").
unit series TFUnit The unit of the timeframe (e.g., TFUnit.minutes, TFUnit.months).
Notes on strings without a suffix:
• Pure digits are minutes; if divisible by 60, they are treated as hours.
• An "M" suffix is months; if divisible by 12, it is converted to years.
autoHTF(tf)
Picks an appropriate **higher timeframe (HTF)** relative to the selected timeframe.
It steps up along a coarse ladder to produce sensible jumps for top‑down analysis.
Mapping → chosen HTF:
≤ 1 min → 60 (1h) ≈ ×60
≤ 3 min → 180 (3h) ≈ ×60
≤ 5 min → 240 (4h) ≈ ×48
≤ 15 min → D (1 day) ≈ ×26–×32 (regular session 6.5–8 h)
> 15 min → W (1 week) ≈ ×64–×80 for 30m; varies with input
≤ 1 h → W (1 week) ≈ ×32–×40
≤ 4 h → M (1 month) ≈ ×36–×44 (~22 trading days / month)
> 4 h → 3M (3 months) ≈ ×36–×66 (e.g., 12h→×36–×44; 8h→×53–×66)
≤ 1 day → 3M (3 months) ≈ ×60–×66 (~20–22 trading days / month)
> 1 day → 12M (1 year) ≈ ×(252–264)/quantity
≤ 1 week → 12M (1 year) ≈ ×52
> 1 week → 48M (4 years) ≈ ×(208)/quantity
= 1 M → 48M (4 years) ≈ ×48
> 1 M → error ("HTF too big")
any → error ("HTF too big")
Notes:
• Inputs in months or years are restricted: only 1M is allowed; larger months/any years throw.
• Returns a Pine timeframe string usable in `request.security()` and `input.timeframe`.
Parameters:
tf (string) : series string Selected timeframe (e.g., "D", "240", or `timeframe.period`).
Returns: series string Suggested higher timeframe.
autoLTF(tf)
Selects an appropriate **lower timeframe LTF)** for intra‑bar evaluation
based on the selected timeframe. The goal is to keep intra‑bar
loops performant while providing enough granularity.
Mapping → chosen LTF:
≤ 1 min → 1S ≈ ×60
≤ 5 min → 5S ≈ ×60
≤ 15 min → 15S ≈ ×60
≤ 30 min → 30S ≈ ×60
> 30 min → 60S (1m) ≈ ×31–×59 (for 31–59 minute charts)
≤ 1 h → 1 (1m) ≈ ×60
≤ 2 h → 2 (2m) ≈ ×60
≤ 4 h → 5 (5m) ≈ ×48
> 4 h → 15 (15m) ≈ ×24–×48 (e.g., 6h→×24, 8h→×32, 12h→×48)
≤ 1 day → 15 (15m) ≈ ×26–×32 (regular sessions ~6.5–8h)
> 1 day → 60 (60m) ≈ ×(26–32) per day × quantity
≤ 1 week → 60 (60m) ≈ ×32–×40 (≈5 sessions of ~6.5–8h)
> 1 week → 240 (4h) ≈ ×(8–10) per week × quantity
≤ 1 M → 240 (4h) ≈ ×33–×44 (~20–22 sessions × 6.5–8h / 4h)
≤ 3 M → D (1d) ≈ ×(20–22) per month × quantity
> 3 M → W (1w) ≈ ×(4–5) per month × quantity
≤ 1 Y → W (1w) ≈ ×52
> 1 Y → M (1M) ≈ ×12 per year × quantity
Notes:
• Ratios for D/W/M are given as ranges because they depend on
**regular session length** (typically ~6.5–8h, not 24h).
• Returned strings can be used with `request.security()` and `input.timeframe`.
Parameters:
tf (string) : series string Selected timeframe (e.g., "D", "240", or timeframe.period).
Returns: series string Suggested lower TF to use for intra‑bar work.
isNewPeriod(tf, offset)
Returns `true` when a new session-aligned period begins, or on the Nth bar of that period.
Parameters:
tf (string) : series string Target higher timeframe (e.g., "D", "W", "M").
offset (simple int) : simple int 0 → checks for the first bar of the new period.
1+ → checks for the N-th bar of the period.
Returns: series bool `true` if the condition is met.
sinceNewPeriod(tf, offset)
Counts how many bars have passed within a higher timeframe (HTF) period.
For daily, weekly, and monthly resolutions, the period is aligned with the trading session.
Parameters:
tf (string) : series string Target parent timeframe (e.g., "60", "D").
offset (simple int) : simple int 0 → Running count for the current period.
1+ → Finalized count for the Nth most recent *completed* period.
Returns: series int Number of bars.
isHigherTF(tf, main)
Returns `true` when the selected timeframe represents a
higher resolution than the active timeframe.
Parameters:
tf (string) : series string Selected timeframe.
main (bool) : series bool When `true`, the comparison is made against the chart's main timeframe
instead of the script's active timeframe. Optional. Defaults to `false`.
Returns: series bool `true` if `tf` > active TF; otherwise `false`.
isActiveTF(tf, main)
Returns `true` when the selected timeframe represents the
exact resolution of the active timeframe.
Parameters:
tf (string) : series string Selected timeframe.
main (bool) : series bool When `true`, the comparison is made against the chart's main timeframe
instead of the script's active timeframe. Optional. Defaults to `false`.
Returns: series bool `true` if `tf` == active TF; otherwise `false`.
isLowerTF(tf, main)
Returns `true` when the selected timeframe represents a
lower resolution than the active timeframe.
Parameters:
tf (string) : series string Selected timeframe.
main (bool) : series bool When `true`, the comparison is made against the chart's main timeframe
instead of the script's active timeframe. Optional. Defaults to `false`.
Returns: series bool `true` if `tf` < active TF; otherwise `false`.
isMultipleTF(tf)
Returns `true` if the selected timeframe (`tf`) is a practical multiple
of the active skript's timeframe. It verifies this by checking if `tf` is a higher timeframe
that has consistently contained more than one bar of the skript's timeframe in recent periods.
The period detection is session-aware.
Parameters:
tf (string) : series string The higher timeframe to check.
Returns: series bool `true` if `tf` is a practical multiple; otherwise `false`.
interpTimestamp(offStart, offEnd, pct)
Calculates a precise absolute timestamp by interpolating within a bar range based on a percentage.
This version works with RELATIVE bar offsets from the current bar.
Parameters:
offStart (int) : series int The relative offset of the starting bar (e.g., 10 for 10 bars ago).
offEnd (int) : series int The relative offset of the ending bar (e.g., 1 for 1 bar ago). Must be <= offStart.
pct (float) : series float The percentage of the bar range to measure (e.g., 50.5 for 50.5%).
Values are clamped to the range.
Returns: series int The calculated, interpolated absolute Unix timestamp in milliseconds.
