myAutoviewAlertsLibrary "myAutoviewAlerts"
My Alerts Functions - To use with autoview
@returns - These functions returns a string to use in alerts to send commands to autoview. You can open an order, place a stop or take order, close an opened order or a opened position, or open a hedge position.
@param a = String - Account Identification
@param e = String - Exchange
@param s = String - Symbol
@param b = String - Book Side
@param q = Float - Quantity
@param fp = Float - Fixed Price
@param delay = Integer - In Seconds
@param i = Integer - Account Index (to multiple accounts allerts)
@param base = String - Base Currency (bitmex) - "Tether" or "Bitcoin"
@param fsl = Float - Stop Loss Limit Price
@param c = String - Close -> "order" or "position"
@param ro = Bool - Reduce Only
@param sl = Bool - Stop Loss -> bitfinex
@param t = String - Type -> "market" or "limit"
@function f_order => Open Orders
@function f_stop => Set Stop Loss Order
@function f_take => Set Take Order
@function f_closeOrder => Close Open Orders
@function f_closePosition => Close Open Positions
@function f_hedge => To Open a Hedge Position (short 100% of balance)
"order"に関するスクリプトを検索
threengine_global_automation_libraryLibrary "threengine_global_automation_library"
A collection of functions used for trade automation
getBaseCurrency()
Gets the base currency for the chart's ticker. Supported trade pairs are USD, USDT, USDC, BTC, and PERP.
Returns: Base currency as a string
getChartSymbol()
Get the current chart's symbol without the base currency appended to it. Supported trade paris are USD, USDT, USDC, BTC, and PERP.
Returns: Ssymbol and base currency
getDecimals()
Calculates how many decimals are on the quote price of the current market
Returns: The current deimal places on the market quote price
checkVar()
Plot a string as a label on the chart to test variable value. Use str.tostring() for any variable that isn't a string.
Returns: Label with stringified variable
getStrategyAlertMessage()
Generates stringified JSON for a limit order that can be passed to the strategy alert_message for a long entry.
Returns: Stringifed JSON for a long entry
taGetAdx()
Calculates the Average Directional Index
Returns: The value of ADX as a float
taGetEma()
Calculates the EMA based on a type, source, and length. Supported types are EMA, SMA, RMA, and WMA.
Returns: The value of the selected EMA
isBetweenTwoTimes()
Checks to see if within a rage based on two times
@retunrs true/false boolean
getAllTradeIDs()
This gets all closed trades and open trades
@retunrs an array of all open and closed trade ID's
getOpenTradeIDs()
This gets all open trades
@retunrs an array of all open trade ID's
orderAlreadyExists()
This checks to see if a provided order id uses the getAllTradeIDs() function to check
@retunrs an array of all open and closed trade ID's
orderCurrentlyExists()
This checks to see if a provided order id uses the getAllTradeIDs() function to check
Returns: an array of all open and closed trade ID's
getContractCount()
calulates the number of contracts you can buy with a set amount of capital and a limit price
Returns: number of contracts you can buy based on amount of capital you want to use and a price
getLadderSteps()
Returns: array of ladder entry prices and amounts based on total amount you want to invest across all ladder rungs and either a range between ladderStart and LadderStop based on specificed number of ladderRungs OR ladderStart, ladderRungs, and LadderSpacingPercent
CVD - Cumulative Volume Delta Candles█ OVERVIEW
This indicator displays cumulative volume delta in candle form. It uses intrabar information to obtain more precise volume delta information than methods using only the chart's timeframe.
█ CONCEPTS
Bar polarity
By bar polarity , we mean the direction of a bar, which is determined by looking at the bar's close vs its open .
Intrabars
Intrabars are chart bars at a lower timeframe than the chart's. Each 1H chart bar of a 24x7 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. Mining information from intrabars can be useful in that it offers traders visibility on the activity inside a chart bar.
Lower timeframes (LTFs)
A lower timeframe is a timeframe that is smaller than the chart's timeframe. This script uses a LTF to access intrabars. The lower the LTF, the more intrabars are analyzed, but the less chart bars can display CVD information because there is a limit to the total number of intrabars that can be analyzed.
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 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. Our Volume Profile indicators use it. Other volume delta indicators in our Community Scripts such as the Realtime 5D Profile use realtime chart updates to achieve more precise volume delta calculations, but that method cannot be used on historical bars, so those indicators only work in real time.
This is the logic we 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.
█ FEATURES
CVD Candles
Cumulative Volume Delta Candles present volume delta information as it evolves during a period of time.
This is how each candle's levels are calculated:
• open : Each candle's' open level is the cumulative volume delta for the current period at the start of the bar.
This value becomes zero on the first candle following a CVD reset.
The candles after the first one always open where the previous candle closed.
The candle's high, low and close levels are then calculated by adding or subtracting a volume value to the open.
• high : The highest volume delta value found in intrabars. If it is not higher than the volume delta for the bar, then that candle will have no upper wick.
• low : The lowest volume delta value found in intrabars. If it is not lower than the volume delta for the bar, then that candle will have no lower wick.
• close : The aggregated volume delta for all intrabars. If volume delta is positive for the chart bar, then the candle's close will be higher than its open, and vice versa.
The candles are plotted in one of two configurable colors, depending on the polarity of volume delta for the bar.
CVD resets
The "cumulative" part of the indicator's name stems from the fact that calculations accumulate during a period of time. This allows you to analyze the progression of volume delta across manageable chunks, which is often more useful than looking at volume delta cumulated from the beginning of a chart's history.
You can configure the reset period using the "CVD Resets" input, which offers the following selections:
• None : Calculations do not reset.
• On a fixed higher timeframe : Calculations reset on the higher timeframe you select in the "Fixed higher timeframe" field.
• At a fixed time that you specify.
• At the beginning of the regular session .
• On a stepped higher timeframe : Calculations reset on a higher timeframe automatically stepped using the chart's timeframe and following these rules:
Chart TF HTF
< 1min 1H
< 3H 1D
<= 12H 1W
< 1W 1M
>= 1W 1Y
The indicator's background shows where resets occur.
Intrabar precision
The precision of calculations increases with the number of intrabars analyzed for each chart bar. It is controlled through the script's "Intrabar precision" input, which offers the following selections:
• Least precise, covering many chart bars
• Less precise, covering some chart bars
• More precise, covering less chart bars
• Most precise, 1min intrabars
As there is a limit to the number of intrabars that can be analyzed by a script, a tradeoff occurs between the number of intrabars analyzed per chart bar and the chart bars for which calculations are possible.
Total volume candles
You can choose to display candles showing the total intrabar volume for the chart bar. This provides you with more context to evaluate a bar's volume delta by showing it relative to the sum of intrabar volume. Note that because of the reasons explained in the "NOTES" section further down, the total volume is the sum of all intrabar volume rather than the volume of the bar at the chart's timeframe.
Total volume candles can be configured with their own up and down colors. You can also control the opacity of their bodies to make them more or less prominent. This publication's chart shows the indicator with total volume candles. They are turned off by default, so you will need to choose to display them in the script's inputs for them to plot.
Divergences
Divergences occur when the polarity of volume delta does not match that of the chart bar. You can identify divergences by coloring the CVD candles differently for them, or by coloring the indicator's background.
Information box
An information box in the lower-left corner of the indicator displays the HTF used for resets, the LTF used for intrabars, and the average quantity of intrabars per chart bar. You can hide the box using the script's inputs.
█ INTERPRETATION
The first thing to look at when analyzing CVD candles is the side of the zero line they are on, as this tells you if CVD is generally bullish or bearish. Next, one should consider the relative position of successive candles, just as you would with a price chart. Are successive candles trending up, down, or stagnating? Keep in mind that whatever trend you identify must be considered in the context of where it appears with regards to the zero line; an uptrend in a negative CVD (below the zero line) may not be as powerful as one taking place in positive CVD values, but it may also predate a movement into positive CVD territory. The same goes with stagnation; a trader in a long position will find stagnation in positive CVD territory less worrisome than stagnation under the zero line.
After consideration of the bigger picture, one can drill down into the details. Exactly what you are looking for in markets will, of course, depend on your trading methodology, but you may find it useful to:
• Evaluate volume delta for the bar in relation to price movement for that bar.
• Evaluate the proportion that volume delta represents of total volume.
• Notice divergences and if the chart's candle shape confirms a hesitation point, as a Doji would.
• Evaluate if the progress of CVD candles correlates with that of chart bars.
• Analyze the wicks. As with price candles, long wicks tend to indicate weakness.
Always keep in mind that unless you have chosen not to reset it, your CVD resets for each period, whether it is fixed or automatically stepped. Consequently, any trend from the preceding period must re-establish itself in the next.
█ NOTES
Know your volume
Traders using volume information should understand the volume data they are using: where it originates and what transactions it includes, as this can vary with instruments, sectors, exchanges, timeframes, and between historical and realtime bars. The information used to build a chart's bars and display volume comes from data providers (exchanges, brokers, etc.) who often maintain distinct feeds for intraday and end-of-day (EOD) timeframes. How volume data is assembled for the two feeds depends on how instruments are traded in that sector and/or the volume reporting policy for each feed. Instruments from crypto and forex markets, for example, will often display similar volume on both feeds. Stocks will often display variations because block trades or other types of trades may not be included in their intraday volume data. Futures will also typically display variations.
Note that as intraday vs EOD variations exist for historical bars on some instruments, differences may also exist between the realtime feeds used on intraday vs 1D or greater timeframes for those same assets. Realtime reporting rules will often be different from historical feed reporting rules, so variations between realtime feeds will often be different from the variations between historical feeds for the same instrument. The Volume X-ray indicator can help you analyze differences between intraday and EOD volumes for the instruments you trade.
If every unit of volume is both bought by a buyer and sold by a seller, how can volume delta make sense?
Traders who do not understand the mechanics of matching engines (the exchange software that matches orders from buyers and sellers) sometimes argue that the concept of volume delta is flawed, as every unit of volume is both bought and sold. While they are rigorously correct in stating that every unit of volume is both bought and sold, they overlook the fact that information can be mined by analyzing variations in the price of successive ticks, or in our case, intrabars.
Our calculations model the situation where, in fully automated order handling, market orders are generally matched to limit orders sitting in the order book. Buy market orders are matched to quotes at the ask level and sell market orders are matched to quotes at the bid level. As explained earlier, we use the same logic when comparing intrabar prices. While using intrabar analysis does not produce results as precise as when individual transactions — or ticks — are analyzed, results are much more precise than those of methods using only chart prices.
Not only does the concept underlying volume delta make sense, it provides a window on an oft-overlooked variable which, with price and time, is the only basic information representing market activity. Furthermore, because the calculation of volume delta also uses price and time variations, one could conceivably surmise that it can provide a more complete model than ones using price and time only. Whether or not volume delta can be useful in your trading practice, as usual, is for you to decide, as each trader's methodology is different.
For Pine Script™ coders
As our latest Polarity Divergences publication, this script uses the recently released request.security_lower_tf() Pine Script™ function discussed in this blog post . It works differently from the usual request.security() in that it can only be used at LTFs, and it returns an array containing one value per intrabar. This makes it much easier for programmers to access intrabar information.
Look first. Then leap.
HTF Liquidity Levels█ OVERVIEW
The indicator introduces a new representation of the previous days, weeks, and months highs & lows ( DWM HL ) with a focus on untapped levels.
█ CONCEPTS
Untapped Levels
It is popularly known that the liquidity is located behind swing points or beyond higher time frames highs/lows (in a sense, an intraday swing point is a day high/low). These key areas are said "liquid" because of the accumulation of resting orders, mainly in the form of stop-loss orders. And this more significantly on higher time frames which have more time for stacking orders. As the result, the indicator aims to keep track of untapped levels that have their liquidity states intact.
Liquidity Pools
Once a liquidity level identified, or better, a cluster of liquidity levels work as magnets for the market. The price is more likely to make its way towards heavier pockets of liquidity, by proximity (the closest liquidity pool), and by difficulty (path with less obstacles). This phenomenon is referred as liquidity run, raid, purge, grab, hunt, sweep, you name it. Consequently, the indicator can help you frame a directional bias during your trading session.
█ NOTES
Drawings
Once a level is tapped, it is highlighted. At the end of each day, all tapped levels are cleared.
Strategy█ OVERVIEW
This library is a Pine Script™ programmer’s tool containing a variety of strategy-related functions to assist in calculations like profit and loss, stop losses and limits. It also includes several useful functions one can use to convert between units in ticks, price, currency or a percentage of the position's size.
█ CONCEPTS
The library contains three types of functions:
1 — Functions beginning with `percent` take either a portion of a price, or the current position's entry price and convert it to the value outlined in the function's documentation.
Example: Converting a percent of the current position entry price to ticks, or calculating a percent profit at a given level for the position.
2 — Functions beginning with `tick` convert a tick value to another form.
These are useful for calculating a price or currency value from a specified number of ticks.
3 — Functions containing `Level` are used to calculate a stop or take profit level using an offset in ticks from the current entry price.
These functions can be used to plot stop or take profit levels on the chart, or as arguments to the `limit` and `stop` parameters in strategy.exit() function calls.
Note that these calculated levels flip automatically with the position's bias.
For example, using `ticksToStopLevel()` will calculate a stop level under the entry price for a long position, and above the entry price for a short position.
There are also two functions to assist in calculating a position size using the entry's stop and a fixed risk expressed as a percentage of the current account's equity. By varying the position size this way, you ensure that entries with different stop levels risk the same proportion of equity.
█ NOTES
Example code using some of the library's functions is included at the end of the library. To see it in action, copy the library's code to a new script in the Pine Editor, and “Add to chart”.
For each trade, the code displays:
• The entry level in orange.
• The stop level in fuchsia.
• The take profit level in green.
The stop and take profit levels automatically flip sides based on whether the current position is long or short.
Labels near the last trade's levels display the percentages used to calculate them, which can be changed in the script's inputs.
We plot markers for entries and exits because strategy code in libraries does not display the usual markers for them.
Look first. Then leap.
█ FUNCTIONS
percentToTicks(percent) Converts a percentage of the average entry price to ticks.
Parameters:
percent : (series int/float) The percentage of `strategy.position_avg_price` to convert to ticks. 50 is 50% of the entry price.
Returns: (float) A value in ticks.
percentToPrice(percent) Converts a percentage of the average entry price to a price.
Parameters:
percent : (series int/float) The percentage of `strategy.position_avg_price` to convert to price. 50 is 50% of the entry price.
Returns: (float) A value in the symbol's quote currency (USD for BTCUSD).
percentToCurrency(price, percent) Converts the percentage of a price to money.
Parameters:
price : (series int/float) The symbol's price.
percent : (series int/float) The percentage of `price` to calculate.
Returns: (float) A value in the symbol's currency.
percentProfit(exitPrice) Calculates the profit (as a percentage of the position's `strategy.position_avg_price` entry price) if the trade is closed at `exitPrice`.
Parameters:
exitPrice : (series int/float) The potential price to close the position.
Returns: (float) Percentage profit for the current position if closed at the `exitPrice`.
priceToTicks(price) Converts a price to ticks.
Parameters:
price : (series int/float) Price to convert to ticks.
Returns: (float) A quantity of ticks.
ticksToPrice(price) Converts ticks to a price offset from the average entry price.
Parameters:
price : (series int/float) Ticks to convert to a price.
Returns: (float) A price level that has a distance from the entry price equal to the specified number of ticks.
ticksToCurrency(ticks) Converts ticks to money.
Parameters:
ticks : (series int/float) Number of ticks.
Returns: (float) Money amount in the symbol's currency.
ticksToStopLevel(ticks) Calculates a stop loss level using a distance in ticks from the current `strategy.position_avg_price` entry price. This value can be plotted on the chart, or used as an argument to the `stop` parameter of a `strategy.exit()` call. NOTE: The stop level automatically flips based on whether the position is long or short.
Parameters:
ticks : (series int/float) The distance in ticks from the entry price to the stop loss level.
Returns: (float) A stop loss level for the current position.
ticksToTpLevel(ticks) Calculates a take profit level using a distance in ticks from the current `strategy.position_avg_price` entry price. This value can be plotted on the chart, or used as an argument to the `limit` parameter of a `strategy.exit()` call. NOTE: The take profit level automatically flips based on whether the position is long or short.
Parameters:
ticks : (series int/float) The distance in ticks from the entry price to the take profit level.
Returns: (float) A take profit level for the current position.
calcPositionSizeByStopLossTicks(stopLossTicks, riskPercent) Calculates the position size needed to implement a given stop loss (in ticks) corresponding to `riskPercent` of equity.
Parameters:
stopLossTicks : (series int) The stop loss (in ticks) that will be used to protect the position.
riskPercent : (series int/float) The maximum risk level as a percent of current equity (`strategy.equity`).
Returns: (int) A quantity of contracts.
calcPositionSizeByStopLossPercent(stopLossPercent, riskPercent, entryPrice) Calculates the position size needed to implement a given stop loss (%) corresponding to `riskPercent` of equity.
Parameters:
stopLossPercent : (series int/float) The stop loss in percent that will be used to protect the position.
riskPercent : (series int/float) The maximum risk level as a percent of current equity (`strategy.equity`).
entryPrice : (series int/float) The entry price of the position.
Returns: (int) A quantity of contracts.
exitPercent(id, lossPercent, profitPercent, qty, qtyPercent, comment, when, alertMessage) A wrapper of the `strategy.exit()` built-in which adds the possibility to specify loss & profit in as a value in percent. NOTE: this function may work incorrectly with pyramiding turned on due to the use of `strategy.position_avg_price` in its calculations of stop loss and take profit offsets.
Parameters:
id : (series string) The order identifier of the `strategy.exit()` call.
lossPercent : (series int/float) Stop loss as a percent of the entry price.
profitPercent : (series int/float) Take profit as a percent of the entry price.
qty : (series int/float) Number of contracts/shares/lots/units to exit a trade with. The default value is `na`.
qtyPercent : (series int/float) The percent of the position's size to exit a trade with. If `qty` is `na`, the default value of `qty_percent` is 100.
comment : (series string) Optional. Additional notes on the order.
when : (series bool) Condition of the order. The order is placed if it is true.
alertMessage : (series string) An optional parameter which replaces the {{strategy.order.alert_message}} placeholder when it is used in the "Create Alert" dialog box's "Message" field.
PointsLibrary "Points"
Provides functions for simplifying operations with collections of x+y coordinates. Where x is typically a bar index or time (millisecond) value.
new(size) Creates two arrays. One for X (int ) and another for Y (float ).
Parameters:
size : The initial size of the arrays.
size(xA, yA) Checks the size of the arrays and if they're equal returns the size.
Parameters:
xA : The X array.
yA : The Y array.
get(xA, yA, index) Gets the X and Y values of the arrays at the index.
Parameters:
xA : The X array.
yA : The Y array.
index : The index.
Returns:
set(xA, yA, index, x, y) Sets the X and Y values of the arrays at the index.
Parameters:
xA : The X array.
yA : The Y array.
index : The index.
x : The x value.
y : The y value.
Returns:
push(xA, yA, x, y) Adds X and Y values to the end of the arrays (as the last element).
Parameters:
xA : The X array.
yA : The Y array.
x : The x value.
y : The y value.
Returns:
unshift(xA, yA, x, y) Adds X and Y values to the beginning of the arrays (as the first element).
Parameters:
xA : The X array.
yA : The Y array.
x : The x value.
y : The y value.
Returns:
insert(xA, yA, index, x, y) Inserts X and Y values to the arrays at the index.
Parameters:
xA : The X array.
yA : The Y array.
index : The index to insert at.
x : The x value.
y : The y value.
Returns:
pop(xA, yA) Removes the last element from the arrays and returns their value.
Parameters:
xA : The X array.
yA : The Y array.
Returns:
shift(xA, yA) Removes the first element from the arrays and returns their value.
Parameters:
xA : The X array.
yA : The Y array.
Returns:
remove(xA, yA) Removes the element from the arrays at the index and returns their value.
Parameters:
xA : The X array.
yA : The Y array.
Returns:
first(xA, yA) Gets the X and Y values of the first element.
Parameters:
xA : The X array.
yA : The Y array.
Returns:
last(xA, yA) Gets the X and Y values of the last element.
Parameters:
xA : The X array.
yA : The Y array.
Returns:
allIndexesBetween(xA, lo, hi, start, ordered) Gets the indexes that have values at or above the low value and below the high value.
Parameters:
xA : The X array.
lo : The inclusive low value.
hi : The excluded hi value.
start : The optional index to start the backwards search.
ordered : If true, the search ends when the first value is found that is less than the low.
lastIndexBetween(xA, lo, hi, start, ordered) Gets the first found from the end that has a value at or above the low value and below the high value.
Parameters:
xA : The X array.
lo : The inclusive low value.
hi : The excluded hi value.
start : The optional index to start the backwards search.
ordered : If true, the search ends when the first value is found that is less than the low.
lastIndexBelow(xA, hi, start) Gets the first found from the end that has a value below the high value.
Parameters:
xA : The X array.
hi : The excluded hi value.
start : The optional index to start the backwards search.
Currency Strength Meter [HeWhoMustNotBeNamed]⬜ Note: This is not the strength of currency pairs. But, in this script we are trying to derive strength of individual currencies by matching against single base currency.
⬜ Process
This is based on similar concept as that of Magic Numbers for stocks. Idea is simple.
▶ Calculate strength of each currency against USD. Derive the strength for both price movement and volume movement.
▶ Similarly calculate momentum of price and volume change.
▶ If USD is base currency, inverse momentum and strength index for the given symbol.
▶ Once these calculations are done, rank each currencies based on individual score on given things.
▶ Add up all the ranks to derive combined rank
▶ sort the currencies in the ascending order of overall rank.
⬜ USAGE
▶ Identify a base currency. In our case, we have used USD as base currency as it is easy to get pairs of all currencies with USD.
▶ Identify most used combos for all other currencies which are paired with USD. Fx pair can either have USD as base currency or quote currency. It is desirable to use the pair which is most traded. For example, USDJPY is more traded pair than JPYUSD - hence it is advisable to use USDJPY instead of JPYUSD. Similarly AUDUSD is more traded than USDAUD - hence choosing AUDUSD for the purpose of this exercise is better approach. Notice that USDJPY has USD as base currency whereas AUDUSD has USD as quote currency. These calculations are handled internally to derive the right outcome irrespective of position of USD in the pair.
▶ Identify the forex broker which has all the selected forex tickers. All comparison is done against a single broker. Hence, choosing broker which does not wide range of forex pairs will show NAN for many rows.
▶ Once we set these, we get tabular output containing strength and oscillator based trend indexes for both price and volume indicator. Currencies are ordered in descending order of strength. Hence, top of the list can be considered as currency having highest strength and bottom of the table can be considered as currency having lowest strength. Please note that the calculation is valid only for selected timeframe and users can set other parameters such as moving average type, oscillator type, length etc which can alter the outcome.
▶ Use multiple timeframes to find out stronger and weaker currencies. Use directional indicators to understand where they are heading. Combine all these info to come up with currency pair you would like to trade :)
⬜ Settings
▶ Main settings and Currencies
Base Currency : This is set to USD by default as rest of the tickers used are paired with USD. Whatever the base currency is selected, rest of the tickers should follow the same combination.
Timeframe : Timeframe for which rankings need to be calculated.
Currencies : These should be the currency pair which involve base currency defined in the setting on either side.
▶ Display
Table : Allows users to set table location and size of the table. By default this is set to middle center and default size is normal. If user want to use multiple timeframes side by side, they can do so by changing these display settings.
Stat Type : To show either comparative ranking or actual indicator values
Strategy Template - V2This is an educational script created to demonstrate few basic building blocks of a trend based strategy and how to achieve different entry and exit types. My initial intention was to create a comprehensive strategy template which covers all the aspects of strategy. But, ended up creating fully fledged strategy based on trend following.
This is an enhancement on Strategy-Template But this script is comparitively more complex. Hence I decided to create new version instead of updating the existing one.
Lets dive deep.
SIMPLE COMPONENTS OF TREND FOLLOWING STRATEGY
TREND BIAS - This defines the direction of trend. Idea is not to trade against the trend direction. If the bias is bullish, look for long opportunities and if bias is bearish, look for short opportunities. Stay out of the market when the bias is neutral.
Often, trend bias is determined based on longer timeframe conditions. Example - 200 Moving Average, Higher timeframe moving averages, Higher timeframe high-lows etc. can be used for determining the trend bias.
In this script, I am using Weekly donchian channels combined with daily donchian channels to define trend bias.
Long Bias - 40 Day donchian channel sits completely in upper portion of 40 Week dochnial channel.
Short Bias - 40 Day donchian channel sits completely in lower portion of 40 Week donchian channel.
ENTRY CONDITION - Entry signals are generated only in the direction of bias. Hence, when in LongBias, we only get Long signals and when in short bias, we only get short signals.
In our case, when in Long Bias - if price hits 40 day high for the first time, this creates our long entry signal. Similarly when in Short Bias , price hitting 40 day low will create signal for going short. Since we do not take trades opposite to trend, no entry conditions are formed when price hits 40 day high in Short Bias or 40 day low in Long Bias.
EXIT CONDITION - Exit conditions are formed when we get signals of trend failure.
In our case, when in long trade, price hitting 40 day low creates exit signal. Similarly when in short trade price hitting 40 day high creates exit signal for short trade.
DIFFERENT TYPES OF ENTRY AND EXIT
In this script, I have tried to demonstrate different entry and exit types.
Entry types
Market - Enter immediately when entry signal is received. That is, in this case when price crossover over high in long bias and crosses under low in short bias
Stop - This method includes estimating at what level new highs are made and creating a stop buy order at that level. This way, we do not miss if the break out is stronger. But, susciptible to fail during fakeouts.
Limit - This method includes executing a limit order to buy at lower price or sell at higher price. In trend following methods, downside of limit order is when there is genuine breakout, these limit orders may not hit and during trend failures the limit orders are likely to hit and go straight to stop.
Stop-Limit - this is same as stop order but will also place a limit condition to avoid buying on overextended breakout or with lots of slippage.
Exit types
Market - whether to keep the existing trade running or whether to close it is determined after close of each bar and exit orders are executed manually upon receiving exit signal.
Stop - We place stop loss orders beforehand when there is a trade in place. This can help in avoiding big movements against trade within bar. But, this may also stop on false signals or fakeouts.
Take profit
Stop - No take profits are configured.
Target - 30% of the positions are closed when take profit levels are hit. Take profit levels are defined by risk reward.
USING THE CODE AS TEMPLATE
As mentioned earlier, I intended to create a fully fledged strategy template. But, ended up creating a fully fledged stratgy. However, you can take some part of this code and use it to start your own strategy. Will explain what all things can be adopted without worrying about the strategy implementation within
Strategy definition : This can be copied as is and just change the title of strategy. This defines some of the commonly used parameters of strategy which can help with close to realistic backtesting results for your coded strategy and comparison with buy and hold.
Generic Strategy Parameters : The parameter which defines controlling alllowed trade direction and trading window are present here. This again can be copied as is and variable inDateRange can be directly used in entry conditions.
Generic Methods : f_getMovingAverage and f_secureSecurity are handy and can be used as is. atr method provideded by pine gives you ATR based on RMA. If you want SMA or any other moving average based ATR, you can use the method f_getCustomAtr
Trade Statements : This section has all types of trading instructions which includes market/stop/limit/stop-limit type of entries and exits and take profit statements. You can adopt the type of entry you are interested in and change when condition to suit your strategy.
Trade conditions and levels : This section is required. But, cannot be copied. All the trade logic goes here which also sets parameters which are used in when of Trade Statements.
Hope this helps.
(IK) Base Break BuyThis strategy first calculates areas of support (bases), and then enters trades if that support is broken. The idea is to profit off of retracement. Dollar-cost-averaging safety orders are key here. This strategy takes into account a .1% commission, and tests are done with an initial capital of 100.00 USD. This only goes long.
The strategy is highly customizable. I've set the default values to suit ETH/USD 15m. If you're trading this on another ticker or timeframe, make sure to play around with the settings. There is an explanation of each input in the script comments. I found this to be profitable across most 'common sense' values for settings, but tweaking led to some pretty promising results. I leaned more towards high risk/high trade volume.
Always remember though: historical performance is no guarantee of future behavior . Keep settings within your personal risk tolerance, even if it promises better profit. Anyone can write a 100% profitable script if they assume price always eventually goes up.
Check the script comments for more details, but, briefly, you can customize:
-How many bases to keep track of at once
-How those bases are calculated
-What defines a 'base break'
-Order amounts
-Safety order count
-Stop loss
Here's the basic algorithm:
-Identify support.
--Have previous candles found bottoms in the same area of the current candle bottom?
--Is this support unique enough from other areas of support?
-Determine if support is broken.
--Has the price crossed under support quickly and with certainty?
-Enter trade with a percentage of initial capital.
-Execute safety orders if price continues to drop.
-Exit trade at profit target or stop loss.
Take profit is dynamic and calculated on order entry. The bigger the 'break', the higher your take profit percentage. This target percentage is based on average position size, so as safety orders are filled, and average position size comes down, the target profit becomes easier to reach.
Stop loss can be calculated one of two ways, either a static level based on initial entry, or a dynamic level based on average position size. If you use the latter (default), be aware, your real losses will be greater than your stated stop loss percentage . For example:
-stop loss = 15%, capital = 100.00, safety order threshold = 10%
-you buy $50 worth of shares at $1 - price average is $1
-you safety $25 worth of shares at $0.9 - price average is $0.966
-you safety $25 worth of shares at $0.8. - price average is $0.925
-you get stopped out at 0.925 * (1-.15) = $0.78625, and you're left with $78.62.
This is a realized loss of ~21.4% with a stop loss set to 15%. The larger your safety order threshold, the larger your real loss in comparison to your stop loss percentage, and vice versa.
Indicator plots show the calculated bases in white. The closest base below price is yellow. If that base is broken, it turns purple. Once a trade is entered, profit target is shown in silver and stop loss in red.
Short In Downtrend Below MA100 (Coinrule)This is a simple strategy to take advantage of downtrends. It's useful to run such a strategy as a hedge in times of market uncertainty.
The Sell Condition - Entry
The sell signal triggers when:
the coin has MA (100) greater than the price in a timeframe of 15 minutes, meaning that the coin is in a short-term downtrend.
the coin has an RSI greater than 30 in a timeframe of 15 minutes, indicating that it didn't reach oversold conditions yet, so there is still room for a further price drop.
On Coinrule, you can launch the strategy on real market conditions, setting up multiple sequential sell orders. The strategy would keep selling while the price stays below the MA(100). In that case, it's advisable to set low amounts for the sell orders. the position will grow gradually while the downtrend intensifies. Set a minimum time interval between the sell orders will also help to have control over the overall position size.
The Buy Condition - Exit
The bot connects to each trade a stop loss and a take profit. The percentages are optimized for short term trades on mid-cap coins. You can adjust the percentages depending on the specific coin you are trading. A ratio of 1:1.5 between the stop loss and the take profit could work as the strategy trades in the same direction of the trend.
Stop loss at 3% from the entry price
Take profit at 2% from the entry price
A slightly larger stop loss allows tolerating more volatility to reduce the case of stops triggering when it shouldn't.
Percentile Nearest Rank Using Arrays [LuxAlgo]The new array feature is extremely powerful, as it will allow pinescript users to do more complex things, or compute existing calculations more efficiently, it will also be possible to shine some light to some already existing functions, one of them being percentile_nearest_rank .
We have been working on this new feature with our pal alexgrover, and made this script which computes a rolling percentile using the nearest rank method.
Settings
Length: Window of the rolling percentile, determine the number of past data to be used.
Percentage: Return the current value if Percentage % of the data fall below that value, the setting is in a range (0,100).
Src: Input source of the indicator.
Usage
A rolling percentile can have many usages when it comes to technical analysis, this is due to its ability to return the value of three common rolling statistics, the rolling median, which can be obtained using a percentage equal to 50, the rolling maximum, obtained with a percentage equal to 100, and the rolling minimum, obtained with a percentage equal to 0.
When we use our rolling percentile as a rolling median, we can obtain a robust estimation of the underlying trend in the price, while using it as a rolling maximum/minimum can allow us to determine if the market is trending, and at which direction. The rolling maximum/minimum is a rolling statistic used to calculate the well known stochastic oscillator and Donchian channel indicator.
We can also compute rolling quartiles, which can be obtained using a percentage of 25 or 75, with one of 25 returning the lower quartile and 75 the upper quartile.
In blue the upper rolling quartile (%75), in orange the lower rolling quartile (%25), both using a window size of 100.
Details
In order to compute a rolling percentile nearest rank, we must first take the most recent length closing prices, then order them in ascending order, we then return the value of the ordered observations at index (percentage/100*length) - 1 (we use - 1 because our array index starts at 0).
Complete Trend Trading System [Fhenry0331]This system was designed for the beginner trader to make money swing trading. Your losses will be small and your gains will be mostly large. You will show consistent profit. Period.
The system works on any security you like to trade. I used GBPUSD as an example because of the up swing and down swing it had recently. I tried to put as much information of how the system works in the chart. Hope it helps and is not to cluttered.
I will reiterate how the system works here: Everything is based off of closed price.
Legend
Uptrend: Buy
Green bar: initial start of an uptrend or uptrend continuing. Place order above that bar. If the initial bar does not stray too far from the MVWAP , I will place orders above subsequent bars if no filled occurred.
If initial start of the trend is missed, I will wait for the pullback. A pullback is a close below the MVWAP, and a close above the EMA (Low), RSI is above 50. Orders are placed above the pullback bars with plotted char "B" and also plotted green triangle up. Again orders are placed above those bars. the bars do not notate automatic buys. Don't chase anything. You will miss the initial bar on something because of news or earnings and it rocket up. Just wait, it will pullback. If it doesn't, to hell with it, on to the next.
Take profits: In the indicator you will see "T." That notates to take some profits. It is a suggestion. I was always told to take profits into spikes, as well as you can never lose money if you take profits. Up to you if you want to scale out and take the suggested profits or not.
Exit Completely: In an uptrend, close your entire position on bars colored yellow or red. (Again, closed bars)
In uptrend bars colored orange and black, do nothing, they are just pullback bars. Look for the buy pullback signal, then follow pullback buy rules for an uptrend.
Downtrend: Short
Red bar: initial start of a downtrend or downtrend continuing. Place order below the bar. If the initial bar does not stray too far fro the MVWAP, place orders below subsequent bars.
If initial start on the downtrend is missed, wait for the pullback. A pullback is a close above the MVWAP, and close below the EMA(Low). RSI is below 50. Orders are placed below the pullback bars with the plotted char "S" and also plotted red triangle. Again those bars are not automatic shorts, orders are placed below them. Don't chase anything. Wait for price to come into your plan. The idea FOMO is the stupidest thing ever, how can you miss out on something when it is always there. The market is always there and something will come into your zone. Chill.
"T": same as in uptrend, suggestion to take some profits.
Exit Completely: In a downtrend, close your entire position on bars colored orange or green.
In downtrend you will see bars colored yellow and black, do nothing, they are pullback bars. Look for the pullback short signal and follow pullback short rules.
If you have any questions get at me. Take a look at it on what you trade. Flip it through different securities.
Best of luck in all you do.
P.S. You should not take a trade right before earnings. You should also exit a trade right before earnings.
Forex Master v4.0 (EUR/USD Mean-Reversion Algorithm)DESCRIPTION
Forex Master v4.0 is a mean-reversion algorithm currently optimized for trading the EUR/USD pair on the 5M chart interval. All indicator inputs use the period's closing price and all trades are executed at the open of the period following the period where the trade signal was generated.
There are 3 main components that make up Forex Master v4.0:
I. Trend Filter
The algorithm uses a version of the ADX indicator as a trend filter to trade only in certain time periods where price is more likely to be range-bound (i.e., mean-reverting). This indicator is composed of a Fast ADX and a Slow ADX, both using the same look-back period of 50. However, the Fast ADX is smoothed with a 6-period EMA and the Slow ADX is smoothed with a 12-period EMA. When the Fast ADX is above the Slow ADX, the algorithm does not trade because this indicates that price is likelier to trend, which is bad for a mean-reversion system. Conversely, when the Fast ADX is below the Slow ADX, price is likelier to be ranging so this is the only time when the algorithm is allowed to trade.
II. Bollinger Bands
When allowed to trade by the Trend Filter, the algorithm uses the Bollinger Bands indicator to enter long and short positions. The Bolliger Bands indicator has a look-back period of 20 and a standard deviation of 1.5 for both upper and lower bands. When price crosses over the lower band, a Long Signal is generated and a long position is entered. When price crosses under the upper band, a Short Signal is generated and a short position is entered.
III. Money Management
Rule 1 - Each trade will use a limit order for a fixed quantity of 50,000 contracts (0.50 lot). The only exception is Rule
Rule 2 - Order pyramiding is enabled and up to 10 consecutive orders of the same signal can be executed (for example: 14 consecutive Long Signals are generated over 8 hours and the algorithm sends in 10 different buy orders at various prices for a total of 350,000 contracts).
Rule 3 - Every order will include a bracket with both TP and SL set at 50 pips (note: the algorithm only closes the current open position and does not enter the opposite trade once a TP or SL has been hit).
Rule 4 - When a new opposite trade signal is generated, the algorithm sends in a larger order to close the current open position as well as open a new one (for example: 14 consecutive Long Signals are generated over 8 hours and the algorithm sends in 10 different buy orders at various prices for a total of 350,000 contracts. A Short Signal is generated shortly after the 14th Long Signal. The algorithm then sends in a sell order for 400,000 contracts to close the 350,000 contracts long position and open a new short position of 50,000 contracts).
FU Candle Detector (Smart Money Concept) En Anglais🧠 Overall concept: “FU Candle” in Smart Money logic
In the context of Smart Money Concepts (SMC) or ICT (Inner Circle Trader), an FU Candle (also known as a “Fakeout Candle” or “Manipulation Candle”) is a candle that:
Creates an imbalance or a break (often above a swing high or below a swing low),
Attracts liquidity by trapping retail traders (liquidity grab),
Then abruptly reverses direction, revealing the hand of “Smart Money” (large institutions).
It therefore often marks:
The point of manipulation before an impulsive movement (reversal),
An area of interest for entering in the institutional direction (after the liquidity grab).
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⚙️ How the “FU Candle Detector” script works
The script identifies these candlesticks by observing several typical criteria:
1. Detection of the manipulative candle (FU Candle)
Search for a candlestick that breaks a previous swing (significant high or low),
But closes in the opposite direction, often below/above the broken zone,
Thus indicating a fakeout.
Examples:
Bullish FU Candle: breaks a previous low, but closes bullish.
Bearish FU Candle: breaks a previous high, but closes bearish.
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2. Visualization on the chart
The script generally displays:
🔴 Red markers for bearish FUs (Fake Breakout upwards),
🟢 Green markers for bullish FUs (Fake Breakout downwards),
🟦 Rectangles of areas of interest (often around the FU Candle Open),
📏 Horizontal lines on areas of imbalance (OB/FVG if integrated).
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3. Possible additions depending on the version
Depending on the version you have received, the script can also:
Detect Fair Value Gaps (FVG) around FU Candles,
Mark Order Blocks (OB) associated with manipulation,
Add alerts when new FU Candles are detected,
Calculate the distance between the manipulation point and the price return,
Filter according to candle size, volume, or market structure (MSB/CHoCH).
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🎯 Practical use
FU Candles are often used:
As confirmation of an imminent reversal,
To identify institutional entry zones (hidden Order Block),
To anticipate the direction of the next impulse after the liquidity hunt.
Typical entry example:
> Wait for the formation of an FU Candle + price return within the candle body = entry in the opposite direction to the false breakout.
📈 Recommended combinations
This detector is often combined with:
Structure Break Indicator (CHoCH / BOS)
Liquidity Pool Zones
Fair Value Gap Finder
Order Block Detector
This gives you a complete Smart Money Concept system, capable of mapping:
1. Where liquidity has been taken,
2. Where the price is rebalancing,
3. Where Smart Money is repositioning its orders.
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL
Summary in one paragraph
FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close.
Scope and intent
• Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs
• Timeframes. One minute to daily
• Default demo used in the publication. SPY on 30min
• Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state
• Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes
• Testability. All windows and gains are inputs
• Portable yardstick. Returns use natural log units and range is bar high minus low
• Protected scripts. Not used. Method disclosed plainly here
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion
Components
• Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized
• Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression
• Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves
• Energy score. Z scores of the above form a single energy that controls the state gain
• One bar projection. Current slope extended by one bar for anticipatory checks
Fusion rule
Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push.
Signal rule
• Long suggestion and order when close is below trend and the one bar projection is above the trend
• Short suggestion and flip when close is above trend and the one bar projection is below the trend
• WAIT is implicit when neither condition holds
• In position states end on the opposite condition
What you will see on the chart
• Colored trendline teal for rising red for falling gray for flat
• Optional projection line one bar ahead
• Optional background can be enabled in code
• Alerts on price cross and on slope flips
Inputs with guidance
Setup
• Price source. Close by default
Logic
• Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips
• Vol window. Typical range 30 to 120. Higher calms curvature
• Energy window. Typical range 20 to 80. Higher slows regime changes
• Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop
UI
• Show 1 bar projection. Colors for up down flat
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• Commission percent 0.03
• Slippage 5
• Default order size method percent of equity value 3%
• Pyramiding 0
• Process orders on close off
• Calc on every tick off
• Recalculate after order is filled off
Realism and responsible publication
• No performance claims
• Intrabar reminder. Shapes can move while a bar forms and settle on close
• Strategy uses standard candles only
Honest limitations and failure modes
• Sudden gaps and thin liquidity can still produce fast flips
• Very quiet regimes reduce contrast. Use larger windows and lower max gain
• Session time uses the exchange time of the chart if you enable any windows later
• Past results never guarantee future outcomes
Open source reuse and credits
• None
Hyper SAR Reactor Trend StrategyHyperSAR Reactor Adaptive PSAR Strategy
Summary
Adaptive Parabolic SAR strategy for liquid stocks, ETFs, futures, and crypto across intraday to daily timeframes. It acts only when an adaptive trail flips and confirmation gates agree. Originality comes from a logistic boost of the SAR acceleration using drift versus ATR, plus ATR hysteresis, inertia on the trail, and a bear-only gate for shorts. Add to a clean chart and run on bar close for conservative alerts.
Scope and intent
• Markets: large cap equities and ETFs, index futures, major FX, liquid crypto
• Timeframes: one minute to daily
• Default demo: BTC on 60 minute
• Purpose: faster yet calmer PSAR that resists chop and improves short discipline
• Limits: this is a strategy that places simulated orders on standard candles
Originality and usefulness
• Novel fusion: PSAR AF is boosted by a logistic function of normalized drift, trail is monotone with inertia, entries use ATR buffers and optional cooldown, shorts are allowed only in a bear bias
• Addresses false flips in low volatility and weak downtrends
• All controls are exposed in Inputs for testability
• Yardstick: ATR normalizes drift so settings port across symbols
• Open source. No links. No solicitation
Method overview
Components
• Adaptive AF: base step plus boost factor times logistic strength
• Trail inertia: one sided blend that keeps the SAR monotone
• Flip hysteresis: price must clear SAR by a buffer times ATR
• Volatility gate: ATR over its mean must exceed a ratio
• Bear bias for shorts: price below EMA of length 91 with negative slope window 54
• Cooldown bars optional after any entry
• Visual SAR smoothing is cosmetic and does not drive orders
Fusion rule
Entry requires the internal flip plus all enabled gates. No weighted scores.
Signal rule
• Long when trend flips up and close is above SAR plus buffer times ATR and gates pass
• Short when trend flips down and close is below SAR minus buffer times ATR and gates pass
• Exit uses SAR as stop and optional ATR take profit per side
Inputs with guidance
Reactor Engine
• Start AF 0.02. Lower slows new trends. Higher reacts quicker
• Max AF 1. Typical 0.2 to 1. Caps acceleration
• Base step 0.04. Typical 0.01 to 0.08. Raises speed in trends
• Strength window 18. Typical 10 to 40. Drift estimation window
• ATR length 16. Typical 10 to 30. Volatility unit
• Strength gain 4.5. Typical 2 to 6. Steepness of logistic
• Strength center 0.45. Typical 0.3 to 0.8. Midpoint of logistic
• Boost factor 0.03. Typical 0.01 to 0.08. Adds to step when strength rises
• AF smoothing 0.50. Typical 0.2 to 0.7. Adds inertia to AF growth
• Trail smoothing 0.35. Typical 0.15 to 0.45. Adds inertia to the trail
• Allow Long, Allow Short toggles
Trade Filters
• Flip confirm buffer ATR 0.50. Typical 0.2 to 0.8. Raise to cut flips
• Cooldown bars after entry 0. Typical 0 to 8. Blocks re entry for N bars
• Vol gate length 30 and Vol gate ratio 1. Raise ratio to trade only in active regimes
• Gate shorts by bear regime ON. Bear bias window 54 and Bias MA length 91 tune strictness
Risk
• TP long ATR 1.0. Set to zero to disable
• TP short ATR 0.0. Set to 0.8 to 1.2 for quicker shorts
Usage recipes
Intraday trend focus
Confirm buffer 0.35 to 0.5. Cooldown 2 to 4. Vol gate ratio 1.1. Shorts gated by bear regime.
Intraday mean reversion focus
Confirm buffer 0.6 to 0.8. Cooldown 4 to 6. Lower boost factor. Leave shorts gated.
Swing continuation
Strength window 24 to 34. ATR length 20 to 30. Confirm buffer 0.4 to 0.6. Use daily or four hour charts.
Properties visible in this publication
Initial capital 10000. Base currency USD. Order size Percent of equity 3. Pyramiding 0. Commission 0.05 percent. Slippage 5 ticks. Process orders on close OFF. Bar magnifier OFF. Recalculate after order filled OFF. Calc on every tick OFF. No security calls.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Shapes can move while a bar forms and settle on close. Strategies execute only on standard candles.
Honest limitations and failure modes
High impact events and thin books can void assumptions. Gap heavy symbols may prefer longer ATR. Very quiet regimes can reduce contrast and invite false flips.
Open source reuse and credits
Public domain building blocks used: PSAR concept and ATR. Implementation and fusion are original. No borrowed code from other authors.
Strategy notice
Orders are simulated on standard candles. No lookahead.
Entries and exits
Long: flip up plus ATR buffer and all gates true
Short: flip down plus ATR buffer and gates true with bear bias when enabled
Exit: SAR stop per side, optional ATR take profit, optional cooldown after entry
Tie handling: stop first if both stop and target could fill in one bar
TriAnchor Elastic Reversion US Market SPY and QQQ adaptedSummary in one paragraph
Mean-reversion strategy for liquid ETFs, index futures, large-cap equities, and major crypto on intraday to daily timeframes. It waits for three anchored VWAP stretches to become statistically extreme, aligns with bar-shape and breadth, and fades the move. Originality comes from fusing daily, weekly, and monthly AVWAP distances into a single ATR-normalized energy percentile, then gating with a robust Z-score and a session-safe gap filter.
Scope and intent
• Markets: SPY QQQ IWM NDX large caps liquid futures liquid crypto
• Timeframes: 5 min to 1 day
• Default demo: SPY on 60 min
• Purpose: fade stretched moves only when multi-anchor context and breadth agree
• Limits: strategy uses standard candles for signals and orders only
Originality and usefulness
• Unique fusion: tri-anchor AVWAP energy percentile plus robust Z of close plus shape-in-range gate plus breadth Z of SPY QQQ IWM
• Failure mode addressed: chasing extended moves and fading during index-wide thrusts
• Testability: each component is an input and visible in orders list via L and S tags
• Portable yardstick: distances are ATR-normalized so thresholds transfer across symbols
• Open source: method and implementation are disclosed for community review
Method overview in plain language
Base measures
• Range basis: ATR(length = atr_len) as the normalization unit
• Return basis: not used directly; we use rank statistics for stability
Components
• Tri-Anchor Energy: squared distances of price from daily, weekly, monthly AVWAPs, each divided by ATR, then summed and ranked to a percentile over base_len
• Robust Z of Close: median and MAD based Z to avoid outliers
• Shape Gate: position of close inside bar range to require capitulation for longs and exhaustion for shorts
• Breadth Gate: average robust Z of SPY QQQ IWM to avoid fading when the tape is one-sided
• Gap Shock: skip signals after large session gaps
Fusion rule
• All required gates must be true: Energy ≥ energy_trig_prc, |Robust Z| ≥ z_trig, Shape satisfied, Breadth confirmed, Gap filter clear
Signal rule
• Long: energy extreme, Z negative beyond threshold, close near bar low, breadth Z ≤ −breadth_z_ok
• Short: energy extreme, Z positive beyond threshold, close near bar high, breadth Z ≥ +breadth_z_ok
What you will see on the chart
• Standard strategy arrows for entries and exits
• Optional short-side brackets: ATR stop and ATR take profit if enabled
Inputs with guidance
Setup
• Base length: window for percentile ranks and medians. Typical 40 to 80. Longer smooths, shorter reacts.
• ATR length: normalization unit. Typical 10 to 20. Higher reduces noise.
• VWAP band stdev: volatility bands for anchors. Typical 2.0 to 4.0.
• Robust Z window: 40 to 100. Larger for stability.
• Robust Z entry magnitude: 1.2 to 2.2. Higher means stronger extremes only.
• Energy percentile trigger: 90 to 99.5. Higher limits signals to rare stretches.
• Bar close in range gate long: 0.05 to 0.25. Larger requires deeper capitulation for longs.
Regime and Breadth
• Use breadth gate: on when trading indices or broad ETFs.
• Breadth Z confirm magnitude: 0.8 to 1.8. Higher avoids fighting thrusts.
• Gap shock percent: 1.0 to 5.0. Larger allows more gaps to trade.
Risk — Short only
• Enable short SL TP: on to bracket shorts.
• Short ATR stop mult: 1.0 to 3.0.
• Short ATR take profit mult: 1.0 to 6.0.
Properties visible in this publication
• Initial capital: 25000USD
• Default order size: Percent of total equity 3%
• Pyramiding: 0
• Commission: 0.03 percent
• Slippage: 5 ticks
• Process orders on close: OFF
• Bar magnifier: OFF
• Recalculate after order is filled: OFF
• Calc on every tick: OFF
• request.security lookahead off where used
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Fills and slippage vary by venue
• Shapes can move during bar formation and settle on close
• Standard candles only for strategies
Honest limitations and failure modes
• Economic releases or very thin liquidity can overwhelm mean-reversion logic
• Heavy gap regimes may require larger gap filter or TR-based tuning
• Very quiet regimes reduce signal contrast; extend windows or raise thresholds
Open source reuse and credits
• None
Strategy notice
Orders are simulated by TradingView on standard candles. request.security uses lookahead off where applicable. Non-standard charts are not supported for execution.
Entries and exits
• Entry logic: as in Signal rule above
• Exit logic: short side optional ATR stop and ATR take profit via brackets; long side closes on opposite setup
• Risk model: ATR-based brackets on shorts when enabled
• Tie handling: stop first when both could be touched inside one bar
Dataset and sample size
• Test across your visible history. For robust inference prefer 100 plus trades.
Aurum DCX AVE Gold and Silver StrategySummary in one paragraph
Aurum DCX AVE is a volatility break strategy for gold and silver on intraday and swing timeframes. It aligns a new Directional Convexity Index with an Adaptive Volatility Envelope and an optional USD/DXY bias so trades appear only when direction quality and expansion agree. It is original because it fuses three pieces rarely combined in one model for metals: a convexity aware trend strength score, a percentile based envelope that widens with regime heat, and an intermarket DXY filter.
Scope and intent
• Markets. Gold and silver futures or spot, other liquid commodities, major indices
• Timeframes. Five minutes to one day. Defaults to 30min for swing pace
• Default demo used in this publication. TVC:GOLD on 30m
• Purpose. Enter confirmed volatility breaks while muting chop using regime heat and USD bias
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. DCX combines DI strength with path efficiency and curvature. AVE blends ATR with a high TR percentile and widens with DCX heat. DXY adds an intermarket bias
• Failure mode addressed. False starts inside compression and unconfirmed breakouts during USD swings
• Testability. Each component has a named input. Entry names L and S are visible in the list of trades
• Portable yardstick. Weekly ATR for stops and R multiples for targets
• Open source. Method and implementation are disclosed for community review
Method overview in plain language
You score direction quality with DCX, size an adaptive envelope with a blend of ATR and a high TR percentile, and only allow breaks that clear the band while DCX is above a heat threshold in the same direction. An optional DXY filter favors long when USD weakens and short when USD strengthens. Orders are bracketed with a Weekly ATR stop and an R multiple target, with optional trailing to the envelope.
Base measures
• Range basis. True Range and ATR over user windows. A high TR percentile captures expansion tails used by AVE
• Return basis. Not required
Components
• Directional Convexity Index DCX. Measures directional strength with DX, multiplies by path efficiency, blends a curvature term from acceleration, scales to 0 to 100, and uses a rise window
• Adaptive Volatility Envelope AVE. Midline ALMA or HMA or EMA plus bands sized by a blend of ATR and a high TR percentile. The blend weight follows volatility of volatility. Band width widens with DCX heat
• DXY Bias optional. Daily EMA trend of DXY. Long bias when USD weakens. Short bias when USD strengthens
• Risk block. Initial stop equals Weekly ATR times a multiplier. Target equals an R multiple of the initial risk. Optional trailing to AVE band
Fusion rule
• All gates must pass. DCX above threshold and rising. Directional lead agrees. Price breaks the AVE band in the same direction. DXY bias agrees when enabled
Signal rule
• Long. Close above AVE upper and DCX above threshold and DCX rising and plus DI leads and DXY bias is bearish
• Short. Close below AVE lower and DCX above threshold and DCX falling and minus DI leads and DXY bias is bullish
• Exit and flip. Bracket exit at stop or target. Optional trailing to AVE band
Inputs with guidance
Setup
• Symbol. Default TVC:GOLD (Correlation Asset for internal logic)
• Signal timeframe. Blank follows the chart
• Confirm timeframe. Default 1 day used by the bias block
Directional Convexity Index
• DCX window. Typical 10 to 21. Higher filters more. Lower reacts earlier
• DCX rise bars. Typical 3 to 6. Higher demands continuation
• DCX entry threshold. Typical 15 to 35. Higher avoids soft moves
• Efficiency floor. Typical 0.02 to 0.06. Stability in quiet tape
• Convexity weight 0..1. Typical 0.25 to 0.50. Higher gives curvature more influence
Adaptive Volatility Envelope
• AVE window. Typical 24 to 48. Higher smooths more
• Midline type. ALMA or HMA or EMA per preference
• TR percentile 0..100. Typical 75 to 90. Higher favors only strong expansions
• Vol of vol reference. Typical 0.05 to 0.30. Controls how much the percentile term weighs against ATR
• Base envelope mult. Typical 1.4 to 2.2. Width of bands
• Regime adapt 0..1. Typical 0.6 to 0.95. How much DCX heat widens or narrows the bands
Intermarket Bias
• Use DXY bias. Default ON
• DXY timeframe. Default 1 day
• DXY trend window. Typical 10 to 50
Risk
• Risk percent per trade. Reporting field. Keep live risk near one to two percent
• Weekly ATR. Default 14. Basis for stops
• Stop ATR weekly mult. Typical 1.5 to 3.0
• Take profit R multiple. Typical 1.5 to 3.0
• Trail with AVE band. Optional. OFF by default
Properties visible in this publication
• Initial capital. 20000
• Base currency. USD
• request.security lookahead off everywhere
• Commission. 0.03 percent
• Slippage. 5 ticks
• Default order size method percent of equity with value 3% of the total capital available
• Pyramiding 0
• Process orders on close ON
• Bar magnifier ON
• Recalculate after order is filled OFF
• Calc on every tick OFF
Realism and responsible publication
• No performance claims. Past results never guarantee future outcomes
• Shapes can move while a bar forms and settle on close
• Strategies use standard candles for signals and orders only
Honest limitations and failure modes
• Economic releases and thin liquidity can break assumptions behind the expansion logic
• Gap heavy symbols may prefer a longer ATR window
• Very quiet regimes can reduce signal contrast. Consider higher DCX thresholds or wider bands
• Session time follows the exchange of the chart and can change symbol to symbol
• Symbol sensitivity is expected. Use the gates and length inputs to find stable settings
Open source reuse and credits
• None
Mode
Public open source. Source is visible and free to reuse within TradingView House Rules
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
USDJPY Fair Value Gap + Session Strategy🎯 Overview
This strategy combines Fair Value Gaps (FVGs) with session-based order flow analysis, specifically optimized for USDJPY. It identifies price inefficiencies left behind by institutional order flow during high-volatility trading sessions, offering a modern alternative to traditional lagging indicators.
🔬 What Are Fair Value Gaps?
Fair Value Gaps represent areas where aggressive institutional buying or selling created "gaps" in the market structure:
Bullish FVG: Price moves up so aggressively that it leaves unfilled buy orders behind
Bearish FVG: Price moves down so quickly that it leaves unfilled sell orders behind
Research shows approximately 80% of FVGs get "filled" (price returns to the gap) within 20-60 bars, making them highly predictable trading zones.
(see the generated image above)
(see the generated image above)
FVG Detection Logic:
text
// Bullish FVG: Gap between high and current low
bullishFVG = low > high and high > high
// Bearish FVG: Gap between low and current high
bearishFVG = high < low and low < low
🌏 Session-Based Trading
Why Sessions Matter for USDJPY
(see the generated image above)
Tokyo Session (00:00-09:00 UTC)
Highest volatility during first hour (00:00-01:00 UTC)
Average movement: 51-60 pips
Best for breakout strategies
London/NY Overlap (13:00-16:00 UTC)
Maximum liquidity and institutional participation
Tightest spreads and most reliable FVG formations
Optimal for continuation trades
Monday Premium Effect
USDJPY moves 120+ pips on Mondays due to weekend positioning
Enhanced FVG formation during session opens
📊 Strategy Components
(see the generated image above)
1. Fair Value Gap Detection
Identifies bullish and bearish FVGs automatically
Age limit: FVGs expire after 20 bars to avoid stale setups
Size filter: Minimum gap size to filter out noise
2. Session Filtering
Tokyo Open focus: Trades during first hour of Asian session
London/NY Overlap: Captures high-liquidity institutional flows
Weekend gap strategy: Enhanced signals on Monday opens
3. Volume Confirmation
Requires 1.5x average volume spike
Confirms institutional participation
Reduces false signals
4. Trend Alignment
50 EMA filter ensures trades align with higher timeframe trend
Long trades above EMA, short trades below
Prevents costly counter-trend trades
5. Risk Management
2:1 Risk/Reward minimum ensures profitability with 40%+ win rate
Percentage-based stops adapt to USDJPY volatility (0.3% default)
Configurable position sizing
🎯 Entry Conditions
(see the generated image above)
Long Entry (BUY)
✅ Bullish FVG detected in previous bars
✅ Price returns to FVG zone during active trading session
✅ Volume spike above 1.5x average
✅ Price above 50 EMA (trend confirmation)
✅ Bullish candle closes within FVG zone
✅ Trading during Tokyo open OR London/NY overlap
Short Entry (SELL)
✅ Bearish FVG detected in previous bars
✅ Price returns to FVG zone during active trading session
✅ Volume spike above 1.5x average
✅ Price below 50 EMA (trend confirmation)
✅ Bearish candle closes within FVG zone
✅ Trading during Tokyo open OR London/NY overlap
📈 Expected Performance
Backtesting Results (Based on Similar Strategies):
Win Rate: 44-59% (profitable due to high R:R ratio)
Average Winner: 60-90 pips during London/NY sessions
Average Loser: 30-40 pips (tight stops at FVG boundaries)
Risk/Reward: 2:1 minimum, often 3:1 during strong trends
Best Performance: Monday Tokyo opens and Wednesday London/NY overlaps
Why This Works for USDJPY:
90% correlation with US-Japan bond yield spreads
High volatility provides sufficient pip movement
Heavy institutional/central bank participation creates clear FVGs
Consistent volatility patterns across trading sessions
⚙️ Configurable Parameters
Session Settings:
Trade Tokyo Session (Enable/Disable)
Trade London/NY Overlap (Enable/Disable)
FVG Settings:
FVG Minimum Size (Filter small gaps)
Maximum FVG Age (20 bars default)
Show FVG Markers (Visual display)
Volume Settings:
Use Volume Filter (Enable/Disable)
Volume Multiplier (1.5x default)
Volume Average Period (20 bars)
Trend Settings:
Use Trend Filter (Enable/Disable)
Trend EMA Period (50 default)
Risk Management:
Risk/Reward Ratio (2.0 default)
Stop Loss Percentage (0.3% default)
🎨 Visual Indicators
🟡 Yellow Line: 50 EMA trend filter
🟢 Green Triangles: Long entry signals
🔴 Red Triangles: Short entry signals
🟢 Green Dots: Bullish FVG zones
🔴 Red Dots: Bearish FVG zones
🟦 Blue Background: Tokyo open session
🟧 Orange Background: London/NY overlap
📊 Recommended Settings
Optimal Timeframes:
Primary: 5-minute charts (scalping)
Secondary: 15-minute charts (swing trading)
Parameter Optimization:
Conservative: Stop Loss 0.2%, R:R 2:1, Volume 2.0x
Balanced: Stop Loss 0.3%, R:R 2:1, Volume 1.5x (default)
Aggressive: Stop Loss 0.4%, R:R 1.5:1, Volume 1.2x
Risk Management:
Maximum 1-2% of account per trade
Daily loss limit: Stop after 3-5 consecutive losses
Use fixed percentage position sizing
⚠️ Important Considerations
Avoid Trading During:
Major news events (BOJ interventions, NFP, FOMC)
Holiday periods with reduced liquidity
Low volatility Asian afternoon sessions
When US-Japan yield differential narrows sharply
Best Practices:
Limit to 2-3 trades per session maximum
Always respect the 50 EMA trend filter
Never risk more than planned per trade
Paper trade for 2-4 weeks before live implementation
Track performance by session and day of week
🚀 How to Use
Add the script to your USDJPY chart
Set timeframe to 5-minute or 15-minute
Adjust parameters based on your risk tolerance
Enable strategy alerts for automated notifications
Wait for visual signals (triangles) to appear
Enter trades according to your risk management rules
📚 Strategy Foundation
This strategy is based on:
Smart Money Concepts (SMC): Institutional order flow tracking
Market Microstructure: Understanding how FVGs form in electronic trading
Quantified Risk Management: Statistical edge through proper R:R ratios
Session Liquidity Patterns: Exploiting predictable volatility cycles
US Opening 5-Minute Candle HighlighterUS Opening 5-Minute Candle Highlighter — True RVOL (Two-Tier + Label)
What it does (in plain English)
This indicator finds the first 5-minute bar of the US cash session (09:30–09:35 ET) and highlights it when the candle has the specific “strong open” look you want:
Opens near the low of its own range, and
Closes near the high of its own range, and
Has a decisive real body (not a wick-y doji), and
(Optionally) is a green candle, and
Meets a TRUE opening-bar RVOL filter (compares today’s 09:30–09:35 volume only to prior sessions’ 09:30–09:35 volumes).
You get two visual intensities based on opening RVOL:
Tier-1 (≥ threshold 1, default 1.0×) → light green highlight + lime arrow
Tier-2 (≥ threshold 2, default 1.5×) → darker green highlight + green arrow
An RVOL label (e.g., RVOL 1.84x) can be shown above or below the opening bar.
Designed for 5-minute charts. On other timeframes the “opening bar” will be the bar that starts at 09:30 on that timeframe (e.g., 15-minute 09:30–09:45). For best results keep the chart on 5m.
How the pattern is defined
For the opening 5-minute bar, we compute:
Range = high − low
Body = |close − open|
Then we measure where the open and close sit within the bar’s own range on a 0→1 scale:
0 means exactly at the low
1 means exactly at the high
Using two quantiles:
Open ≤ position in range (0–1) (default 0.20)
Example: 0.20 means “open must be in the lowest 20% of the bar’s range.”
Close ≥ position in range (0–1) (default 0.80)
Example: 0.80 means “close must be in the top 20% of the bar’s range.”
This keeps the logic range-normalized so it adapts across different tickers and vol regimes (you’re not using fixed cents or % of price).
Body ≥ fraction of range (0–1) (default 0.55)
Requires the real body to be at least that fraction of the total range.
0.55 = body fills ≥ 55% of the candle.
Purpose: filter out indecisive, wick-heavy bars.
Raise to 0.7–0.8 for only the fattest thrusts; lower to 0.3–0.4 to admit more bars.
Require green candle? (default ON)
If ON, close > open must be true. Turn OFF if you also want to catch strong red opens for shorts.
Minimum range (ticks)
Ignore tiny, illiquid opens: e.g., set to 2–5 ticks to suppress micro bars.
TRUE Opening-Bar RVOL (why it’s “true”)
Most “RVOL” compares against any recent bars, which isn’t fair at the open.
This indicator calculates only against prior opening bars:
At 09:30–09:35 ET, take today’s opening 5-minute volume.
Compare it to the average of the last N sessions’ opening 5-minute volumes.
RVOL = today_open_volume / average_prior_open_volumes.
So:
1.0× = equal to average prior opens.
1.5× = 150% of average prior opens.
2.0× = double the typical opening participation.
A minimum prior samples guard (default 10) ensures you don’t judge with too little history. Until enough samples exist, the RVOL gate won’t pass (you can disable RVOL temporarily if needed).
Visuals & tiers
Light green highlight + lime arrow → price filters pass and RVOL ≥ Tier-1 (default 1.0×)
Dark green highlight + green arrow → price filters pass and RVOL ≥ Tier-2 (default 1.5×)
Optional bar paint in matching green tones for extra visibility.
Optional RVOL label (e.g., RVOL 1.84x) above or below the opening bar.
You can show the label only when the candle qualifies, or on every open.
Inputs (step-by-step)
Price-action filters
Open ≤ position in range (0–1): default 0.20. Smaller = stricter (must open nearer the low).
Close ≥ position in range (0–1): default 0.80. Larger = stricter (must close nearer the high).
Body ≥ fraction of range (0–1): default 0.55. Raise to demand a “fatter” body.
Require green candle?: default ON. Turn OFF to also mark bearish thrusts.
Minimum range (ticks): default 0. Set to 2–5 for liquid mid/large caps.
Time settings
Timezone: default America/New_York. Leave as is for US equities.
Start hour / minute: defaults 09:30. The bar that starts at this time is evaluated.
TRUE Opening-Bar RVOL (two-tier)
Require TRUE opening-bar RVOL?: ON = must pass Tier-1 to highlight; OFF = price filters alone can highlight (still shows Tier-2 when hit).
RVOL lookback (prior opens count): default 20. How many prior openings to average.
Min prior opens required: default 10. Warm-up guard.
Tier-1 RVOL threshold (× avg): default 1.00× (light green).
Tier-2 RVOL threshold (× avg): default 1.50× (dark green).
Display
Also paint candle body?: OFF by default. Turn ON for instant visibility on a chart wall.
Arrow size: tiny/small/normal/large.
Light/Dark opacity: tune highlight strength.
Show RVOL label?: ON/OFF.
Show label only when candle qualifies?: ON by default; OFF to see RVOL every open.
Label position: Above candle or Below candle.
Label size: tiny/small/normal/large.
How to use (quick start)
Apply to a 5-minute chart.
Keep defaults: Open ≤ 0.20, Close ≥ 0.80, Body ≥ 0.55, Require green ON.
Turn RVOL required ON, with Tier-1 = 1.0×, Tier-2 = 1.5×, Lookback = 20, Min prior = 10.
Optional: enable Paint bar and set Arrow size = large for monitor-wall visibility.
Optional: show RVOL label below the bar to keep wicks clean.
Interpretation:
Dark green = A+ opening thrust with strong participation (≥ Tier-2).
Light green = Valid opening thrust with at least average participation (≥ Tier-1).
No highlight = one or more filters failed (quantiles, body, green, range, or RVOL if required).
Alerts
Two alert conditions are included:
Opening 5m Match — Tier-2 RVOL → fires when the opening candle passes price filters and RVOL ≥ Tier-2.
Opening 5m Match — Tier-1 RVOL → fires when the opening candle passes price filters and RVOL ≥ Tier-1 (but < Tier-2).
Recommended alert settings
Condition: choose the script + desired tier.
Options: Once Per Bar Close (you want the confirmed 09:30–09:35 bar).
Set your watchlist to symbols of interest (themes/sectors) and let the alerts pull you to the right charts.
Recommended starting values
Quantiles: Open ≤ 0.20, Close ≥ 0.80
Body fraction: 0.55
Require green: ON
RVOL: Required ON, Tier-1 = 1.0×, Tier-2 = 1.5×, Lookback 20, Min prior 10
Display: Paint bar ON, Arrow large, Label ON, Below candle
Tune tighter for A-plus selectivity:
Open ≤ 0.15, Close ≥ 0.85, Body ≥ 0.65, Tier-2 2.0×.
Notes, tips & limitations
5-minute timeframe is the intended use. On higher TFs, the 09:30 bar spans more than 5 minutes; geometry may not reflect the first 5 minutes alone.
RTH only: The opening detection looks at the clock (09:30 ET). Pre-market bars are ignored for the signal and for RVOL history.
Warm-up period: Until you have Min prior opens required samples, the RVOL gate won’t pass. You can temporarily toggle RVOL off.
DST & timezone: Leave timezone on America/New_York for US equities. If you trade non-US exchanges, set the appropriate TZ and opening time.
Illiquid tickers: Use Minimum range (ticks) and require RVOL to reduce noise.
No strategy orders: This is a visual/alert tool. Combine with your execution and risk plan.
Why this is useful on multi-monitor setups
Instant pattern recognition: the two-shade green makes A vs A+ opens pop at a glance.
Adaptive thresholds: quantiles & body are within-bar, so it works across $5 and $500 names.
Fair volume test: TRUE opening RVOL avoids comparing to pre-market or midday bars.
Optional labels: glanceable RVOL x-value helps triage the strongest themes quickly.
Dynamic Swing Anchored VWAP STRAT (Zeiierman/PineIndicators)Dynamic Swing Anchored VWAP STRATEGY — Zeiierman × PineIndicators (Pine Script v6)
A pivot-to-pivot Anchored VWAP strategy that adapts to volatility, enters long on bullish structure, and closes on bearish structure. Built for TradingView in Pine Script v6.
Full credits to zeiierman.
Repainting notice: The original indicator logic is repainting. Swing labels (HH/HL/LH/LL) are finalized after enough bars have printed, so labels do not occur in real time. It is not possible to execute at historical label points. Treat results as educational and validate with Bar Replay and paper trading before considering any discretionary use.
Concept
The script identifies swing highs/lows over a user-defined lookback ( Swing Period ). When structure flips (most recent swing low is newer than the most recent swing high, or vice versa), a new regime begins.
At each confirmed pivot, a fresh Anchored VWAP segment is started and updated bar-by-bar using an EWMA-style decay on price×volume and volume.
Responsiveness is controlled by Adaptive Price Tracking (APT) . Optionally, APT auto-adjusts with an ATR ratio so that high volatility accelerates responsiveness and low volatility smooths it.
Longs are opened/held in bullish regimes and closed when the regime turns bearish. No short positions are taken by design.
How it works (under the hood)
Swing detection: Uses ta.highestbars / ta.lowestbars over prd to update swing highs (ph) and lows (pl), plus their bar indices (phL, plL).
Regime logic: If phL > plL → bullish regime; else → bearish regime. A change in this condition triggers a re-anchor of the VWAP at the newest pivot.
Adaptive VWAP math: APT is converted to an exponential decay factor ( alphaFromAPT ), then applied to running sums of price×volume and volume, producing the current VWAP estimate.
Rendering: Each pivot-anchored VWAP segment is drawn as a polyline and color-coded by regime. Optional structure labels (HH/HL/LH/LL) annotate the swing character.
Orders: On bullish flips, strategy.entry("L") opens/maintains a long; on bearish flips, strategy.close("L") exits.
Inputs & controls
Swing Period (prd) — Higher values identify larger, slower swings; lower values catch more frequent pivots but add noise.
Adaptive Price Tracking (APT) — Governs the VWAP’s “half-life.” Smaller APT → faster/closer to price; larger APT → smoother/stabler.
Adapt APT by ATR ratio — When enabled, APT scales with volatility so the VWAP speeds up in turbulent markets and slows down in quiet markets.
Volatility Bias — Tunes the strength of APT’s response to volatility (above 1 = stronger effect; below 1 = milder).
Style settings — Colors for swing labels and VWAP segments, plus line width for visibility.
Trade logic summary
Entry: Long when the swing structure turns bullish (latest swing low is more recent than the last swing high).
Exit: Close the long when structure turns bearish.
Position size: qty = strategy.equity / close × 5 (dynamic sizing; scales with account equity and instrument price). Consider reducing the multiplier for a more conservative profile.
Recommended workflow
Apply to instruments with reliable volume (equities, futures, crypto; FX tick volume can work but varies by broker).
Start on your preferred timeframe. Intraday often benefits from smaller APT (more reactive); higher timeframes may prefer larger APT (smoother).
Begin with defaults ( prd=50, APT=20 ); then toggle “Adapt by ATR” and vary Volatility Bias to observe how segments tighten/loosen.
Use Bar Replay to watch how pivots confirm and how the strategy re-anchors VWAP at those confirmations.
Layer your own risk rules (stops/targets, max position cap, session filters) before any discretionary use.
Practical tips
Context filter: Consider combining with a higher-timeframe bias (e.g., daily trend) and using this strategy as an entry timing layer.
First pivot preference: Some traders prefer only the first bullish pivot after a bearish regime (and vice versa) to reduce whipsaw in choppy ranges.
Deviations: You can add VWAP deviation bands to pre-plan partial exits or re-entries on mean-reversion pulls.
Sessions: Session-based filters (RTH vs. ETH) can materially change behavior on futures and equities.
Extending the script (ideas)
Add stops/targets (e.g., ATR stop below last swing low; partial profits at k×VWAP deviation).
Introduce mirrored short logic for two-sided testing.
Include alert conditions for regime flips or for price-VWAP interactions.
Incorporate HTF confirmation (e.g., only long when daily VWAP slope ≥ 0).
Throttle entries (e.g., once per regime flip) to avoid over-trading in ranges.
Known limitations
Repainting: Swing labels and pivot confirmations depend on future bars; historical labels can look “perfect.” Treat them as annotations, not executable signals.
Execution realism: Strategy includes commission and slippage fields, yet actual fills differ by venue/liquidity.
No guarantees: Past behavior does not imply future results. This publication is for research/education only and not financial advice.
Defaults (backtest environment)
Initial capital: 10,000
Commission value: 0.01
Slippage: 1
Overlay: true
Max bars back: 5000; Max labels/polylines set for deep swing histories
Quick checklist
Add to chart and verify that the instrument has volume.
Use defaults, then tune APT and Volatility Bias with/without ATR adaptation.
Observe how each pivot re-anchors VWAP and how regime flips drive entries/exits.
Paper trade across several symbols/timeframes before any discretionary decisions.
Attribution & license
Original indicator concept and logic: Zeiierman — please credit the author.
Strategy wrapper and publication: PineIndicators .
License: CC BY-NC-SA 4.0 (Attribution-NonCommercial-ShareAlike). Respect the license when forking or publishing derivatives.
PumpC PAC & MAsPumpC – PAC & MAs (Open Source)
A complete Price Action Candles (PAC) toolkit combining classical price action patterns (Fair Value Gaps, Inside Bars, Hammers, Inverted Hammers, and Volume Imbalances) with a flexible Moving Averages (MAs) module and an advanced bar-coloring system.
This script highlights supply/demand inefficiencies and micro-patterns with forward-extending boxes, recolors zones when mitigated, qualifies patterns with a global High-Volume filter, and ships with ready-to-use alerts. It works across intraday through swing trading on any market (e.g., NASDAQ:QQQ , $CME:ES1!, FX:EURUSD , BITSTAMP:BTCUSD ).
This is an open-source script. The description is detailed so users understand what the script does, how it works, and how to use it. It makes no performance claims and does not provide trade advice.
Acknowledgment & Credits
This script originates from the structural and box-handling logic found in the Super OrderBlock / FVG / BoS Tools by makuchaku & eFe. Their pioneering framework provided the base methods for managing arrays of boxes, extending zones forward, and recoloring once mitigated.
Building on that foundation, I have substantially expanded and adapted the code to create a unified Price Action Candles toolkit . This includes Al Brooks–inspired PAC logic, additional patterns like Inside Bars, Hammers, Inverted Hammers, and the new Volume Imbalance module, along with strong-bar coloring, close-threshold detection, a flexible global High-Volume filter, and a multi-timeframe Moving Averages system.
What it does
Fair Value Gaps (FVG) : Detects 3-bar displacement gaps, plots forward-extending boxes, and optionally recolors them once mitigated.
Inside Bars (IB) : Highlights bars fully contained within the prior candle’s range, with optional high-volume filter.
Hammers (H) & Inverted Hammers (IH) : Identifies rejection candles using configurable body/upper/lower wick thresholds. High-volume qualification optional.
Volume Imbalances (VI) : Detects inter-body gaps where one candle’s body does not overlap the prior candle’s body. Boxes extend forward until wick-based mitigation occurs (only after the two-bar formation completes). Alerts available for creation and mitigation.
Mitigation Recolor : Each pattern can flip to a mitigated color once price trades back through its vertical zone.
Moving Averages (MAs) : Four configurable EMAs/SMAs, with per-MA timeframe, length, color, and clutter-free plotting rules.
Strong Bar Coloring : Highlights bullish/bearish engulfing reversals with different colors for high-volume vs low-volume cases.
Close Threshold Bars : Marks candles that close in the top or bottom portion of their range, even if the body is small. Helps spot continuation pressure before a full trend bar forms.
Alerts : Notifications available for FVG+, FVG−, IB, H, IH, VI creation, and VI mitigation.
Connection to Al Brooks’ PAC teachings
This script reflects Al Brooks’ Price Action Candle methodology. PAC patterns like Inside Bars, Hammers, and Inverted Hammers are not trade signals on their own—they gain meaning in context of trend, failed breakouts, and effort vs. result.
By layering in volume imbalances, strong-bar reversals, and volume filters, this script focuses attention on the PACs that show true participation and conviction, aligning with Brooks’ emphasis on reading crowd psychology through price action.
Why the High-Volume filter matters
Volume is a key proxy for conviction. A PAC or VI formed on light volume can be misleading noise; one formed on above-average volume carries more weight.
Elevates Inside Bars that show absorption/compression with heavy activity.
Distinguishes Hammers that reject price aggressively vs. weak drifts.
Filters Inverted Hammers to emphasize true supply pressure.
Highlights VI zones where institutional order flow left inefficiencies.
Differentiates strong engulfing reversals from weaker, low-participation moves.
Inputs & Customization
Inputs are grouped logically for fast configuration:
High-Volume Filter : Global lookback & multiple, per-pattern toggles.
FVG : Visibility, mitigated recolor, box style/transparency, label controls.
IB : Visibility, require high volume, mitigated recolor, colors, label settings.
Hammer / IH : Visibility, require high volume, mitigated recolor, wick/body thresholds.
VI : Visibility, require high volume, mitigated recolor, box style, labels, mitigation alerts.
Strong Bars : Enable/disable, separate colors for high-volume and low-volume outcomes.
Close Threshold Bars : Customizable close thresholds, labels, optional count markers.
MAs : EMA/SMA type, per-MA toggle, length, timeframe, color.
Alerts
New Bullish FVG (+)
New Bearish FVG (−)
New Inside Bar (IB)
New Hammer (H)
New Inverted Hammer (IH)
New Volume Imbalance (VI)
VI Mitigated
Strong Bullish Engulfing / Bearish Engulfing (high- and low-volume variants)
Suggested workflow
Choose your market & timeframe (script works across equities, futures, FX, crypto).
Toggle only the PACs you actually trade. Assign distinct colors for clarity.
Use MAs for directional bias and higher timeframe structure.
Enable High-Volume filters when you want to emphasize conviction.
Watch mitigation recolors to see which levels/zones have been interacted with.
Use alerts selectively for setups aligned with your plan.
Originality
Builds upon Super OrderBlock / FVG / BoS Tools (makuchaku & eFe) for FVG/box framework.
Expanded into a unified PAC toolkit including IB, H, IH, and VI patterns.
Brooks-inspired design: Patterns contextualized with volume and trend, not isolated.
Flexible high-volume gating with per-pattern toggles.
New VI integration with wick-based mitigation.
Strong Bar Coloring differentiates conviction vs weak reversals.
MTF-aware MAs prevent clutter while providing structure.
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Disclaimer
For educational and informational purposes only. This script is not financial advice. Trading carries risk—always test thoroughly before live use.
Prime NumbersPrime Numbers highlights prime numbers (no surprise there 😅), tokens and the recent "active" feature in "input".
🔸 CONCEPTS
🔹 What are Prime Numbers?
A prime number (or a prime) is a natural number greater than 1 that is not a product of two smaller natural numbers.
Wikipedia: Prime number
🔹 Prime Factorization
The fundamental theorem of arithmetic states that every integer larger than 1 can be written as a product of one or more primes. More strongly, this product is unique in the sense that any two prime factorizations of the same number will have the same number of copies of the same primes, although their ordering may differ. So, although there are many different ways of finding a factorization using an integer factorization algorithm, they all must produce the same result. Primes can thus be considered the "basic building blocks" of the natural numbers.
Wikipedia: Fundamental theorem of arithmetic
Math Is Fun: Prime Factorization
We divide a given number by Prime Numbers until only Primes remain.
Example:
24 / 2 = 12 | 24 / 3 = 8
12 / 3 = 4 | 8 / 2 = 4
4 / 2 = 2 | 4 / 2 = 2
|
24 = 2 x 3 x 2 | 24 = 3 x 2 x 2
or | or
24 = 2² x 3 | 24 = 2² x 3
In other words, every natural/integer number above 1 has a unique representation as a product of prime numbers, no matter how the number is divided. Only the order can change, but the factors (the basic elements) are always the same.
🔸 USAGE
The Prime Numbers publication contains two use cases:
Prime Factorization: performed on "close" prices, or a manual chosen number.
List Prime Numbers: shows a list of Prime Numbers.
The other two options are discussed in the DETAILS chapter:
Prime Factorization Without Arrays
Find Prime Numbers
🔹 Prime Factorization
Users can choose to perform Prime Factorization on close prices or a manually given number.
❗️ Note that this option only applies to close prices above 1, which are also rounded since Prime Factorization can only be performed on natural (integer) numbers above 1.
In the image below, the left example shows Prime Factorization performed on each close price for the latest 50 bars (which is set with "Run script only on 'Last x Bars'" -> 50).
The right example shows Prime Factorization performed on a manually given number, in this case "1,340,011". This is done only on the last bar.
When the "Source" option "close price" is chosen, one can toggle "Also current price", where both the historical and the latest current price are factored. If disabled, only historical prices are factored.
Note that, depending on the chosen options, only applicable settings are available, due to a recent feature, namely the parameter "active" in settings.
Setting the "Source" option to "Manual - Limited" will factorize any given number between 1 and 1,340,011, the latter being the highest value in the available arrays with primes.
Setting to "Manual - Not Limited" enables the user to enter a higher number. If all factors of the manual entered number are in the 1 - 1,340,011 range, these factors will be shown; however, if a factor is higher than 1,340,011, the calculation will stop, after which a warning is shown:
The calculated factors are displayed as a label where identical factors are simplified with an exponent notation in superscript.
For example 2 x 2 x 2 x 5 x 7 x 7 will be noted as 2³ x 5 x 7²
🔹 List Prime Numbers
The "List Prime Numbers" option enables users to enter a number, where the first found Prime Number is shown, together with the next x Prime Numbers ("Amount", max. 200)
The highest shown Prime Number is 1,340,011.
One can set the number of shown columns to customize the displayed numbers ("Max. columns", max. 20).
🔸 DETAILS
The Prime Numbers publication consists out of 4 parts:
Prime Factorization Without Arrays
Prime Factorization
List Prime Numbers
Find Prime Numbers
The usage of "Prime Factorization" and "List Prime Numbers" is explained above.
🔹 Prime Factorization Without Arrays
This option is only there to highlight a hurdle while performing Prime Factorization.
The basic method of Prime Factorization is to divide the base number by 2, 3, ... until the result is an integer number. Continue until the remaining number and its factors are all primes.
The division should be done by primes, but then you need to know which one is a prime.
In practice, one performs a loop from 2 to the base number.
Example:
Base_number = input.int(24)
arr = array.new()
n = Base_number
go = true
while go
for i = 2 to n
if n % i == 0
if n / i == 1
go := false
arr.push(i)
label.new(bar_index, high, str.tostring(arr))
else
arr.push(i)
n /= i
break
Small numbers won't cause issues, but when performing the calculations on, for example, 124,001 and a timeframe of, for example, 1 hour, the script will struggle and finally give a runtime error.
How to solve this?
If we use an array with only primes, we need fewer calculations since if we divide by a non-prime number, we have to divide further until all factors are primes.
I've filled arrays with prime numbers and made libraries of them. (see chapter "Find Prime Numbers" to know how these primes were found).
🔹 Tokens
A hurdle was to fill the libraries with as many prime numbers as possible.
Initially, the maximum token limit of a library was 80K.
Very recently, that limit was lifted to 100K. Kudos to the TradingView developers!
What are tokens?
Tokens are the smallest elements of a program that are meaningful to the compiler. They are also known as the fundamental building blocks of the program.
I have included a code block below the publication code (// - - - Educational (2) - - - ) which, if copied and made to a library, will contain exactly 100K tokens.
Adding more exported functions will throw a "too many tokens" error when saving the library. Subtracting 100K from the shown amount of tokens gives you the amount of used tokens for that particular function.
In that way, one can experiment with the impact of each code addition in terms of tokens.
For example adding the following code in the library:
export a() => a = array.from(1) will result in a 100,041 tokens error, in other words (100,041 - 100,000) that functions contains 41 tokens.
Some more examples, some are straightforward, others are not )
// adding these lines in one of the arrays results in x tokens
, 1 // 2 tokens
, 111, 111, 111 // 12 tokens
, 1111 // 5 tokens
, 111111111 // 10 tokens
, 1111111111111111111 // 20 tokens
, 1234567890123456789 // 20 tokens
, 1111111111111111111 + 1 // 20 tokens
, 1111111111111111111 + 8 // 20 tokens
, 1111111111111111111 + 9 // 20 tokens
, 1111111111111111111 * 1 // 20 tokens
, 1111111111111111111 * 9 // 21 tokens
, 9999999999999999999 // 21 tokens
, 1111111111111111111 * 10 // 21 tokens
, 11111111111111111110 // 21 tokens
//adding these functions to the library results in x tokens
export f() => 1 // 4 tokens
export f() => v = 1 // 4 tokens
export f() => var v = 1 // 4 tokens
export f() => var v = 1, v // 4 tokens
//adding these functions to the library results in x tokens
export a() => const arraya = array.from(1) // 42 tokens
export a() => arraya = array.from(1) // 42 tokens
export a() => a = array.from(1) // 41 tokens
export a() => array.from(1) // 32 tokens
export a() => a = array.new() // 44 tokens
export a() => a = array.new(), a.push(1) // 56 tokens
What if we could lower the amount of tokens, so we can export more Prime Numbers?
Look at this example:
829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193
Eight numbers contain the same number 8291.
If we make a function that removes recurrent values, we get fewer tokens!
829111, 829121, 829123, 829151, 829159, 829177, 829187, 829193
//is transformed to:
829111, 21, 23, 51, 59, 77, 87, 93
The code block below the publication code (// - - - Educational (1) - - - ) shows how these values were reduced. With each step of 100, only the first Prime Number is shown fully.
This function could be enhanced even more to reduce recurrent thousands, tens of thousands, etc.
Using this technique enables us to export more Prime Numbers. The number of necessary libraries was reduced to half or less.
The reduced Prime Numbers are restored using the restoreValues() function, found in the library fikira/Primes_4.
🔹 Find Prime Numbers
This function is merely added to show how I filled arrays with Prime Numbers, which were, in turn, added to libraries (after reduction of recurrent values).
To know whether a number is a Prime Number, we divide the given number by values of the Primes array (Primes 2 -> max. 1,340,011). Once the division results in an integer, where the divisor is smaller than the dividend, the calculation stops since the given number is not a Prime.
When we perform these calculations in a loop, we can check whether a series of numbers is a Prime or not. Each time a number is proven not to be a Prime, the loop starts again with a higher number. Once all Primes of the array are used without the result being an integer, we have found a new Prime Number, which is added to the array.
Doing such calculations on one bar will result in a runtime error.
To solve this, the findPrimeNumbers() function remembers the index of the array. Once a limit has been reached on 1 bar (for example, the number of iterations), calculations will stop on that bar and restart on the next bar.
This spreads the workload over several bars, making it possible to continue these calculations without a runtime error.
The result is placed in log.info() , which can be copied and pasted into a hardcoded array of Prime Number values.
These settings adjust the amount of workload per bar:
Max Size: maximum size of Primes array.
Max Bars Runtime: maximum amount of bars where the function is called.
Max Numbers To Process Per Bar: maximum numbers to check on each bar, whether they are Prime Numbers.
Max Iterations Per Bar: maximum loop calculations per bar.
🔹 The End
❗️ The code and description is written without the help of an LLM, I've only used Grammarly to improve my description (without AI :) )
