Return Line Uptrends [theEccentricTrader]█ OVERVIEW
This indicator simply plots multi-part return line uptrends and should be used in conjunction with my Downtrends, Uptrends and Return Line Downtrends indicators as a visual aid to my Trend Counter indicator.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Muti-Part Upper and Lower Trends
• A multi-part return line uptrend begins with the formation of a new return line uptrend, or higher peak, and continues until a new downtrend, or lower peak, completes the trend.
• A multi-part downtrend begins with the formation of a new downtrend, or lower peak, and continues until a new return line uptrend, or higher peak, completes the trend.
• A multi-part uptrend begins with the formation of a new uptrend, or higher trough, and continues until a new return line downtrend, or lower trough, completes the trend.
• A multi-part return line downtrend begins with the formation of a new return line downtrend, or lower trough, and continues until a new uptrend, or higher trough, completes the trend.
█ FEATURES
Plots
Green up-arrows, with the number of the trend part, denote return line uptrends.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
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Trend Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed trend scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Muti-Part Upper and Lower Trends
• A multi-part return line uptrend begins with the formation of a new return line uptrend, or higher peak, and continues until a new downtrend, or lower peak, completes the trend.
• A multi-part downtrend begins with the formation of a new downtrend, or lower peak, and continues until a new return line uptrend, or higher peak, completes the trend.
• A multi-part uptrend begins with the formation of a new uptrend, or higher trough, and continues until a new return line downtrend, or lower trough, completes the trend.
• A multi-part return line downtrend begins with the formation of a new return line downtrend, or lower trough, and continues until a new uptrend, or higher trough, completes the trend.
█ FEATURES
Inputs
Start Date
End Date
Position
Text Size
Show Sample Period
Table
The table is colour coded, consists of seven columns and, as many as, forty-one rows. Blue cells denote the multi-part trend scenarios, green cells denote the corresponding return line uptrend and uptrend scenarios and red cells denote the corresponding downtrend and return line downtrend scenarios.
The trend scenarios are listed in the first column with their corresponding total counts to the right, in the second and fifth columns. The last row in column one, displays the sample period which can be adjusted or hidden via indicator settings.
The third and sixth columns display the trend scenarios as percentage of total 1-part trends. And columns four and seven display the total trend scenarios as percentages of the, last, or preceding trend part. For example 4-part trends as a percentages of 3-part trends. This offers more insight into what might happen next at any given point in time.
Plots
For a visual aid to this indicator please use in conjunction with my Return Line Uptrends, Downtrends, Uptrends and Return Line Downtrends indicators which can all be found on my profile page under scripts, or in community scripts under the same names. Unfortunately, I could not fit all the plots with the correct offsets into one script so I had to make a separate indicator for each trend type. I decided against labels as this would limit the visual data points to 500.
Green up-arrows, with the number of the trend part, denote return line uptrends and uptrends. Red down-arrows, with the number of the trend part, denote downtrends and return line downtrends.
█ HOW TO USE
This is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe.
It can, for example, give you an idea of whether the current trend will continue or fail, based on the current trend scenario and what has happened in the past under similar circumstances. Such information can be very useful when conducting top down analysis across multiple timeframes and making strategic decisions.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Flat Market and Low ADX Indicator [CHE]Why use the Flat Market and Low ADX Indicator ?
Flat markets, where prices remain within a narrow range for an extended period, can be both critical and dangerous for traders. In a flat market, the price action becomes less predictable, and traders may struggle to find profitable trading opportunities. As a result, many traders may decide to take a break from the market until a clear trend emerges.
However, flat markets can also be dangerous for traders who continue to trade despite the lack of clear trends. In the absence of a clear direction, traders may be tempted to take larger risks or make impulsive trades in an attempt to capture small profits. Such behavior can quickly lead to significant losses, especially if the market suddenly breaks out of its flat range, causing traders to experience large drawdowns.
Therefore, it is essential to approach flat markets with caution and to have a clear trading plan that incorporates strategies for both trending and flat markets. Traders may also use technical indicators, such as the Flat Market and Low ADX Indicator, to help identify flat markets and determine when it is appropriate to enter or exit a position.
The confluence between flat markets and low ADX readings can further increase the risk of trading during these periods. The ADX (Average Directional Index) is a technical indicator used to measure the strength of a trend. A low ADX reading indicates that the market is in a consolidation phase, which can coincide with a flat market. When a flat market occurs during a period of low ADX, traders should be even more cautious, as there is little to no directional bias in the market. In this situation, traders may want to consider waiting for a clear trend to emerge or using range-bound trading strategies to avoid taking excessive risks.
Introduction:
Pine Script is a programming language used for developing custom technical analysis indicators and trading strategies in TradingView. This particular script is an indicator designed to identify flat markets and low ADX conditions. In this description, we will delve deeper into the functionality of this script and how it can be used to improve trading decisions.
Description:
The first input in the script is the length of the moving average used for calculating the center line. This moving average is used to define the high and low range of the market. The script then calculates the middle value of the range by taking the double exponential moving average (EMA) of the high, low, and close prices.
The script then determines whether the market is flat by comparing the middle value of the range with the high and low values. If the middle value is greater than the high value or less than the low value, the market is not flat. If the middle value is within the high and low range, the script considers the market to be flat. The script also uses RSI filter settings to further confirm if the market is flat or not. If the RSI value is between the RSI min and max values, then the market is considered flat. If the RSI value is outside this range, the market is not considered flat.
The script also calculates the ADX (Average Directional Index) to determine whether it's in a low area. ADX is a technical indicator used to measure the strength of a trend. The script uses the ADX filter settings to define the ADX threshold value. If the ADX value is below the threshold value, the script considers the market to be in a low ADX area.
The script provides various input options to customize the display settings, including the option to show the flat market and low ADX areas. Users can choose their preferred colors for the flat market and low ADX areas and adjust the transparency levels to suit their needs.
Conclusion:
In conclusion, this Pine Script indicator is designed to identify flat market and low ADX conditions, which can help traders make informed trading decisions. The script uses a range of inputs and calculations to determine the market direction, RSI filter, and ADX filter. By customizing the display settings, users can adjust the indicator to suit their preferences and improve their trading strategies. Overall, this script can be a valuable tool for traders looking to gain an edge in the markets.
Acknowledgments:
Thanks to the Pine Script™ v5 User Manual www.tradingview.com
Triangulation : Statistically Approved ReversalsA lot of calculation, but a simple and effective result displayed on the chart.
It automatically identifies a very favorable period for a price reversal, by analyzing the daily and intraday price action statistics from the maximum of the most recent bars from the historical data. No repainting. Alerts can be set.
The statistical study is done in real time for each instrument. The probabilities therefore vary over time and adapt to the latest information collected by the indicator.
The time range of the data study can be changed by simply changing the UT :
- 30m = 3.5 last months feed statistics
- 15m = 52 last days feed statistics
- 5m = 17 last days feed statistics (recommanded)
HOW TO USE
This indicator informs when we are in a time period strongly favorable to reversal.
==> Crossing probabilities of different kinds, in price and in time => Triangulation of top and bottom !
HOW It WORK :
fractal statistics on high and low formation.
hour's probabilities of making the high/low of the day are crossed with day's probabilities of making the high/low of the week.
First for the day, we study:
- value of the probability compared to the average probabilities
- value of the coefficient between the high probability and the low probability
which we then refine for the hour, with the same calculation.
Result: bright color for a day + hour with high probability, weak color if the probability is low but remains the only possible bias. Between these two possibilities, intermediate colors are possible - just like looking for shorts if the day is bullish, if it is a high probability hour!
This color is displayed in the background, only if we are forming the high of the day for tops, and the low of the day for bottoms - detected with a stochastic.
All probabilities are studied in real time for the current asset.
We will call this signal "killstats", for "killzones statistics"
fractal statistics on the probability of closure under specific predefined levels according to 36 cycles.
the probabilities of several cycles are studied, for example:
NY session versus London and Asian sessions, London session compared to its opening, NY session compared to its opening, "algorithmic cycles" ( 1h30), Opening of NY compared to its intersection with London..
Each cycle producing a probability of closing with respect to the opening price of each period. The periods are : (Etc/UTC)
15-18h / 15-16h / 9-13h / 14-17h / 18-22h / 10-12h / 9-10h30 / 10h30-12h / 12-13h30 / 13h30-15h / 15h-16h30 / 16h30-18h
The cycles can be superimposed, which allows to support or attenuate a signal for the key periods of the day: 9am-12pm, and 3pm-6pm. The period of the day covered by the study of cycles is 9h-22h.
Result : ==> a straight line with a half bell. Colors = almost transparent for 53% probability (low), and very intense for a high probability (75%). The line displayed corresponds to the opening price, which we are supposed to close within the time limit - before the end of the period, where the line stops.
If the price goes in the opposite direction to the one predicted by the statistics, then a background connects the price to the close level to be respected.
if direction and close is respected, nothing is displayed : there is no opportunity, no divergence between statistics and actual price moves.
By unchecking the "light mode", you can see each close level displayed on the chart, with the corresponding probability and the number of times the cycle was detected. The color varies from intense for a high probability (75%), to light for a low probability (53%)
We will call this signal "cyclic anomalies"
By default, as shown in the indicator presentation image, the "intersection only" option is checked: only the intersection between 1) killstats and 2) cyclic anomalies is displayed. (filter +-30% of killstats signals)
MORE INFORMATIONS
/!\ : during a backtest, it is necessary to refresh the studied data to benefit from the real time signals, and for that you have to use the replay mode. if "Backtesting informations?"is checked, labels are displayed on the graph to warn of the % distortion of the signals. I recommend using the replay mode every 250 candles, and every 1000 candles for premium accounts, to have real signals.
- Alerts can be set for killzone, or intersections ( As in presentation picture)
- The ideal use is in m5. It can trigger several times a day, sometimes in opposite directions, and sometimes not trigger for several days.
- Premium account have 20k candles data, and not 5k => signals may vary depending on your tradingview subscription.
GKD-B Baseline [Loxx]Giga Kaleidoscope Baseline is a Baseline module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is an NNFX algorithmic trading strategy?
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend (such as "Baseline" shown on the chart above)
3. Confirmation 1 - a technical indicator used to identify trend. This should agree with the "Baseline"
4. Confirmation 2 - a technical indicator used to identify trend. This filters/verifies the trend identified by "Baseline" and "Confirmation 1"
5. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown.
6. Exit - a technical indicator used to determine when trend is exhausted.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 module (Confirmation 1/2, Numbers 3 and 4 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 5 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 6 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average as shown on the chart above
Volatility/Volume: Jurik Volty
Confirmation 1: Vortex
Confirmation 2: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Now that you have a general understanding of the NNFX algorithm and the GKD trading system. let's go over what's inside the GKD-B Baseline itself.
GKD Baseline Special Features and Notable Inputs
GKD Baseline v1.0 includes 63 different moving averages:
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Ehlers Optimal Tracking Filter - EOTF
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Instantaneous Trendline
Kalman Filter
Kaufman Adaptive Moving Average - KAMA
Laguerre Filter
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
Description. The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Ehlers Optimal Tracking Filter - EOTF
The Elher's Optimum Tracking Filter quickly adjusts rapid shifts in the price and yet is relatively smooth when the price has a sideways action. The operation of this filter is similar to Kaufman’s Adaptive Moving
Average
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
T3 is basically an EMA on steroids, You can read about T3 here:
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Instantaneous Trendline
The Instantaneous Trendline is created by removing the dominant cycle component from the price information which makes this Moving Average suitable for medium to long-term trading.
Kalman Filter
Kalman filter is an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies. This means that the filter was originally designed to work with noisy data. Also, it is able to work with incomplete data. Another advantage is that it is designed for and applied in dynamic systems; our price chart belongs to such systems. This version is true to the original design of the trade-ready Kalman Filter where velocity is the triggering mechanism.
Kalman Filter is a more accurate smoothing/prediction algorithm than the moving average because it is adaptive: it accounts for estimation errors and tries to adjust its predictions from the information it learned in the previous stage. Theoretically, Kalman Filter consists of measurement and transition components.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Laguerre Filter
The Laguerre Filter is a smoothing filter which is based on Laguerre polynomials. The filter requires the current price, three prior prices, a user defined factor called Alpha to fill its calculation.
Adjusting the Alpha coefficient is used to increase or decrease its lag and its smoothness.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
Exotic Triggers
This version of Baseline allows the user to select from exotic or source triggers. An exotic trigger determines trend by either slope or some other mechanism that is special to each moving average. A source trigger is one of 32 different source types from Loxx's Exotic Source Types. You can read about these source types here:
Volatility Goldie Locks Zone
This volatility filter is the standard first pass filter that is used for all NNFX systems despite the additional volatility/volume filter used in step 5. For this filter, price must fall into a range of maximum and minimum values calculated using multiples of volatility. Unlike the standard NNFX systems, this version of volatility filtering is separated from the core Baseline and uses it's own moving average with Loxx's Exotic Source Types. The green and red dots at the top of the chart denote whether a candle qualifies for a either or long or short respectively. The green and red triangles at the bottom of the chart denote whether the trigger has crossed up or down and qualifies inside the Goldie Locks zone. White coloring of the Goldie Locks Zone mean line is where volatility is too low to trade.
Volatility Types Included
v1.0 Included Volatility
Close-to-Close
Close-to-Close volatility is a classic and most commonly used volatility measure, sometimes referred to as historical volatility .
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a bigger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility calculated using only stock's closing prices. It is the simplest volatility estimator. But in many cases, it is not precise enough. Stock prices could jump considerably during a trading session, and return to the open value at the end. That means that a big amount of price information is not taken into account by close-to-close volatility .
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. That is useful as close to close prices could show little difference while large price movements could have happened during the day. Thus Parkinson's volatility is considered to be more precise and requires less data for calculation than the close-close volatility .
One drawback of this estimator is that it doesn't take into account price movements after market close. Hence it systematically undervalues volatility . That drawback is taken into account in the Garman-Klass's volatility estimator.
Garman-Klass
Garman Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing price. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change is a process of continuous diffusion (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremums.
Researchers Rogers and Satchel have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates drift term (mean return not equal to zero). As a result, it provides a better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. It means an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
We can think of the Yang-Zhang volatility as the combination of the overnight (close-to-open volatility ) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility . It considered being 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator consists of using the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e. it assumes that the underlying asset follows a GBM process with zero drift. Therefore the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility . It's the standard deviation of ln(close/close(1))
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by θ.
θavg(var ;M) + (1 − θ) avg (var ;N) = 2θvar/(M+1-(M-1)L) + 2(1-θ)var/(M+1-(M-1)L)
Solving for θ can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg (var; N) against avg (var; M) - avg (var; N) and using the resulting beta estimate as θ.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Additional features will be added in future releases.
This indicator is only available to ALGX Trading VIP group members . You can see the Author's Instructions below to get more information on how to get access.
Scalping The Bull IndicatorName: Scalping The Bull Indicator
Category: Scalping, Trend Following, Mean Reversion.
Timeframe: 1M, 5M, 30M, 1D depending on the specific technique.
Technical Analysis: The indicator supports the operations of the trader named "Scalping The Bull" which uses price action and exponential moving averages.
Suggested usage: Altcoin showing strong trends for scalping and intra-day trades. Trigger points are used as entry and exit points and to be used to understand when a signal has more power.
It is possible to identify the following conformations:
Shimano: look at the price records of a consecutive series of closings between the EMA 60 and the EMA 223 when a certain threshold is reached. Use the trigger points as price structures to identify entry and exit zones (e.g. breakout of the yesterday high as for entry point) .
Bomb: look at the price registers a percentage variation in a single candle, greater than a threshold such as 2%, in particular on shorter timeframes and around the trigger points.
Viagra: look at there is a consecutive series of closes below the EMA 10.
Downward fake: look when, after a cross under (Death Cross), the price returns above the EMA 223 using the yesterday high as a trigger point.
Emergence: look at the EMA 60 is about to cross over the EMA 223.
Anti-crossing: look at, after an important price rise and a subsequent retracement, the EMA 60 is about to cross under the EMA 223 but a bullish impulse brings the price back above the EMAs.
For Sales: look at two types of situations: 1) when the price falls by more than 10% from the opening price and around the yesterday’s low or 2) when the price falls and then reaches, in the last 5 days, a bigger percentage and then breaks a trigger point.
Colour change: look at the opening price of the session - indicated as a trigger point.
Third touch of EMA 60: look for 3 touches below the EMA 60, and enter when there is a close above the EMA 60.
Third touch of EMA 223: look for 3 touches when there are 3 touches below the EMA 223, and enter when there is a close above the EMA 60.
Bud: look at price when it crosses upwards the average 10 and subsequently at least 2 "rest" candles are between the maximum and minimum of the breaking candle.
Fake on EMA 10: look for the open of a candle higher than the EMA 10, the minimum of the candle lower and the closing price returns above the EMA 10..
For Stop Loss and Profit Targets consider a proper R/R depending on Risk Management, using price structures such as the low of the entering candle and a quick Position Management moving quickly the Stop-Loss at Break-Even.
Configuration:
Market
EMA: The indicator automatically configure itself on market it knows (Binance, Piazza Affari and NASDAQ) otherwise it can be configured manually fo Crypto market (5/10/60/223) or Stock Market (5/10/50/200).
Additional Average: You can display an additional average, e.g. 20-period average.
Chart elements:
Session Separators: indicates the beginning of the current session (in blue)
Background: signals with the background in green an uptrend situation ( 60 > 223) and in red background a downtrend situation (60 < 223).
Trigger points:
Today's highs and lows: draw on the chart the opening price of the daily candle and the highs and lows of the day (high in purple, low in red and open in green)
Yesterday's highs and lows: draw on the chart the opening price of the daily candle, the highs and lows of the previous day (high in yellow, low in red).
Credits
Massimo : for refactoring and suggestions.
AG FX - Pivot PointsPivot Points High Low
Definition
The Pivot Points High Low indicator is used to determine and anticipate potential changes in market price and reversals. The Highs referred to in the title are created based on the number of bars that exhibit lower highs on either side of a Pivot Point High, whereas the Lows are created based on the number of bars that exhibit higher lows on either side of a Pivot Point Low.
Calculations
As mentioned above, Pivot Point Highs are calculated by the number of bars with lower highs on either side of a Pivot Point High calculation. Similarly, Pivot Point Lows are calculated by the number of bars with higher lows on either side of a Pivot Point Low calculation.
Takeaways and what to look for
A Pivot Point is more significant or noteworthy if the trend is extended or longer than average. This can mean if a trader selects a higher period for before and after the Pivot Point, the trend could be longer and therefore prove the Pivot Point itself more notable.
Additionally, Pivot Points can help a trader assess where would be best to draw. By analyzing price changes and reversals, a trader has more of an ability to determine and predict price patterns and general price trends.
Summary
The Pivot Points High Low indicator can predict and determine price changes and potential reversals in the market. Pivot Points can also help traders identify price patterns and trends, depending on the period and significance of the Pivot Point value.
Fibonacci-Trading-Indikator_3Daily (weekly, monthly) profits with the Fibonacci trading indicator_3
Quotes move in Fibonacci ratios in liquid markets. With this indicator you receive information for daily trades or for position trades based on a week or on a monthly basis, in which area you should ideally enter the market and where the minimum achievable price target is. This price target is 61.8% of yesterday's trading range, or the trading range of the previous week, or the trading range of the previous month, depending on the time frame for which the indicator should calculate the minimum achievable high / low. This is also where you realize your profit.
For this calculation, the following entries must be made in the properties window of the indicator:
• Preselection uptrend / downtrend.
• Time frame (day, week, ...) of the price bar for the possible high / low to be determined.
• Trading range of the previous day, or the previous week, or the previous month.
• Current lowest low of the selected time frame when trading has started and prices are rising.
• Current highest high of the selected time frame when trading has started and prices are falling.
Important areas for trading are:
• The entry range 0% - 23.6% for long or short.
• The target price level 61.8%.
Choose a suitable time frame to detect the direction of movement while the quotes are still moving in the entry area. The camelback indicator can be of great help. Also test the resolution setting of the camelback indicator. With a resolution of 1 hour in the 6 or 12 minute chart, you get a perspective for the broader direction. Movement patterns of corrections or consolidations, if they last more than a day or a week, also give clues to the coming direction of movement for the trade. So look back to see what happened yesterday, a week ago, or a month ago. Pay attention to the market anatomy, find out how the market works, count the price bars in consolidations and trends.
After entering the values the indicator will show the Fibonacci expansion price levels for the possible high or low for the selected time frame. Buy / sell within the entry range between 0% and 23.6% as the market moves towards the last long / or short entry point. This is the course range up to the 23.6% course level. The 61.8% price level is the minimum expected price target. We assume that the current bar will reach at least 61.8% of the trading range of the previous day, week or month. Depending on the set time frame. You should therefore realize the profits you have made with 50% of the position when the prices have reached the 61.8% level. With a suitable trailing stop you can be stopped with the rest of the position, but do not risk more than 50% of the profits.
With the quarter or year preselection and the corresponding entries, the minimum expected quarterly high / quarterly low or annual high / annual low can be determined.
The Fibonacci price levels can be shown and hidden. In the chart click on the gear wheel for “Chart Settings”. In the “Scaling” menu, the price levels can be displayed with the preselection “Label for indicator names” and “Label for last indicator value”. Slide the chart to the right to find possible support and resistance at the price levels that could provide confirmation of the target.
In the event of input errors or missing entries for a time frame, the indicator is hidden.
Pay attention to your trade management to avoid losses.
The new Fibonacci Trading Indicator_3 has the following additions and changes:
Area code for the quarter time frame has been added.
The entry area received a 23.6% and a 50% subdivision. Two envelope lines above the 23.6% entry level in the case of an upward trend and below the 23.6% entry level in the case of a downtrend, with a width of 23.6% and 14.6% of the entry level, are intended to indicate that the closing price is higher the quotations have broken out of the entry-level area.
A volatility stop for upward and downward trends can be activated.
A factor is added to the fluctuation range of each price bar for the stop. Then a moving average is calculated with an adjustable period. The period setting should be set between 5 and 10. The result can be smoothed adjustable.
Presetting:
Periods = 10
Factor = 1.4
Smoothing = 7
With the assumption that the market entry in an upward trend occurs when the prices break out above a bar high, the result of the stop calculation is subtracted from the bar high. In the case of a downward trend, the result of the stop calculation is added to the price bar low.
When entering the market, set the factor to 2.4. If inside bars follow a trend movement, the stop should be brought closer. Try the factor setting 0.4 or less. The smallest adjustable factor is 0.1.
For the entry into an established trend, as described in an idea contribution by me, there are two switchable moving averages. The application for the (MA_H) takes place on high and for the (MA_L) adjustable on high, low, shot, h + 1/2 etc. Period and offset (shift) are adjustable. With this idea, the entry into the market occurs between a 618% correction (the Fibonacci entry point) and the DEP (average entry point). The DEP in this case is the MA_H with period = 4 and an offset = 1 in the case of a downward trend, or the MA_L with the same setting and application to lows in an upward trend.
Also test the MA_L in trends with the settings (period, offset) 3.3 or 5, 3 or 7.5 and applying it to closing prices for a close encompassing of the highs / lows.
Tägliche (wöchentliche, monatliche) Gewinne mit dem Fibonacci-Trading Indikator_3
Kursnotierungen bewegen sich in liquiden Märkten in Fibonacci-Verhältnisse. Mit diesem Indikator erhalten Sie für Tagesgeschäfte, oder für Positionstrades auf Basis einer Woche, oder auf Basis eines Monats Informationen, in welchem Bereich Sie idealerweise in den Markt einsteigen sollten und wo das mindeste erreichbare Kursziel liegt. Dieses Kursziel liegt bei 61,8% der gestrigen Handelspanne, oder der Handelspanne der Vorwoche, oder der Handelspanne des Vormonats, also abhängig davon für welchen Zeitrahmen der Indikator das mindeste erreichbare Hoch/Tief berechnen soll. Dort realisieren Sie auch Ihren Gewinn.
Für diese Berechnung sind folgende Eingaben im Eigenschaftenfenster des Indikators einzustellen:
• Vorwahl Aufwärtstrend/ Abwärtstrend.
• Zeitrahmen (Tag, Woche, …) des Kursbalkens für das zu ermittelnde mögliche Hoch/ Tief.
• Handelspanne des vorherigen Tages, oder der vorherigen Woche, oder des vorherigen Monats.
• Aktuell tiefstes Tief des vorgewählten Zeitrahmens, wenn der Handel begonnen hat und die Notierungen steigen.
• Aktuell höchstes Hoch des vorgewählten Zeitrahmens, wenn der Handel begonnen hat und die Notierungen fallen.
Wichtige Bereiche für das Trading sind:
• Der Einstiegsbereich 0% - 23,6% für long oder short.
• Der Kursziellevel 61,8%.
Wählen Sie für die Erkennung der Bewegungsrichtung einen geeigneten Zeitrahmen, während sich die Notierungen noch im Einstiegsbereich bewegen. Der Camelback-Indikator kann eine gute Hilfe sein. Testen Sie auch die Auflösung-Einstellung des Camelback-Indikators. Mit der Auflösung 1 Stunde Im 6- oder 12 Minuten-Chart erhalten Sie einen Blickwinkel für die große Richtung. Auch Bewegungsmuster von Korrekturen oder Konsolidierungen, wenn sie mehr als einen Tag oder eine Woche andauern geben Hinweise auf die kommende Bewegungsrichtung für den Trade. Schauen Sie also zurück um zu prüfen, was sich gestern, vor einer Woche oder vor einem Monat abgespielt hat. Achten sie auf die Marktanatomie, finden Sie heraus wie der Markt funktioniert, zählen Sie Kursstäbe in Konsolidierungen und Trends.
Nach Eingabe der Werte zeigt der Indikator die Fibonacci-Ausweitungskurslevels für das mögliche Hoch oder Tief für den ausgewählten Zeitrahmen. Kaufen/ verkaufen Sie innerhalb des Einstiegsbereichs zwischen 0% und 23,6%, während sich der Markt in Richtung des letzten long-/ oder short-Einstiegspunktes bewegt. Das ist der Kursbereich bis zum 23,6%- Kurslevel. Der 61,8%-Kurslevel ist das mindeste erwartbare Kursziel. Wir gehen davon aus, dass der aktuelle Kursbalken mindestens 61,8% der Handelsspanne des vorherigen Tages, der vorherigen Woche oder des vorherigen Monats erreichen wird. Abhängig vom eingestellten Zeitrahmen. Realisieren Sie deshalb die angelaufenen Gewinne mit 50% der Position, wenn die Notierungen den 61,8% - Level erreicht haben. Mit einem geeigneten Trailing-Stopp lassen Sie sich mit der restlichen Position ausstoppen, riskieren Sie dafür aber nicht mehr als 50 % der angelaufenen Gewinne.
Mit der Vorwahl Quartal oder Jahr und den entsprechenden Eingaben kann auch das mindeste erwartbare Quartalshoch/ Quartalstief bzw. Jahreshoch/ Jahrestief ermittelt werden.
Die Fibonacci-Kurslevels lassen sich ein- und ausblenden. Klicken Sie im Chart auf das Zahnrad für „Chart Einstellungen“. Im Menü „Skalierungen“ kann mit der Vorwahl „Label für Indikatornahmen“ und „Label für letzten Indikatorwert“ die Kurslevels angezeigt werden. Schieben Sie den Chart nach rechts um mögliche Unterstützungen und Widerstände an den Kurslevels zu finden, die Bestätigung für das Ziel geben könnten.
Bei Eingabefehlern oder fehlenden Eingaben zu einem Zeitrahmen wird der Indikator ausgeblendet.
Achten Sie zur Vermeidung von Verlusten auf ihr Handelsmanagement.
Der neue Fibonacci-Trading-Indikator_3 besitz folgende Zusätze und Änderungen:
Vorwahl für den Zeitrahmen Quartal wurde hinzugefügt.
Der Einstiegsbereich erhielt eine 23,6% und eine 50% Unterteilung. Zwei Umschlagslinien über dem 23,6%-Einstiegslevel bei einem Aufwärtstrend, bzw. unter dem 23,6%-Einstiegslevel bei einem Abwärtstrend, mit der Breite 23,6% und 14,6% vom Einstiegsbereich, sollen bei höherem Schlusskurs signalisieren, dass die Notierungen aus dem Einstiegsbereich ausgebrochen sind.
Ein Volatilitätsstopp jeweils für Aufwärts- und Abwärtstrend kann zugeschaltet werden.
Für den Stopp wird die Schwankungsbreite jedes Kursbalkens wird mit einem Faktor beaufschlagt. Danach erfolgt die Berechnung eines gleitenden Durchschnitts mit einstellbarer Periode. Die Periodeneinstellung sollte zwischen 5 und 10 eingestellt werden. Das Ergebnis kann einstellbar geglättet werden.
Voreinstellung:
Perioden = 10
Faktor = 1,4
Glättung = 7
Mit der Annahme, dass der Markteinstieg in einem Aufwärtstrend bei Ausbruch der Notierungen über ein Kursbalkenhoch erfolgt, wird das Ergebnis der Stoppberechnung vom Kursbalkenhoch subtrahiert. Bei einem Abwärtstrend wird das Ergebnis der Stoppberechnung zum Kursbalkentief addiert.
Stellen Sie bei Markteintritt den Faktor auf 2,4. Folgen nach einer Trendbewegung Innenstäbe sollte der Stopp näher herangeführt werden. Probieren Sie die Faktoreinstellung 0,4 oder kleiner. Der kleinste einstellbare Faktor ist 0,1.
Für den Einstieg in einen etablierten Trend, wie in einem Ideenbeitrag von mir beschrieben, gibt es zwei zuschaltbare gleitende Durchschnitte. Die Anwendung für den (MA_H) erfolgt auf Hochs und für den (MA_L) einstellbar auf Hoch, Tief, Schuss, h+l/2 usw.. Periode und Offset (Verschiebung) sind einstellbar. Bei dieser Idee erfolgt der Einstieg in den Markt zwischen einer 618%-Korrektur (dem Fibonacci-Einstiegspunkt) und dem DEP (Durchschnittlicher Einstiegspunkt). Der DEP ist in diesem Fall der MA_H mit Periode = 4 und einem Offset = 1, bei einem Abwärtstrend, oder der MA_L mit identischer Einstellung und Anwendung auf Tiefs in einem Aufwärtstrend.
Testen Sie den MA_L auch in Trends mit den Einstellungen (Periode, Offset) 3,3 oder 5, 3 oder 7,5 und Anwendung auf Schlusskurse für eine enge Umfassung der Hochs/ Tiefs.
Non Parametric Adaptive Moving AverageIntroduction
Not be confused with non-parametric statistics, i define a "non-parametric" indicator as an indicator who does not have any parameter input. Such indicators can be useful since they don't need to go through parameter optimization. I present here a non parametric adaptive moving average based on exponential averaging using a modified ratio of open-close to high-low range indicator as smoothing variable.
The Indicator
The ratio of open-close to high-low range is a measurement involving calculating the ratio between the absolute close/open price difference and the range (high - low) , now the relationship between high/low and open/close price has been studied in econometrics for some time but there are no reason that the ohlc range ratio may be an indicator of volatility, however we can make the hypothesis that trending markets contain less indecision than ranging market and that indecision is measured by the high/low movements, this is an idea that i've heard various time.
Since the range is always greater than the absolute close/open difference we have a scaled smoothing variable in a range of 0/1, this allow to perform exponential averaging. The ratio of open-close to high-low range is calculated using the vwap of the close/high/low/open price in order to increase the smoothing effect. The vwap tend to smooth more with low time frames than higher ones, since the indicator use vwap for the calculation of its smoothing variable, smoothing may differ depending on the time frame you are in.
1 minute tf
1 hour tf
Conclusion
Making non parametric indicators is quite efficient, but they wont necessarily outperform classical parametric indicators. I also presented a modified version of the ratio of open-close to high-low range who can provide a smoothing variable for exponential averaging. I hope the indicator can help you in any way.
Thanks for reading !
Volume Bubbles & Liquidity Heatmap 30% + biasLuxAlgo gave us an open script, I just primmed it up with the use of Chat GPT:There is no single magic number (like “delta must be 800”) that will guarantee directional follow-through in every market. But you can make a mathematically rigorous filter that gives you a high-probability test — by normalizing the delta against that market’s typical behavior and requiring multiple confirmations. Below is a compact, actionable algorithm you can implement immediately (in your platform or spreadsheet) plus concrete thresholds and the math behind them.
High-IQ rule set (math + trade logic)
Use three independent checks. Only take the trade if ALL three pass.
1) Z-score (statistical significance of the delta)
Compute rolling mean
𝜇
μ and std dev
𝜎
σ of delta on the same timeframe (e.g. 5m) over a lookback window
𝑊
W (suggest
𝑊
=
50
W=50–200 bars).
𝑍
=
delta
bar
−
𝜇
𝑊
𝜎
𝑊
Z=
σ
W
delta
bar
−μ
W
Threshold: require
𝑍
≥
2.5
Z≥2.5 (strong) — accept 2.0 for less strict, 3.0 for very rare signals.
Why: a Z>=2.5 means this delta is an outlier (~<1% one-sided), not normal noise.
2) Relative Imbalance (strength vs total volume)
Compute imbalance ratio:
𝑅
=
∣
delta
bar
∣
volume
bar
R=
volume
bar
∣delta
bar
∣
Threshold: require
𝑅
≥
0.25
R≥0.25 (25% of the bar’s volume is one-sided). For scalping you can tighten to 0.30–0.40.
Why: a big delta with tiny volume isn’t meaningful; this normalizes to participation.
3) Net follow-through over a confirmation window
Look ahead
𝑁
N bars (or check the next bar if you need intrabar speed). Compute cumulative delta and price move:
cum_delta
𝑁
=
∑
𝑖
=
1
𝑁
delta
bar
+
𝑖
cum_delta
N
=
i=1
∑
N
delta
bar+i
price_move
=
close
bar
+
𝑁
−
close
bar
price_move=close
bar+N
−close
bar
Thresholds: require
cum_delta
𝑁
cum_delta
N
has the same sign as the trigger and
∣
cum_delta
𝑁
∣
≥
0.5
×
∣
delta
bar
∣
∣cum_delta
N
∣≥0.5×∣delta
bar
∣, and
price_move
price_move exceeds a minimum meaningful tick amount (instrument dependent). For ES / US30 type futures: price move ≥ 5–10 ticks; for forex pairs maybe 10–20 pips? Use ATR
20
20
×0.05 as a generic minimum.
Why: separates immediate absorption (buy delta then sellers soak it) from genuine continuation.
Bonus check — Structural context (must be satisfied)
Trigger should not occur against a strong structural barrier (VWAP, daily high/low, previous session POC) unless you’re explicitly trading exhaustion/absorption setups.
If signal occurs near resistance and price does not clear that resistance within
𝑁
N bars, treat as probable trap.
Putting it together — final trade decision
Take the long (example):
If
𝑍
≥
2.5
Z≥2.5 and
𝑅
≥
0.25
R≥0.25 and cum_delta_N confirms and no hard resistance above (or you’re willing to trade absorption), then enter.
Place stop: under the low of the last 2–3 bars or X ATR (instrument dependent).
Initial target: risk:reward 1:1 minimum, scale out at 1.5–2R after confirming further delta.
Concrete numeric illustration using your numbers
You saw FOL = 456, then sell reaction with ~350 opposite. How to interpret:
Suppose your 5-min rolling mean
𝜇
μ = 100 and
𝜎
σ=120 (example):
𝑍
=
(
456
−
100
)
/
120
≈
2.97
⇒
statistically big
Z=(456−100)/120≈2.97⇒statistically big
So it passes Z.
If volume on that bar = 2000 contracts:
𝑅
=
456
/
2000
=
0.228
⇒
just below 0.25 threshold
R=456/2000=0.228⇒just below 0.25 threshold
So it fails R (weak participation proportionally), explaining why 456 alone didn’t move price.
Seller came back with 350 opposite soon after — check cum_delta_N:
cum_delta
𝑛
𝑒
𝑥
𝑡
3
≈
456
−
350
=
106
net
cum_delta
next3
≈456−350=106 net
Net is small relative to the initial spike — not convincing follow-through.
Conclusion: despite a big absolute number (456), relative measures and lack of follow-through meant the move failed. That’s exactly why raw numbers alone are unreliable.
Advanced refinement (for elite performance)
Use rolling median + MAD instead of mean/std if delta distribution is skewed.
Scale Z by volume volatility: divide Z by
volume
bar
/
volume
‾
volume
bar
/
volume
to penalize low-volume bars.
Use a signed cumulative delta over micro-windows: compute windowed cumulative delta standardized:
𝑍
cum
=
∑
𝑖
=
0
𝑀
−
1
delta
𝑡
−
𝑖
−
𝑀
𝜇
𝑀
𝜎
Z
cum
=
M
σ
∑
i=0
M−1
delta
t−i
−Mμ
and require
𝑍
cum
≥
3
Z
cum
≥3 for very high confidence.
Add market-depth / DOM confirmation (if available): require that resting ask size above is less than resting bid size below by a factor (i.e. visible liquidity supports the move).
Practical thresholds to start with (tune per instrument)
Lookback
𝑊
W: 100 bars (5m → about a trading day)
Z threshold: 2.5
Imbalance ratio
𝑅
R: ≥ 0.25 (tighten to 0.30 for scalping)
Confirmation window
𝑁
N: next 1–3 bars for intraday scalps; 3–6 bars for short swings
Cum delta confirmation: ≥ 0.5 × initial delta and same sign
Price move confirmation: ≥ 0.03 × ATR20 (or set absolute ticks per instrument)
TL;DR — the single best rule
Don’t chase absolute numbers. Use Z-score of delta + delta/volume ratio + real follow-through. If all three align, odds are heavily in your favor.
If you want, I can:
give you a tiny script (pseudocode or Pine / Python) that computes Z, R, cum_delta_N and flags qualifying bars, or
run the calculation on a sample of your recent bars if you paste a small CSV of time, delta, volume, close.
Which do you want? (I’ll give code right away.)
You said:
give me a percentage of difference where we have a high probability
ChatGPT said:
Thought for 7s
Nice — straight to the point. Here’s a concise, practical set of percentage thresholds (and associated confidence estimates) you can use right now to flag a “high probability” delta signal. I’ll give you three tiers (good / strong / elite), explain what each means, show how to compute it, and give a short example using your 456/2000 bar.
One-line rule
Compute delta percent
𝑃
=
∣
delta
∣
volume
×
100
%
P=
volume
∣delta∣
×100%.
Then require Z-score of delta ≥ 2.5 and P to be at or above the threshold below for the desired confidence tier.
Threshold tiers (percent of bar volume)
Good (high-probability trade candidate)
P ≥ 20–25%
Typical success probability (when combined with Z≥2.5 and no hard structural resistance): ~60–70%.
Use when you want a steady flow of signals with decent edge.
Strong (high confidence)
P ≥ 30–35%
Typical success probability: ~70–80% (with Z≥2.5 + structural alignment).
Fewer signals, higher win-rate. Good default for intraday.
Elite (very high probability / low false positives)
P ≥ 40–50%
Typical success probability: ~80–90% (with Z≥3 and confirmation).
Rare signals. Use for meaningful size or when you need maximum certainty.
Why percentage matters (short)
Absolute delta (456) is meaningless without volume context. A 456 delta on 2,000 volume → P = 456/2000 = 22.8% → sits just below the Good threshold, which matches why it failed: decent but not dominant participation.
Additional required checks (don’t skip these)
To turn P into a reliable filter, always require:
Z-score of the delta ≥ 2.5 (or ≥3 for Elite signals).
No immediate structural barrier (VWAP, strong resistance) that would plausibly absorb the order.
Follow-through: within next N bars (N = 1–3 for scalps) price moves in the same direction by ≥ 0.03×ATR20 (or instrument-specific tick threshold). If this fails, cut fast.
Combine all three and your realized win-rate will approach the probabilities above.
Practical quick checklist (to apply each signal)
Compute P = |delta|/volume. Is P ≥ 30%? (or your chosen tier)
Compute Z = (delta − mean)/std over last 100 bars. Is Z ≥ 2.5?
Is price not pinned under a heavy resistance?
Enter on next bar close (or intrabar on continuation), stop under last 2-bar low (for longs).
If price fails to move ≥ 0.03×ATR20 within 3 bars, exit.
Example (your bar)
delta = 456, volume = 2000 → P = 22.8% → below Good threshold (25%).
Even if Z was high, P failed — explains the failure. You need P ≥ ~30% plus Z≥2.5 to call it a Strong signal.
Final notes (instrument & timeframe)
These percentages were calibrated for futures/US indices and short intraday bars (1–5m).
For FX or low-tick instruments, use absolute ticks + a smaller P threshold (start at 15–20%).
Always backtest on the specific instrument/timeframe and tune thresholds.
If you want, I’ll generate a tiny script (Python or Pine) that calculates P and Z and flags Good/Strong/Elite signals for your chart history so you can see exact historical hit rates. Which language (Python or Pine)?
You said:
so if we have 456 g vs 350 r what pct is that in favour of green?
ChatGPT said:
Perfect — let’s calculate it carefully, digit by digit so we don’t make a slip.
We have:
Green (buy) volume = 456
Red (sell) volume = 350
We want to know what percentage is in favor of green, relative to the total volume.
Step 1. Compute total volume
Total
=
456
+
350
=
806
Total=456+350=806
Step 2. Compute green’s share
\text{Green %} = \frac{456}{806} \times 100
Now do it precisely:
456
÷
806
=
0.565506
456÷806=0.565506 (rounded)
So:
0.565506
×
100
=
56.55
%
0.565506×100=56.55%
Step 3. Compute red’s share (for context)
350
806
=
0.434494
→
43.45
%
806
350
=0.434494→43.45%
Step 4. Compute difference (bias toward green)
56.55
%
−
43.45
%
=
13.10
%
56.55%−43.45%=13.10%
✅ Final answer:
Green = 56.6% of total
Red = 43.4% of total
Bias = +13.1 percentage points in favor of green
So that’s only a 13% advantage to buyers — modest pressure, not a dominant imbalance.
For a high-probability signal (as we discussed earlier), you generally want ≥30% imbalance (e.g. ~65/35 split or stronger).
Original:
''The Volume Bubbles & Liquidity Heatmap indicator is a powerful trading tool designed to give traders a clearer picture of volume dynamics and liquidity distribution across multiple timeframes. By combining dynamic volume bubbles with a liquidity heatmap, this indicator makes it easy to identify areas of price interest, spot market imbalances, and improve decision-making for both scalpers and swing traders.
This trading indicator is ideal for volume traders, price action traders, and liquidity-focused traders who need a clean, multi-dimensional view of buyer/seller activity and the zones where market participants are most active. With full customization over bubble display, timeframes, and visual settings, traders can tailor the tool to fit virtually any trading strategy or market.''
Charles PO3# Charles PO3 - Release Notes
## 📊 Introduction
**Charles PO3** is a powerful PO3 (Power of 3) indicator designed for traders who need to simultaneously observe **Higher Time Frame (HTF)** price action on **Lower Time Frame (LTF)** charts.
This indicator draws multiple HTF candles on the right side of the chart and connects the current price to the HTF **Open, High, and Low** with dynamic projection lines. It helps you:
- View **Daily/Weekly** structure on a minute chart.
- Track HTF key price levels in **real time**.
- Better understand **multi-timeframe trend relationships**.
- Improve **timeframe consistency** in your trading decisions.
**Applicable Markets**: Forex, Futures, Stocks, Cryptocurrencies, and all other financial markets.
This script is based on the (www.google.com) created by (www.google.com).
This indicator is released under TradingViews default license (Mozilla Public License 2.0)
-----
## ✨ Core Features
### 🕐 Smart Timeframe Management
- **Automatic Timeframe Selection**: Automatically selects a suitable HTF based on the current chart period (optionally 1 or 2 levels of progression).
- **Manual Timeframe**: Supports custom selection of any timeframe (15 minutes, 1 hour, 4 hours, Daily, Weekly, etc.).
- **Custom Opening Time**: Supports custom HTF candle opening time and timezone (useful for non-standard trading sessions).
### 📈 Candle Display
- **Configurable Quantity**: Display 1-20 HTF candles (default 5).
- **Three Sizes**: Small, Medium, Large candles available.
- **Two Types**:
- Standard Candles
- Heikin Ashi (Smoothed Candles)
- **Custom Colors**:
- Bullish (Up) Candles: Independent color settings for body, wick, and border.
- Bearish (Down) Candles: Independent color settings for body, wick, and border.
- **Position Adjustment**: Adjustable offset from the right edge of the chart and spacing between candles.
### 🎯 Dynamic Projection Lines
- **Open Price Projection**: Extends from the HTF Open price to the center of the current candle.
- **High/Low Projection**: Extends from the HTF High/Low to the center of the current candle.
- **Real-Time Updates**: Projection lines automatically update their starting point upon price breakthrough.
- **Customizable Style**:
- Three line styles: Solid, Dashed, Dotted.
- Adjustable color and width.
- Independent On/Off switches.
### 🏷️ OHLC Price Labels
- **Real-Time Price Display**: Shows O/H/L/C prices to the right of the latest HTF candle.
- **Six Font Sizes**: Auto, Tiny, Small, Normal, Large, Huge.
- **Follows Candle Movement**: Label position updates dynamically with the candle.
### 🕒 Smart Time Labels
- **Adaptive Format**:
- **Daily**: Displays the day of the week (Mon, Tue, Wed...).
- **Weekly**: Displays Month-Day (10-05, 10-12...).
- **Other Timeframes**: Displays Hour:Minute (14:30, 21:00...).
- **Asset Type Recognition**:
- **Forex/Futures**: Automatically adjusts to display trading days (Mon-Fri).
- **Crypto**: Displays actual date (7 days a week).
- **Center Alignment**: Time label is positioned below the center of the candle.
- **Customizable Color**: Supports adjusting text color (default gray).
### 📊 HTF Data Mode
- **Weekly**: Only use HTF data to generate projections when on a weekly chart.
- **Always**: Always use HTF data.
- **Never**: Always use LTF data to construct the HTF candles.
### 🐛 Debug Tools
- **Debug Table**: Real-time display of indicator status (parameters, candle count, label count, etc.).
- **Pine Logs**: Detailed logs for timestamp conversions and label creation.
- **Optional Switch**: Debug features can be disabled in a production environment to improve performance.
-----
## ⚙️ Parameter Descriptions
### 📁 Settings (Basic Settings)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Timeframe** | Timeframe | Blank (Auto) | Sets the HTF timeframe; leave blank for automatic selection. |
| **Set Automatically** | Boolean | ✅ | Enables automatic timeframe selection. |
| **Two Levels** | Boolean | ✅ | Use 2 levels of progression (e.g., 15min→4H); off uses 1 level (15min→1H). |
| **Number of HTF Candles** | Integer | 5 | Number of HTF candles to display (1-20). |
| **Offset** | Integer | 10 | Bar offset of the candle group from the right edge of the chart. |
| **Size** | Option | Medium | Candle size: Small / Medium / Large. |
| **Type** | Option | Candles | Candle type: Candles (Standard) / Heikin Ashi (Smoothed). |
| **Margin** | Integer | 1 | Spacing between candles (in bars). |
| **Use HTF data to generate candles** | Option | Weekly | Weekly / Always / Never. |
### 🟢 Up Candles (Bullish Candles)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Body** | Color | \#6ba583 | Color for the bullish candle body. |
| **Wick** | Color | Black | Color for the bullish candle wick. |
| **Border** | Color | Black | Color for the bullish candle border. |
### 🔴 Down Candles (Bearish Candles)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Body** | Color | \#d75442 | Color for the bearish candle body. |
| **Wick** | Color | Black | Color for the bearish candle wick. |
| **Border** | Color | Black | Color for the bearish candle border. |
### 📏 Projections (Projection Lines & Labels)
#### Open Price Projection Line
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Open** | Boolean | ✅ | Show Open price projection line. |
| ⚫ **Color** | Color | Translucent Black | Open price line color. |
| **Style** | Option | Dotted | Solid / Dotted / Dashed. |
| **Width** | Integer | 1 | Line width (1-5). |
#### High/Low Projection Lines
| Parameter | Type | Default | Description |
|---|---|---|---|
| **High/Low** | Boolean | ✅ | Show High/Low projection lines. |
| ⚫ **Color** | Color | Translucent Black | High/Low line color. |
| **Style** | Option | Dotted | Solid / Dotted / Dashed. |
| **Width** | Integer | 1 | Line width (1-5). |
#### OHLC Price Labels
| Parameter | Type | Default | Description |
|---|---|---|---|
| **OHLC Prices** | Boolean | ✅ | Show price labels. |
| ⚫ **Color** | Color | Translucent Black | Text color. |
| **Size** | Option | Auto | Auto / Tiny / Small / Normal / Large / Huge. |
#### HTF Time Labels
| Parameter | Type | Default | Description |
|---|---|---|---|
| **HTF Time** | Boolean | ✅ | Show time labels. |
| **Time Label Color** | Color | Gray | Time text color. |
### 🕐 Custom Opening Time (Custom Opening Time)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Use Custom Opening Time?** | Boolean | ❌ | Enable custom opening time. |
| **Timezone** | Option | Exchange | Timezone selection (using Timezone library). |
| **Time (hh:mm)** | Time | 02:00 | Custom opening time (hour:minute). |
### 🐛 Debug (Debugging)
| Parameter | Type | Default | Description |
|---|---|---|---|
| **Enable Debug Info** | Boolean | ❌ | Enable Pine Logs for detailed logging. |
| **Show Debug Table** | Boolean | ✅ | Display the debug info table in the top right corner. |
-----
## 🎓 Usage Recommendations
### Recommended Timeframe Combinations
- **1-Minute Chart** → HTF: 15 Minutes
- **5-Minute Chart** → HTF: 1 Hour
- **15-Minute Chart** → HTF: 4 Hours
- **1-Hour Chart** → HTF: Daily
- **4-Hour Chart** → HTF: Weekly
- **Daily Chart** → HTF: Weekly/Monthly
### Best Practices
1. **Trend Trading**: Use the Daily HTF on a 1-Hour chart to ensure you are trading with the higher-timeframe trend.
2. **Support/Resistance**: The HTF High/Low projection lines serve as natural support and resistance levels.
3. **Open Breakout**: Observe the HTF Open price projection line to catch directional breakouts after the open.
4. **Time Synchronization**: Use the time labels to understand the lifecycle stage of the HTF candle.
5. **Multi-Timeframe Confirmation**: Observe multiple HTF candles simultaneously to confirm trend consistency.
-----
## 📌 Version Information
- **Version**: 1.0
- **Pine Script**: v6
- **Dependency Library**: `n00btraders/Timezone/1`
- **Chart Limitations**:
- Max historical bars: 500
- Max Box objects: 500
- Max Label objects: Default (TradingView limit)
-----
**Happy Trading\! 📈**
ICT Concepts(Liquidity, FVG & Liquidity Sweeps)📄 Description:
A Smart Money Concept (SMC)-based utility that blends ICT-style Liquidity Sweeps, Fair Value Gap (FVG) mapping, and Swing Structure proxies – designed for traders seeking clean precision in price imbalance analysis.
⸻
🔍 1. What This Script Does
T his indicator brings together three core Institutional Concepts:
• Liquidity Sweep Detection : Identifies buy/sell-side liquidity grabs (fakeouts) confirmed by volume spikes – a common precursor to institutional order flow shifts.
• Fair Value Gaps (FVGs) : Highlights inefficiencies between price legs using strict ICT-style 3-candle or gap-based rules. These are areas institutions often revisit.
• Swing Structure Proxy (OB Mapping) : Tracks dynamic swing highs/lows to act as proxy zones for potential order blocks and structural boundaries.
It also includes a cooldown-based signal filtering engine to prevent overfitting and noise, helping traders avoid false positives in choppy markets.
⚙️ 2. How It Works (Core Logic)
✅ A. Liquidity Sweep Engine
• Looks back N bars to find Equal Highs or Equal Lows.
• Triggers a signal only if price sweeps the level and closes on the other side with a volume spike.
• Customizable volume threshold (e.g., 1.5x average volume).
• Includes a signal cooldown period to reduce clutter and boost quality.
Bullish Sweep = Price dips below equal lows but closes higher
Bearish Sweep = Price spikes above equal highs but closes lower
Visuals: Signal arrows with alerts (BUY LQ / SELL LQ)
⸻
✅ B. Fair Value Gap (FVG) Zones
• Detects FVGs using:
• Sequential logic: Low > High (bullish), High < Low (bearish)
• Gap logic: Open gaps at bar open
• Dynamic box drawing:
• Automatically extends FVG zones until price fully closes through them.
• Different color coding for bullish (teal) and bearish (orange) gaps.
• Customizable:
• Opacity control
• Option to include/exclude gap-based FVGs
• Hide filled zones
• Limit total zones rendered (for performance)
⸻
✅ C. Swing High/Low Structure
• Uses a lookback period to find latest swing high/low levels.
• Acts as a proxy for Order Block zones or structural shift reference points.
• Plotted as red (high) and green (low) lines.
⸻
🚀 3. How to Use It
• Scalpers and Intraday Traders can use Liquidity Sweep + FVG Confluence to time reversals or catch early entries into trend continuation moves.
• Swing Traders can observe swing OB proxies and recent FVG zones to frame directional bias and target zones.
• Volume-Aware Traders benefit from the volume filter that confirms sweeps are meaningful – not just random stop hunts.
🔔 Set alerts on:
• Bullish Liquidity Sweeps
• Bearish Liquidity Sweeps
You can use this in combination with your own trend filters, or even confluence it with Order Blocks, VWAP, or EMA trend tools.
⸻
💡 What Makes It Original?
• The script doesn’t merely combine standard tools — it builds a cohesive ICT-style detection system using:
• A custom volume-confirmed liquidity sweep filter
• Dynamic FVG rendering with filled logic + performance optimization
• Visual hierarchy to avoid clutter: clean line plots, contextual boxes, and conditional signals
• Highly customizable yet lightweight, making it suitable for fast-paced decision making.
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✅ Notes
• Invite-only script for serious traders interested in Smart Money and ICT concepts.
• Does not repaint signals.
• All visuals are dynamically managed for clarity and performance.
BB_MES Playbook Levels + Auto Alerts (Start/TP1/TP2)Indicator Name: MES Playbook Levels + Auto Alerts (Start/TP1/TP2)
1. Indicator Overview
This is a comprehensive technical analysis tool designed for day traders, specifically for Micro E-mini S&P 500 futures (MES) but applicable to other instruments. Its primary purpose is to automate the drawing of key price levels and to provide timely alerts for a specific trading strategy, often called a "playbook" setup.
The core of the strategy involves identifying a "start" level during the regular trading session. Once the price crosses this level, the indicator automatically projects two take-profit (TP1 and TP2) targets and monitors the price action in relation to these levels.
2. Key Features
Automatic Level Plotting: The indicator plots several critical price levels on the chart, saving the trader from having to draw them manually every day.
Dynamic Start Levels: It offers two methods for establishing the bullish and bearish entry or "start" levels:
Previous Day's High/Low (PDH/PDL): The default setting uses the high and low of the prior trading day as the trigger points for long and short trades.
RTH VWAP Bands: Alternatively, it can calculate the Volume-Weighted Average Price (VWAP) that resets at the start of the Regular Trading Hours (RTH) session and create a "band" around it. The edges of this band then serve as the start levels.
Automated Take-Profit Targets: Upon a cross of a "start" level, the indicator immediately plots two take-profit lines (TP1 and TP2) based on a user-defined point value.
Trade State Management: The script intelligently manages the state of a trade. It knows when a long or short trade is active and will stop looking for new signals until the current trade is concluded (either by hitting TP2 or the end of the session).
Comprehensive Alerts: A major feature is its robust alert system. Traders can set up alerts for a wide variety of events, allowing for less screen time.
Session Highlighting: It specifically monitors the Regular Trading Hours (RTH) session and can also plot the high and low of the overnight (ON) session.
3. On-Chart Visuals
When you apply this indicator to your chart, you will see the following lines and plots:
Previous Day Levels:
PDH (Previous Day High): Plotted as a green line.
PDL (Previous Day Low): Plotted as a red line.
PDC (Previous Day Close): Plotted as a gray line.
Start Levels:
StartBull: A lime green line representing the trigger for a long trade.
StartBear: A maroon line representing the trigger for a short trade.
Take-Profit Levels:
TP1 / TP2: Teal-colored lines that appear only after a StartBull or StartBear level is crossed. TP1 is a dotted line, and TP2 is solid.
Other Levels:
RTH VWAP: A blue line showing the volume-weighted average price for the main session only.
ON High / ON Low: Orange lines showing the high and low points established outside of the RTH session.
4. How It Works: The Trading Logic
Define Session: The script first identifies the Regular Trading Hours (e.g., 9:30 AM to 4:00 PM EST).
Calculate Levels: It calculates the PDH/PDL and the RTH VWAP. Based on user input, it determines the startBullLevel (either PDH or the upper VWAP band) and the startBearLevel (either PDL or the lower VWAP band).
Wait for Signal: During the RTH session, the indicator waits for the live price (close) to cross over the startBullLevel or cross under the startBearLevel.
Initiate Trade State:
If a bullish cross occurs (longStart), it logs the entryPrice, sets the trade state to longActive, and plots the TP1 and TP2 lines above the entry price.
If a bearish cross occurs (shortStart), it does the opposite, plotting TP1 and TP2 below the entry price.
Monitor Trade: While a trade is active, it checks if the price hits TP1 or TP2.
End Trade:
When the price hits the TP2 level, the trade is considered complete. The script clears the TP lines from the chart and resets itself to look for the next start signal.
At the end of the RTH session, any active trade is automatically terminated, and all TP lines are cleared to ensure a clean slate for the next day.
5. Input Settings (Customization)
The user can customize the following parameters in the indicator's settings:
RTH Session: Define the start and end times for the main trading session.
Start from RTH VWAP band: A checkbox to switch between using PDH/PDL or the VWAP band for start levels.
VWAP band offset (pts): If using the VWAP band, this sets how many points away from the VWAP the start levels are drawn.
TP1 (pts): The number of points from the entry price to set the first take-profit target.
TP2 (pts): The number of points for the second take-profit target.
Show Overnight High/Low: A toggle to show or hide the overnight session levels.
6. Configurable Alerts
You can create alerts in TradingView for any of the following conditions generated by the script:
StartBull / StartBear: Triggers when a long or short trade is initiated.
TP1 Hit / TP2 Hit: Triggers when the price reaches the take-profit levels for both long and short trades.
Level Crosses: Separate alerts can be set for when the price crosses the PDH, PDL, PDC, RTH VWAP, ON High, or ON Low. This is useful for general market awareness.
HH/HL/LH/LL Swing MapHH/HL/LH/LL Swing Map
Overview
The HH/HL/LH/LL Swing Map is a Pine Script v6 indicator for TradingView that classifies market structure swings in real time. It identifies and labels Higher Highs (HH), Higher Lows (HL), Lower Highs (LH), and Lower Lows (LL) using verified pivot logic, ensuring accuracy without repainting. Custom non-repainting comparisons support reliable structure mapping. Designed for price action traders, it provides a clear, systematic view of evolving swing structure directly on the chart.
How It Works
The indicator uses ta.pivothigh and ta.pivotlow functions with configurable left/right bar settings to verify swing points—delaying labels until full verification for no repaints. Each verified pivot is compared to the previous swing of the same type: If a new high is above the prior high, it is marked as HH; otherwise, LH. If a new low is above the prior low, it is marked as HL; otherwise, LL. Labels and optional triangle markers are plotted on the exact bar where the swing confirms, with customizable offsets in ticks for consistent placement. Users can also enable connection lines between consecutive highs or lows, providing a simple zigzag visualization of structure shifts.
Key Features
• Non-Repainting Logic: Uses verified pivots (bar_index - rightBars) for accurate HH/HL/LH/LL classification.
• Customizable Labels: Adjustable colors, offsets, and visibility for clean chart integration.
• Optional Connection Lines: Connects successive highs and lows to highlight market structure flow.
• Trend Clarity: Quickly distinguishes bullish (HH/HL) and bearish (LH/LL) conditions.
• Alerts Built-In: Alert conditions trigger when new HH, HL, LH, or LL points are verified.
• Lightweight Design: Refined for fast rendering without cluttering the chart.
What It Displays
The indicator plots visual labels and markers for each verified structural pivot (HH, HL, LH, LL). It can also draw connecting lines between pivots to form a simplified swing map of price action. These elements help traders spot shifts in trend direction, continuation, and reversal zones.
Originality
This is an original Pine v6 implementation. It applies verified pivot logic, label/line management, and alert conditions.
Common Ways People Use It
• Price action traders mapping bullish or bearish structure (HH/HL vs. LH/LL).
• Swing traders validating entry/exit signals with structural verification.
• Technical analysts combining market structure with support/resistance or supply/demand zones.
• Day traders monitoring micro-structure shifts for intraday scalping strategies.
Configuration Notes
Users can adjust left/right bar counts for swing verification, label and triangle visibility, line drawing options, and color schemes. Offsets allow labels to remain readable across symbols and timeframes. Alerts may be set for specific structure changes (e.g., “New Higher High Verified”).
Legal Disclaimer
These indicators are for informational and educational purposes only—not investment, financial, or trading advice. Past performance is not indicative of future results; trading involves high risk of loss. Provided "as is" with no warranties. Consult a qualified professional before decisions. By using, you assume all risk and agree to this disclaimer.
ICT Multi-Timeframe Market Structure Tracker [SwissAlgo]ICT Multi-Timeframe Market Structure Tracker
Tracks the ICT market structure across three core timeframes (1-Week, 1-Day, 1-Hour) simultaneously.
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Why this Indicator?
You know market structure matters, whether you trade stocks, Forex, commodities, or crypto.
You've studied ICT concepts - " Change of Character ", " Break of Structure ", " Premium/discount zones ". You understand that multi-timeframe alignment is where the edge lives.
But here's what's probably happening while you apply the ICT concepts for your trading decisions:
You're manually drawing structural highs and lows across three timeframes
You're calculating Fibonacci retracements by hand for each timeframe
You're switching between weekly, daily, and hourly charts, trying to remember where each pivot was, trying to detect the critical events you're waiting for
By the time you've mapped it all out, the setup is gone. Or worse, you missed that the 1-hour just broke the structure while you were checking the weekly bias.
What about seeing all three timeframes at once instead? You need to know immediately when the price enters a premium or discount zone. You need alerts that fire when structure breaks or character changes - across all timeframes - without babysitting your screen.
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The Indicator, at a Glance
This indicator:
tracks ICT market structure across three core timeframes (1-Week, 1-Day, 1-Hour) simultaneously .
automatically plots Fibonacci retracement levels from your defined structural pivots
monitors price position (during retracements) in real-time
sends consolidated alerts when actionable events occur on any timeframe
The 1-Week View: Mid-Term Trend Bias for lower timeframes
The 1-Day View: Swings nested within the 1-Week Structure
The 1-Hour View: Swings nested within the 1-Day Structure
One glance tells you:
* Current trend direction per timeframe
* Exact Fib zone price is trading right now
* Whether the structure just broke or the character changed
* If you're in a potential long/short setup zone
The indicator helps you reduce chart-hopping, manual calculations, and minimize the missed structural shifts.
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Who is this for?
This tool is built for day traders who understand ICT concepts and need efficient multi-timeframe structure tracking. If you know what a Change of Character is, why 0.382-0.5 retracements matter in uptrends, and how to trade external structure, this indicator eliminates the manual structure tracking so you can focus on confirming and executing your trading tactics.
New to ICT? This indicator assumes foundational knowledge of the Inner Circle Trader methodology developed by Michael J. Huddleston. Before using this tool, familiarize yourself with concepts like market structure breaks, premium/discount arrays, and liquidity engineering. The ICT framework offers a unique perspective on institutional order flow and price action - but this indicator is designed for those already applying these concepts, not learning them for the first time.
Critical Skill Required : You must understand the difference between external structure (key swing highs/lows that define market direction) and internal structure (minor fluctuations within the range).
Selecting incorrect pivots - such as marking internal noise instead of true structural points - will generate false signals and undermine the entire analysis. This indicator tracks structure based on YOUR inputs. If those inputs are wrong, every Fibonacci level, alert, and bias signal will be wrong. Learn to identify clean structural breaks before using this tool.
Trading Experience Matters: This tool tracks structure and fires alerts, but interpreting those signals requires understanding context, confluences, and risk management. If you're early in your trading journey, consider this a professional-grade instrument that becomes powerful once you have the conceptual foundation to use it effectively.
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How It Works
Step 1: Define Your Structure
You, the ICT expert or student, define the structural high and low for each timeframe, with their exact dates. This empowers you to control the analysis.
Based on your entries, the indicator establishes trend direction by timeframe and calculates Fibonacci retracement levels automatically.
* Structural High/Low: Key swing points that define external structure per ICT methodology
* Auto-Validation: Built-in autoscan feature confirms your pivot entries match actual price extremes
* Deterministic Behavior: Date stamps ensure the indicator behaves consistently across all sessions
Step 2: Monitor The Tables
Two tables provide a structural context:
Multi-Timeframe Analysis Table (top-right):
Current close, high, low, and 0.5 Fib for all three timeframes
Trend direction (↑/↓)
Days since structure established (i.e., "age" or maturity)
Current Fibonacci zone
Real-time alerts: Trend changes, breakouts, and trade bias signals
Detailed Fibonacci Table (middle-right):
All nine Fib retracement levels (1.0 to 0.0) for the selected timeframe
Exact price at each level
Percentage distance from current price
Visual marker showing current position
Step 3: Monitor The Chart
Visual elements show structure at a glance:
Fibonacci Retracement Zones: Color-coded bands show premium (red), discount (green), and equilibrium (gray) areas based on trend direction
Structural Lines: Red (high) and green (low) horizontal lines mark your defined pivots with automatic fill showing the current range (based on higher timeframe pivots)
Pivot Dots: Optional small markers highlight potential structural turning points on your current timeframe (reference only - always validate pivots yourself)
Trend Indicator: Top-center banner displays the selected timeframe's current trend
Auto-pivot points
Step 4: Get Alerts and Decide the Way Forward
Set one alert on the 1-hour chart only (if you set the alert on other timeframes, you may get delayed feedback).
You'll receive notifications when ANY of these events occur on ANY timeframe:
* Change of Character (ChoC): Trend reversal confirmed by price breaking the opposite structural level
* Break of Structure (BoS): Continuation confirmed by price breaking the same-direction structural level
* Trade Bias Signals: Price entering key Fibonacci zones (0.382-0.5 for longs in uptrend, 0.5-0.618 for shorts in downtrend, with + and ++ variants for deeper retracements)
* Reversal Warnings: Price entering extreme zones (0.882-1.0 or 0.0-0.118), suggesting potential trend exhaustion and reversal towards the opposite direction
All alerts fire once per bar close with a consolidated message showing which timeframes triggered and what conditions were met.
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Understanding the 3 Timeframes Hierarchy
The three timeframes may be conceived as nested layers of structure:
* 1-Week (Macro Bias) : May help you determine your core directional bias (long/short) in a mid-term perspective. The 1-Week TF may operate as your highest-conviction filter and help you contextualize shorter-term market moves (which may align or misalign with the trend appearing on such a timeframe).
* 1-Day (Swing Structure) : Operates within the weekly range. The daily structure can contradict the weekly structure temporarily (due to retracements, consolidations). This is where you may identify intermediate swing opportunities.
* 1-Hour (Execution Structure) : Operates within the daily range. It may help you identify entry timing and short-term bias. Can show opposite trends during retracements, and some traders look for alignment with higher timeframes as part of their setup criteria.
Example: Weekly uptrend (bullish bias) → Daily pulls back into downtrend (retracement phase) → Hourly shows uptrend resumption (this may be interpreted as an entry signal). All three trends can differ simultaneously, but when all three align (in one direction or another), you may start evaluating your moves.
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Using the Tool effectively
When this indicator signals a potential setup (entering key Fibonacci zones, structure breaks, or bias shifts), treat it as a starting point for deeper analysis, not a direct entry signal.
Before executing, consider using additional tools to refine timing:
Fair Value Gaps (FVG) : Identify imbalances where the price moved too quickly, leaving potential fill zones
Order Blocks : Locate the last opposing candle before a strong move - often institutional entry points
Liquidity Zones : Map where stop losses likely cluster (equal highs/lows, round numbers)
Premium/Discount Confirmation: Verify you're buying at a discount or selling at a premium relative to the current range
Session Timing/Kill Zones : Align entries with high-liquidity sessions (London/New York opens)
This indicator shows you where the structure sits and when it shifts. Your job is to combine that context with precise entry models. The alerts narrow your focus to high-probability zones - then you apply your edge within those zones.
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How to Set Up Alerts
This indicator monitors all three timeframes simultaneously and fires consolidated alerts when any condition triggers. Follow these steps to configure alerts properly:
Step 1: Set Your Chart to the 1-Hour Timeframe
Alerts must be created on the 1-hour chart for optimal timing
Do not use higher timeframes (4H, 1D, 1W) or alerts may be delayed
Lower timeframes (15M, 5M) will work but may generate more frequent notifications
Step 2: Open the Alert Menu
Click the "Alert" button (clock icon) in the top toolbar
Or use keyboard shortcut: Alt+A (Windows) / Option+A (Mac)
Step 3: Configure Alert Settings
Condition: Select "ICT Multi-Timeframe Market Structure Tracker "
Alert Type: Choose "Any alert() function call"
Options: Select "Once Per Bar Close"
Expiration: Set to "Open-ended alert" (no expiration)
Alert Name: Choose a descriptive name (e.g., "BTC Market Structure Alerts")
Step 4: Configure Notifications
Notification Methods: Check your preferred channels (app notification, email, webhook, etc.)
Sound: Optional — choose alert sound if desired
Step 5: Create Alert
Click the "Create" button
Alert is now active and will monitor all three timeframes
Important Notes:
You only need ONE alert setup total — it monitors 1W, 1D, and 1H simultaneously
Alert messages show which timeframe(s) triggered and what conditions were met
Alerts fire once per bar close to avoid mid-bar noise
If you change your structural pivot inputs, the alert continues working with new parameters
Example Alert Message:
BTC Market Structure Alert:
🟢 1D Bullish BoS
📈 1H Long Setup (0.382-0.5)
This tells you the 1-Day broke structure bullishly AND the 1-Hour entered a long setup zone — both events happened on the same bar close.
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Key Features
* Tracks 1-Week, 1-Day, and 1-Hour structure simultaneously
* Automatic Fibonacci retracement calculation (9 levels + extensions up or down, depending on timeframe trend)
* Real-time Change of Character and Break of Structure detection
* Color-coded premium/discount zone visualization
* Multi-condition alerts across all timeframes (single alert setup required)
* Autoscan validation to confirm manual pivot entry accuracy
* Timezone-adjustable for global markets
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Important Notes
* Requires ICT Knowledge: This is not a plug-and-play system. Understanding market structure, liquidity concepts, and Fibonacci confluence is essential for effective use.
* Manual Structure Definition: You define the structural pivots. The indicator tracks and alerts - it doesn't make trading decisions.
* Chart Timeframe: Set alerts on the 1-hour chart for optimal timing across all three monitored timeframes.
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Disclaimer
This indicator is for educational and informational purposes only. It does not constitute financial, investment, or trading advice.
The indicator:
* Makes no guarantees about future market performance
* Cannot predict market movements with certainty
* May generate false indications
* Relies on historical patterns that may not repeat
* Should not be used as the sole basis for trading decisions
Users are responsible for:
* Conducting independent research and analysis
* Understanding the risks of trading
* Making their own investment/divestment decisions
* Managing position sizes and risk exposure appropriately
Trading involves substantial risk and may not be suitable for all investors. Past performance does not guarantee future results. Users should only invest what they can afford to lose and consult qualified professionals before making financial decisions. The indicator’s assumptions may be invalidated by changing market conditions.
By using this tool, users acknowledge these limitations and accept full responsibility for their trading decisions.
Opening Range IndicatorComplete Trading Guide: Opening Range Breakout Strategy
What Are Opening Ranges?
Opening ranges capture the high and low prices during the first few minutes of market open. These levels often act as key support and resistance throughout the trading day because:
Heavy volume occurs at market open as overnight orders execute
Institutional activity is concentrated during opening minutes
Price discovery happens as market participants react to overnight news
Psychological levels are established that traders watch all day
Understanding the Three Timeframes
OR5 (5-Minute Range: 9:30-9:35 AM)
Most sensitive - captures immediate market reaction
Quick signals but higher false breakout rate
Best for scalping and momentum trading
Use for early entry when conviction is high
OR15 (15-Minute Range: 9:30-9:45 AM)
Balanced approach - most popular among day traders
Moderate sensitivity with better reliability
Good for swing trades lasting several hours
Primary timeframe for most strategies
OR30 (30-Minute Range: 9:30-10:00 AM)
Most reliable but slower signals
Lower false breakout rate
Best for position trades and trend following
Use when looking for major moves
Core Trading Strategies
Strategy 1: Basic Breakout
Setup:
Wait for price to break above OR15 high or below OR15 low
Enter on the breakout candle close
Stop loss: Opposite side of the range
Target: 2-3x the range size
Example:
OR15 range: $100.00 - $102.00 (Range = $2.00)
Long entry: Break above $102.00
Stop loss: $99.50 (below OR15 low)
Target: $104.00+ (2x range size)
Strategy 2: Multiple Confirmation
Setup:
Wait for OR5 break first (early signal)
Confirm with OR15 break in same direction
Enter on OR15 confirmation
Stop: Below OR30 if available, or OR15 opposite level
Why it works:
Multiple timeframe confirmation reduces false signals and increases probability of sustained moves.
Strategy 3: Failed Breakout Reversal
Setup:
Price breaks OR15 level but fails to hold
Wait for re-entry into the range
Enter reversal trade toward opposite OR level
Stop: Recent breakout high/low
Target: Opposite side of range + extension
Key insight: Failed breakouts often lead to strong moves in the opposite direction.
Advanced Techniques
Range Quality Assessment
High-Quality Ranges (Trade these):
Range size: 0.5% - 2% of stock price
Clean boundaries (not choppy)
Volume spike during range formation
Clear rejection at range levels
Low-Quality Ranges (Avoid these):
Very narrow ranges (<0.3% of stock price)
Extremely wide ranges (>3% of stock price)
Choppy, overlapping candles
Low volume during formation
Volume Confirmation
For Breakouts:
Look for volume spike (2x+ average) on breakout
Declining volume often signals false breakout
Rising volume during range formation shows interest
Market Context Filters
Best Conditions:
Trending market days (SPY/QQQ with clear direction)
Earnings reactions or news-driven moves
High-volume stocks with good liquidity
Volatility above average (VIX considerations)
Avoid Trading When:
Extremely low volume days
Major economic announcements pending
Holidays or half-days
Choppy, sideways market conditions
Risk Management Rules
Position Sizing
Conservative: Risk 0.5% of account per trade
Moderate: Risk 1% of account per trade
Aggressive: Risk 2% maximum per trade
Stop Loss Placement
Inside the range: Quick exit but higher stop-out rate
Outside opposite level: More room but larger risk
ATR-based: 1.5-2x Average True Range below entry
Profit Taking
Target 1: 1x range size (take 50% off)
Target 2: 2x range size (take 25% off)
Runner: Trail remaining 25% with moving stops
Specific Entry Techniques
Breakout Entry Methods
Method 1: Immediate Entry
Enter as soon as price closes above/below range
Fastest entry but highest false signal rate
Best for strong momentum situations
Method 2: Pullback Entry
Wait for breakout, then pullback to range level
Enter when price bounces off former resistance/support
Better risk/reward but may miss some moves
Method 3: Volume Confirmation
Wait for breakout + volume spike
Enter after volume confirmation candle
Reduces false signals significantly
Multiple Timeframe Entries
Aggressive: OR5 break → immediate entry
Conservative: OR5 + OR15 + OR30 all align → enter
Balanced: OR15 break with OR30 support → enter
Common Mistakes to Avoid
1. Trading Poor-Quality Ranges
❌ Don't trade ranges that are too narrow or too wide
✅ Focus on clean, well-defined ranges with good volume
2. Ignoring Volume
❌ Don't chase breakouts without volume confirmation
✅ Always check for volume spike on breakouts
3. Over-Trading
❌ Don't force trades when ranges are unclear
✅ Wait for high-probability setups only
4. Poor Risk Management
❌ Don't risk more than planned or use tight stops in volatile conditions
✅ Stick to predetermined risk levels
5. Fighting the Trend
❌ Don't fade breakouts in strongly trending markets
✅ Align trades with overall market direction
Daily Trading Routine
Pre-Market (8:00-9:30 AM)
Check overnight news and earnings
Review major indices (SPY, QQQ, IWM)
Identify potential opening range candidates
Set alerts for range breakouts
Market Open (9:30-10:00 AM)
Watch opening range formation
Note volume and price action quality
Mark key levels on charts
Prepare for breakout signals
Trading Session (10:00 AM - 4:00 PM)
Execute breakout strategies
Manage existing positions
Trail stops as profits develop
Look for additional setups
Post-Market Review
Analyze winning and losing trades
Review range quality vs. outcomes
Identify improvement areas
Prepare for next session
Best Stocks/ETFs for Opening Range Trading
Large Cap Stocks (Best for beginners):
AAPL, MSFT, GOOGL, AMZN, TSLA
High liquidity, predictable behavior
Good range formation most days
ETFs (Consistent patterns):
SPY, QQQ, IWM, XLF, XLE
Excellent liquidity
Clear range boundaries
Mid-Cap Growth (Advanced traders):
Stocks with good volume (1M+ shares daily)
Recent news catalysts
Clean technical patterns
Performance Optimization
Track These Metrics:
Win rate by range type (OR5 vs OR15 vs OR30)
Average R/R (risk vs reward ratio)
Best performing market conditions
Time of day performance
Continuous Improvement:
Keep detailed trade journal
Review failed breakouts for patterns
Adjust position sizing based on win rate
Refine entry timing based on backtesting
Final Tips for Success
Start small - Paper trade or use tiny positions initially
Focus on quality - Better to miss trades than take bad ones
Stay disciplined - Stick to your rules even during losing streaks
Adapt to conditions - What works in trending markets may fail in choppy conditions
Keep learning - Markets evolve, so should your approach
The opening range strategy is powerful because it captures natural market behavior, but like all strategies, it requires practice, discipline, and proper risk management to be profitable long-term.
The Black Sheep v1.0Black Sheep v1.0 is a comprehensive, multi-signal indicator designed to identify statistically significant market anomalies that often signal the activity of institutional traders or "smart money." The core principle is that institutional footprints are visible not in typical price action but in the unusual and statistically improbable events that deviate from the norm.
This indicator does not provide simple buy or sell signals. Instead, it acts as a powerful scanner, alerting you to moments of potential market manipulation, absorption, exhaustion, or stealth accumulation. Each signal is grounded in a statistical comparison of the current bar's price range and volume against a recent baseline, making it adaptive to any market and timeframe.
The name "Black Sheep" reflects the indicator's purpose: to find the bars that stand out from the flock—the anomalies that tell a deeper story about market dynamics.
Features
8 Unique Signals: Identifies distinct market phenomena, from stop hunts to absorption events.
Statistically Driven: Uses standard deviations for volume and range to define "unusual" activity, adapting automatically to changing market volatility.
Fully Customizable: Every parameter for every signal can be tweaked, allowing you to fine-tune the indicator's sensitivity to your specific trading instrument and style.
Clear Visual Alerts: Signals are plotted as clean, non-intrusive labels on the chart for immediate recognition.
Comprehensive Tooltips: Every setting is explained directly in the indicator's menu, making configuration intuitive.
The Signals Explained
Each of the 8 signals is designed to detect a specific type of market behavior.
1. Ghost Spike (Stop Hunt)
Concept: A sharp, sudden spike that breaks a recent high or low, only to reverse quickly. Crucially, this move happens on low volume, suggesting it lacks genuine market conviction. This is the classic signature of a stop hunt, designed to trigger stop-loss orders and trap retail traders.
Logic: Identifies bars with a very large range, a tiny body (wick-dominated), and volume that is statistically lower than average.
2. Absorption Candle (Iceberg Order)
Concept: Indicates a major battle between buyers and sellers at a key price level. This candle is characterized by massive volume but a very small body. It suggests a large passive order (an "iceberg order") is absorbing all the aggressive market orders, preventing price from moving. This is a sign of a strong support or resistance level being defended.
Logic: Detects bars with statistically massive volume but a price range that is mostly wicks.
3. VWAP Slingshot
Concept: The Volume-Weighted Average Price (VWAP) is a key benchmark for institutional traders. This signal identifies a sharp, high-volume rejection from the VWAP line. It signifies that price tested this important level and was forcefully "slingshotted" away, validating its importance as a dynamic support/resistance zone.
Logic: Triggers on a bar that touches the VWAP, has a long rejection wick (measured in ATRs), and is accompanied by high volume.
4. Session Close Markup
Concept: Highlights aggressive, high-volume buying or selling that occurs in the final minutes of a major trading session (e.g., the NYSE close). This can indicate institutions "marking up" or "marking down" the closing price for portfolio management or positioning themselves for the next session.
Logic: Fires within a user-defined window before the session close on candles with a large, decisive body and high volume.
5. Dawn Raid (Pre-Market Spike)
Concept: A "Dawn Raid" is a sudden burst of high-volume activity during the typically quiet and illiquid pre-market session. This is often the first sign of significant interest in an asset, usually triggered by news, an earnings release, or a large fund building a position before the market opens.
Logic: Detects candles in the pre-market session with volume that is multiple standard deviations above the average pre-market volume.
6. Liquidity Vacuum
Concept: Identifies periods of extremely low volume and price volatility. In these "vacuums," the market is thin, and even small orders can cause disproportionate price movement. These periods often precede explosive, high-volume breakouts, acting as the "calm before the storm."
Logic: Flags candles where both volume and range are a small fraction of their recent averages (ATR and average volume).
7. Delta Divergence
Concept: A classic pattern that signals weakening momentum. A bearish divergence occurs when price makes a higher high, but the candle's body ("delta") fails to confirm it, suggesting the upward thrust is losing power. A bullish divergence occurs when price makes a lower low, but the delta shows less downward conviction.
Logic: Compares recent price pivot highs/lows with the corresponding pivots of the candle's delta (close - open).
8. Fake Breakout (High Volume)
Concept: This signal captures a failed breakout attempt that occurs on high volume. Unlike the low-volume Ghost Spike, this pattern shows that there was a genuine attempt to break a level, but it was met with even stronger opposing force. This creates a powerful trap and often leads to a strong reversal.
Logic: Identifies a large-range breakout candle with a small body and high volume.
How to Use
The Black Sheep indicator should be used as a confluence tool, not a standalone system. The signals it generates are points of interest that warrant further investigation. Use them to:
Confirm or deny a trade thesis based on your existing strategy.
Identify potential market tops and bottoms.
Spot institutional trapping and positioning.
Understand the context behind price movements.
For best results, combine these signals with analysis of market structure, support/resistance levels, order flow, and other contextual clues. Adjust the input settings for each signal to match the volatility profile of the asset you are trading.
Smart Money Flow TrackerSmart Money Flow Tracker - Liquidity & Fair Value Gap Indicator
Overview
The Smart Money Flow Tracker is a comprehensive Pine Script indicator designed to identify and analyze institutional trading patterns through liquidity prints and Fair Value Gaps (FVGs). This advanced tool combines multiple analytical approaches to help traders understand where smart money is operating in the market, providing crucial insights for better trade timing and market structure analysis.
Core Functionality
1. Liquidity Prints Detection
The indicator identifies liquidity prints by analyzing pivot highs and lows that represent potential areas where institutional orders may be resting. Key features include:
Pivot-Based Analysis: Uses configurable pivot lengths (default 5) to identify significant highs and lows
Volume Confirmation: Optional volume filter ensures liquidity prints occur during periods of significant trading activity
Dynamic Labeling: Visual markers on chart showing liquidity print locations with customizable colors
Success Rate Tracking: Monitors how often liquidity prints lead to meaningful price reactions
2. Fair Value Gap (FVG) Analysis with Volume Integration
Advanced FVG detection that goes beyond basic gap identification:
Three-Bar Pattern Recognition: Identifies gaps where the high of bar 1 is below the low of bar 3 (bullish) or low of bar 1 is above high of bar 3 (bearish)
Volume-Enhanced Detection: Incorporates comprehensive volume analysis including:
Average volume calculation over configurable periods
Total volume across the 3-bar FVG pattern
Dominant volume bar identification
Volume ratio calculations for strength assessment
Volume Threshold Filtering: Optional minimum volume requirements to filter out low-conviction FVGs
Visual Enhancement: FVG boxes with volume-based coloring and detailed volume labels
3. Comprehensive Statistics Dashboard
Real-time statistics table displaying:
Total liquidity prints detected
Success rate percentage with dynamic color coding
Volume filter status
Total Fair Value Gaps identified
High-volume FVG count and percentage
All metrics update in real-time as new data becomes available
4. Advanced Alert System
Multiple alert conditions for different scenarios:
Standard liquidity print detection
Volume-confirmed liquidity prints
Bullish and bearish FVG formation
High-volume FVG alerts for institutional-grade setups
Key Input Parameters
Display Controls
Show Liquidity Prints: Toggle main functionality on/off
Show Statistics Table: Control visibility of the analytics dashboard
Show Fair Value Gaps: Enable/disable FVG detection and display
Technical Settings
Pivot Length: Adjusts sensitivity of liquidity print detection (1-20 range)
Volume Confirmation: Requires above-average volume for liquidity print validation
Volume Lookback: Period for calculating average volume (5-50 bars)
FVG Volume Settings
Show FVG Volume Info: Display detailed volume metrics on FVG labels
FVG Volume Threshold: Minimum volume multiplier for high-volume FVG classification
FVG Volume Average Period: Lookback period for FVG volume calculations
Visual Customization
Bullish/Bearish Colors: Separate color schemes for different market directions
Text Colors: Bright lime green for optimal visibility on all background types
Table Positioning: Flexible placement options for the statistics dashboard
Trading Applications & Use Cases
1. Institutional Order Flow Analysis
Liquidity Hunting: Identify areas where institutions may be targeting retail stops
Smart Money Tracking: Follow institutional footprints through volume-confirmed liquidity prints
Market Structure Understanding: Recognize key levels where large orders are likely resting
2. Fair Value Gap Trading Strategies
Gap Fill Trading: Trade the statistical tendency of FVGs to get filled
Volume-Confirmed Entries: Use high-volume FVGs as higher-probability trade setups
Institutional FVG Recognition: Focus on FVGs with dominant volume bars indicating institutional participation
3. Multi-Timeframe Analysis
Higher Timeframe Context: Use on daily/weekly charts to identify major institutional levels
Intraday Precision: Apply to lower timeframes for precise entry and exit timing
Cross-Timeframe Confirmation: Combine signals across multiple timeframes for enhanced accuracy
4. Risk Management Applications
Stop Loss Placement: Use liquidity print levels as logical stop loss areas
Position Sizing: Adjust position sizes based on volume confirmation and success rates
Trade Filtering: Use statistics dashboard to assess current market conditions
Technical Logic & Methodology
Liquidity Print Algorithm
Pivot Identification: Scans for pivot highs/lows using the specified lookback period
Volume Validation: Optionally confirms prints occur during above-average volume periods
Success Tracking: Monitors subsequent price action to calculate effectiveness rates
Dynamic Updates: Continuously updates statistics as new data becomes available
FVG Detection Process
Pattern Recognition: Identifies 3-bar patterns with qualifying gaps
Volume Analysis: Calculates comprehensive volume metrics across the pattern
Strength Assessment: Determines volume ratios and dominant bars
Classification: Categorizes FVGs based on volume thresholds and characteristics
Visual Representation: Creates boxes and labels with volume-based styling
Statistical Framework
Real-time Calculations: All metrics update with each new bar
Percentage-based Metrics: Success rates and volume confirmations shown as percentages
Color-coded Feedback: Visual indicators for quick assessment of current conditions
Historical Tracking: Maintains running totals throughout the session
Best Practices for Usage
1. Parameter Optimization
Start with default settings and adjust based on market conditions
Lower pivot lengths for more sensitive detection on volatile instruments
Higher volume thresholds for cleaner signals in high-volume markets
2. Market Context Consideration
Combine with broader market structure analysis
Consider economic events and news that may affect institutional flow
Adjust expectations based on market volatility and liquidity conditions
3. Integration with Other Analysis
Use alongside support/resistance levels for confluence
Combine with momentum indicators for timing confirmation
Integrate with volume profile analysis for additional context
Conclusion
The Smart Money Flow Tracker represents a sophisticated approach to institutional flow analysis, combining traditional liquidity concepts with modern volume analytics. By providing both visual signals and comprehensive statistics, it enables traders to make more informed decisions based on where smart money is likely operating in the market. The indicator's flexibility and customization options make it suitable for various trading styles and timeframes, from scalping to position trading.
Trend Bars with Okuninushi Line Filter# Trend Bars with Okuninushi Line Filter: A Powerful Trading Indicator
## Introduction
The **Trend Bars with Okuninushi Line Filter** is an innovative technical indicator that combines two powerful concepts: trend bar analysis and the Okuninushi Line filter. This indicator helps traders identify high-quality trending moves by analyzing candle body strength relative to the overall price range while ensuring the price action aligns with the dominant market structure.
## What Are Trend Bars?
Trend bars are candles where the body (distance between open and close) represents a significant portion of the total price range (high to low). These bars indicate strong directional momentum with minimal indecision, making them valuable signals for trend continuation.
### Key Characteristics:
- **Strong directional movement**: Large body relative to total range
- **Minimal upper/lower shadows**: Shows sustained pressure in one direction
- **High conviction**: Represents decisive market action
## The Okuninushi Line Filter
The Okuninushi Line, also known as the Kijun Line in Ichimoku analysis, is calculated as the midpoint of the highest high and lowest low over a specified period (default: 52 periods).
**Formula**: `(Highest High + Lowest Low) / 2`
This line acts as a dynamic support/resistance level and trend filter, helping to:
- Identify the overall market bias
- Filter out counter-trend signals
- Provide confluence for trade entries
## How the Indicator Works
The indicator combines these two concepts with the following logic:
### Bull Trend Bars (Green)
A candle is colored **green** when ALL conditions are met:
1. **Bullish candle**: Close > Open
2. **Strong body**: |Close - Open| ≥ Threshold × (High - Low)
3. **Above trend filter**: Close > Okuninushi Line
### Bear Trend Bars (Red)
A candle is colored **red** when ALL conditions are met:
1. **Bearish candle**: Close < Open
2. **Strong body**: |Close - Open| ≥ Threshold × (High - Low)
3. **Below trend filter**: Close < Okuninushi Line
### Neutral Bars (Gray)
All other candles that don't meet the complete criteria are colored **gray**.
## Customizable Parameters
### Trend Bar Threshold
- **Range**: 10% to 100%
- **Default**: 75%
- **Purpose**: Controls how "strong" a candle must be to qualify as a trend bar
**Threshold Effects:**
- **Low (10-30%)**: More sensitive, catches smaller trending moves
- **Medium (50-75%)**: Balanced approach, filters out most noise
- **High (80-100%)**: Very selective, only captures the strongest moves
### Okuninushi Line Length
- **Default**: 52 periods
- **Purpose**: Determines the lookback period for calculating the midpoint
- **Common Settings**:
- 26 periods: More responsive to recent price action
- 52 periods: Standard setting, good balance
- 104 periods: Longer-term trend perspective
## Trading Applications
### 1. Trend Continuation Signals
- **Green bars**: Look for bullish continuation opportunities
- **Red bars**: Consider bearish continuation setups
- **Gray bars**: Exercise caution, mixed signals
### 2. Market Structure Analysis
- Clusters of same-colored bars indicate strong trends
- Alternating colors suggest choppy, indecisive markets
- Transition from red to green (or vice versa) may signal trend changes
### 3. Entry Timing
- Use colored bars as confirmation for existing trade setups
- Wait for color alignment with your market bias
- Avoid trading during predominantly gray periods
### 4. Risk Management
- Gray bars can serve as early warning signs of weakening trends
- Color changes might indicate appropriate exit points
- Use in conjunction with other risk management tools
## Advantages
1. **Dual Filtering**: Combines momentum (trend bars) with trend direction (Okuninushi Line)
2. **Visual Clarity**: Immediate visual feedback through candle coloring
3. **Customizable**: Adjustable parameters for different trading styles
4. **Versatile**: Works across multiple timeframes and instruments
5. **Objective**: Rule-based system reduces subjective interpretation
## Limitations
1. **Lagging Nature**: Based on historical price data
2. **False Signals**: Can produce whipsaws in choppy markets
3. **Parameter Sensitivity**: Requires optimization for different instruments
4. **Market Conditions**: May be less effective in ranging markets
## Best Practices
### Optimization Tips:
- **Volatile Markets**: Use higher thresholds (80-90%)
- **Steady Trends**: Use moderate thresholds (60-75%)
- **Short-term Trading**: Shorter Okuninushi Line periods (26)
- **Long-term Analysis**: Longer Okuninushi Line periods (104+)
### Combination Strategies:
- Pair with volume indicators for confirmation
- Use alongside support/resistance levels
- Combine with other trend-following indicators
- Consider market context and overall trend direction
## Conclusion
The Trend Bars with Okuninushi Line Filter offers traders a sophisticated yet intuitive way to identify high-quality trending moves. By combining the momentum characteristics of trend bars with the directional filter of the Okuninushi Line, this indicator helps traders focus on the most promising opportunities while avoiding low-probability setups.
Remember that no single indicator should be used in isolation. Always consider market context, risk management, and other technical factors when making trading decisions. The true power of this indicator lies in its ability to quickly highlight periods of strong, aligned price action – exactly what trend traders are looking for.
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*Disclaimer: This article is for educational purposes only and should not be considered as financial advice. Always conduct your own research and consider your risk tolerance before making any trading decisions.*
Trend FriendTrend Friend — What it is and how to use it
I built Trend Friend to stop redrawing the same trendlines all day. It automatically connects confirmed swing points (fractals) and keeps the most relevant lines in front of you. The goal: give you clean, actionable structure without the guesswork.
What it does (in plain English)
Finds swing highs/lows using a Fractal Period you choose.
Draws auto-trendlines between the two most recent confirmed highs and the two most recent confirmed lows.
Colours by intent:
Lines drawn from highs (potential resistance / bearish) = Red
Lines drawn from lows (potential support / bullish) = Green
Keeps the chart tidy: The newest lines are styled as “recent,” older lines are dimmed as “historical,” and it prunes anything beyond your chosen limit.
Optional crosses & alerts: You can highlight when price closes across the most recent line and set alerts for new lines formed and upper/lower line crosses.
Structure labels: It tags HH, LH, HL, LL at the swing points, so you can quickly read trend/rotation.
How it works (under the hood)
A “fractal” here is a confirmed pivot: the highest high (or lowest low) with n bars on each side. That means pivots only confirm after n bars, so signals are cleaner and less noisy.
When a new pivot prints, the script connects it to the prior pivot of the same type (high→high, low→low). That gives you one “bearish” line from highs and one “bullish” line from lows.
The newest line is marked as recent (brighter), and the previous recent line becomes historical (dimmed). You can keep as many pairs as you want, but I usually keep it tight.
Inputs you’ll actually use
Fractal Period (n): this is the big one. It controls how swingy/strict the pivots are.
Lower n → more swings, more lines (faster, noisier)
Higher n → fewer swings, cleaner lines (slower, swing-trade friendly)
Max pair of lines: how many pairs (up+down) to keep on the chart. 1–3 is a sweet spot.
Extend: extend lines Right (my default) or Both ways if you like the context.
Line widths & colours: recent vs. historical are separate so you can make the active lines pop.
Show crosses: toggle the X markers when price crosses a line. I turn this on when I’m actively hunting breakouts/retests.
Reading the chart
Red lines (from highs): I treat these as potential resistance. A clean break + hold above a red line often flips me from “fade” to “follow.”
Green lines (from lows): Potential support. Same idea in reverse: break + hold below and I stop buying dips until I see structure reclaim.
HH / LH / HL / LL dots: quick read on structure.
HH/HL bias = uptrend continuation potential
LH/LL bias = downtrend continuation potential
Mixed prints = rotation/chop—tighten risk or wait for clarity.
My H1 guidance (fine-tuning Fractal Period)
If you’re mainly on H1 (my use case), tune like this:
Fast / aggressive: n = 6–8 (lots of signals, good for momentum days; more chop risk)
Balanced (recommended): n = 9–12 (keeps lines meaningful but responsive)
Slow / swing focus: n = 13–21 (filters noise; better for trend days and higher-TF confluence)
Rule of thumb: if you’re getting too many touches and whipsaws, increase n. If you’re late to obvious breaks, decrease n.
How I trade it (example workflow)
Pick your n for the session (H1: start at 9–12).
Mark the recent red & green lines. That’s your immediate structure.
Look for interaction:
Rejections from a line = fade potential back into the range.
Break + close across a line = watch the retest for continuation.
Confirm with context: session bias, HTF structure, and your own tools (VWAP, RSI, volume, FVG/OB, etc.).
Plan the trade: enter on retest or reclaim, stop beyond the line/last swing, target the opposite side or next structure.
Alerts (set and forget)
“New trendline formed” — fires when a new high/low pivot confirms and a fresh line is drawn.
“Upper/lower trendline crossed” — fires when price crosses the most recent red/green line.
Use these to track structure shifts without staring at the screen.
Good to know (honest limitations)
Confirmation lag: pivots need n bars on both sides, so signals arrive after the swing confirms. That’s by design—less noise, fewer fake lines.
Lines update as structure evolves: when a new pivot forms, the previous “recent” line becomes “historical,” and older ones can be removed based on your max setting.
Not an auto trendline crystal ball: it won’t predict which line holds or breaks—it just keeps the most relevant structure clean and up to date.
Final notes
Works on any timeframe; I built it with H1 in mind and scale to H4/D1 by increasing n.
Pairs nicely with session tools and VWAP for intraday, or with supply/demand / FVGs for swing planning.
Risk first: lines are structure, not guarantees. Manage position size and stops as usual.
Not financial advice. Trade your plan. Stay nimble.
ICT Sessions & Killzones +PRO (VinceFxBT)ICT Sessions & Killzones +PRO (VinceFxBT)
All in one Session and Killzone script for FX, Futures and Crypto markets. It includes London, New York, CBDR & Asia Sessions and Killzones.
Features
Includes London, New York, Asia, CBDR sessions
Includes all ICT Killzones
Extended session highs/lows up to 90s back, until mitigated.
Set recurring alerts for session highs and lows
Includes Indices price levels and opens
Uses UTC timezones with automatic Daylight Saving Time so NO timezone correction needed ; ) Works out of the box for all regions, including different dates of DST for US/EU.
Session highs/lows displayed on chart as lines, box or background color
Customize line styles, width and colors
Customize colors for Sessions and Killzones
Optionally include weekends for Session or Killzone separately
Optionally display day separators and labels
Fully control which options are displayed at higher or lower timeframes. (e.g. hide sessions when timeframe is 1h or higher)
Session display options
Session Background Color.
Session High & Low Lines, including Session Middle Line.
Extended session highs/lows until mitigated
Extended Session Highs & Lows until mitigated.
Session Background Color with extended Asia Session Highs & Lows until mitigated.
Set recurring alerts for session highs and lows
Set automatic alerts when previous and/or current session levels are broken.
4-Hour Range HighlighterThe 4-Hour Range Highlighter is a powerful visual analysis tool designed for traders operating on lower timeframes (like 5m, 15m, or 1H). It overlays the critical price range of the 4-hour (4H) candlestick onto your chart, providing immediate context from a higher timeframe. This helps you align your intraday trades with the dominant higher-timeframe structure, identifying key support and resistance zones, breakouts, and market volatility at a glance.
Key Features:
Visual Range Overlay: Draws a semi-transparent colored background spanning the entire High and Low of each 4-hour period.
Trend-Based Coloring: Automatically colors the range based on the 4H candle's direction:
Green: Bullish 4H candle (Close > Open)
Red: Bearish 4H candle (Close < Open)
Blue: Neutral 4H candle (Close = Open)
Customizable High/Low Lines: Optional, subtle lines plot the exact high and low of the 4H bar, acting as dynamic support/resistance levels.
Fully Customizable: Easily change colors and toggle visual elements on/off in the settings to match your chart's theme.
How to Use It:
Identify Key Levels: The top and bottom of the shaded area represent significant intraday support and resistance. Watch for price reactions at these levels.
Trade in Context: Use the trend color to gauge sentiment. For example, look for buy opportunities near the low of a bullish (green) 4H range.
Spot Breakouts: A strong candle closing above the high or below the low of the current 4H range can signal a continuation or the start of a new strong move.
Gauge Volatility: A large shaded area indicates a high-volatility 4H period. A small area suggests consolidation or low volatility.
Settings:
Visual Settings: Toggle the background and choose colors for Bullish, Bearish, and Neutral ranges.
Line Settings: Toggle the high/low lines and customize their colors.
Note: This is a visual aid, not a standalone trading system. It provides context but does not generate buy/sell signals. Always use it in conjunction with your own analysis and risk management.
Perfect for Day Traders, Swing Traders, and anyone who needs higher-timeframe context on their chart!
How to Use / Instructions:
After adding the script to your chart, open the settings menu (click on the indicator's name and then the gear icon).
In the "Inputs" tab, you will find two groups: "Visual Settings" and "Line Settings".
In Visual Settings, you can:
Toggle Show 4H Range Background on/off.
Change the Bullish Color, Bearish Color, and Neutral Color for the transparent background.
In Line Settings, you can:
Toggle Show High/Low Lines on/off.
Change the line colors for each trend type.
Adjust the colors to your preference. The default settings use transparency for a clean look that doesn't clutter the chart.
BTC/USD 3-Min Binary Prediction [v7.2 EN]BTC/USD 3-Minute Binary Prediction Indicator v7.2 - Complete Guide
Overview
This is an advanced technical analysis indicator designed for Bitcoin/USD binary options trading with 3-minute expiration times. The system aims for an 83% win rate by combining multiple analysis layers and pattern recognition.
How It Works
Core Prediction Logic
- Timeframe: Predicts whether BTC price will be ±$25 higher (HIGH) or lower (LOW) after 3 minutes
- Entry Signals: Generates HIGH/LOW signals when confidence exceeds threshold (default 75%)
- Verification: Automatically tracks and displays win/loss statistics in real-time
5-Layer Filter System
The indicator uses a sophisticated scoring system (0-100 points):
1. Trend Filter (25 points) - Analyzes EMA alignments and price momentum
2. Leading Indicators (25 points) - RSI and MACD divergence analysis
3. Volume Confirmation (20 points) - Detects unusual volume patterns
4. Support/Resistance (15 points) - Identifies key price levels
5. Momentum Alignment (15 points) - Measures acceleration and deceleration
Pattern Recognition
Automatically detects and visualizes:
- Double Tops/Bottoms - Reversal patterns
- Triangles - Ascending, descending, symmetrical
- Channels - Trending price channels
- Candlestick Patterns - Engulfing, hammer, hanging man
Multi-Timeframe Analysis
- Uses 1-minute and 5-minute data for confirmation
- Aligns multiple timeframes for higher probability trades
- Monitors trend consistency across timeframes
Key Features
Display Panels
1. Statistics Panel (Top Right)
- Overall win rate percentage
- Hourly performance (wins/losses)
- Daily performance
- Current system status
2. Analysis Panel (Left Side)
- Market trend analysis
- RSI status (overbought/oversold)
- Volume conditions
- Filter scores for each component
- Final HIGH/LOW/WAIT decision
Visual Signals
- Green Triangle (↑) = HIGH prediction
- Red Triangle (↓) = LOW prediction
- Yellow Background = Entry opportunity
- Blue Background = Waiting for result
Configuration Options
Basic Settings
- Range Width: Target price movement (default $50 = ±$25)
- Min Confidence: Minimum confidence to enter (default 75%)
- Max Daily Trades: Risk management limit (default 5)
Filters (Can be toggled on/off)
- Trend Filter
- Volume Confirmation
- Support/Resistance Filter
- Momentum Alignment
Display Options
- Show/hide signals, statistics, analysis
- Minimal Mode for cleaner charts
- EMA line visibility
Important Risk Warnings
Binary Options Trading Risks:
1. High Risk Product - Binary options are extremely risky and banned in many countries
2. Not Investment Advice - This tool is for educational/analytical purposes only
3. No Guaranteed Returns - Past performance doesn't predict future results
4. Capital at Risk - You can lose your entire investment in seconds
Technical Limitations:
- Requires stable internet connection
- Performance varies with market conditions
- High volatility can reduce accuracy
- Not suitable for news events or low liquidity periods
Best Practices
1. Paper Trade First - Test thoroughly on demo accounts
2. Risk Management - Never risk more than 1-2% per trade
3. Market Conditions - Works best in normal volatility conditions
4. Avoid Major Events - Don't trade during major news releases
5. Monitor Performance - Track your actual results vs displayed statistics
Setup Instructions
1. Add to TradingView chart (BTC/USD preferred)
2. Use 30-second or 1-minute chart timeframe
3. Adjust settings based on your risk tolerance
4. Monitor F-Score (should be >65 for entries)
5. Wait for clear HIGH/LOW signals with high confidence
Alert Configuration
The indicator provides three alert types:
- HIGH Signal alerts
- LOW Signal alerts
- General entry opportunity alerts
Legal Disclaimer
Binary options trading may not be legal in your jurisdiction. Many countries including the USA, Canada, and EU nations have restrictions or outright bans on binary options. Always check local regulations and consult with financial advisors before trading.
Remember: This is a technical analysis tool, not a money-printing machine. Successful trading requires discipline, risk management, and continuous learning. The displayed statistics are historical and don't guarantee future performance.
