ATR PivotsThe "ATR Pivots" script is a technical analysis tool designed to help traders identify key levels of support and resistance on a chart. The indicator uses various metrics such as the Average True Range (ATR), Daily True Range ( DTR ), Daily True Range Percentage (DTR%), Average Daily Range (ADR), Previous Day High ( PDH ), and Previous Day Low ( PDL ) to provide a comprehensive picture of the volatility and movement of a security. The script also includes an EMA cloud and 200 EMA for trend identification and a 1-minute ATR scalping strategy for traders to make informed trading decisions.
ATR Detail:-
The ATR is a measure of the volatility of a security over a given period of time. It is calculated by taking the average of the true range (the difference between the high and low of a security) over a set number of periods. The user can input the number of periods (ATR length) to be used for the ATR calculation. The script also allows the user to choose whether to use the current close or not for the calculation. The script calculates various levels of support and resistance based on the relationship between the security's range ( high-low ) and the ATR. The levels are calculated by multiplying the ATR by different Fibonacci ratios (0.236, 0.382, 0.5, 0.618, 0.786, 1.000) and then adding or subtracting the result from the previous close. The script plots these levels on the chart, with the -100 level being the most significant level. The user also has an option to choose whether to plot all Fibonacci levels or not.
DTR and DTR% Detail:-
The Daily True Range Percentage (DTR%) is a metric that measures the daily volatility of a security as a percentage of its previous close. It is calculated by dividing the Daily True Range ( DTR ) by the previous close. DTR is the range between the current period's high and low and gives a measure of the volatility of the security on a daily basis. DTR% can be used as an indicator of the percentage of movement of the security on a daily basis. In this script, DTR% is used in combination with other metrics such as the Average True Range (ATR) and Fibonacci ratios to calculate key levels of support and resistance for the security. The idea behind using DTR% is that it can help traders to better understand the daily volatility of the security and make more informed trading decisions.
For example, if a security has a DTR% of 2%, it suggests that the security has a relatively low level of volatility and is less likely to experience significant price movements on a daily basis. On the other hand, if a security has a DTR% of 10%, it suggests that the security has a relatively high level of volatility and is more likely to experience significant price movements on a daily basis.
ADR:-
The script then calculates the ADR (Average Daily Range) which is the average of the daily range of the security, using the formula (Period High - Period Low) / ATR Length. This gives a measure of the average volatility of the security on a daily basis, which can be useful for determining potential levels of support and resistance .
PDH /PDL:-
The script also calculates PDH (Previous Day High) and PDL (Previous Day Low) which are the High and low of the previous day of the security. This gives a measure of the previous day's volatility and movement, which can be useful for determining potential levels of support and resistance .
EMA Cloud and 200 EMA Detail:-
The EMA cloud is a technical analysis tool that helps traders identify the trend of the market by comparing two different exponential moving averages (EMAs) of different lengths. The cloud is created by plotting the fast EMA and the slow EMA on the chart and filling the space between them. The user can input the length of the fast and slow EMA , and the script will calculate and plot these EMAs on the chart. The space between the two EMAs is then filled with a color that represents the trend, with green indicating a bullish trend and red indicating a bearish trend . Additionally, the script also plots a 200 EMA , which is a commonly used long-term trend indicator. When the fast EMA is above the slow EMA and the 200 EMA , it is considered a bullish signal, indicating an uptrend. When the fast EMA is below the slow EMA and the 200 EMA , it is considered a bearish signal, indicating a downtrend. The EMA cloud and 200 EMA can be used together to help traders identify the overall trend of the market and make more informed trading decisions.
1 Minute ATR Scalping Strategy:-
The script also includes a 1-minute ATR scalping strategy that can be used by traders looking for quick profits in the market. The strategy involves using the ATR levels calculated by the script as well as the EMA cloud and 200 EMA to identify potential buy and sell opportunities. For example, if the 1-minute ATR is above 11 in NIFTY and the EMA cloud is bullish , the strategy suggests buying the security. Similarly, if the 1-minute ATR is above 30 in BANKNIFTY and the EMA cloud is bullish , the strategy suggests buying the security.
Inside Candle:-
The Inside Candle is a price action pattern that occurs when the current candle's high and low are entirely within the range of the previous candle's high and low. This pattern indicates indecision or consolidation in the market and can be a potential sign of a trend reversal. When used in the 15-minute chart, traders can look for Inside Candle patterns that occur at key levels of support or resistance. If the Inside Candle pattern occurs at a key level and the price subsequently breaks out of the range of the Inside Candle, it can be a signal to enter a trade in the direction of the breakout. Traders can also use the Inside Candle pattern to trade in a tight range, or to reduce their exposure to a current trend.
Risk Management:-
As with any trading strategy, it is important to practice proper risk management when using the ATR Pivots script and the 1-minute ATR scalping strategy. This may include setting stop-loss orders, using appropriate position sizing, and diversifying your portfolio. It is also important to note that past performance is not indicative of future results and that the script and strategy provided are for educational purposes only.
In conclusion, the "ATR Pivots" script is a powerful tool that can help traders identify key levels of support and resistance , as well as trend direction. The additional metrics such as DTR , DTR%, ADR, PDH , and PDL provide a more comprehensive picture of the volatility and movement of the security, making it easier for traders to make better trading decisions. The inclusion of the EMA cloud and 200 EMA for trend identification, and the 1-minute ATR scalping strategy for quick profits can further enhance a trader's decision-making process. However, it is important to practice proper risk management and understand that past performance is not indicative of future results.
Special thanks to satymahajan for the idea of clubbing Average True Range with Fibonacci levels.
Search in scripts for "Exponential Moving Average"
Fast EMA above Slow EMA with MACD (by Coinrule)An exponential moving average ( EMA ) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average . An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average ( SMA ), which applies an equal weight to all observations in the period.
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
The result of that calculation is the MACD line. A nine-day EMA of the MACD called the "signal line," is then plotted on top of the MACD line, which can function as a trigger for buy and sell signals. Traders may buy the coin when the MACD crosses above its signal line and sell—or short—the security when the MACD crosses below the signal line. Moving average convergence divergence ( MACD ) indicators can be interpreted in several ways, but the more common methods are crossovers, divergences, and rapid rises/falls.
The Strategy enters and closes the trade when the following conditions are met:
LONG
The MACD histogram turns bullish
EMA8 is greater than EMA26
EXIT
Price increases 3% trailing
Price decreases 1% trailing
This strategy is back-tested from 1 January 2022 to simulate how the strategy would work in a bear market and provides good returns.
Pairs that produce very strong results include AXSUSDT on the 5-minute timeframe. This short timeframe means that this strategy opens and closes trades regularly.
Additionally, the trailing stop loss and take profit conditions can also be changed to match your needs.
The strategy assumes each order is using 30% of the available coins to make the results more realistic and to simulate you only ran this strategy on 30% of your holdings. A trading fee of 0.1% is also taken into account and is aligned to the base fee applied on Binance.
SUPER MACD📈 MACD Indicator Update - Version 2
🔹 New Features and Improvements:
1️⃣ New MACD Calculation Options:
Users can now choose from various Moving Averages to calculate the MACD. The default options are SMA (Simple Moving Average) and EMA (Exponential Moving Average), but there are 14 other versions available to experiment with:
SMA (Simple Moving Average)
EMA (Exponential Moving Average)
WMA (Weighted Moving Average)
RMA (Smoothed Moving Average)
HMA (Hull Moving Average)
JMA (Jurik Moving Average)
DEMA (Double Exponential Moving Average)
TEMA (Triple Exponential Moving Average)
LSMA (Least Squares Moving Average)
VWMA (Volume-Weighted Moving Average)
SMMA (Smoothed Moving Average)
KAMA (Kaufman’s Adaptive Moving Average)
ALMA (Arnaud Legoux Moving Average)
FRAMA (Fractal Adaptive Moving Average)
VIDYA (Variable Index Dynamic Average)
2️⃣ Improved Input Visibility and Organization:
We’ve reorganized the inputs so that the most commonly used ones are now placed at the beginning for quicker and more convenient configuration.
3️⃣ Bug Fixes and Code Improvements:
Minor bugs have been fixed, and the code has been optimized for better stability and performance. The code is now cleaner and fully functional in version 6.
4️⃣ Cometreon Public Library Integration:
To lighten the code and improve its modularity, we’ve integrated the Cometreon public library. This makes the code more efficient and reduces the need to duplicate common functions.
☄️ With this update, the MACD indicator becomes even more versatile and user-friendly, offering a wide range of calculation methods and an improved interface!
oussamacryptoWhat Is an Exponential Moving Average (EMA)?
An exponential moving average (EMA) is a type of moving average (MA) that places a greater weight and significance on the most recent data points. The exponential moving average is also referred to as the exponentially weighted moving average. An exponentially weighted moving average reacts more significantly to recent price changes than a simple moving average simple moving average (SMA), which applies an equal weight to all observations in the period.
Fisher Transform of MACD w/ Quantile Bands [Loxx]Fisher Transform of MACD w/ Quantile Bands is a Fisher Transform indicator with Quantile Bands that takes as it's source a MACD. The MACD has two different source inputs for fast and slow moving averages.
What is Fisher Transform?
The Fisher Transform is a technical indicator created by John F. Ehlers that converts prices into a Gaussian normal distribution.
The indicator highlights when prices have moved to an extreme, based on recent prices. This may help in spotting turning points in the price of an asset. It also helps show the trend and isolate the price waves within a trend.
What is Quantile Bands?
In statistics and the theory of probability, quantiles are cutpoints dividing the range of a probability distribution into contiguous intervals with equal probabilities, or dividing the observations in a sample in the same way. There is one less quantile than the number of groups created. Thus quartiles are the three cut points that will divide a dataset into four equal-size groups (cf. depicted example). Common quantiles have special names: for instance quartile, decile (creating 10 groups: see below for more). The groups created are termed halves, thirds, quarters, etc., though sometimes the terms for the quantile are used for the groups created, rather than for the cut points.
q-Quantiles are values that partition a finite set of values into q subsets of (nearly) equal sizes. There are q − 1 of the q-quantiles, one for each integer k satisfying 0 < k < q. In some cases the value of a quantile may not be uniquely determined, as can be the case for the median (2-quantile) of a uniform probability distribution on a set of even size. Quantiles can also be applied to continuous distributions, providing a way to generalize rank statistics to continuous variables. When the cumulative distribution function of a random variable is known, the q-quantiles are the application of the quantile function (the inverse function of the cumulative distribution function) to the values {1/q, 2/q, …, (q − 1)/q}.
What is MACD?
Moving average convergence divergence ( MACD ) is a trend-following momentum indicator that shows the relationship between two moving averages of a security’s price. The MACD is calculated by subtracting the 26-period exponential moving average ( EMA ) from the 12-period EMA .
Included:
Zero-line and signal cross options for bar coloring, signals, and alerts
Alerts
Signals
Loxx's Expanded Source Types
35+ moving average types
STD Stepped Ehlers Optimal Tracking Filter MTF w/ Alerts [Loxx]STD Stepped Ehlers Optimal Tracking Filter MTF w/ Alerts is the traditional Ehlers Optimal Tracking Filter but with stepped price levels, access to multiple time frames, and alerts.
What is Ehlers Optimal Tracking Filter?
From "OPTIMAL TRACKING FILTERS" by John Ehlers:
"Dr. R.E. Kalman introduced his concept of optimum estimation in 1960. Since that time, his technique has proven to be a powerful and practical tool. The approach is particularly well suited for optimizing the performance of modern terrestrial and space navigation systems. Many traders not directly involved in system analysis have heard about Kalman filtering and have expressed an interest in learning more about it for market applications. Although attempts have been made to provide simple, intuitive explanations, none has been completely successful. Almost without exception, descriptions have become mired in the jargon and state-space notation of the “cult”.
Surprisingly, in spite of the obscure-looking mathematics (the most impenetrable of which can be found in Dr. Kalman’s original paper), Kalman filtering is a fairly direct and simple concept. In the spirit of being pragmatic, we will not deal with the full-blown matrix equations in this description and we will be less than rigorous in the application to trading. Rigorous application requires knowledge of the probability distributions of the statistics. Nonetheless we end with practically useful results. We will depart from the classical approach by working backwards from Exponential Moving Averages. In this process, we introduce a way to create a nearly zero lag moving average. From there, we will use the concept of a Tracking Index that optimizes the filter tracking for the given uncertainty in price movement and the uncertainty in our ability to measure it."
Included:
-Standard deviation stepping filter, price is required to exceed XX deviations before the moving average line shifts direction
-Selection of filtering based on source price, the moving average, or both; you can also set the Filter deviations to 0 for no filtering at all
-Toggle on/off bar coloring
-Toggle on/off signals
-Long/Short alerts
AMASling - All Moving Average Sling ShotThis indicator modifies the SlingShot System by Chris Moody to allow it to be based on 'any' Fast and Slow moving average pair. Open Long / Close Long / Open Short / Close Short alerts can be generated for automated bot trading based on the SlingShot strategy:
• Conservative Entry = Fast MA above Slow MA, and previous bar close below Fast MA, and current price above Fast MA
• Conservative Entry = Fast MA below Slow MA, and previous bar close above Fast MA, and current price below Fast MA
• Aggressive Entry = Fast MA above Slow MA, and price below Fast MA
• Aggressive Exit = Fast MA below Slow MA, and price above Fast MA
Entries and exits can also be made based on moving average crossovers, I initially put this in to make it easy to compare to a more standard strategy, but upon backtesting combining crossovers with the SlingShot appeared to produce better results on some charts.
Alerts can also be filtered to allow long deals only when the fast moving average is above the slow moving average (uptrend) and short deals only when the fast moving average is below the slow moving averages (downtrend).
If you have a strategy that can buy based on External Indicators you can use the 'Backtest Signal' which plots the values set in the 'Long / Short Signals' section.
The Fast, Slow and Signal Moving Averages can be set to:
• Simple Moving Average (SMA)
• Exponential Moving Average (EMA)
• Weighted Moving Average (WMA)
• Volume-Weighted Moving Average (VWMA)
• Hull Moving Average (HMA)
• Exponentially Weighted Moving Average (RMA) (SMMA)
• Linear regression curve Moving Average (LSMA)
• Double EMA (DEMA)
• Double SMA (DSMA)
• Double WMA (DWMA)
• Double RMA (DRMA)
• Triple EMA (TEMA)
• Triple SMA (TSMA)
• Triple WMA (TWMA)
• Triple RMA (TRMA)
• Symmetrically Weighted Moving Average (SWMA) ** length does not apply **
• Arnaud Legoux Moving Average (ALMA)
• Variable Index Dynamic Average (VIDYA)
• Fractal Adaptive Moving Average (FRAMA)
'Backtest Signal' and 'Deal State' are plotted to display.none, so change the Style Settings for the chart if you need to see them for testing.
Yes I did choose the name because 'It's Amasling!'
Exponentially Deviating Moving Average (MZ EDMA)Exponentially Deviating Moving Average (MZ EDMA) is derived from Exponential Moving Average to predict better exit in top reversal case.
EDMA Philosophy
EDMA is calculated in following steps:
In first step, Exponentially expanding moving line is calculated with same code as of EMA but with different smoothness (1 instead of 2).
In 2nd step, Exponentially contracting moving line is calculated using 1st calculated line as source input and also using same code as of EMA but with different smoothness (1 instead of 2).
In 3rd step, Hull Moving Average with 3/2 of EDMA length is calculated using final line as source input. This final HMA will be equal to Exponentially Deviating Moving Average.
EDMA Advantages
EDMA's main advantage is that in case of top price reversal it deviates from conventional EMA of 2*Length. This benefits in using EDMA for EMA cross with quick signals avoiding unnecessary crossovers. EDMA's deviation in case of top reversal can be seen as below:
EDMA presents better smoothened curve which acts as better Support and resistance. EDMA coparison with conventional EMA of 2*length of EDMA is as follows.
Additional Features
EMA Band: EMA band is shown on chart to better visualize EMA cross with EDMA.
Dynamic Coloring: Chikou Filter library is used for derivation of dynamic coloring of EDMA and its band.
Alerts: Alerts are provided of all trade signals. Weak buy/sell would trigger if EMA of 2*EDMA_length crosses EDMA. Strong buy/sell would trigger if EMA of same length as of EDMA crosses EDMA.
Trade Confirmation with Chikou Filter: Trend filteration from Chikou filter library is used as an option to enhance trades signals accuracy.
Defaults
Currently default EDMA and EMA1 length is set to 20 period which I've found better for higher timeframes but this can be adjusted according to user's timeframe. I would soon add Multi Timeframe option in script too. Chikou filter's period is set to 25.
MTF MACD (PPO) [TANHEF]Mult-Timeframe Moving Average Convergence Divergence (MACD) and Percentage Price Oscillator (PPO) indicator that allows for viewing of 1 to 5 different Timeframes.
Brief Summary
The primary benefit of multi-timeframe indicators is getting better entries and confirmation from viewing multiple time frames at once, which can often get overlooked.
MACD shouldn't be only used by itself, it is a lot more consistent when applied in the same direction as the trend as well as multiple other things including support, resistance, and volume improve the outcomes of the MACD results.
Personally, I look for good entries on higher and lower time frames (multiple timeframes must agree with the buying or selling). For example, if a higher timeframe looks like a good long entry (MACD line is crossing up and below the zero line), then the lower timeframes should be checked to ensure they are not oversold or overextended (the MACD line must be low or below the zero), once the lower and higher timeframes are in agreeance an entry can be made.
What is Moving Average Convergence Divergence (MACD)?
Moving average convergence divergence (MACD) is a trend-following momentum indicator that shows the relationship between two moving averages of the price. The MACD is calculated by subtracting the 26-period exponential moving average (EMA) from the 12-period EMA.
What is the Percentage Price Oscillator (PPO)?
The PPO is identical to the MACD indicator, except the PPO measures percentage difference between two EMAs, while the MACD measures absolute (or dollar) difference. The PPO has the advantage of being comparable to other assets with different prices, whereas MACD readings are not comparable. For example, regardless of the asset's price, a PPO result of 10 means the short-term average is 10% above the long-term average.
A signal line can be displayed on Timeframe, including:
- MACD & Signal Line crosses (Green when MACD above Signal Line and Red when MACD below Signal Line)
- Histogram Direction (fast and slow EMA gap)
- SuperTrend for identifying trend direction (green for uptrend, red for downtrend)
- EMA Trend for identifying trend direction (above EMA = up trend and green, below EMA = down trend and red)
Cross Dots and Potential cross dots
- Green Dot, is displayed when the MACD crosses the Signal Line
- Red Dot, is displayed when the MACD crosses the Signal Line
- Yellow Dot. Potential cross up (green dot) on next bar. Displayed when if the same distance a MACD moves on a bar is applied to the next bar will cause a MACD and Signal Line Cross. This is calculated by checking if the value change of one bar is added to the current MACD value would lead to a cross on the next bar, the it is a potential up dot.
- Purple Dot. Potential cross down (red dot) on next bar. Displayed when if the same distance a MACD moves on a bar is applied to the next bar will cause a MACD and Signal Line Cross. This is calculated by checking if the value change of one bar is added to the current MACD value would lead to a cross on the next bar, the it is a potential down dot.
Best Fit Settings
- Can be applied to the MACD, Signal Line, and Histogram to re-scale (stretch) to fit them within the space of the +2 and -2 range that each timeframe is provided on this indicator.
- The lookback distance value is used to lookback a certain distance to ensure everything scaled to fit well.
Labels are displayed on the right of the indicators, including:
- a label identifying 'line indicator' is currently being displayed
- the Timeframe corresponding to each MACD or PPO indicator
- the MACD or PPO of each Timeframe
SuperTrended Moving AveragesA different approach to SuperTrend:
adding 100 periods Exponential Moving Average in calculation of SuperTrend and also 0.5 ATR Multiplier to have a clear view of the ongoing trend and also provides significant Supports and Resistances.
Default Moving Average type set as EMA (Exponential Moving Average) but users can choose from 11 different Moving Average types as:
SMA : Simple Moving Average
EMA : Exponential Moving Average
WMA : Weighted Moving Average
DEMA : Double Exponential Moving Average
TMA : Triangular Moving Average
VAR : Variable Index Dynamic Moving Average a.k.a. VIDYA
WWMA : Welles Wilder's Moving Average
ZLEMA : Zero Lag Exponential Moving Average
TSF : True Strength Force
HULL : Hull Moving Average
TILL : Tillson T3 Moving Average
Credits going to @CryptoErge for sharing his development to public.
Multi-X by HamidBoxHello to All, introducing Multi Types Crossover strategy,
simply the best way of trading with Crossover and Crossunder Strategy, How it Works???
I added 5 types of Moving Averages,
1: Simple Moving Average ( SMA )
2: Exponential Moving Average ( EMA )
3: Weighted Moving Average ( WMA )
4: Volume Weighted Moving Average ( VWMA )
5: Relative Moving Average (RMA)
With this indicator, you can do scalping, You can trade not only with similar types of Moving Average indicators but also with different types of Moving Average indicators.
what is mean? like: Normal Condition is:
( Simple Moving Average ) Crossover to ( Simple Moving Average ), SMA x SMA
( Exponential Moving Average ) Crossover to ( Exponential Moving Average ), EMA x EMA
But we can Crossover with:
( Exponential Moving Average ) Crossover to ( Simple Moving Average ), EMA x SMA
( Simple Moving Average ) Crossover to ( Weighted Moving Average ), SMA x WMA
( Weighted Moving Average ) Crossover to ( Weighted Moving Average ), WMA x WMA
( Simple Moving Average ) Crossover to (Relative Moving Average), WMA x RMA
and also I added Moving Average ZONE in this tool, What does it work???
The zone will tell us what type of direction the market has, if the market is above the zone, it's mean we have a Bullish Trend, and if the market is below the zone, it means the market has a Bearish Trend,
so if you want to play on the safe side, never trade when the market is in Bearish Trend, and if you want to play on aggressive mood, you can skip Moving Average Zone section.
Pinescript v4 - The Holy Grail (Trailing Stop)After studying several other scripts, I believe I have found the Holy Grail! (Or perhaps I've just found a bug with Tradingview's Pinescript v4 language) Anyhow, I'm publishing this script in the hope that someone smarter than myself could shed some light on the fact that adding a trailing stop to any strategy seems to make it miraculously...no that's an understatement...incredulously, stupendously, mind-bendingly profitable. I'm talking about INSANE profit factors, higher than 200x, with drawdowns of <10%. Sounds too good to be true? Maybe it is...or you could hook it up to your LIVE broker, and pray it doesn't explode. This is an upgraded version of my original Pin Bar Strategy.
Recommended Chart Settings:
Asset Class: Forex
Time Frame: H1
Long Entry Conditions:
a) Exponential Moving Average Fan up trend
b) Presence of a Bullish Pin Bar
c) Pin Bar pierces the Exponential Moving Average Fan
Short Entry Conditions:
a) Exponential Moving Average down trend
b) Presence of a Bearish Pin Bar
c) Pin Bar pierces the Exponential Moving Average Fan
Exit Conditions:
a) Trailing stop is hit
b) Moving Averages cross-back (optional)
c) It's the weekend
Default Robot Settings:
Equity Risk (%): 3 //how much account balance to risk per trade
Stop Loss (x*ATR, Float): 0.5 //stoploss = x * ATR, you can change x
Stop Loss Trail Points (Pips): 1 //the magic sauce, not sure how this works
Stop Loss Trail Offset (Pips): 1 //the magic sauce, not sure how this works
Slow SMA (Period): 50 //slow moving average period
Medium EMA (Period): 18 //medium exponential moving average period
Fast EMA (Period): 6 //fast exponential moving average period
ATR (Period): 14 // average true range period
Cancel Entry After X Bars (Period): 3 //cancel the order after x bars not triggered, you can change x
Backtest Results (2019 to 2020, H1, Default Settings):
AUDUSD - 1604% profit, 239.6 profit factor, 4.9% drawdown (INSANE)
NZDUSD - 1688.7% profit, 100.3 profit factor, 2.5% drawdown
GBPUSD - 1168.8% profit, 98.7 profit factor, 0% drawdown
USDJPY - 900.7% profit, 93.7 profit factor, 4.9% drawdown
USDCAD - 819% profit, 31.7 profit factor, 8.1% drawdown
EURUSD - 685.6% profit, 26.8 profit factor, 5.9% drawdown
USDCHF - 1008% profit, 18.7 profit factor, 8.6% drawdown
GBPJPY - 1173.4% profit, 16.1 profit factor, 7.9% drawdown
EURAUD - 613.3% profit, 14.4 profit factor, 9.8% drawdown
AUDJPY - 1619% profit, 11.26 profit factor, 9.1% drawdown
EURJPY - 897.2% profit, 6 profit factor, 13.8% drawdown
EURGBP - 608.9% profit, 5.3 profit factor, 9.8% drawdown (NOT TOO SHABBY)
As you can clearly see above, this forex robot is projected by the Tradingview backtester to be INSANELY profitable for all common forex pairs. So what was the difference between this strategy and my previous strategies? Check my code and look for "trail_points" and "trail_offset"; you can even look them up in the PineScript v4 documentation. They specify a trailing stop as the exit condition, which automatically closes the trade if price reverses against you.
I however suspect that the backtester is not properly calculating intra-bar price movement, and is using a simplified model. With this simplfied approach, the trailing stop code becomes some sort of "holy grail" generator, making every trade entered profitable.
Risk Warning:
This is a forex trading strategy that involves high risk of equity loss, and backtest performance will not equal future results. You agree to use this script at your own risk.
Hint:
To get more realistic results, and *maybe* overcome the intrabar simulation error, change the settings to: "Stop Loss Trail Points (pips)": 100
I am not sure if this eradicates the bug, but the entries and exits look more proper, and the profit factors are more believable.
SMA Simple, EMA Exponential Moving Averages with high lowThis is a rewrite of my previous moving average script.
In this version, I have added the 3 day high and low as these are often used as short term trend following entry points
Traders often try to buy the 3 day average of lows in an uptrend and sell the 3 day average of highs in a downtrend
In the same fashion, I have added the 3 week high and low averages for longer term trend following for swing trading
I have added the 18 day, week, month simple moving averages ( SMA ) as I follow these from Ira Epsteins free you tube trading videos).
His 50 years of experience has taught him these are best
I have also added some longer term SMA , 100 day, 200 day, 100w, and 200w
Exponential EMA averages for longer term charts are included 100d, 200d, 100w, 100m, 200m
You can configure the script in the options to remove the ones you don't want to follow
I have removed the micro averages from my previous script since they are for short term scalping day trading hyper-trading which I don't do
Exponential averages are shown as crosses
some of the longer term averages are circles just to set them apart
Tabajara simple versionIndicator Tabajara from the brazilian trader André Machado.
Simple version with moving averages SMA 20 and SMA 200.
If fast moving average (20) is ascending, positive candles will receive green color.
Descending fast moving average (20) makes negative candles receive red color.
In other cases the candles will be gray (positive) and black (negative).
The slow moving average (SMA 200) shows the primary trend.
It´s also possible using the indicator with exponential moving averages.
Well Rounded Moving AverageIntroduction
There are tons of filters, way to many, and some of them are redundant in the sense they produce the same results as others. The task to find an optimal filter is still a big challenge among technical analysis and engineering, a good filter is the Kalman filter who is one of the more precise filters out there. The optimal filter theorem state that : The optimal estimator has the form of a linear observer , this in short mean that an optimal filter must use measurements of the inputs and outputs, and this is what does the Kalman filter. I have tried myself to Kalman filters with more or less success as well as understanding optimality by studying Linear–quadratic–Gaussian control, i failed to get a complete understanding of those subjects but today i present a moving average filter (WRMA) constructed with all the knowledge i have in control theory and who aim to provide a very well response to market price, this mean low lag for fast decision timing and low overshoots for better precision.
Construction
An good filter must use information about its output, this is what exponential smoothing is about, simple exponential smoothing (EMA) is close to a simple moving average and can be defined as :
output = output(1) + α(input - output(1))
where α (alpha) is a smoothing constant, typically equal to 2/(Period+1) for the EMA.
This approach can be further developed by introducing more smoothing constants and output control (See double/triple exponential smoothing - alpha-beta filter) .
The moving average i propose will use only one smoothing constant, and is described as follow :
a = nz(a ) + alpha*nz(A )
b = nz(b ) + alpha*nz(B )
y = ema(a + b,p1)
A = src - y
B = src - ema(y,p2)
The filter is divided into two components a and b (more terms can add more control/effects if chosen well) , a adjust itself to the output error and is responsive while b is independent of the output and is mainly smoother, adding those components together create an output y , A is the output error and B is the error of an exponential moving average.
Comparison
There are a lot of low-lag filters out there, but the overshoots they induce in order to reduce lag is not a great effect. The first comparison is with a least square moving average, a moving average who fit a line in a price window of period length .
Lsma in blue and WRMA in red with both length = 100 . The lsma is a bit smoother but induce terrible overshoots
ZLMA in blue and WRMA in red with both length = 100 . The lag difference between each moving average is really low while VWRMA is way more precise.
Hull MA in blue and WRMA in red with both length = 100 . The Hull MA have similar overshoots than the LSMA.
Reduced overshoots moving average (ROMA) in blue and WRMA in red with both length = 100 . ROMA is an indicator i have made to reduce the overshoots of a LSMA, but at the end WRMA still reduce way more the overshoots while being smoother and having similar lag.
I have added a smoother version, just activate the extra smooth option in the indicator settings window. Here the result with length = 200 :
This result is a little bit similar to a 2 order Butterworth filter. Our filter have more overshoots which in this case could be useful to reduce the error with edges since other low pass filters tend to smooth their amplitude thus reducing edge estimation precision.
Conclusions
I have presented a well rounded filter in term of smoothness/stability and reactivity. Try to add more terms to have different results, you could maybe end up with interesting results, if its the case share them with the community :)
As for control theory i have seen neural networks integrated to Kalman flters which leaded to great accuracy, AI is everywhere and promise to be a game a changer in real time data smoothing. So i asked myself if it was possible for a neural networks to develop pinescript indicators, if yes then i could be replaced by AI ? Brrr how frightening.
Thanks for reading :)
MACD percentage price oscillatorMACD Percentage Price Oscillator is a variation of the MACD indicator. Signal line crossovers are almost identical. The major difference is the MACD Percentage scale which enables comparison between stocks at different prices.
MACD Percentage Price Oscillator's trading signals are the same as for the MACD indicator. The MACD indicator is primarily used to trade trends and should not be used in a ranging market. Signals are taken when MACD crosses its signal line, calculated as a 9 day exponential moving average of MACD.
First check whether price is trending. If the MACD indicator is flat or stays close to the zero line, the market is ranging and signals are unreliable.
Signals are far stronger if there is either:
- a divergence on the MACD indicator; or
- a large swing above or below the zero line.
- Unless there is a divergence, do not go long if the signal is above the zero line, nor go short if the signal is below zero. Place stop-losses below the last minor Low when long, or the last minor High when short.
The main advantage of MACD Percentage over MACD is the ability to compare indicator values across stocks.
The only difference with MACD Percentage Price Oscillator is that the difference between the fast and slow moving averages is calculated as a percentage of the slow moving average: MACD = (12 Day EMA - 26 Day EMA) / 26 Day EMA
Moving Average RibbonThis is an extension of the Madrid Moving Average Ribbon public script to allow for different kinds of moving averages (the original allows only exponential and simple). Possible entries in the MA Type argument field are:
sma (simple moving average)
ema (exponential moving average)
wma (weighted moving average)
trima (triangular moving average)
zlema (zero-lag exponential moving average)
dema (double exponential moving average)
tema (triple exponential moving average)
hma (hull moving average)
If the argument given by the user does not match anything from the above list, it will default to ema.
Impulse Reactor RSI-SMA Trend Indicator [ApexLegion]Impulse Reactor RSI-SMA Trend Indicator
Introduction and Theoretical Background
Design Rationale
Standard indicators frequently generate binary 'BUY' or 'SELL' signals without accounting for the broader market context. This often results in erratic "Flip-Flop" behavior, where signals are triggered indiscriminately regardless of the prevailing volatility regime.
Impulse Reactor was engineered to address this limitation by unifying two critical requirements: Quantitative Rigor and Execution Flexibility.
The Solution
Composite Analytical Framework This script is not a simple visual overlay of existing indicators. It is an algorithmic synthesis designed to function as a unified decision-making engine. The primary objective was to implement rigorous quantitative analysis (Volatility Normalization, Structural Filtering) directly within an alert-enabled framework. This architecture is designed to process signals through strict, multi-factor validation protocols before generating real-time notifications, allowing users to focus on structurally validated setups without manual monitoring.
How It Works
This is not a simple visual mashup. It utilizes a cross-validation algorithm where the Trend Structure acts as a gatekeeper for Momentum signals:
Logic over Lag: Unlike simple moving average crossovers, this script uses a 15-layer Gradient Ribbon to detect "Laminar Flow." If the ribbon is knotted (Compression), the system mathematically suppresses all signals.
Volatility Normalization: The core calculation adapts to ATR (Average True Range). This means the indicator automatically expands in volatile markets and contracts in quiet ones, maintaining accuracy without constant manual tweaking.
Adaptive Signal Thresholding: It incorporates an 'Anti-Greed' algorithm (Dynamic Thresholding) that automatically adjusts entry criteria based on trend duration. This logic aims to mitigate the risk of entering positions during periods of statistical trend exhaustion.
Why Use It?
Market State Decoding: The gradient Ribbon visualizes the underlying trend phase in real-time.
◦ Cyan/Blue Flow: Strong Bullish Trend (Laminar Flow).
◦ Magenta/Pink Flow: Strong Bearish Trend.
◦ Compressed/Knotted: When the ribbon lines are tightly squeezed or overlapping, it signals Consolidation. The system filters signals here to avoid chop.
Noise Reduction: The goal is not to catch every pivot, but to isolate high-confidence setups. The logic explicitly filters out minor fluctuations to help maintain position alignment with the broader trend.
⚖️ Chapter 1: System Architecture
Introduction: Composite Analytical Framework
System Overview
Impulse Reactor serves as a comprehensive technical analysis engine designed to synthesize three distinct market dimensions—Momentum, Volatility, and Trend Structure—into a unified decision-making framework. Unlike traditional methods that analyze these metrics in isolation, this system functions as a central processing unit that integrates disparate data streams to construct a coherent model of market behavior.
Operational Objective
The primary objective is to transition from single-dimensional signal generation to a multi-factor assessment model. By fusing data from the Impulse Core (Volatility), Gradient Oscillator (Momentum), and Structural Baseline (Trend), the system aims to filter out stochastic noise and identify high-probability trade setups grounded in quantitative confluence.
Market Microstructure Analysis: Limitations of Conventional Models
Extensive backtesting and quantitative analysis have identified three critical inefficiencies in standard oscillator-based strategies:
• Bounded Oscillator Limitations (The "Oscillation Trap"): Traditional indicators such as RSI or Stochastics are mathematically constrained between fixed values (0 to 100). In strong trending environments, these metrics often saturate in "overbought" or "oversold" zones. Consequently, traders relying on static thresholds frequently exit structurally valid positions prematurely or initiate counter-trend trades against prevailing momentum, resulting in suboptimal performance.
• Quantitative Blindness to Quality: Standard moving averages and trend indicators often fail to distinguish the qualitative nature of price movement. They treat low-volume drift and high-velocity expansion identically. This inability to account for "Volatility Quality" leads to delayed responsiveness during critical market events.
• Fractal Dissonance (Timeframe Disconnect): Financial markets exhibit fractal characteristics where trends on lower timeframes may contradict higher timeframe structures. Manual integration of multi-timeframe analysis increases cognitive load and susceptibility to human error, often resulting in conflicting biases at the point of execution.
Core Design Principles
To mitigate the aforementioned systemic inefficiencies, Impulse Reactor employs a modular architecture governed by three foundational principles:
Principle A:
Volatility Precursor Analysis Market mechanics demonstrate that volatility expansion often functions as a leading indicator for directional price movement. The system is engineered to detect "Volatility Deviation" — specifically, the divergence between short-term and long-term volatility baselines—prior to its manifestation in price action. This allows for entry timing aligned with the expansion phase of market volatility.
Principle B:
Momentum Density Visualization The system replaces singular momentum lines with a "Momentum Density" model utilizing a 15-layer Simple Moving Average (SMA) Ribbon.
• Concept: This visualization represents the aggregate strength and consistency of the trend.
• Application: A fully aligned and expanded ribbon indicates a robust trend structure ("Laminar Flow") capable of withstanding minor counter-trend noise, whereas a compressed ribbon signals consolidation or structural weakness.
Principle C:
Adaptive Confluence Protocols Signal validity is strictly governed by a multi-dimensional confluence logic. The system suppresses signal generation unless there is synchronized confirmation across all three analytical vectors:
1. Volatility: Confirmed expansion via the Impulse Core.
2. Momentum: Directional alignment via the Hybrid Oscillator.
3. Structure: Trend validation via the Baseline. This strict filtering mechanism significantly reduces false positives in non-trending (choppy) environments while maintaining sensitivity to genuine breakouts.
🔍 Chapter 2: Core Modules & Algorithmic Logic
Module A: Impulse Core (Normalized Volatility Deviation)
Operational Logic The Impulse Core functions as a volatility-normalized momentum gauge rather than a standard oscillator. It is designed to identify "Volatility Contraction" (Squeeze) and "Volatility Expansion" phases by quantifying the divergence between short-term and long-term volatility states.
Volatility Z-Score Normalization
The formula implements a custom normalization algorithm. Unlike standard oscillators that rely on absolute price changes, this logic calculates the Z-Score of the Volatility Spread.
◦ Numerator: (atr_f - atr_s) captures the raw momentum of volatility expansion.
◦ Denominator: (std_f + 1e-6) standardizes this value against historical variance.
◦ Result: This allows the indicator scales consistently across assets (e.g., Bitcoin vs. Euro) without manual recalibration.
f_impulse() =>
atr_f = ta.atr(fastLen) // Fast Volatility Baseline
atr_s = ta.atr(slowLen) // Slow Volatility Baseline
std_f = ta.stdev(atr_f, devLen) // Volatility Standard Deviation
(atr_f - atr_s) / (std_f + 1e-6) // Normalized Differential Calculation
Algorithmic Framework
• Differential Calculation: The system computes the spread between a Fast Volatility Baseline (ATR-10) and a Slow Volatility Baseline (ATR-30).
• Normalization Protocol: To standardize consistency across diverse asset classes (e.g., Forex vs. Crypto), the raw differential is divided by the standard deviation of the volatility itself over a 30-period lookback.
• Signal Generation:
◦ Contraction (Squeeze): When the Fast ATR compresses below the Slow ATR, it registers a potential volatility buildup phase.
◦ Expansion (Release): A rapid divergence of the Fast ATR above the Slow ATR signals a confirmed volatility expansion, validating the strength of the move.
Module B: Gradient Oscillator (RSI-SMA Hybrid)
Design Rationale To mitigate the "noise" and "false reversal" signals common in single-line oscillators (like standard RSI), this module utilizes a 15-Layer Gradient Ribbon to visualize momentum density and persistence.
Technical Architecture
• Ribbon Array: The system generates 15 sequential Simple Moving Averages (SMA) applied to a volatility-adjusted RSI source. The length of each layer increases incrementally.
• State Analysis:
Momentum Alignment (Laminar Flow): When all 15 layers are expanded and parallel, it indicates a robust trend where buying/selling pressure is distributed evenly across multiple timeframes. This state helps filter out premature "overbought/oversold" signals.
• Consolidation (Compression): When the distance between the fastest layer (Layer 1) and the slowest layer (Layer 15) approaches zero or the layers intersect, the system identifies a "Non-Tradable Zone," preventing entries during choppy market conditions.
// Laminar Flow Validation
f_validate_trend() =>
// Calculate spread between Ribbon layers
ribbon_spread = ta.stdev(ribbon_array, 15)
// Only allow signals if Ribbon is expanded (Laminar Flow)
is_flowing = ribbon_spread > min_expansion_threshold
// If compressed (Knotted), force signal to false
is_flowing ? signal : na
Module C: Adaptive Signal Filtering (Behavioral Bias Mitigation)
This subsystem, operating as an algorithmic "Anti-Greed" Mechanism, addresses the statistical tendency for signal degradation following prolonged trends.
Dynamic Threshold Adjustment
• Win Streak Detection: The algorithm internally tracks the outcome of closed trade cycles.
• Sensitivity Multiplier: Upon detecting consecutive successful signals in the same direction, a Penalty_Factor is applied to the entry logic.
• Operational Impact: This effectively raises the Required_Slope threshold for subsequent signals. For example, after three consecutive bullish signals, the system requires a 30% steeper trend angle to validate a fourth entry. This enforces stricter discipline during extended trends to reduce the probability of entering at the point of trend exhaustion.
Anti-Greed Logic: Dynamic Threshold Calculation
f_adjust_threshold(base_slope, win_streak) =>
// Adds a 10% penalty to the difficulty for every consecutive win
penalty_factor = 0.10
risk_scaler = 1 + (win_streak * penalty_factor)
// Returns the new, harder-to-reach threshold
base_slope * risk_scaler
Module D: Trend Baseline (Triple-Smoothed Structure)
The Trend Baseline serves as the structural filter for all signals. It employs a Triple-Smoothed Hybrid Algorithm designed to balance lag reduction with noise filtration.
Smoothing Stages
1. Volatility Banding: Utilizes a SuperTrend-based calculation to establish the upper and lower boundaries of price action.
2. Weighted Filter: Applies a Weighted Moving Average (WMA) to prioritize recent price data.
3. Exponential Smoothing: A final Exponential Moving Average (EMA) pass is applied to create a seamless baseline curve.
Functionality
This "Heavy" baseline resists minor intraday volatility spikes while remaining responsive to sustained structural shifts. A signal is only considered valid if the price action maintains structural integrity relative to this baseline
🚦 Chapter 3: Risk Management & Exit Protocols
Quantitative Risk Management (TP/SL & Trailing)
Foundational Architecture: Volatility-Adjusted Geometry Unlike strategies relying on static nominal values, Impulse Reactor establishes dynamic risk boundaries derived from quantitative volatility metrics. This design aligns trade invalidation levels mathematically with the current market regime.
• ATR-Based Dynamic Bracketing:
The protocol calculates Stop-Loss and Take-Profit levels by applying Fibonacci coefficients (Default: 0.786 for SL / 1.618 for TP) to the Average True Range (ATR).
◦ High Volatility Environments: The risk bands automatically expand to accommodate wider variance, preventing premature exits caused by standard market noise.
◦ Low Volatility Environments: The bands contract to tighten risk parameters, thereby dynamically adjusting the Risk-to-Reward (R:R) geometry.
• Close-Validation Protocol ("Soft Stop"):
Institutional algorithms frequently execute liquidity sweeps—driving prices briefly below key support levels to accumulate inventory.
◦ Mechanism: When the "Soft Stop" feature is enabled, the system filters out intraday volatility spikes. The stop-loss is conditional; execution is triggered only if the candle closes beyond the invalidation threshold.
◦ Strategic Advantage: This logic distinguishes between momentary price wicks and genuine structural breakdowns, preserving positions during transient volatility.
• Step-Function Trailing Mechanism:
To protect unrealized PnL while allowing for normal price breathing, a two-phase trailing methodology is employed:
◦ Phase 1 (Activation): The trailing function remains dormant until the price advances by a pre-defined percentage threshold.
◦ Phase 2 (Dynamic Floor): Once armed, the stop level creates a moving floor, adjusting relative to price action while maintaining a volatility-based (ATR) buffer to systematically protect unrealized PnL.
• Algorithmic Exit Protocols (Dynamic Liquidity Analysis)
◦ Rationale: Inefficiencies of Static Targets Static "Take Profit" levels often result in suboptimal exits. They compel traders to close positions based on arbitrary figures rather than evolving market structure, potentially capping upside during significant trends or retaining positions while the underlying trend structure deteriorates.
◦ Solution: Structural Integrity Assessment The system utilizes a Dynamic Liquidity Engine to continuously audit the validity of the position. Instead of targeting a specific price point, the algorithm evaluates whether the trend remains statistically robust.
Multi-Factor Exit Logic (The Tri-Vector System)
The Smart Exit protocol executes only when specific algorithmic invalidation criteria are met:
• 1. Momentum Exhaustion (Confluence Decay): The system monitors a 168-hour rolling average of the Confluence Score. A significant deviation below this historical baseline indicates momentum exhaustion, signaling that the driving force behind the trend has dissipated prior to a price reversal. This enables preemptive exits before a potential drawdown.
• 2. Statistical Over-Extension (Mean Reversion): Utilizing the core volatility logic, the system identifies instances where price deviates beyond 2.0 standard deviations from the mean. While the trend may be technically bullish, this statistical anomaly suggests a high probability of mean reversion (elastic snap-back), triggering a defensive exit to capitalize on peak valuation.
• 3. Oscillator Rejection (Immediate Pivot): To manage sudden V-shaped volatility, the system monitors RSI pivots. If a sharp "Pivot High" or divergence is detected, the protocol triggers an immediate "Peak Exit," bypassing standard trend filters to secure liquidity during high-velocity reversals.
🎨 Chapter 4: Visualization Guide
Gradient Oscillator Ribbon
The 15-layer SMA ribbon visualized via plot(r1...r15) represents the "Momentum Density" of the market.
• Visuals:
◦ Cyan/Blue Ribbon: Indicates Bullish Momentum.
◦ Pink/Magenta Ribbon: Indicates Bearish Momentum.
• Interpretation:
◦ Laminar Flow: When the ribbon expands widely and flows in parallel, it signifies a robust trend where momentum is distributed evenly across timeframes. This is the ideal state for trend-following.
◦ Compression (Consolidation): If the ribbon becomes narrow, twisted, or knotted, it indicates a "Non-Tradable Zone" where the market lacks a unified direction. Traders are advised to wait for clarity.
◦ Over-Extension: If the top layer crosses the Overbought (85) or Oversold (15) lines, it visually warns of potential market overheating.
Trend Baseline
The thick, color-changing line plotted via plot(baseline) represents the Structural Backbone of the market.
• Visuals: Changes color based on the trend direction (Blue for Bullish, Pink for Bearish).
• Interpretation:
Structural Filter: Long positions are statistically favored only when price action sustains above this baseline, while short positions are favored below it.
Dynamic Support/Resistance: The baseline acts as a dynamic support level during uptrends and resistance during downtrends.
Entry Signals & Labels
Text labels ("Long Entry", "Short Entry") appear when the system detects high-probability setups grounded in quantitative confluence.
• Visuals: Labeled signals appear above/below specific candles.
• Interpretation:
These signals represent moments where Volatility (Expansion), Momentum (Alignment), and Structure (Trend) are synchronized.
Smart Exit: Labels such as "Smart Exit" or "Peak Exit" appear when the system detects momentum exhaustion or structural decay, prompting a defensive exit to preserve capital.
Dynamic TP/SL Boxes
The semi-transparent colored zones drawn via fill() represent the risk management geometry.
• Visuals: Colored boxes extending from the entry point to the Take Profit (TP) and Stop Loss (SL) levels.
• Function:
Volatility-Adjusted Geometry: Unlike static price targets, these boxes expand during high volatility (to prevent wicks from stopping you out) and contract during low volatility (to optimize Risk-to-Reward ratios).
SAR + MACD Glow
Small glowing shapes appearing above or below candles.
• Visuals: Triangle or circle glows near the price bars.
• Interpretation:
This visual indicates a secondary confirmation where Parabolic SAR and MACD align with the main trend direction. It serves as an additional confluence factor to increase confidence in the trade setup.
Support/Resistance Table
A small table located at the bottom-right of the chart.
• Function: Automatically identifies and displays recent Pivot Highs (Resistance) and Pivot Lows (Support).
• Interpretation: These levels can be used as potential targets for Take Profit or invalidation points for manual Stop Loss adjustments.
🖥️ Chapter 5: Dashboard & Operational Guide
Integrated Analytics Panel (Dashboard Overview)
To facilitate rapid decision-making without manual calculation, the system aggregates critical market dimensions into a unified "Heads-Up Display" (HUD). This panel monitors real-time metrics across multiple timeframes and analytical vectors.
A. Intermediate Structure (12H Trend)
• Function: Anchors the intraday analysis to the broader market structure using a 12-hour rolling window.
• Interpretation:
◦ Bullish (> +0.5%): Indicates a positive structural bias. Long setups align with the macro flow.
◦ Bearish (< -0.5%): Indicates structural weakness. Short setups are statistically favored.
◦ Neutral: Represents a ranging environment where the Confluence Score becomes the primary weighting factor.
B. Composite Confluence Score (Signal Confidence)
• Definition: A probability metric derived from the synchronization of Volatility (Impulse Core), Momentum (Ribbon), and Trend (Baseline).
• Grading Scale:
Strong Buy/Sell (> 7.0 / < 3.0): Indicates full alignment across all three vectors. Represents a "Prime Setup" eligible for standard position sizing.
Buy/Sell (5.0–7.0 / 3.0–5.0): Indicates a valid trend but with moderate volatility confirmation.
Neutral: Signals conflicting data (e.g., Bullish Momentum vs. Bearish Structure). Trading is not recommended ("No-Trade Zone").
C. Statistical Deviation Status (Mean Reversion)
• Logic: Utilizes Bollinger Band deviation principles to quantify how far price has stretched from the statistical mean (20 SMA).
• Alert States:
Over-Extended (> 2.0 SD): Warning that price is statistically likely to revert to the mean (Elastic Snap-back), even if the trend remains technically valid. New entries are discouraged in this zone.
Normal: Price is within standard distribution limits, suitable for trend-following entries.
D. Volatility Regime Classification
• Metric: Compares current ATR against a 100-period historical baseline to categorize the market state.
• Regimes:
Low Volatility (Lvl < 1.0): Market Compression. Often precedes volatility expansion events.
Mid Volatility (Lvl 1.0 - 1.5): Standard operating environment.
High Volatility (Lvl > 1.5): Elevated market stress. Risk parameters should be adjusted (e.g., reduced position size) to account for increased variance.
E. Performance Telemetry
• Function: Displays the historical reliability of the Trend Baseline for the current asset and timeframe.
• Operational Threshold: If the displayed Win Rate falls below 40%, it suggests the current market behavior is incoherent (choppy) and does not respect trend logic. In such cases, switching assets or timeframes is recommended.
Operational Protocols & Signal Decoding
Visual Interpretation Standards
• Laminar Flow (Trade Confirmation): A valid trend is visually confirmed when the 15-layer SMA Ribbon is fully expanded and parallel. This indicates distributed momentum across timeframes.
• Consolidation (No-Trade): If the ribbon appears twisted, knotted, or compressed, the market lacks a unified directional vector.
• Baseline Interaction: The Triple-Smoothed Baseline acts as a dynamic support/resistance filter. Long positions remain valid only while price sustains above this structure.
System Calibration (Settings)
• Adaptive Signal Filtering (Prev. Anti-Greed): Enabled by default. This logic automatically raises the required trend slope threshold following consecutive wins to mitigate behavioral bias.
• Impulse Sensitivity: Controls the reactivity of the Volatility Core. Higher settings capture faster moves but may introduce more noise.
⚙️ Chapter 6: System Configuration & Alert Guide
This section provides a complete breakdown of every adjustable setting within Impulse Reactor to assist you in tailoring the engine to your specific needs.
🌐 LANGUAGE SETTINGS (Localization)
◦ Select Language (Default: English):
Function: Instantly translates all chart labels, dashboard texts into your preferred language.
Supported: English, Korean, Chinese, Spanish
⚡ IMPULSE CORE SETTINGS (Volatility Engine)
◦ Deviation Lookback (Default: 30): The period used to calculate the standard deviation of volatility.
Role: Sets the baseline for normalizing momentum. Higher values make the core smoother but slower to react.
◦ Fast Pulse Length (Default: 10): The short-term ATR period.
Role: Detects rapid volatility expansion.
◦ Slow Pulse Length (Default: 30): The long-term ATR baseline.
Role: Establishes the background volatility level. The core signal is derived from the divergence between Fast and Slow pulses.
🎯 TP/SL SETTINGS (Risk Management)
◦ SL/TP Fibonacci (Default: 0.786 / 1.618): Selects the Fibonacci ratio used for risk calculation.
◦ SL/TP Multiplier (Default: 1.5 / 2): Applies a multiplier to the ATR-based bands.
Role: Expands or contracts the Take Profit and Stop Loss boxes. Increase these values for higher volatility assets (like Altcoins) to avoid premature stop-outs.
◦ ATR Length (Default: 14): The lookback period for calculating the Average True Range used in risk geometry.
◦ Use Soft Stop (Close Basis):
Role: If enabled, Stop Loss alerts only trigger if a candle closes beyond the invalidation level. This prevents being stopped out by wick manipulations.
🔊 RIBBON SETTINGS (Momentum Visualization)
◦ Show SMA Ribbon: Toggles the visibility of the 15-layer gradient ribbon.
◦ Ribbon Line Count (Default: 15): The number of SMA lines in the ribbon array.
◦ Ribbon Start Length (Default: 2) & Step (Default: 1): Defines the spread of the ribbon.
Role: Controls the "thickness" of the momentum density visualization. A wider step creates a broader ribbon, useful for higher timeframes.
📎 DISPLAY OPTIONS
◦ Show Entry Lines / TP/SL Box / Position Labels / S/R Levels / Dashboard: Toggles individual visual elements on the chart to reduce clutter.
◦ Show SAR+MACD Glow: Enables the secondary confirmation shapes (triangles/circles) above/below candles.
📈 TREND BASELINE (Structural Filter)
◦ Supertrend Factor (Default: 12) & ATR Period (Default: 90): Controls the sensitivity of the underlying Supertrend algorithm used for the baseline calculation.
◦ WMA Length (40) & EMA Length (14): The smoothing periods for the Triple-Smoothed Baseline.
◦ Min Trend Duration (Default: 10): The minimum number of bars the trend must be established before a signal is considered valid.
🧠 SMART EXIT (Dynamic Liquidity)
◦ Use Smart Exit: Enables the momentum exhaustion logic.
◦ Exit Threshold Score (Default: 3): The sensitivity level for triggering a Smart Exit. Lower values trigger earlier exits.
◦ Average Period (168) & Min Hold Bars (5): Defines the rolling window for momentum decay analysis and the minimum duration a trade must be held before Smart Exit logic activates.
🛡️ TRAILING STOP (Step)
◦ Use Trailing Stop: Activates the step-function trailing mechanism.
◦ Step 1 Activation % (0.5) & Offset % (0.5): The price must move 0.5% in your favor to arm the first trail level, which sets a stop 0.5% behind price.
◦ Step 2 Activation % (1) & Offset % (0.2): Once price moves 1%, the trail tightens to 0.2%, securing the position.
🌀 SAR & MACD SETTINGS (Secondary Confirmation)
◦ SAR Start/Increment/Max: Standard Parabolic SAR parameters.
◦ SAR Score Scaling (ATR): Adjusts how much weight the SAR signal has in the overall confluence score.
◦ MACD Fast/Slow/Signal: Standard MACD parameters used for the "Glow" signals.
🔄 ANTI-GREED LOGIC (Behavioral Bias)
◦ Strict Entry after Win: Enables the negative feedback loop.
◦ Strict Multiplier (Default: 1.1): Increases the entry difficulty by 10% after each win.
Role: Prevents overtrading and entering at the top of an extended trend.
🌍 HTF FILTER (Multi-Timeframe)
◦ Use Auto-Adaptive HTF Filter: Automatically selects a higher timeframe (e.g., 1H -> 4H) to filter signals.
◦ Bypass HTF on Steep Trigger: Allows an entry even against the HTF trend if the local momentum slope is exceptionally steep (catch powerful reversals).
📉 RSI PEAK & CHOPPINESS
◦ RSI Peak Exit (Instant): Triggers an immediate exit if a sharp RSI pivot (V-shape) is detected.
◦ Choppiness Filter: Suppresses signals if the Choppiness Index is above the threshold (Default: 60), indicating a flat market.
📐 SLOPE TRIGGER LOGIC
◦ Force Entry on Steep Slope: Overrides other filters if the price angle is extremely vertical (high velocity).
◦ Slope Sensitivity (1.5): The angle required to trigger this override.
⛔ FLAT MARKET FILTER (ADX & ATR)
◦ Use ADX Filter: Blocks signals if ADX is below the threshold (Default: 20), indicating no trend.
◦ Use ATR Flat Filter: Blocks signals if volatility drops below a critical level (dead market).
🔔 Alert Configuration Guide
Impulse Reactor is designed with a comprehensive suite of alert conditions, allowing you to automate your trading or receive real-time notifications for specific market events.
How to Set Up:
Click the "Alert" (Clock) icon in the TradingView toolbar.
Select "Impulse Reactor " from the Condition dropdown.
Choose one of the specific trigger conditions below:
🚀 Entry Signals (Trend Initiation)
Long Entry:
Trigger: Fires when a confirmed Bullish Setup is detected (Momentum + Volatility + Structure align).
Usage: Use this to enter new Long positions.
Short Entry:
Trigger: Fires when a confirmed Bearish Setup is detected.
Usage: Use this to enter new Short positions.
🎯 Profit Taking (Target Levels)
Long TP:
Trigger: Fires when price hits the calculated Take Profit level for a Long trade.
Usage: Automate partial or full profit taking.
Short TP:
Trigger: Fires when price hits the calculated Take Profit level for a Short trade.
Usage: Automate partial or full profit taking.
🛡️ Defensive Exits (Risk Management)
Smart Exit:
Trigger: Fires when the system detects momentum decay or statistical exhaustion (even if the trend hasn't fully reversed).
Usage: Recommended for tightening stops or closing positions early to preserve gains.
Overbought / Oversold:
Trigger: Fires when the ribbon extends into extreme zones.
Usage: Warning signal to prepare for a potential reversal or pullback.
💡 Secondary Confirmation (Confluence)
SAR+MACD Bullish:
Trigger: Fires when Parabolic SAR and MACD align bullishly with the main trend.
Usage: Ideal for Pyramiding (adding to an existing winning position).
SAR+MACD Bearish:
Trigger: Fires when Parabolic SAR and MACD align bearishly.
Usage: Ideal for adding to short positions.
⚠️ Chapter 7: Conclusion & Risk Disclosure
Methodological Synthesis
Impulse Reactor represents a shift from reactive price tracking to proactive energy analysis. By decomposing market activity into its atomic components — Volatility, Momentum, and Structure — and reconstructing them into a coherent decision model, the system aims to provide a quantitative framework for market engagement. It is designed not to predict the future, but to identify high-probability conditions where kinetic energy and trend structure align.
Disclaimer & Risk Warnings
◦ Educational Purpose Only
This indicator, including all associated code, documentation, and visual outputs, is provided strictly for educational and informational purposes. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments.
◦ No Guarantee of Performance
Past performance is not indicative of future results. All metrics displayed on the dashboard (including "Win Rate" and "P&L") are theoretical calculations based on historical data. These figures do not account for real-world trading factors such as slippage, liquidity gaps, spread costs, or broker commissions.
◦ High-Risk Warning
Trading cryptocurrencies, futures, and leveraged financial products involves a substantial risk of loss. The use of leverage can amplify both gains and losses. Users acknowledge that they are solely responsible for their trading decisions and should conduct independent due diligence before executing any trades.
◦ Software Limitations
The software is provided "as is" without warranty. Users should be aware that market data feeds on analysis platforms may experience latency or outages, which can affect signal generation accuracy.
EMA Dynamic Crossover Detector with Real-Time Signal TableDescriptionWhat This Indicator Does:This indicator monitors all possible crossovers between four key exponential moving averages (20, 50, 100, and 200 periods) and displays them both visually on the chart and in an organized data table. Unlike standard EMA indicators that only plot the lines, this tool actively detects every crossover event, marks the exact crossover point with a circle, records the precise price level, and maintains a running log of all crossovers during the trading session. It's designed for traders who want comprehensive EMA crossover analysis without manually watching multiple moving average pairs.Key Features:
Four Essential EMAs: Plots 20, 50, 100, and 200-period exponential moving averages with color-coded thin lines for clean chart presentation
Complete Crossover Detection: Monitors all 6 possible EMA pair combinations (20×50, 20×100, 20×200, 50×100, 50×200, 100×200) in both directions
Precise Price Marking: Places colored circles at the exact average price where crossovers occur (not just at candle close)
Real-Time Signal Table: Displays up to 10 most recent crossovers with timestamp, direction, exact price, and signal type
Session Filtering: Only records crossovers during active trading hours (10:00-18:00 Istanbul time) to avoid noise from low-liquidity periods
Automatic Daily Reset: Clears the signal table at the start of each new trading day for fresh analysis
Built-In Alerts: Two alert conditions (bullish and bearish crossovers) that can be configured to send notifications
How It Works:The indicator calculates four exponential moving averages using the standard EMA formula, then continuously monitors for crossover events using Pine Script's ta.crossover() and ta.crossunder() functions:Bullish Crossovers (Green ▲):
When a faster EMA crosses above a slower EMA, indicating potential upward momentum:
20 crosses above 50, 100, or 200
50 crosses above 100 or 200
100 crosses above 200 (Golden Cross when it's the 50×200)
Bearish Crossovers (Red ▼):
When a faster EMA crosses below a slower EMA, indicating potential downward momentum:
20 crosses below 50, 100, or 200
50 crosses below 100 or 200
100 crosses below 200 (Death Cross when it's the 50×200)
Price Calculation:
Instead of marking crossovers at the candle's close price (which might not be where the actual cross occurred), the indicator calculates the average price between the two crossing EMAs, providing a more accurate representation of the crossover point.Signal Table Structure:The table in the top-right corner displays four columns:
Saat (Time): Exact time of crossover in HH:MM format
Yön (Direction): Arrow indicator (▲ green for bullish, ▼ red for bearish)
Fiyat (Price): Calculated average price at the crossover point
Durum (Status): Signal classification ("ALIŞ" for buy signals, "SATIŞ" for sell signals) with color-coded background
The table shows up to 10 most recent crossovers, automatically updating as new signals appear. If no crossovers have occurred during the session within the time filter, it displays "Henüz kesişim yok" (No crossovers yet).EMA Color Coding:
EMA 20 (Aqua/Turquoise): Fastest-reacting, most sensitive to recent price changes
EMA 50 (Green): Short-term trend indicator
EMA 100 (Yellow): Medium-term trend indicator
EMA 200 (Red): Long-term trend baseline, key support/resistance level
How to Use:For Day Traders:
Monitor 20×50 crossovers for quick entry/exit signals within the day
Use the time filter (10:00-18:00) to focus on high-volume trading hours
Check the signal table throughout the session to track momentum shifts
Look for confirmation: if 20 crosses above 50 and price is above EMA 200, bullish bias is stronger
For Swing Traders:
Focus on 50×200 crossovers (Golden Cross/Death Cross) for major trend changes
Use higher timeframes (4H, Daily) for more reliable signals
Wait for price to close above/below the crossover point before entering
Combine with support/resistance levels for better entry timing
For Position Traders:
Monitor 100×200 crossovers on daily/weekly charts for long-term trend changes
Use as confirmation of major market shifts
Don't react to every crossover—wait for sustained movement after the cross
Consider multiple timeframe analysis (if crossovers align on weekly and daily, signal is stronger)
Understanding EMA Hierarchies:The indicator becomes most powerful when you understand EMA relationships:Bullish Hierarchy (Strongest to Weakest):
All EMAs ascending (20 > 50 > 100 > 200): Strong uptrend
20 crosses above 50 while both are above 200: Pullback ending in uptrend
50 crosses above 200 while 20/50 below: Early trend reversal signal
Bearish Hierarchy (Strongest to Weakest):
All EMAs descending (20 < 50 < 100 < 200): Strong downtrend
20 crosses below 50 while both are below 200: Rally ending in downtrend
50 crosses below 200 while 20/50 above: Early trend reversal signal
Trading Strategy Examples:Pullback Entry Strategy:
Identify major trend using EMA 200 (price above = uptrend, below = downtrend)
Wait for pullback (20 crosses below 50 in uptrend, or above 50 in downtrend)
Enter when 20 re-crosses 50 in the trend direction
Place stop below/above the recent swing point
Exit when 20 crosses 50 against the trend again
Golden Cross/Death Cross Strategy:
Wait for 50×200 crossover (appears in the signal table)
Verify: Check if crossover occurs with increasing volume
Entry: Enter in the direction of the cross after a pullback
Stop: Place stop below/above the 200 EMA
Target: Swing high/low or when opposite crossover occurs
Multi-Crossover Confirmation:
Watch for multiple crossovers in the same direction within a short period
Example: 20×50 crossover followed by 20×100 = strengthening momentum
Enter after the second confirmation crossover
More crossovers = stronger signal but also means you're entering later
Time Filter Benefits:The 10:00-18:00 Istanbul time filter prevents recording crossovers during:
Pre-market volatility and gaps
Low-volume overnight sessions (for 24-hour markets)
After-hours erratic movements
Easy [CHE] Easy — Minimalist Pine Script for detecting EMA direction changes to define fixed price zones for simple support and resistance visualization, ideal for manual trading workflows.
Summary
This indicator's programming is kept minimalist and super simple, with core logic in under 20 lines for easy comprehension and modification. It creates fixed price zones based on divergences between a base exponential moving average and its smoother counterpart, helping traders spot potential consolidation or reversal areas without dynamic adjustments. By locking the zone at the high and low of the signal bar, it avoids over-expansion in volatile conditions, offering a stable reference line colored by price position relative to the zone. This approach differs from expanding channels by prioritizing simplicity and persistence until a new qualifying signal, reducing visual clutter while highlighting directional bias through midpoint coloring.
Motivation: Why this design?
Traders often face noisy signals from moving averages that flip frequently in sideways markets or lag during breakouts, leading to premature entries or missed opportunities. This indicator addresses that by focusing on confirmed direction shifts between the base and smoothed averages, then anchoring a non-expanding zone to capture the initial price range of the shift. The result is a cleaner tool for marking equilibrium levels, assuming price respects these bounds in ranging or mildly trending conditions.
What’s different vs. standard approaches?
- Reference baseline: Traditional moving average crossovers or simple channels that update every bar.
- Architecture differences:
- Zones are set only on new divergence signals and remain fixed until reset by a gap from the prior zone.
- No ongoing high-low expansion; relies on persistent variables to hold bounds across bars.
- Midpoint plotting with conditional coloring based on close position, plus a highlight for zone initiations.
- Practical effect: Charts show persistent horizontal references instead of drifting lines, making it easier to gauge if price is rejecting or embracing the zone—useful for avoiding false breaks in low-volatility setups.
How it works (technical)
The indicator first computes a base exponential moving average of closing prices over a user-defined length, then applies a second exponential moving average to smooth that base. It checks if both the base and smoothed values are increasing or decreasing compared to their prior values, indicating aligned direction. A signal triggers when this alignment breaks, marking a potential shift.
On a new signal, if the current bar's high and low fall outside any existing zone (or none exists), the zone bounds update to those extremes and persist via dedicated variables. The midpoint of these bounds becomes the primary plot line, colored green if below the close (bullish lean), red if above (bearish lean), or gray otherwise. A secondary thick line highlights the midpoint briefly when a zone first sets, aiding visual confirmation. No higher timeframe data or external fetches are used, so updates occur on each bar close without lookahead.
Parameter Guide
EMA Length — Sets the period for the base moving average; longer values smooth more, reducing signal frequency but increasing lag. Default: 50. Trade-offs/Tips: Shorter for faster response in intraday charts (risks noise); longer for daily trends (may miss early shifts).
Smoother Length — Defines the period for the secondary smoothing on the base average; higher values dampen minor wiggles for stabler direction checks. Default: 3. Trade-offs/Tips: Keep low (2–5) for sensitivity; increase to 7+ if zones trigger too often in choppy markets, at cost of delayed signals.
Reading & Interpretation
The main circle plot at the zone midpoint serves as a dynamic equilibrium line: green suggests price is above the zone (potential strength), red indicates below (potential weakness), and gray shows containment within bounds (neutral consolidation). A sudden thick foreground line at the midpoint flags a fresh zone start, prompting review of the prior bar's context. Absence of a plot means no active zone, implying reliance on price action alone until the next signal.
Practical Workflows & Combinations
- Trend following: Enter long on green midpoint after a higher low touches the zone lower bound, confirmed by structure like higher highs; filter shorts similarly on red with lower highs.
- Exits/Stops: Use the opposite zone bound as a conservative stop (e.g., below lower for longs); trail aggressively to midpoint on strong moves, tightening near gray neutrality.
- Multi-asset/Multi-TF: Defaults work across forex and stocks on 1H–Daily; for crypto volatility, shorten EMA Length to 20–30. Pair with volume oscillators for confirmation, avoiding isolated use.
Behavior, Constraints & Performance
- Repaint/confirmation: Plots update on bar close using historical closes, so confirmed signals hold; live bars may shift until close but without future references.
- security()/HTF: Not used, eliminating related repaint risks.
- Resources: Minimal overhead—no loops, arrays, or bar limits exceeded; suitable for real-time on any timeframe.
- Known limits: Fixed zones may lag in strong trends (price drifts away without reset); signals skip if no gap from prior zone, potentially missing clustered shifts. Assumes standard OHLC data; untested on non-equity assets.
Sensible Defaults & Quick Tuning
Start with EMA Length at 50 and Smoother Length at 3 for balanced daily charts. If signals fire too frequently (e.g., in ranges), extend EMA Length to 100 for fewer but stabler zones. For sluggish response in trends, drop Smoother Length to 2 and EMA Length to 30, monitoring for added noise. In high-vol setups, widen both to 75/5 to filter extremes, trading speed for reliability.
What this indicator is—and isn’t
This is a lightweight visualization layer for EMA-driven zones, aiding manual chart reading and basic signal spotting. It is not a standalone system, predictive model, or automated alert generator—integrate with broader analysis like market structure and risk rules. (Unknown/Optional: No built-in alerts or multi-timeframe scaling.)
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
ZLEMA Trend Index 2.0ZTI — ZLEMA Trend Index 2.0 (0–1000)
Overview
Price Mapped ZTI v2.0 - Enhanced Zero-Lag Trend Index.
This indicator is a significant upgrade to the original ZTI v1.0, featuring enhanced resolution from 0-100 to 0-1000 levels for dramatically improved price action accuracy. The Price Mapped ZTI uses direct price-to-level mapping to eliminate statistical noise and provide true proportional representation of market movements.
Key Innovation: Instead of statistical normalization, this version maps current price position within a user-defined lookback period directly to the ZTI scale, ensuring perfect correlation with actual price movements. I believe this is the best way to capture trends instead of directly on the charts using a plethora of indicators which introduces bad signals resulting in drawdowns. The RSI-like ZTI overbought and oversold lines filter valid trends by slicing through the current trading zone. Unlike RSI that can introduce false signals, the ZTI levels 1 to 1000 is faithfully mapped to the lowest to highest price in the current trading zone (lookback period in days) which can be changed in the settings. The ZTI line will never go off the beyond the ZTI levels in case of extreme trend continuation as the trading zone is constantly updated to reflect only the most recent bars based on lookback days.
Core Features
✅ 10x Higher Resolution - 0-1000 scale provides granular movement detection
✅ Adjustable Trading Zone - Customizable lookback period from 1-50 days
✅ Price-Proportional Mapping - Direct correlation between price position and ZTI level
✅ Zero Statistical Lag - No rolling averages or standard deviation calculations
✅ Multi-Strategy Adaptability - Single parameter adjustment for different trading styles
Trading Zone Optimization
📊 Lookback Period Strategies
Short-term (1-3 days):
Ultra-responsive to recent price action
Perfect for scalping and day trading
Tight range produces more sensitive signals
Medium-term (7-14 days):
Balanced view of recent trading range
Ideal for swing trading
Captures meaningful support/resistance levels
Long-term (21-30 days):
Broader market context
Excellent for position trading
Smooths out short-term market noise
⚡ Market Condition Adaptation
Volatile Markets: Use shorter lookback (3-5 days) for tighter ranges
Trending Markets: Use longer lookback (14-21 days) for broader context
Ranging Markets: Use medium lookback (7-10 days) for clear boundaries
🎯 Timeframe Optimization
1-minute charts: 1-2 day lookback
5-minute charts: 2-5 day lookback
Hourly charts: 7-14 day lookback
Daily charts: 21-50 day lookback
Trading Applications
Scalping Setup (2-day lookback):
Super tight range for quick reversals
ZTI 800+ = immediate short opportunity
ZTI 200- = immediate long opportunity
Swing Trading Setup (10-day lookback):
Meaningful swing levels captured
ZTI extremes = high-probability reversal zones
More stable signals, reduced whipsaws
Advanced Usage
🔧 Real-Time Adaptability
Trending days: Increase to 14+ days for broader perspective
Range-bound days: Decrease to 3 days for tighter signals
High volatility: Shorter lookback for responsiveness
Low volatility: Longer lookback to avoid false signals
💡 Multi-Timeframe Approach
Entry signals: Use 7-day ZTI on main timeframe
Trend confirmation: Use 21-day ZTI on higher timeframe
Exit timing: Use 3-day ZTI for precise exits
🌐 Session Optimization
Asian session: Shorter lookback (3-5 days) for range-bound conditions
London/NY session: Longer lookback (7-14 days) for trending conditions
How It Works
The indicator maps the current price position within the specified lookback period directly to a 0-1000 scale and plots it using ZLEMA (Zero Lag Exponential Moving Average) which has the least lag of the available popular moving averages:
Price at recent high = ZTI at 1000
Price at recent low = ZTI at 1
Price at mid-range = ZTI at 500
This creates perfect proportional representation where every price movement translates directly to corresponding ZTI movement, eliminating the false signals common in traditional oscillators.
This single, versatile indicator adapts to any market condition, timeframe, or trading style through one simple parameter adjustment, making it an essential tool for traders at every level.
Credits
ZLEMA techniques widely attributed to John Ehlers.
Disclaimer
This tool is for educational purposes only and is not financial advice. Backtest and forward‑test before live use, and always manage risk.
Please note that I set this as closed source to prevent source code cloning by others, repackaging and republishing which results in multiple confusing choices of the same indicator.
Volume Momentum [BackQuant]Volume Momentum
The Volume Momentum indicator is designed to help traders identify shifts in market momentum based on volume data. By analyzing the relative volume momentum, this indicator provides insights into whether the market is gaining strength (uptrend) or losing momentum (downtrend). The strategy uses a combination of percentile-based volume normalization, weighted moving averages (WMA), and exponential moving averages (EMA) to assess volume trends.
The system focuses on the relationship between price and volume, utilizing normalized volume data to highlight key market changes. This approach allows traders to focus on volume-driven price movements, helping them to capture momentum shifts early.
Key Features
1. Volume Normalization and Percentile Calculation:
The signed volume (positive when the close is higher than the open, negative when the close is lower) is normalized against the rolling average volume. This normalized volume is then subjected to a percentile interpolation, allowing for a robust statistical measure of how the current volume compares to historical data. The percentile level is customizable, with 50 representing the median.
2. Weighted and Smoothed Moving Averages for Trend Detection:
The normalized volume is smoothed using weighted moving averages (WMA) and exponential moving averages (EMA). These smoothing techniques help eliminate noise, providing a clearer view of the underlying momentum. The WMA filters out short-term fluctuations, while the EMA ensures that the most recent data points have a higher weight, making the system more responsive to current market conditions.
3. Trend Reversal Detection:
The indicator detects momentum shifts by evaluating whether the volume momentum crosses above or below zero. A positive volume momentum indicates a potential uptrend, while a negative momentum suggests a possible downtrend. These trend reversals are identified through crossover and crossunder conditions, triggering alerts when significant changes occur.
4. Dynamic Trend Background and Bar Coloring:
The script offers customizable background coloring based on the trend direction. When volume momentum is positive, the background is colored green, indicating a bullish trend. When volume momentum is negative, the background is colored red, signaling a bearish trend. Additionally, the bars themselves can be colored based on the trend, further helping traders quickly visualize market momentum.
5. Alerts for Momentum Shifts:
The system provides real-time alerts for traders to monitor when volume momentum crosses a critical threshold (zero), signaling a trend reversal. The alerts notify traders when the market momentum turns bullish or bearish, assisting them in making timely decisions.
6. Customizable Parameters for Flexible Usage:
Users can fine-tune the behavior of the indicator by adjusting various parameters:
Volume Rolling Mean: The period used to calculate the average volume for normalization.
Percentile Interpolation Length: Defines the range over which the percentile is calculated.
Percentile Level: Determines the percentile threshold (e.g., 50 for the median).
WMA and Smoothing Periods: Control the smoothing and response time of the indicator.
7. Trend Background Visualization and Trend-Based Bar Coloring:
The background fill is shaded according to whether the volume momentum is positive or negative, providing a visual cue to indicate market strength. Additionally, bars can be color-coded to highlight the trend, making it easier to see the trend’s direction without needing to analyze numerical data manually.
8. Note on Mean-Reversion Strategy:
If you take the inverse of the signals, this indicator can be adapted for a mean-reversion strategy. Instead of following the trend, the strategy would involve buying assets that are underperforming and selling assets that are overperforming, based on volume momentum. However, it’s important to note that this approach may not work effectively on highly correlated assets, as their price movements may be too similar, reducing the effectiveness of the mean-reversion strategy.
Final Thoughts
The Volume Momentum indicator offers a comprehensive approach to analyzing volume-based momentum shifts in the market. By using volume normalization, percentile interpolation, and smoothed moving averages, this system helps identify the strength and direction of market trends. Whether used for trend-following or adapted for mean-reversion, this tool provides traders with actionable insights into the market’s volume-driven movements, improving decision-making and portfolio management.
TrendTwisterV1.5 (Forex Ready + Indicators)A Precision Trend-Following TradingView Strategy for Forex**
HullShiftFX is a Pine Script strategy for TradingView that combines the power of the **Hull Moving Average (HMA)** and a **shifted Exponential Moving Average (EMA)** with multi-layered momentum filters including **RSI** and **dual Stochastic Oscillators**.
It’s designed for traders looking to catch high-probability breakouts with tight risk management and visual clarity.
Chart settings:
1. Select "Auto - Fits data to screen"
2. Please Select "Scale Price Chart Only" (To make the chart not squished)
### ✅ Entry Conditions
**Long Position:**
- Price closes above the 12-period Hull Moving Average.
- Price closes above the 5-period EMA shifted forward by 2 bars.
- RSI is above 50.
- Stochastic Oscillator (12,3,3) %K is above 50.
- Stochastic Oscillator (5,3,3) %K is above 50.
- Hull MA crosses above the shifted EMA.
**Short Position:**
- Price closes below the 12-period Hull Moving Average.
- Price closes below the 5-period EMA shifted forward by 2 bars.
- RSI is below 50.
- Stochastic Oscillator (12,3,3) %K is below 50.
- Stochastic Oscillator (5,3,3) %K is below 50.
- Hull MA crosses below the shifted EMA.
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## 📉 Risk Management
- **Stop Loss:** Set at the low (for long) or high (for short) of the previous 2 candles.
- **Take Profit:** Calculated at a risk/reward ratio of **1.65x** the stop loss distance.
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## 📊 Indicators Used
- **Hull Moving Average (12)**
- **Exponential Moving Average (5) **
- **Relative Strength Index (14)**
- **Stochastic Oscillators:**
- %K (12,3,3)
- %K (5,3,3)
