MACD Indicator for 5 Min ScalpThis Indicator merges the 1 min MACD with BollingerBands to dedect a bigger than avarage tick on the Macd for the 5 min Scalping Strategy
You can change the length of the bollinger bands for the upper and lower channel individually so that you can get better signals
if a tick is bigger than avarage it will be colored, else it would be gray
this is the same indicator i used to get entrys in my 5 min scalping statagy, but i wouldnt just go in a trade when there is a bigger than usual tick. You have to look at other things to
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Customizable Non-Repainting HTF MACD MFI Scalper Bot Strategy v2Customizable Non-Repainting HTF MACD MFI Scalper Bot Strategy v2
This script was originally shared by Wunderbit as a free open source script for the community to work with. This is my second published iteration of this idea.
WHAT THIS SCRIPT DOES:
It is intended for use on an algorithmic bot trading platform but can be used for scalping and manual trading.
This strategy is based on the trend-following momentum indicator . It includes the Money Flow index as an additional point for entry.
This is a new and improved version geared for lower timeframes (15-5 minutes), but can be run on larger ones as well. I am testing it live as my high frequency trader.
HOW IT DOES IT:
It uses a combination of MACD and MFI indicators to create entry signals. Parameters for each indicator have been surfaced for user configurability.
Take profits are now trailing profits, and the stop loss is now fixed. Why? I found that the trailing stop loss with ATR in the previous version yields very good results for back tests but becomes very difficult to deploy live due to transaction fees. As you can see the average trade is a higher profit percentage than the previous version.
HOW IS MY VERSION ORIGINAL:
Now instead of using ATR stop loss, we have a fixed stop loss - counter intuitively to what some may believe this performs better in live trading scenarios since it gives the strategy room to move. I noticed that the ATR trailing stop was stopping out too fast and was eating away balance due to transaction fees.
The take profit on the other hand is now a trailing profit with a customizable deviation. This ensures that you can have a minimum profit you want to take in order to exit.
I have depracated the old ATR trailing stop as it became too confusing to have those as different options. I kept the old version for others that want to experiment with it. The source code still requires some cleanup, but its fully functional.
I added in a way to show RSI values and ATR values with a checkbox so that you can use the new an improved ATR Filter (and grab the right RSI values for the RSI filter). This will help to filter out times of very low volatility where we are unlikely to find a profitable trade. Use the "Show Data" checkbox to see what the values are on the indicator pane, then use those values to gauge what you want to filter out.
Both versions
Delayed Signals : The script has been refactored to use a time frame drop down. The higher time frame can be run on a faster chart (recommended on one minute chart for fastest signal confirmation and relay to algotrading platform.)
Repainting Issues : All indicators have been recoded to use the security function that checks to see if the current calculation is in realtime, if it is, then it uses the previous bar for calculation. If you are still experiencing repainting issues based on intended (or non intended use), please provide a report with screenshot and explanation so I can try to address.
Filtering : I have added to additional filters an ABOVE EMA Filter and a BELOW RSI Filter (both can be turned on and off)
Customizable Long and Close Messages : This allows someone to use the script for algorithmic trading without having to alter code. It also means you can use one indicator for all of your different alterts required for your bots.
HOW TO USE IT:
It is intended to be used in the 5-30 minute time frames, but you might be able to get a good configuration for higher time frames. I welcome feedback from other users on what they have found.
Find a pair with high volatility (example KUCOIN:ETH3LUSDT ) - I have found it works particularly well with 3L and 3S tokens for crypto. although it the limitation is that confrigurations I have found to work typically have low R/R ratio, but very high win rate and profit factor.
Ideally set one minute chart for bots, but you can use other charts for manual trading. The signal will be delayed by one bar but I have found configurations that still test well.
Select a time frame in configuration for your indicator calculations.
Select the strategy config for time frame (resolution). I like to use 5 and 15 minutes for scalping scenarios, but I am interested in hearing back from other community memebers.
Optimize your indicator without filters : customize your settings for MACD and MFI that are profitable with your chart and selected time frame calculation. Try different Take Profits (try about 2-5%) and stop loss (try about 5-8%). See if your back test is profitable and continue to optimize.
Use the Trend, RSI, ATR Filter to further refine your signals for entry. You will get less entries but you can increase your win ratio.
You can use the open and close messages for a platform integration, but I choose to set mine up on the destination platform and let the platform close it. With certain platforms you cannot be sure what your entry point actually was compared to Trading View due to slippage and timing, so I let the platform decide when it is actually profitable.
Limitations: this works rather well for short term, and does some good forward testing but back testing large data sets is a problem when switching from very small time frame to large time frame. For instance, finding a configuration that works on a one minute chart but then changing to a 1 hour chart means you lose some of your intra bar calclulations. There are some new features in pine script which might be able to address, this, but I have not had a chance to work on that issue.
MACD Volume S2 By Gammaprod>> How to use this indicator :
1. Set your teadingview theme to dark theme.
2. My indicator is valid for forex, stock and but more valid for crypto.
3. Use three timeframe for more validation (choose between those, that fit to your trading style) :
- Timeframe 1m, 5m, and 15m for Scalping
- Timeframe 30m, 1h and 4h for Intraday
- Timeframe 4h, 1D and 1W for Swing Trading
4 . Always use THREE INDICATORS FROM GAMMAPROD, those three indicators is back to back each other, by the way, I only made those three indicators only (for now) :
- Trendlines Boll Ichi Crypto by Gammaprod
- Stoch RSI Divs Zone Crypto by Gammaprod
- MACD Volume Crypto by Gammaprod
>> How to setting :
1. Trendlines Boll Ichi Crypto by Gammaprod
A. Support and Resistence
- Well if you familiar with this indicator you can add it, but recommended for Timeframe 30m or more
B. Trendlines Primary or Trendlines Secondary
- Timeframe 1m you DON'T NEED Trendlines Primary or Trendlines Secondary
- Timeframe 5m you DON'T NEED Trendlines Secondary, but you CAN ADD Trendlines Primary if you fell it helpful (for me, it is helpful to find where the candles start or the end trend or a consolidation or where the candles will surpass a resistance or a support).
- Timeframe 15m you DON'T NEED Trendlines Secondary, DEFENITELY add Trendlines Primary it will help to find where the candles stop or a consolidation or where the candles will surpass a resistance or a support).
- Timeframe 30m or more, DEFENITELY NEED BOTH Trendlines Primary and Secondary Trendlines, it will help to find where the candle stop or consolidation or where the candle will surpass a resistance or support).
C. Bolinger, Ichimoku Cloud and Lagging Span
- Please DON'T CHANGE IT at all, it's really helpful to know when and where to make an entry decesion or a trend or a consolidation, if you don't understand how to read it, you better to learn it first (on "how to read" section and "How to OPEN position" the section below)
2. Stoch RSI Divs Zone Crypto by Gammaprod (DON'T CHANGE IT)
3. MACD Volume Crypto by Gammaprod (DON'T CHANGE IT)
>> How to read :
1. Sell or Buy Priority :
A. Buy Priority
- Color background on macd and stoch rsi is pink or purple sell is the priority, (if you're not sure to buy, just wait until the best moment to sell)
B. Buy Priority
- Color background on macd and stoch rsi Teal or light green buy is the priority, (if you're not sure to sell, just wait until the best moment to buy)
C. Indecision / Golden Moment
- Color background on stoch rsi yellow is indecision / golden moment of reversal pattern (wait until it formed background only on Stoch RSI), please becareful at this moment.
2. Trend / Consolidation :
A. BULLISH trend
- When Stoch RSI and MACD have teal or light green background that's means BULLISH trend, better to confirm by the candle is above green cloud and lagging span (red line) is also above the candle.
B. BEARISH trend
- When Stoch RSI and MACD have the Pink or purple background that's means BEARISH trend, better to confirm by the candle is above purple cloud and lagging span (red line) is also below the candle.
C. CONSOLIDATION
- When Stoch RSI have the mix background that's means CONSOLIDATION, better to confirm by the candle is in or near to green / purple cloud and lagging span (red line) is also on the candle.
3. Special Mark
A. Ideal Bullish :
- Near line 20 and green / teal background = When Stoch RSI have the char R / H on lime color label, that's means divergence or hidden divergence for buy position, if you not see this label that's means just a standard confirmation for buy
B. Not an Ideal Bullish :
- Near line 80 and green / teal background = if this happens make sure you know what happen, it could be a false signal or bullish continual pattern
C. Ideal Bearish :
- Near line 80 and pink / purple background = When Stoch RSI have the char R / H on lime color label, that's means divergence or hidden divergence for buy position, if you not see this label that's means just a standard confirmation for sell position.
D. Not an Ideal Bearish:
- Near line 20 and pink / purple background = if this happens make sure you know what happen, it could be a false signal or bearish continual pattern
E. The Beginning of Reversal (from BEARISH to BULLISH) :
- When Stoch RSI line shaping GREEN position is near 20.
- MACD lines still PINK, position lines is UNDER the HISTOGRAM, but the HISTOGRAM start to SHAPE FALL PINK (light pink) and the BACKGROUND still PINK / PURPLE.
- Position CANDLES NEAR BLUE line, NEAR PURPLE CLOUD, and lagging span (red line) STILL ON the area candle. (it used to be confirmed with the golden moment).
F. The Beginning of Reversal (from BULLISH to BEARISH) :
- When Stoch RSI line shaping PINK position is near 80.
- MACD lines still GREEN, position lines is ABOVE the HISTOGRAM, but the HISTOGRAM start to SHAPE FALL GREEN (light green) and the BACKGROUND still TEAL / GREEN.
- Position CANDLES NEAR WHITE line, NEAR TEAL CLOUD, and lagging span (red line) STILL ON the area candle. (it used to be confirmed with the golden moment).
G. False Signals, or It could be a Golden Moment (better to see it on TF 15 or bigger):
- Near line 20 or 80 and yellow background = When Stoch RSI have the char R / H on color label, that's means divergence or hidden divergence for buy / sell position, if you not see this label that's means just a standard confirmation for buy / sell depends on where the Stoch RSI line if near 20 that's means buy, near 80 means sell
>> How to OPEN position:
A. Bullish
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles above the green cloud.
- Lagging span (red line) above the candles.
- then open buy near yellow line (the first option) / blue line (the second option) (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Teal or Green background.
- The lines is shaping green.
- Better if on the bottom (at a range 20).
3. MACD Volume Crypto by Gammaprod
- Teal or Green background.
- The lines is shaped or shaping green.
- Better if at the green histogram.
B. Bearish
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles below the purple cloud.
- Lagging span (red line) below the candles.
- then open buy near yellow line (the first option) / white line (the second option) (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Pink or purple background.
- The lines are shaping pink.
- Better if the line on the top (at a range 80).
3. MACD Volume Crypto by Gammaprod
- Pink or purple background.
- The lines are shaped or shaping green.
- Better if at the pink histogram.
C. Consolidation
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles on the cloud (green or purple).
- Lagging span (red line) on the candles.
- then open buy near the white or blue line (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Mix background specially on a timeframe 15m or more.
- The line move fast up and down.
- Better if on the bottom or the top of the lines (at a range 20 or 80).
3. MACD Volume Crypto by Gammaprod
- Changing the background.
- The line is near the middle line.
- Have small Histogram.
>> The secret ingridient is comparing the timeframe :
The example scalping (Timeframe 1m, 5m and 15m)
- TF 1m is for making an open position.
- TF 5m is for making a judgement of the trend market.
- TF 15m is to confirm that judgement from TF 5m, be careful if it not similar then it used to be a consolidation or the beginning of the reversal.
There's a lot a way to open the position than above information that i gave it to you, but consider there are a limit char on this column, I hope it will help your trading and make a more profit on it.
Stoch RSI, Div, Zone S3 by Gammaprod>> How to use this indicator :
1. Set your teadingview theme to dark theme.
2. My indicator is valid for forex, stock and but more valid for crypto.
3. Use three timeframe for more validation (choose between those, that fit to your trading style) :
- Timeframe 1m, 5m, and 15m for Scalping
- Timeframe 30m, 1h and 4h for Intraday
- Timeframe 4h, 1D and 1W for Swing Trading
4 . Always use THREE INDICATORS FROM GAMMAPROD, those three indicators is back to back each other, by the way, I only made those three indicators only (for now) :
- Trendlines Boll Ichi Crypto by Gammaprod
- Stoch RSI Divs Zone Crypto by Gammaprod
- MACD Volume Crypto by Gammaprod
>> How to setting :
1. Trendlines Boll Ichi Crypto by Gammaprod
A. Support and Resistence
- Well if you familiar with this indicator you can add it, but recommended for Timeframe 30m or more
B. Trendlines Primary or Trendlines Secondary
- Timeframe 1m you DON'T NEED Trendlines Primary or Trendlines Secondary
- Timeframe 5m you DON'T NEED Trendlines Secondary, but you CAN ADD Trendlines Primary if you fell it helpful (for me, it is helpful to find where the candles start or the end trend or a consolidation or where the candles will surpass a resistance or a support).
- Timeframe 15m you DON'T NEED Trendlines Secondary, DEFENITELY add Trendlines Primary it will help to find where the candles stop or a consolidation or where the candles will surpass a resistance or a support).
- Timeframe 30m or more, DEFENITELY NEED BOTH Trendlines Primary and Secondary Trendlines, it will help to find where the candle stop or consolidation or where the candle will surpass a resistance or support).
C. Bolinger, Ichimoku Cloud and Lagging Span
- Please DON'T CHANGE IT at all, it's really helpful to know when and where to make an entry decesion or a trend or a consolidation, if you don't understand how to read it, you better to learn it first (on "how to read" section and "How to OPEN position" the section below)
2. Stoch RSI Divs Zone Crypto by Gammaprod (DON'T CHANGE IT)
3. MACD Volume Crypto by Gammaprod (DON'T CHANGE IT)
>> How to read :
1. Sell or Buy Priority :
A. Buy Priority
- Color background on macd and stoch rsi is pink or purple sell is the priority, (if you're not sure to buy, just wait until the best moment to sell)
B. Buy Priority
- Color background on macd and stoch rsi Teal or light green buy is the priority, (if you're not sure to sell, just wait until the best moment to buy)
C. Indecision / Golden Moment
- Color background on stoch rsi yellow is indecision / golden moment of reversal pattern (wait until it formed background only on Stoch RSI), please becareful at this moment.
2. Trend / Consolidation :
A. BULLISH trend
- When Stoch RSI and MACD have teal or light green background that's means BULLISH trend, better to confirm by the candle is above green cloud and lagging span (red line) is also above the candle.
B. BEARISH trend
- When Stoch RSI and MACD have the Pink or purple background that's means BEARISH trend, better to confirm by the candle is above purple cloud and lagging span (red line) is also below the candle.
C. CONSOLIDATION
- When Stoch RSI have the mix background that's means CONSOLIDATION, better to confirm by the candle is in or near to green / purple cloud and lagging span (red line) is also on the candle.
3. Special Mark
A. Ideal Bullish :
- Near line 20 and green / teal background = When Stoch RSI have the char R / H on lime color label, that's means divergence or hidden divergence for buy position, if you not see this label that's means just a standard confirmation for buy
B. Not an Ideal Bullish :
- Near line 80 and green / teal background = if this happens make sure you know what happen, it could be a false signal or bullish continual pattern
C. Ideal Bearish :
- Near line 80 and pink / purple background = When Stoch RSI have the char R / H on lime color label, that's means divergence or hidden divergence for buy position, if you not see this label that's means just a standard confirmation for sell position.
D. Not an Ideal Bearish:
- Near line 20 and pink / purple background = if this happens make sure you know what happen, it could be a false signal or bearish continual pattern
E. The Beginning of Reversal (from BEARISH to BULLISH) :
- When Stoch RSI line shaping GREEN position is near 20.
- MACD lines still PINK, position lines is UNDER the HISTOGRAM, but the HISTOGRAM start to SHAPE FALL PINK (light pink) and the BACKGROUND still PINK / PURPLE.
- Position CANDLES NEAR BLUE line, NEAR PURPLE CLOUD, and lagging span (red line) STILL ON the area candle. (it used to be confirmed with the golden moment).
F. The Beginning of Reversal (from BULLISH to BEARISH) :
- When Stoch RSI line shaping PINK position is near 80.
- MACD lines still GREEN, position lines is ABOVE the HISTOGRAM, but the HISTOGRAM start to SHAPE FALL GREEN (light green) and the BACKGROUND still TEAL / GREEN.
- Position CANDLES NEAR WHITE line, NEAR TEAL CLOUD, and lagging span (red line) STILL ON the area candle. (it used to be confirmed with the golden moment).
G. False Signals, or It could be a Golden Moment (better to see it on TF 15 or bigger):
- Near line 20 or 80 and yellow background = When Stoch RSI have the char R / H on color label, that's means divergence or hidden divergence for buy / sell position, if you not see this label that's means just a standard confirmation for buy / sell depends on where the Stoch RSI line if near 20 that's means buy, near 80 means sell
>> How to OPEN position:
A. Bullish
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles above the green cloud.
- Lagging span (red line) above the candles.
- then open buy near yellow line (the first option) / blue line (the second option) (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Teal or Green background.
- The lines is shaping green.
- Better if on the bottom (at a range 20).
3. MACD Volume Crypto by Gammaprod
- Teal or Green background.
- The lines is shaped or shaping green.
- Better if at the green histogram.
B. Bearish
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles below the purple cloud.
- Lagging span (red line) below the candles.
- then open buy near yellow line (the first option) / white line (the second option) (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Pink or purple background.
- The lines are shaping pink.
- Better if the line on the top (at a range 80).
3. MACD Volume Crypto by Gammaprod
- Pink or purple background.
- The lines are shaped or shaping green.
- Better if at the pink histogram.
C. Consolidation
1. Trendlines Boll Ichi Crypto by Gammaprod
- The candles on the cloud (green or purple).
- Lagging span (red line) on the candles.
- then open buy near the white or blue line (always confirm the position with two other indicators below).
2. Stoch RSI Divs Zone Crypto by Gammaprod
- Mix background specially on a timeframe 15m or more.
- The line move fast up and down.
- Better if on the bottom or the top of the lines (at a range 20 or 80).
3. MACD Volume Crypto by Gammaprod
- Changing the background.
- The line is near the middle line.
- Have small Histogram.
>> The secret ingridient is comparing the timeframe :
The example scalping (Timeframe 1m, 5m and 15m)
- TF 1m is for making an open position.
- TF 5m is for making a judgement of the trend market.
- TF 15m is to confirm that judgement from TF 5m, be careful if it not similar then it used to be a consolidation or the beginning of the reversal.
There's a lot a way to open the position than above information that i gave it to you, but consider there are a limit char on this column, I hope it will help your trading and make a more profit on it.
Bogdan Ciocoiu - Code runnerDescription
The Code Runner is a hybrid indicator that leverages other pre-configured, integrated open-source algorithms to help traders spot regular and continuation divergences.
The Code Runner specialises in integrating some of the most popular oscillators well known for their accuracy when scalping using divergence strategies.
Uniqueness
The Code Runner stands out as a one-stop-shop pack of oscillator algorithms that traders can further customise to spot divergences.
The indicator's uniqueness stands from its capability to recast each algorithm to apply to the same scale. This feature is achieved by manually adjusting the outputs of each algorithm to fit on a scale between +100 and -100.
Another benefit of the Code Runner comes from its standardisation of outputs, mainly consisting of lines. Showing lines enables traders to draw potential regular and continuation divergences quickly.
The indicator has been pre-configured to support scalping at 1-5 minutes.
Open-source
The Code Runner uses the following open-source scripts and algorithms:
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
www.tradingview.com
These algorithms are available in the public domain either in TradingView space or outside (given their popularity in the financial markets industry).
Crypto EMA Trend Reversal StrategyThis is an EMA crossover strategy which involves 5 EMAs to trigger trades. The strategy has two take profit settings and uses a stop loss.
TP1 and SL are based on ATR and TP2 is an EMA crossover.
The strategy goes both long and short and the default settings work particularly well as a scalping strategy for ETHUSDT on the 5M time frame.
I have also created another version with tweaked settings for scalping LINKUSDT on the 5M with very similar results.
There is an option to add a volume condition parameter within the script on lines 26-28 which can be added to the end of lines 34-35 in the following format: and vol_cond
I personally don't currently use the volume condition parameter.
EBB & Flow: a multi-EMA-based BB cloudIntro
This is an idea evolved out of the market maker method and EMA convergence, divergence, and mean reversion.
The market maker method informs us that the 5, 13, 50 and 200 EMAs are important to regulating price. Those EMA lengths are multiples of the 50 and 200 on lower major timeframes -- the 1 minute, 5, 15, 1H, 4H, 1D. I include the 21 because it is also a multiple and in crypto very often respected.
When market makers are testing price, they set their range and spike in the direction they test for liquidity. This can get chaotic. For instance, in a shorter time frame consolidation inside a bigger timeframe uptrend, it can be too easy to forget where you are in the many trends playing out.
When the EMAs are dragged over each other during normal price movement, you get these crisscrossing tracks of price, and the individual breaks can be hard to trace.
The range is what matters, ultimately, and the range is dynamic. In that case, the Bollinger Band is a great tool for detecting outliers in this case.
The Answer
So the answer this indicator seeks to give, is to look for outliers. This gives you a scalping strategy built on Traders Reality thinking and best put together with the PVSRA indicator, which I may include in this indicator just for the sake of concision, but they can work alongside each other or separately.
The key thing is the different EMA clouds, which are bollinger bands. Tight bands mean imminent breaks, favouring the trend. Vector candles out of a zone, pins to the low/high, etc. are all very relevant alongside this indicator.
You can also use it on its own and scalp the breaks of a cloud.
How it works
Each cloud is a standard deviation from their respective EMA, all in the same colour. The deviation multiple is 1.618 by default. Yes, fibonacci sequences are usually nonsense, but it works better with the BB than 2, 2.5 or 3.
Using just the clouds, you can see where each EMA is headed and how it behaves within the deviation of the others.
But that on its own isn't enough.
The indicator will also print snowflakes above and below the candle for notable outliers. It will be in the colour of the cloud it breaks, but only if that break is also breaking the smaller EMA clouds too.
The most snowflakes will be yellow because that's the 13 EMA. That one is dependent on nothing else and every break will print a snowflake. The 21 will be dependent on the 13. The 50 dependent on the 13 and 21 breaks. The 200 the most important.
For example, if the 200 EMA-BB or EBB is broken at the upper band, deviating by more than 162% of price over a 200 period EMA, and that break is not above the 50 EMA cloud, there will be no snowflake. However, if it exceeds the 13, 21, 50, and 200 clouds, then a purple snowflake will appear above the bar.
Any snowflake is an extreme in price. The purple is an especially good point of entry. That doesn't mean it is a perfect entry. You can build position from it, though, and be relatively certain of a price correction in the near future, because not only was this major EMA cloud violated, but all of the smaller ones too.
Reminder
You still need your PVSRA and candlesticks. This indicator on its own may have a nice hit rate for scalping and building position, as an alternative to the TDI or alongside it, but it is not enough on its own, just like the TDI.
Enjoy!
L1 Mid-Term Swing Oscillator v1Level: 1
Background
Oscillators are widely used set of technical analysis indicators. They are popular primarily for their ability to alert of a possible trend change before that change manifests itself in price and volume . They should work best in times of sideways markets.
Function
L1 Short-Mid-Long-Term Swing Oscillator puts three terms of oscillators to cover short-term, middle-term and long-term oscillators at the same time. By resonating all these three oscillators, short-term scalping signal and middle term swing signal are disclosed. You can see both short and mid term signal under one indicator which give you more confidence to follow the trend.
Key Signal
I didn't handle the key signals well. I piled up all the useful signals I found, and it is really difficult to classify them one by one. I feel tired when I think about this problem. Therefore, the code of the overall signal is rather confusing, sorry.
Pros and Cons
Pros:
1. Three oscillators are used to cover short, mid, long term oscillations.
2. Short-Mid term resonance can be observed to have higher confidence level.
3. Use single indicator for scalping and swing trading is possible.
Cons:
1. No deep dive into very accurate long and short entries.
2. A trade off between sensitivity and stability may be needed by traders' subjective judge.
Remarks
I enjoyed the fun of put three different oscillator together to cover short, mid, long terms. But how to use them perfectly is really more brainstorming.
Readme
In real life, I am a prolific inventor. I have successfully applied for more than 60 international and regional patents in the past 12 years. But in the past two years or so, I have tried to transfer my creativity to the development of trading strategies. Tradingview is the ideal platform for me. I am selecting and contributing some of the hundreds of scripts to publish in Tradingview community. Welcome everyone to interact with me to discuss these interesting pine scripts.
The scripts posted are categorized into 5 levels according to my efforts or manhours put into these works.
Level 1 : interesting script snippets or distinctive improvement from classic indicators or strategy. Level 1 scripts can usually appear in more complex indicators as a function module or element.
Level 2 : composite indicator/strategy. By selecting or combining several independent or dependent functions or sub indicators in proper way, the composite script exhibits a resonance phenomenon which can filter out noise or fake trading signal to enhance trading confidence level.
Level 3 : comprehensive indicator/strategy. They are simple trading systems based on my strategies. They are commonly containing several or all of entry signal, close signal, stop loss, take profit, re-entry, risk management, and position sizing techniques. Even some interesting fundamental and mass psychological aspects are incorporated.
Level 4 : script snippets or functions that do not disclose source code. Interesting element that can reveal market laws and work as raw material for indicators and strategies. If you find Level 1~2 scripts are helpful, Level 4 is a private version that took me far more efforts to develop.
Level 5 : indicator/strategy that do not disclose source code. private version of Level 3 script with my accumulated script processing skills or a large number of custom functions. I had a private function library built in past two years. Level 5 scripts use many of them to achieve private trading strategy.
Bandpass Cycle Indicator [Ehlers]This indicator is NOT used for entry and exit conditions when trading. Instead, it's purpose is to tell you what the state of the market is: trending or cyclical.
>WHO IS THIS FOR?
This is especially useful for strategies that use scalping or martingale betting to turn a profit. You don't want to be caught in a bullish trend with several open short orders. Algo traders welcome.
>HOW DOES IT WORK?
I'm glad you asked. It's based on Ehlers' work regarding signal filtering. Essentially, it uses a bandpass filter to reduce noise that is inherent in the market and display the underlying frequency.
First, we get rid of the high-frequency noise - think jitters, long wicks, etc... price action that usually effects EMAs and other MAs. We don't want any of that.
Next, we get rid of low-frequency noise - this is a little more difficult to picture, but we're essentially ignoring cycles (Elliot waves) from other longer time frames. We don't care if the Daily bars are just about to reverse if it doesn't affect our scalping strategy.
Finally, we find the root mean square (RMS) of the high and low points of our newly created signal (red) and plot them (black). These will act as triggers to tell us if a market is in cycle or trending.
>HOW DO YOU READ IT?
Background colors:
-Blue is cycle - you're safe.
-Red is trending down
-Green is trending up
Crossovers:
-Red above Upper Black: Uptrend
-Red below Lower Black: Downtrend
-Red in the middle: Cycle
>IS IT PREDICTIVE?
Momentum tends to pick up quickly and decline quickly, so if you'll often see a small Red or Green strip before a large price movement.
After long periods of cyclic movement (or consolidation), there isn't much momentum in the system, so any small price action will be considered a trend -> these small movements are picked up by other human traders and bots. Trading volume increases more and more until you have a swing in one direction.
So yes, it can be predictive due to the nature of signals and oscillation. Maybe not necessarily predictive of which direction price will go, but when volatility is about to increase.
5 EMAs plus Crossing AlertsHi all,
This is a simple indicator that plots 5 EMA lines of your choice to the screen.
Can be used to trigger scalping Bots (stoploss around 0.5% recommended, take profit 1% or higher, please backtest!)
Also can be used for manual scalping, 1 or 2 candles at a time.
Features:
1) Alerts are triggered when EMAs 1 (Signal line) and 2 (Baseline) cross - a Long signal is called if the cross is above EMA 3 (Trendline), a short if the cross is below EMA3
2) Signals are represented visually as a triangle on the chart, below the candles is a long, above is a short
3) TradingView Alerts can be easily set as I have labelled the signals clearly as many other Indicators like this aren’t easy to work out if trying to create alerts to trigger a 3commas bot, for example!
Each EMA is fully customisable and if you wish to take advantage of the alerts, only a few simple rules need to be followed:
EMA1 needs to be less than EMA2.
EMA2 needs to be the same or greater than EMA3
That’s it, happy trading!
Big shout out to B and the gang over at Crypto Trading Group!
BB+AO STRATto be used with AO indicator, based on forex strat --
www.forexstrategiesresources.com
works on 1/3/5/15/30 candles, buy signals are best when the black 3 fast ema crosses up through the red mid band
BB+AO ALERTSto be used with AO indicator, based on forex strat --
www.forexstrategiesresources.com
works on 1/3/5/15/30 candles, buy signals are best when the black 3 fast ema crosses up through the red mid band
BB+AO STRATto be used with AO, based on forex strat --
www.forexstrategiesresources.com
works on 1/3/5/15/30 candles
Volume-Weighted RSI [VWRSI 2D Pro]A modular, volume-weighted RSI indicator built for clarity and control.
✅ Profile-based auto modes (Scalping → Macro)
✅ Toggleable Buy/Sell signals with strict mode
✅ RSI MA overlays for smoother entries
Buy Signal
RSI crosses above RSI MA
RSI > 50 (or > 55 in strict mode)
Sell Signal
RSI crosses below RSI MA
RSI < 50 (or < 45 in strict mode)
Strict mode filters out weak signals for higher conviction entries.
Volatility-Adaptive RSI Thresholds:
Traditional RSI uses static levels (70/30).
VWRSI Pro replaces these with dynamic bands:
🔹dynHigh = mean + mult × deviation
🔹 dynLow = mean − mult × deviation
Technical write-up can be found here: github.com
Adaptive Market Wave TheoryAdaptive Market Wave Theory
🌊 CORE INNOVATION: PROBABILISTIC PHASE DETECTION WITH MULTI-AGENT CONSENSUS
Adaptive Market Wave Theory (AMWT) represents a fundamental paradigm shift in how traders approach market phase identification. Rather than counting waves subjectively or drawing static breakout levels, AMWT treats the market as a hidden state machine —using Hidden Markov Models, multi-agent consensus systems, and reinforcement learning algorithms to quantify what traditional methods leave to interpretation.
The Wave Analysis Problem:
Traditional wave counting methodologies (Elliott Wave, harmonic patterns, ABC corrections) share fatal weaknesses that AMWT directly addresses:
1. Non-Falsifiability : Invalid wave counts can always be "recounted" or "adjusted." If your Wave 3 fails, it becomes "Wave 3 of a larger degree" or "actually Wave C." There's no objective failure condition.
2. Observer Bias : Two expert wave analysts examining the same chart routinely reach different conclusions. This isn't a feature—it's a fundamental methodology flaw.
3. No Confidence Measure : Traditional analysis says "This IS Wave 3." But with what probability? 51%? 95%? The binary nature prevents proper position sizing and risk management.
4. Static Rules : Fixed Fibonacci ratios and wave guidelines cannot adapt to changing market regimes. What worked in 2019 may fail in 2024.
5. No Accountability : Wave methodologies rarely track their own performance. There's no feedback loop to improve.
The AMWT Solution:
AMWT addresses each limitation through rigorous mathematical frameworks borrowed from speech recognition, machine learning, and reinforcement learning:
• Non-Falsifiability → Hard Invalidation : Wave hypotheses die permanently when price violates calculated invalidation levels. No recounting allowed.
• Observer Bias → Multi-Agent Consensus : Three independent analytical agents must agree. Single-methodology bias is eliminated.
• No Confidence → Probabilistic States : Every market state has a calculated probability from Hidden Markov Model inference. "72% probability of impulse state" replaces "This is Wave 3."
• Static Rules → Adaptive Learning : Thompson Sampling multi-armed bandits learn which agents perform best in current conditions. The system adapts in real-time.
• No Accountability → Performance Tracking : Comprehensive statistics track every signal's outcome. The system knows its own performance.
The Core Insight:
"Traditional wave analysis asks 'What count is this?' AMWT asks 'What is the probability we are in an impulsive state, with what confidence, confirmed by how many independent methodologies, and anchored to what liquidity event?'"
🔬 THEORETICAL FOUNDATION: HIDDEN MARKOV MODELS
Why Hidden Markov Models?
Markets exist in hidden states that we cannot directly observe—only their effects on price are visible. When the market is in an "impulse up" state, we see rising prices, expanding volume, and trending indicators. But we don't observe the state itself—we infer it from observables.
This is precisely the problem Hidden Markov Models (HMMs) solve. Originally developed for speech recognition (inferring words from sound waves), HMMs excel at estimating hidden states from noisy observations.
HMM Components:
1. Hidden States (S) : The unobservable market conditions
2. Observations (O) : What we can measure (price, volume, indicators)
3. Transition Matrix (A) : Probability of moving between states
4. Emission Matrix (B) : Probability of observations given each state
5. Initial Distribution (π) : Starting state probabilities
AMWT's Six Market States:
State 0: IMPULSE_UP
• Definition: Strong bullish momentum with high participation
• Observable Signatures: Rising prices, expanding volume, RSI >60, price above upper Bollinger Band, MACD histogram positive and rising
• Typical Duration: 5-20 bars depending on timeframe
• What It Means: Institutional buying pressure, trend acceleration phase
State 1: IMPULSE_DN
• Definition: Strong bearish momentum with high participation
• Observable Signatures: Falling prices, expanding volume, RSI <40, price below lower Bollinger Band, MACD histogram negative and falling
• Typical Duration: 5-20 bars (often shorter than bullish impulses—markets fall faster)
• What It Means: Institutional selling pressure, panic or distribution acceleration
State 2: CORRECTION
• Definition: Counter-trend consolidation with declining momentum
• Observable Signatures: Sideways or mild counter-trend movement, contracting volume, RSI returning toward 50, Bollinger Bands narrowing
• Typical Duration: 8-30 bars
• What It Means: Profit-taking, digestion of prior move, potential accumulation for next leg
State 3: ACCUMULATION
• Definition: Base-building near lows where informed participants absorb supply
• Observable Signatures: Price near recent lows but not making new lows, volume spikes on up bars, RSI showing positive divergence, tight range
• Typical Duration: 15-50 bars
• What It Means: Smart money buying from weak hands, preparing for markup phase
State 4: DISTRIBUTION
• Definition: Top-forming near highs where informed participants distribute holdings
• Observable Signatures: Price near recent highs but struggling to advance, volume spikes on down bars, RSI showing negative divergence, widening range
• Typical Duration: 15-50 bars
• What It Means: Smart money selling to late buyers, preparing for markdown phase
State 5: TRANSITION
• Definition: Regime change period with mixed signals and elevated uncertainty
• Observable Signatures: Conflicting indicators, whipsaw price action, no clear momentum, high volatility without direction
• Typical Duration: 5-15 bars
• What It Means: Market deciding next direction, dangerous for directional trades
The Transition Matrix:
The transition matrix A captures the probability of moving from one state to another. AMWT initializes with empirically-derived values then updates online:
From/To IMP_UP IMP_DN CORR ACCUM DIST TRANS
IMP_UP 0.70 0.02 0.20 0.02 0.04 0.02
IMP_DN 0.02 0.70 0.20 0.04 0.02 0.02
CORR 0.15 0.15 0.50 0.10 0.10 0.00
ACCUM 0.30 0.05 0.15 0.40 0.05 0.05
DIST 0.05 0.30 0.15 0.05 0.40 0.05
TRANS 0.20 0.20 0.20 0.15 0.15 0.10
Key Insights from Transition Probabilities:
• Impulse states are sticky (70% self-transition): Once trending, markets tend to continue
• Corrections can transition to either impulse direction (15% each): The next move after correction is uncertain
• Accumulation strongly favors IMP_UP transition (30%): Base-building leads to rallies
• Distribution strongly favors IMP_DN transition (30%): Topping leads to declines
The Viterbi Algorithm:
Given a sequence of observations, how do we find the most likely state sequence? This is the Viterbi algorithm—dynamic programming to find the optimal path through the state space.
Mathematical Formulation:
δ_t(j) = max_i × B_j(O_t)
Where:
δ_t(j) = probability of most likely path ending in state j at time t
A_ij = transition probability from state i to state j
B_j(O_t) = emission probability of observation O_t given state j
AMWT Implementation:
AMWT runs Viterbi over a rolling window (default 50 bars), computing the most likely state sequence and extracting:
• Current state estimate
• State confidence (probability of current state vs alternatives)
• State sequence for pattern detection
Online Learning (Baum-Welch Adaptation):
Unlike static HMMs, AMWT continuously updates its transition and emission matrices based on observed market behavior:
f_onlineUpdateHMM(prev_state, curr_state, observation, decay) =>
// Update transition matrix
A *= decay
A += (1.0 - decay)
// Renormalize row
// Update emission matrix
B *= decay
B += (1.0 - decay)
// Renormalize row
The decay parameter (default 0.85) controls adaptation speed:
• Higher decay (0.95): Slower adaptation, more stable, better for consistent markets
• Lower decay (0.80): Faster adaptation, more reactive, better for regime changes
Why This Matters for Trading:
Traditional indicators give you a number (RSI = 72). AMWT gives you a probabilistic state assessment :
"There is a 78% probability we are in IMPULSE_UP state, with 15% probability of CORRECTION and 7% distributed among other states. The transition matrix suggests 70% chance of remaining in IMPULSE_UP next bar, 20% chance of transitioning to CORRECTION."
This enables:
• Position sizing by confidence : 90% confidence = full size; 60% confidence = half size
• Risk management by transition probability : High correction probability = tighten stops
• Strategy selection by state : IMPULSE = trend-follow; CORRECTION = wait; ACCUMULATION = scale in
🎰 THE 3-BANDIT CONSENSUS SYSTEM
The Multi-Agent Philosophy:
No single analytical methodology works in all market conditions. Trend-following excels in trending markets but gets chopped in ranges. Mean-reversion excels in ranges but gets crushed in trends. Structure-based analysis works when structure is clear but fails in chaotic markets.
AMWT's solution: employ three independent agents , each analyzing the market from a different perspective, then use Thompson Sampling to learn which agents perform best in current conditions.
Agent 1: TREND AGENT
Philosophy : Markets trend. Follow the trend until it ends.
Analytical Components:
• EMA Alignment: EMA8 > EMA21 > EMA50 (bullish) or inverse (bearish)
• MACD Histogram: Direction and rate of change
• Price Momentum: Close relative to ATR-normalized movement
• VWAP Position: Price above/below volume-weighted average price
Signal Generation:
Strong Bull: EMA aligned bull AND MACD histogram > 0 AND momentum > 0.3 AND close > VWAP
→ Signal: +1 (Long), Confidence: 0.75 + |momentum| × 0.4
Moderate Bull: EMA stack bull AND MACD rising AND momentum > 0.1
→ Signal: +1 (Long), Confidence: 0.65 + |momentum| × 0.3
Strong Bear: EMA aligned bear AND MACD histogram < 0 AND momentum < -0.3 AND close < VWAP
→ Signal: -1 (Short), Confidence: 0.75 + |momentum| × 0.4
Moderate Bear: EMA stack bear AND MACD falling AND momentum < -0.1
→ Signal: -1 (Short), Confidence: 0.65 + |momentum| × 0.3
When Trend Agent Excels:
• Trend days (IB extension >1.5x)
• Post-breakout continuation
• Institutional accumulation/distribution phases
When Trend Agent Fails:
• Range-bound markets (ADX <20)
• Chop zones after volatility spikes
• Reversal days at major levels
Agent 2: REVERSION AGENT
Philosophy: Markets revert to mean. Extreme readings reverse.
Analytical Components:
• Bollinger Band Position: Distance from bands, percent B
• RSI Extremes: Overbought (>70) and oversold (<30)
• Stochastic: %K/%D crossovers at extremes
• Band Squeeze: Bollinger Band width contraction
Signal Generation:
Oversold Bounce: BB %B < 0.20 AND RSI < 35 AND Stochastic < 25
→ Signal: +1 (Long), Confidence: 0.70 + (30 - RSI) × 0.01
Overbought Fade: BB %B > 0.80 AND RSI > 65 AND Stochastic > 75
→ Signal: -1 (Short), Confidence: 0.70 + (RSI - 70) × 0.01
Squeeze Fire Bull: Band squeeze ending AND close > upper band
→ Signal: +1 (Long), Confidence: 0.65
Squeeze Fire Bear: Band squeeze ending AND close < lower band
→ Signal: -1 (Short), Confidence: 0.65
When Reversion Agent Excels:
• Rotation days (price stays within IB)
• Range-bound consolidation
• After extended moves without pullback
When Reversion Agent Fails:
• Strong trend days (RSI can stay overbought for days)
• Breakout moves
• News-driven directional moves
Agent 3: STRUCTURE AGENT
Philosophy: Market structure reveals institutional intent. Follow the smart money.
Analytical Components:
• Break of Structure (BOS): Price breaks prior swing high/low
• Change of Character (CHOCH): First break against prevailing trend
• Higher Highs/Higher Lows: Bullish structure
• Lower Highs/Lower Lows: Bearish structure
• Liquidity Sweeps: Stop runs that reverse
Signal Generation:
BOS Bull: Price breaks above prior swing high with momentum
→ Signal: +1 (Long), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bull: First higher low after downtrend, breaking structure
→ Signal: +1 (Long), Confidence: 0.75
BOS Bear: Price breaks below prior swing low with momentum
→ Signal: -1 (Short), Confidence: 0.70 + structure_strength × 0.2
CHOCH Bear: First lower high after uptrend, breaking structure
→ Signal: -1 (Short), Confidence: 0.75
Liquidity Sweep Long: Price sweeps below swing low then reverses strongly
→ Signal: +1 (Long), Confidence: 0.80
Liquidity Sweep Short: Price sweeps above swing high then reverses strongly
→ Signal: -1 (Short), Confidence: 0.80
When Structure Agent Excels:
• After liquidity grabs (stop runs)
• At major swing points
• During institutional accumulation/distribution
When Structure Agent Fails:
• Choppy, structureless markets
• During news events (structure becomes noise)
• Very low timeframes (noise overwhelms structure)
Thompson Sampling: The Bandit Algorithm
With three agents giving potentially different signals, how do we decide which to trust? This is the multi-armed bandit problem —balancing exploitation (using what works) with exploration (testing alternatives).
Thompson Sampling Solution:
Each agent maintains a Beta distribution representing its success/failure history:
Agent success rate modeled as Beta(α, β)
Where:
α = number of successful signals + 1
β = number of failed signals + 1
On Each Bar:
1. Sample from each agent's Beta distribution
2. Weight agent signals by sampled probabilities
3. Combine weighted signals into consensus
4. Update α/β based on trade outcomes
Mathematical Implementation:
// Beta sampling via Gamma ratio method
f_beta_sample(alpha, beta) =>
g1 = f_gamma_sample(alpha)
g2 = f_gamma_sample(beta)
g1 / (g1 + g2)
// Thompson Sampling selection
for each agent:
sampled_prob = f_beta_sample(agent.alpha, agent.beta)
weight = sampled_prob / sum(all_sampled_probs)
consensus += agent.signal × agent.confidence × weight
Why Thompson Sampling?
• Automatic Exploration : Agents with few samples get occasional chances (high variance in Beta distribution)
• Bayesian Optimal : Mathematically proven optimal solution to exploration-exploitation tradeoff
• Uncertainty-Aware : Small sample size = more exploration; large sample size = more exploitation
• Self-Correcting : Poor performers naturally get lower weights over time
Example Evolution:
Day 1 (Initial):
Trend Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Reversion Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
Structure Agent: Beta(1,1) → samples ~0.50 (high uncertainty)
After 50 Signals:
Trend Agent: Beta(28,23) → samples ~0.55 (moderate confidence)
Reversion Agent: Beta(18,33) → samples ~0.35 (underperforming)
Structure Agent: Beta(32,19) → samples ~0.63 (outperforming)
Result: Structure Agent now receives highest weight in consensus
Consensus Requirements by Mode:
Aggressive Mode:
• Minimum 1/3 agents agreeing
• Consensus threshold: 45%
• Use case: More signals, higher risk tolerance
Balanced Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 55%
• Use case: Standard trading
Conservative Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 65%
• Use case: Higher quality, fewer signals
Institutional Mode:
• Minimum 2/3 agents agreeing
• Consensus threshold: 75%
• Additional: Session quality >0.65, mode adjustment +0.10
• Use case: Highest quality signals only
🌀 INTELLIGENT CHOP DETECTION ENGINE
The Chop Problem:
Most trading losses occur not from being wrong about direction, but from trading in conditions where direction doesn't exist . Choppy, range-bound markets generate false signals from every methodology—trend-following, mean-reversion, and structure-based alike.
AMWT's chop detection engine identifies these low-probability environments before signals fire, preventing the most damaging trades.
Five-Factor Chop Analysis:
Factor 1: ADX Component (25% weight)
ADX (Average Directional Index) measures trend strength regardless of direction.
ADX < 15: Very weak trend (high chop score)
ADX 15-20: Weak trend (moderate chop score)
ADX 20-25: Developing trend (low chop score)
ADX > 25: Strong trend (minimal chop score)
adx_chop = (i_adxThreshold - adx_val) / i_adxThreshold × 100
Why ADX Works: ADX synthesizes +DI and -DI movements. Low ADX means price is moving but not directionally—the definition of chop.
Factor 2: Choppiness Index (25% weight)
The Choppiness Index measures price efficiency using the ratio of ATR sum to price range:
CI = 100 × LOG10(SUM(ATR, n) / (Highest - Lowest)) / LOG10(n)
CI > 61.8: Choppy (range-bound, inefficient movement)
CI < 38.2: Trending (directional, efficient movement)
CI 38.2-61.8: Transitional
chop_idx_score = (ci_val - 38.2) / (61.8 - 38.2) × 100
Why Choppiness Index Works: In trending markets, price covers distance efficiently (low ATR sum relative to range). In choppy markets, price oscillates wildly but goes nowhere (high ATR sum relative to range).
Factor 3: Range Compression (20% weight)
Compares recent range to longer-term range, detecting volatility squeezes:
recent_range = Highest(20) - Lowest(20)
longer_range = Highest(50) - Lowest(50)
compression = 1 - (recent_range / longer_range)
compression > 0.5: Strong squeeze (potential breakout imminent)
compression < 0.2: No compression (normal volatility)
range_compression_score = compression × 100
Why Range Compression Matters: Compression precedes expansion. High compression = market coiling, preparing for move. Signals during compression often fail because the breakout hasn't occurred yet.
Factor 4: Channel Position (15% weight)
Tracks price position within the macro channel:
channel_position = (close - channel_low) / (channel_high - channel_low)
position 0.4-0.6: Center of channel (indecision zone)
position <0.2 or >0.8: Near extremes (potential reversal or breakout)
channel_chop = abs(0.5 - channel_position) < 0.15 ? high_score : low_score
Why Channel Position Matters: Price in the middle of a range is in "no man's land"—equally likely to go either direction. Signals in the channel center have lower probability.
Factor 5: Volume Quality (15% weight)
Assesses volume relative to average:
vol_ratio = volume / SMA(volume, 20)
vol_ratio < 0.7: Low volume (lack of conviction)
vol_ratio 0.7-1.3: Normal volume
vol_ratio > 1.3: High volume (conviction present)
volume_chop = vol_ratio < 0.8 ? (1 - vol_ratio) × 100 : 0
Why Volume Quality Matters: Low volume moves lack institutional participation. These moves are more likely to reverse or stall.
Combined Chop Intensity:
chopIntensity = (adx_chop × 0.25) + (chop_idx_score × 0.25) +
(range_compression_score × 0.20) + (channel_chop × 0.15) +
(volume_chop × i_volumeChopWeight × 0.15)
Regime Classifications:
Based on chop intensity and component analysis:
• Strong Trend (0-20%): ADX >30, clear directional momentum, trade aggressively
• Trending (20-35%): ADX >20, moderate directional bias, trade normally
• Transitioning (35-50%): Mixed signals, regime change possible, reduce size
• Mid-Range (50-60%): Price trapped in channel center, avoid new positions
• Ranging (60-70%): Low ADX, price oscillating within bounds, fade extremes only
• Compression (70-80%): Volatility squeeze, expansion imminent, wait for breakout
• Strong Chop (80-100%): Multiple chop factors aligned, avoid trading entirely
Signal Suppression:
When chop intensity exceeds the configurable threshold (default 80%), signals are suppressed entirely. The dashboard displays "⚠️ CHOP ZONE" with the current regime classification.
Chop Box Visualization:
When chop is detected, AMWT draws a semi-transparent box on the chart showing the chop zone. This visual reminder helps traders avoid entering positions during unfavorable conditions.
💧 LIQUIDITY ANCHORING SYSTEM
The Liquidity Concept:
Markets move from liquidity pool to liquidity pool. Stop losses cluster at predictable locations—below swing lows (buy stops become sell orders when triggered) and above swing highs (sell stops become buy orders when triggered). Institutions know where these clusters are and often engineer moves to trigger them before reversing.
AMWT identifies and tracks these liquidity events, using them as anchors for signal confidence.
Liquidity Event Types:
Type 1: Volume Spikes
Definition: Volume > SMA(volume, 20) × i_volThreshold (default 2.8x)
Interpretation: Sudden volume surge indicates institutional activity
• Near swing low + reversal: Likely accumulation
• Near swing high + reversal: Likely distribution
• With continuation: Institutional conviction in direction
Type 2: Stop Runs (Liquidity Sweeps)
Definition: Price briefly exceeds swing high/low then reverses within N bars
Detection:
• Price breaks above recent swing high (triggering buy stops)
• Then closes back below that high within 3 bars
• Signal: Bullish stop run complete, reversal likely
Or inverse for bearish:
• Price breaks below recent swing low (triggering sell stops)
• Then closes back above that low within 3 bars
• Signal: Bearish stop run complete, reversal likely
Type 3: Absorption Events
Definition: High volume with small candle body
Detection:
• Volume > 2x average
• Candle body < 30% of candle range
• Interpretation: Large orders being filled without moving price
• Implication: Accumulation (at lows) or distribution (at highs)
Type 4: BSL/SSL Pools (Buy-Side/Sell-Side Liquidity)
BSL (Buy-Side Liquidity):
• Cluster of swing highs within ATR proximity
• Stop losses from shorts sit above these highs
• Breaking BSL triggers short covering (fuel for rally)
SSL (Sell-Side Liquidity):
• Cluster of swing lows within ATR proximity
• Stop losses from longs sit below these lows
• Breaking SSL triggers long liquidation (fuel for decline)
Liquidity Pool Mapping:
AMWT continuously scans for and maps liquidity pools:
// Detect swing highs/lows using pivot function
swing_high = ta.pivothigh(high, 5, 5)
swing_low = ta.pivotlow(low, 5, 5)
// Track recent swing points
if not na(swing_high)
bsl_levels.push(swing_high)
if not na(swing_low)
ssl_levels.push(swing_low)
// Display on chart with labels
Confluence Scoring Integration:
When signals fire near identified liquidity events, confluence scoring increases:
• Signal near volume spike: +10% confidence
• Signal after liquidity sweep: +15% confidence
• Signal at BSL/SSL pool: +10% confidence
• Signal aligned with absorption zone: +10% confidence
Why Liquidity Anchoring Matters:
Signals "in a vacuum" have lower probability than signals anchored to institutional activity. A long signal after a liquidity sweep below swing lows has trapped shorts providing fuel. A long signal in the middle of nowhere has no such catalyst.
📊 SIGNAL GRADING SYSTEM
The Quality Problem:
Not all signals are created equal. A signal with 6/6 factors aligned is fundamentally different from a signal with 3/6 factors aligned. Traditional indicators treat them the same. AMWT grades every signal based on confluence.
Confluence Components (100 points total):
1. Bandit Consensus Strength (25 points)
consensus_str = weighted average of agent confidences
score = consensus_str × 25
Example:
Trend Agent: +1 signal, 0.80 confidence, 0.35 weight
Reversion Agent: 0 signal, 0.50 confidence, 0.25 weight
Structure Agent: +1 signal, 0.75 confidence, 0.40 weight
Weighted consensus = (0.80×0.35 + 0×0.25 + 0.75×0.40) / (0.35 + 0.40) = 0.77
Score = 0.77 × 25 = 19.25 points
2. HMM State Confidence (15 points)
score = hmm_confidence × 15
Example:
HMM reports 82% probability of IMPULSE_UP
Score = 0.82 × 15 = 12.3 points
3. Session Quality (15 points)
Session quality varies by time:
• London/NY Overlap: 1.0 (15 points)
• New York Session: 0.95 (14.25 points)
• London Session: 0.70 (10.5 points)
• Asian Session: 0.40 (6 points)
• Off-Hours: 0.30 (4.5 points)
• Weekend: 0.10 (1.5 points)
4. Energy/Participation (10 points)
energy = (realized_vol / avg_vol) × 0.4 + (range / ATR) × 0.35 + (volume / avg_volume) × 0.25
score = min(energy, 1.0) × 10
5. Volume Confirmation (10 points)
if volume > SMA(volume, 20) × 1.5:
score = 10
else if volume > SMA(volume, 20):
score = 5
else:
score = 0
6. Structure Alignment (10 points)
For long signals:
• Bullish structure (HH + HL): 10 points
• Higher low only: 6 points
• Neutral structure: 3 points
• Bearish structure: 0 points
Inverse for short signals
7. Trend Alignment (10 points)
For long signals:
• Price > EMA21 > EMA50: 10 points
• Price > EMA21: 6 points
• Neutral: 3 points
• Against trend: 0 points
8. Entry Trigger Quality (5 points)
• Strong trigger (multiple confirmations): 5 points
• Moderate trigger (single confirmation): 3 points
• Weak trigger (marginal): 1 point
Grade Scale:
Total Score → Grade
85-100 → A+ (Exceptional—all factors aligned)
70-84 → A (Strong—high probability)
55-69 → B (Acceptable—proceed with caution)
Below 55 → C (Marginal—filtered by default)
Grade-Based Signal Brightness:
Signal arrows on the chart have transparency based on grade:
• A+: Full brightness (alpha = 0)
• A: Slight fade (alpha = 15)
• B: Moderate fade (alpha = 35)
• C: Significant fade (alpha = 55)
This visual hierarchy helps traders instantly identify signal quality.
Minimum Grade Filter:
Configurable filter (default: C) sets the minimum grade for signal display:
• Set to "A" for only highest-quality signals
• Set to "B" for moderate selectivity
• Set to "C" for all signals (maximum quantity)
🕐 SESSION INTELLIGENCE
Why Sessions Matter:
Markets behave differently at different times. The London open is fundamentally different from the Asian lunch hour. AMWT incorporates session-aware logic to optimize signal quality.
Session Definitions:
Asian Session (18:00-03:00 ET)
• Characteristics: Lower volatility, range-bound tendency, fewer institutional participants
• Quality Score: 0.40 (40% of peak quality)
• Strategy Implications: Fade extremes, expect ranges, smaller position sizes
• Best For: Mean-reversion setups, accumulation/distribution identification
London Session (03:00-12:00 ET)
• Characteristics: European institutional activity, volatility pickup, trend initiation
• Quality Score: 0.70 (70% of peak quality)
• Strategy Implications: Watch for trend development, breakouts more reliable
• Best For: Initial trend identification, structure breaks
New York Session (08:00-17:00 ET)
• Characteristics: Highest liquidity, US institutional activity, major moves
• Quality Score: 0.95 (95% of peak quality)
• Strategy Implications: Best environment for directional trades
• Best For: Trend continuation, momentum plays
London/NY Overlap (08:00-12:00 ET)
• Characteristics: Peak liquidity, both European and US participants active
• Quality Score: 1.0 (100%—maximum quality)
• Strategy Implications: Highest probability for successful breakouts and trends
• Best For: All signal types—this is prime time
Off-Hours
• Characteristics: Thin liquidity, erratic price action, gaps possible
• Quality Score: 0.30 (30% of peak quality)
• Strategy Implications: Avoid new positions, wider stops if holding
• Best For: Waiting
Smart Weekend Detection:
AMWT properly handles the Sunday evening futures open:
// Traditional (broken):
isWeekend = dayofweek == saturday OR dayofweek == sunday
// AMWT (correct):
anySessionActive = not na(asianTime) or not na(londonTime) or not na(nyTime)
isWeekend = calendarWeekend AND NOT anySessionActive
This ensures Sunday 6pm ET (when futures open) correctly shows "Asian Session" rather than "Weekend."
Session Transition Boosts:
Certain session transitions create trading opportunities:
• Asian → London transition: +15% confidence boost (volatility expansion likely)
• London → Overlap transition: +20% confidence boost (peak liquidity approaching)
• Overlap → NY-only transition: -10% confidence adjustment (liquidity declining)
• Any → Off-Hours transition: Signal suppression recommended
📈 TRADE MANAGEMENT SYSTEM
The Signal Spam Problem:
Many indicators generate signal after signal, creating confusion and overtrading. AMWT implements a complete trade lifecycle management system that prevents signal spam and tracks performance.
Trade Lock Mechanism:
Once a signal fires, the system enters a "trade lock" state:
Trade Lock Duration: Configurable (default 30 bars)
Early Exit Conditions:
• TP3 hit (full target reached)
• Stop Loss hit (trade failed)
• Lock expiration (time-based exit)
During lock:
• No new signals of same type displayed
• Opposite signals can override (reversal)
• Trade status tracked in dashboard
Target Levels:
Each signal generates three profit targets based on ATR:
TP1 (Conservative Target)
• Default: 1.0 × ATR
• Purpose: Quick partial profit, reduce risk
• Action: Take 30-40% off position, move stop to breakeven
TP2 (Standard Target)
• Default: 2.5 × ATR
• Purpose: Main profit target
• Action: Take 40-50% off position, trail stop
TP3 (Extended Target)
• Default: 5.0 × ATR
• Purpose: Runner target for trend days
• Action: Close remaining position or continue trailing
Stop Loss:
• Default: 1.9 × ATR from entry
• Purpose: Define maximum risk
• Placement: Below recent swing low (longs) or above recent swing high (shorts)
Invalidation Level:
Beyond stop loss, AMWT calculates an "invalidation" level where the wave hypothesis dies:
invalidation = entry - (ATR × INVALIDATION_MULT × 1.5)
If price reaches invalidation, the current market interpretation is wrong—not just the trade.
Visual Trade Management:
During active trades, AMWT displays:
• Entry arrow with grade label (▲A+, ▼B, etc.)
• TP1, TP2, TP3 horizontal lines in green
• Stop Loss line in red
• Invalidation line in orange (dashed)
• Progress indicator in dashboard
Persistent Execution Markers:
When targets or stops are hit, permanent markers appear:
• TP hit: Green dot with "TP1"/"TP2"/"TP3" label
• SL hit: Red dot with "SL" label
These persist on the chart for review and statistics.
💰 PERFORMANCE TRACKING & STATISTICS
Tracked Metrics:
• Total Trades: Count of all signals that entered trade lock
• Winning Trades: Signals where at least TP1 was reached before SL
• Losing Trades: Signals where SL was hit before any TP
• Win Rate: Winning / Total × 100%
• Total R Profit: Sum of R-multiples from winning trades
• Total R Loss: Sum of R-multiples from losing trades
• Net R: Total R Profit - Total R Loss
Currency Conversion System:
AMWT can display P&L in multiple formats:
R-Multiple (Default)
• Shows risk-normalized returns
• "Net P&L: +4.2R | 78 trades" means 4.2 times initial risk gained over 78 trades
• Best for comparing across different position sizes
Currency Conversion (USD/EUR/GBP/JPY/INR)
• Converts R-multiples to currency based on:
- Dollar Risk Per Trade (user input)
- Tick Value (user input)
- Selected currency
Example Configuration:
Dollar Risk Per Trade: $100
Display Currency: USD
If Net R = +4.2R
Display: Net P&L: +$420.00 | 78 trades
Ticks
• For futures traders who think in ticks
• Converts based on tick value input
Statistics Reset:
Two reset methods:
1. Toggle Reset
• Turn "Reset Statistics" toggle ON then OFF
• Clears all statistics immediately
2. Date-Based Reset
• Set "Reset After Date" (YYYY-MM-DD format)
• Only trades after this date are counted
• Useful for isolating recent performance
🎨 VISUAL FEATURES
Macro Channel:
Dynamic regression-based channel showing market boundaries:
• Upper/lower bounds calculated from swing pivot linear regression
• Adapts to current market structure
• Shows overall trend direction and potential reversal zones
Chop Boxes:
Semi-transparent overlay during high-chop periods:
• Purple/orange coloring indicates dangerous conditions
• Visual reminder to avoid new positions
Confluence Heat Zones:
Background shading indicating setup quality:
• Darker shading = higher confluence
• Lighter shading = lower confluence
• Helps identify optimal entry timing
EMA Ribbon:
Trend visualization via moving average fill:
• EMA 8/21/50 with gradient fill between
• Green fill when bullish aligned
• Red fill when bearish aligned
• Gray when neutral
Absorption Zone Boxes:
Marks potential accumulation/distribution areas:
• High volume + small body = absorption
• Boxes drawn at these levels
• Often act as support/resistance
Liquidity Pool Lines:
BSL/SSL levels with labels:
• Dashed lines at liquidity clusters
• "BSL" label above swing high clusters
• "SSL" label below swing low clusters
Six Professional Themes:
• Quantum: Deep purples and cyans (default)
• Cyberpunk: Neon pinks and blues
• Professional: Muted grays and greens
• Ocean: Blues and teals
• Matrix: Greens and blacks
• Ember: Oranges and reds
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: Learning the System (Week 1)
Goal: Understand AMWT concepts and dashboard interpretation
Setup:
• Signal Mode: Balanced
• Display: All features enabled
• Grade Filter: C (see all signals)
Actions:
• Paper trade ONLY—no real money
• Observe HMM state transitions throughout the day
• Note when agents agree vs disagree
• Watch chop detection engage and disengage
• Track which grades produce winners vs losers
Key Learning Questions:
• How often do A+ signals win vs B signals? (Should see clear difference)
• Which agent tends to be right in current market? (Check dashboard)
• When does chop detection save you from bad trades?
• How do signals near liquidity events perform vs signals in vacuum?
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to your instrument and timeframe
Signal Mode Testing:
• Run 5 days on Aggressive mode (more signals)
• Run 5 days on Conservative mode (fewer signals)
• Compare: Which produces better risk-adjusted returns?
Grade Filter Testing:
• Track A+ only for 20 signals
• Track A and above for 20 signals
• Track B and above for 20 signals
• Compare win rates and expectancy
Chop Threshold Testing:
• Default (80%): Standard filtering
• Try 70%: More aggressive filtering
• Try 90%: Less filtering
• Which produces best results for your instrument?
Phase 3: Strategy Development (Weeks 3-4)
Goal: Develop personal trading rules based on system signals
Position Sizing by Grade:
• A+ grade: 100% position size
• A grade: 75% position size
• B grade: 50% position size
• C grade: 25% position size (or skip)
Session-Based Rules:
• London/NY Overlap: Take all A/A+ signals
• NY Session: Take all A+ signals, selective on A
• Asian Session: Only A+ signals with extra confirmation
• Off-Hours: No new positions
Chop Zone Rules:
• Chop >70%: Reduce position size 50%
• Chop >80%: No new positions
• Chop <50%: Full position size allowed
Phase 4: Live Micro-Sizing (Month 2)
Goal: Validate paper trading results with minimal risk
Setup:
• 10-20% of intended full position size
• Take ONLY A+ signals initially
• Follow trade management religiously
Tracking:
• Log every trade: Entry, Exit, Grade, HMM State, Chop Level, Agent Consensus
• Calculate: Win rate by grade, by session, by chop level
• Compare to paper trading (should be within 15%)
Red Flags:
• Win rate diverges significantly from paper trading: Execution issues
• Consistent losses during certain sessions: Adjust session rules
• Losses cluster when specific agent dominates: Review that agent's logic
Phase 5: Scaling Up (Months 3-6)
Goal: Gradually increase to full position size
Progression:
• Month 3: 25-40% size (if micro-sizing profitable)
• Month 4: 40-60% size
• Month 5: 60-80% size
• Month 6: 80-100% size
Scale-Up Requirements:
• Minimum 30 trades at current size
• Win rate ≥50%
• Net R positive
• No revenge trading incidents
• Emotional control maintained
💡 DEVELOPMENT INSIGHTS
Why HMM Over Simple Indicators:
Early versions used standard indicators (RSI >70 = overbought, etc.). Win rates hovered at 52-55%. The problem: indicators don't capture state. RSI can stay "overbought" for weeks in a strong trend.
The insight: markets exist in states, and state persistence matters more than indicator levels. Implementing HMM with state transition probabilities increased signal quality significantly. The system now knows not just "RSI is high" but "we're in IMPULSE_UP state with 70% probability of staying in IMPULSE_UP."
The Multi-Agent Evolution:
Original version used a single analytical methodology—trend-following. Performance was inconsistent: great in trends, destroyed in ranges. Added mean-reversion agent: now it was inconsistent the other way.
The breakthrough: use multiple agents and let the system learn which works . Thompson Sampling wasn't the first attempt—tried simple averaging, voting, even hard-coded regime switching. Thompson Sampling won because it's mathematically optimal and automatically adapts without manual regime detection.
Chop Detection Revelation:
Chop detection was added almost as an afterthought. "Let's filter out obviously bad conditions." Testing revealed it was the most impactful single feature. Filtering chop zones reduced losing trades by 35% while only reducing total signals by 20%. The insight: avoiding bad trades matters more than finding good ones.
Liquidity Anchoring Discovery:
Watched hundreds of trades. Noticed pattern: signals that fired after liquidity events (stop runs, volume spikes) had significantly higher win rates than signals in quiet markets. Implemented liquidity detection and anchoring. Win rate on liquidity-anchored signals: 68% vs 52% on non-anchored signals.
The Grade System Impact:
Early system had binary signals (fire or don't fire). Adding grading transformed it. Traders could finally match position size to signal quality. A+ signals deserved full size; C signals deserved caution. Just implementing grade-based sizing improved portfolio Sharpe ratio by 0.3.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What AMWT Is NOT:
• NOT a Holy Grail : No system wins every trade. AMWT improves probability, not certainty.
• NOT Fully Automated : AMWT provides signals and analysis; execution requires human judgment.
• NOT News-Proof : Exogenous shocks (FOMC surprises, geopolitical events) invalidate all technical analysis.
• NOT for Scalping : HMM state estimation needs time to develop. Sub-minute timeframes are not appropriate.
Core Assumptions:
1. Markets Have States : Assumes markets transition between identifiable regimes. Violation: Random walk markets with no regime structure.
2. States Are Inferable : Assumes observable indicators reveal hidden states. Violation: Market manipulation creating false signals.
3. History Informs Future : Assumes past agent performance predicts future performance. Violation: Regime changes that invalidate historical patterns.
4. Liquidity Events Matter : Assumes institutional activity creates predictable patterns. Violation: Markets with no institutional participation.
Performs Best On:
• Liquid Futures : ES, NQ, MNQ, MES, CL, GC
• Major Forex Pairs : EUR/USD, GBP/USD, USD/JPY
• Large-Cap Stocks : AAPL, MSFT, TSLA, NVDA (>$5B market cap)
• Liquid Crypto : BTC, ETH on major exchanges
Performs Poorly On:
• Illiquid Instruments : Low volume stocks, exotic pairs
• Very Low Timeframes : Sub-5-minute charts (noise overwhelms signal)
• Binary Event Days : Earnings, FDA approvals, court rulings
• Manipulated Markets : Penny stocks, low-cap altcoins
Known Weaknesses:
• Warmup Period : HMM needs ~50 bars to initialize properly. Early signals may be unreliable.
• Regime Change Lag : Thompson Sampling adapts over time, not instantly. Sudden regime changes may cause short-term underperformance.
• Complexity : More parameters than simple indicators. Requires understanding to use effectively.
⚠️ RISK DISCLOSURE
Trading futures, stocks, options, forex, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Adaptive Market Wave Theory, while based on rigorous mathematical frameworks including Hidden Markov Models and multi-armed bandit algorithms, does not guarantee profits and can result in significant losses.
AMWT's methodologies—HMM state estimation, Thompson Sampling agent selection, and confluence-based grading—have theoretical foundations but past performance is not indicative of future results.
Hidden Markov Model assumptions may not hold during:
• Major news events disrupting normal market behavior
• Flash crashes or circuit breaker events
• Low liquidity periods with erratic price action
• Algorithmic manipulation or spoofing
Multi-agent consensus assumes independent analytical perspectives provide edge. Market conditions change. Edges that existed historically can diminish or disappear.
Users must independently validate system performance on their specific instruments, timeframes, and broker execution environment. Paper trade extensively before risking capital. Start with micro position sizing.
Never risk more than you can afford to lose completely. Use proper position sizing. Implement stop losses without exception.
By using this indicator, you acknowledge these risks and accept full responsibility for all trading decisions and outcomes.
"Elliott Wave was a first-order approximation of market phase behavior. AMWT is the second—probabilistic, adaptive, and accountable."
Initial Public Release
Core Engine:
• True Hidden Markov Model with online Baum-Welch learning
• Viterbi algorithm for optimal state sequence decoding
• 6-state market regime classification
Agent System:
• 3-Bandit consensus (Trend, Reversion, Structure)
• Thompson Sampling with true Beta distribution sampling
• Adaptive weight learning based on performance
Signal Generation:
• Quality-based confluence grading (A+/A/B/C)
• Four signal modes (Aggressive/Balanced/Conservative/Institutional)
• Grade-based visual brightness
Chop Detection:
• 5-factor analysis (ADX, Choppiness Index, Range Compression, Channel Position, Volume)
• 7 regime classifications
• Configurable signal suppression threshold
Liquidity:
• Volume spike detection
• Stop run (liquidity sweep) identification
• BSL/SSL pool mapping
• Absorption zone detection
Trade Management:
• Trade lock with configurable duration
• TP1/TP2/TP3 targets
• ATR-based stop loss
• Persistent execution markers
Session Intelligence:
• Asian/London/NY/Overlap detection
• Smart weekend handling (Sunday futures open)
• Session quality scoring
Performance:
• Statistics tracking with reset functionality
• 7 currency display modes
• Win rate and Net R calculation
Visuals:
• Macro channel with linear regression
• Chop boxes
• EMA ribbon
• Liquidity pool lines
• 6 professional themes
Dashboards:
• Main Dashboard: Market State, Consensus, Trade Status, Statistics
📋 AMWT vs AMWT-PRO:
This version includes all core AMWT functionality:
✓ Full Hidden Markov Model state estimation
✓ 3-Bandit Thompson Sampling consensus system
✓ Complete 5-factor chop detection engine
✓ All four signal modes
✓ Full trade management with TP/SL tracking
✓ Main dashboard with complete statistics
✓ All visual features (channels, zones, pools)
✓ Identical signal generation to PRO
✓ Six professional themes
✓ Full alert system
The PRO version adds the AMWT Advisor panel—a secondary dashboard providing:
• Real-time Market Pulse situation assessment
• Agent Matrix visualization (individual agent votes)
• Structure analysis breakdown
• "Watch For" upcoming setups
• Action Command coaching
Both versions generate identical signals . The Advisor provides additional guidance for interpreting those signals.
Taking you to school. - Dskyz, Trade with probability. Trade with consensus. Trade with AMWT.
TrintityTrendIntroducing TrinityTrend
A multi-signal indicator combining:
Candle TrendStrength
SuperTrend logic
TTM Squeeze detection
Built for clarity, momentum, and volatility awareness—across any timeframe.
TrendStrength Mode
Candle coloring reflects directional conviction.
Strong uptrend
Strong downtrend
Neutral or indecisive
Helps traders stay with momentum and avoid chop.
SuperTrend Overlay
SuperTrend Logic Dynamic trailing stop based on volatility.
🟩 Price above = bullish bias
🟥 Price below = bearish bias
Great for swing entries and exits.
TTM Squeeze Detection
TTM Squeeze Mode Detects compression zones before breakout.
Squeeze on = buildup (You can change the color of this)
Pairs well with TrendStrength for timing entries.
Multi-Timeframe Versatility
Multi-Timeframe Ready:
Intraday scalping
Daily swing setups
Weekly macro bias
Toggle modes to match your strategy
Ping-Pong Fade (BB + Absorption Proxy)Ping-Pong Fade is a mean-reversion fade indicator designed to capture short-term reversals at statistically extreme price levels only when real participation and absorption behavior are present.
This script intentionally mashes up Bollinger Bands, volume expansion, and candle structure to filter out weak band touches and isolate defended extremes.
Why This Mashup Exists
Bollinger Band fades fail most often when:
Price is expanding with conviction
Breakouts are supported by strong directional bodies
There is no opposing liquidity at the extremes
This indicator solves that by requiring three independent confirmations before signaling a fade:
Statistical Extremity (Bollinger Bands)
Participation (Volume Expansion)
Absorption / Rejection (Candle Structure)
Only when all three align does the script trigger a signal.
Component Breakdown & How They Work Together
1. Bollinger Bands – Where price should react
Uses a standard SMA + standard deviation envelope
Defines upper and lower statistical extremes
Provides the location for potential fades, not the signal by itself
Bands answer where, not whether.
2. Volume Spike Filter – Who is involved
Compares current volume to a moving average
Requires volume to exceed a configurable multiple
Ensures the interaction at the band is meaningful, not illiquid noise
No volume = no real defense = no trade.
3. Candle Body % (Absorption Proxy) – How price is behaving
Measures candle body relative to full range
Small bodies at the band imply:
Heavy two-sided trading
Aggression being absorbed
Failure to close through the extreme
This acts as a practical proxy for order-flow absorption without requiring Level II or footprint data.
Big range + small body + high volume = pressure met with resistance.
Signal Logic (The “Ping-Pong” Effect)
🔽 Short Fade
Triggered when:
Price probes above the upper Bollinger Band
Volume spikes above normal
Candle shows a small body and fails to close strong at highs
Interpretation:
Buyers pushed price to an extreme, but were absorbed. Expect rotation back toward the mean.
🔼 Long Fade
Triggered when:
Price probes below the lower Bollinger Band
Volume spikes above normal
Candle shows a small body and fails to close strong at lows
Interpretation:
Sellers forced price down, but were absorbed. Expect a bounce toward the mean.
What This Indicator Is Best Used For
Intraday mean-reversion setups
Range-bound or rotational markets
Scalping and short-term fades near extremes
Confirmation layer alongside VWAP, structure, or HTF bias
What It Is Not
A breakout tool
A trend-following indicator
A standalone system without context
Core Philosophy
Extreme + Volume + Failure = Opportunity
Ping-Pong Fade is designed to show you when price tries to escape its range — and fails — allowing you to fade the move with structure and intent.
MEGA Sector Rotation CRYPTOCAP - 8 Narrativas (Optimized Daily)### MEGA Sector Rotation CRYPTOCAP - 7 Narratives
**Description for publishing on TradingView:**
This advanced indicator lets you visualize in real time the **rotation of narratives** within the crypto market through 7 key sectors, normalized for perfect side-by-side comparison.
Each line represents the **historical relative strength** (min-max normalization over 5000 bars) of a specific narrative, based on TradingView's official aggregated market caps (CRYPTOCAP) and custom sums. The lines oscillate between 0 and 100, with clear crossovers signaling when a sector is gaining or losing momentum relative to the others.
**The 7 narratives included:**
1. **Layer1** (pink) – Aggregated market cap of major Layer 1 blockchains.
2. **Memecoins** (bright green) – Official MEME.C sector (PEPE, SHIB, WIF, BONK, etc.).
3. **AI** (orange) – Artificial Intelligence and Big Data narrative.
4. **Exchanges** (purple) – Exchange tokens (centralized and decentralized).
5. **DeFi Total** (cyan) – Full aggregated market cap of the DeFi ecosystem.
6. **RWA Custom** (brown) – Custom sum of Real World Assets: ONDO + LINK + CFG + SYRUP.
7. **Privacy** (dark orange) – Custom sum of privacy coins: XMR + ZEC + DASH.
**Quick interpretation:**
- Line >80 and rising → Narrative is **HOT** (strong bullish rotation).
- Line <20 → Narrative is **COLD** (losing strength).
- Bullish crossovers → Money rotating into that sector.
- Transparent fills between lines to highlight leadership zones.
**Features:**
- Optimized for **lower timeframes** (5m, 15m, 1H, 4H) → ideal for day trading and scalping narratives.
- Works on any TF thanks to 5-minute resolution data.
- Thick lines, vibrant colors, and horizontal references (20/50/80) for instant reading.
Perfect for spotting early which narrative is attracting capital flows and anticipating sector moves in the crypto market.
Add this indicator and trade rotations like a pro!
#crypto #sectorrotation #narratives #altcoins #tradingview
PREMIUM TRADE ZONES - [EntryLab]PREMIUM Trade Zones was created to help both beginner and advanced traders avoid one of the most common causes of losses: trading during sideways, choppy market conditions.
Sideways price action often occurs around the RSI 50 level, where market indecision is high. This indicator visually highlights a No Trade Zone around that area, encouraging traders to stay patient and avoid low-probability setups. Above and below this zone, clearly defined Short Trade Zones and Long Trade Zones provide additional confluence for potential entries when momentum is more favorable.
Trade Zones is especially useful for traders who may occasionally struggle with discipline — something we all experience — by offering a constant visual reminder of where trading conditions are optimal versus where caution is warranted.
The indicator is fully customizable through the settings panel, allowing users to adjust zone levels, colors, text visibility, and signal elements to suit their individual trading style and strategy. We personally use Trade Zones as an added layer of confluence when market conditions feel uncertain, consistently steering clear of the No Trade Zone where indecision and chop are most likely to occur.
This free indicator was built to support our community in developing better trading habits, improving decision-making, and progressing toward long-term consistency and profitability.
Regards,
ENTRYLAB
Triple MA Alignment [odnac]
Overview
The Triple MA Alignment indicator is a powerful tool designed to visualize and analyze the alignment of three moving averages (MAs) with customizable types and lengths. It helps traders identify trends and potential reversal points by displaying the relative positions of three MAs and marking specific alignment patterns on the chart. This indicator is ideal for traders looking to understand market momentum and trend direction through moving average crossovers and alignments.
Features
Customizable Moving Average Types: Choose from Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA/RMA), Weighted Moving Average (WMA), or Volume-Weighted Moving Average (VWMA).
Flexible MA Lengths: Adjust the lengths of three moving averages to suit your trading strategy (default lengths: 7, 25, 99).
Alignment Detection: Identifies six unique MA alignment patterns (A1 to A6) based on the relative positions of the three MAs.
Visual Cues: Plots MAs on the chart with distinct colors and marks alignment patterns with shapes and labels for easy interpretation.
Special Signals: Highlights specific transitions (e.g., "P" and "B" for A1, "P" and "S" for A4) to indicate potential trend changes or continuations.
How It Works
The indicator calculates three moving averages based on user-selected type and lengths. It then analyzes their relative positions to detect six possible alignment patterns:
A1 (1-2-3): MA1 > MA2 > MA3 (Strong bullish alignment)
A2 (2-1-3): MA2 > MA1 > MA3
A3 (2-3-1): MA2 > MA3 > MA1
A4 (3-2-1): MA3 > MA2 > MA1 (Strong bearish alignment)
A5 (3-1-2): MA3 > MA1 > MA2
A6 (1-3-2): MA1 > MA3 > MA2
When an alignment occurs, a shape (square, diamond, or circle) is plotted at the top or bottom of the chart, depending on the pattern. Additionally, when the alignment changes, a text label (e.g., "2", "3", "5", "6") is displayed to highlight the new pattern. Special signals ("P", "B", "S") are plotted for specific transitions to indicate potential trading opportunities.
Settings
Show Triple MA: Toggle to display or hide the three moving averages on the chart.
Show Triple MA Edge: Toggle to display or hide alignment shapes and labels.
MA Length 1, 2, 3: Set the periods for the three moving averages (default: 7, 25, 99).
MA Type: Select the moving average type (SMA, EMA, SMMA, WMA, VWMA).
Usage
Add the Indicator: Apply the indicator to your TradingView chart.
Adjust Settings: Customize MA lengths and type to match your trading style (e.g., shorter lengths for scalping, longer for swing trading).
Interpret Alignments:
A1 (Green Square): Indicates a strong bullish trend, often a signal to consider long positions.
A4 (Red Square): Indicates a strong bearish trend, often a signal to consider short positions.
A2, A3, A5, A6: Represent transitional or consolidation phases, useful for identifying potential reversals or continuations.
Special Signals (P, B, S): Watch for "P" (Pullback), "B" (Breakout), or "S" (Sell) labels for additional context.
Combine with Other Tools: Use alongside support/resistance levels, volume analysis, or other indicators for confirmation.
Supertrend + OBV AND Logic (long only)Supertrend + OBV Regime Filter (Long-Only) is a rule-based trend regime detection script that combines ATR-based Supertrend structure with volume-confirmed momentum using On-Balance Volume (OBV). The Supertrend (ATR 10, multiplier 3) defines the primary market regime and acts as the absolute authority for trend direction, while OBV—manually calculated for robustness and smoothed using EMA(20) with a signal EMA(20)—is used to confirm participation and momentum.
A long signal is generated only on confirmed bar close when the Supertrend is bullish (price above the Supertrend line) and OBV momentum turns positive via an EMA crossover, enforcing strict AND-logic confirmation and preventing entries during low-volume or transitional phases.
The strategy maintains a single long position per trend, with no pyramiding, averaging, or discretionary overrides. A full exit is triggered immediately when the Supertrend flips bearish, serving as a hard regime exit rather than a profit-target-based stop.
Additionally, an OBV downside crossover generates a non-executable “Protect” signal (visual only), intended for risk-management actions such as reducing exposure or pausing position additions, particularly for grid or DCA implementations.
This script is not designed as a grid, scalping, or buy-and-hold strategy; instead, it functions as a conservative trend and regime filter suitable for discretionary trading or as a signal layer to control automated long-bias execution systems. Forward testing and proper risk management are strongly recommended.
Market Regime | NY Session Killzones Indicator [ApexLegion]Market Regime | NY Session Killzones Indicator
Introduction and Theoretical Background
The Market Regime | NY Session Killzones indicator is designed exclusively for New York market hours (07:00-16:00 ET). Unlike universal indicators that attempt to function across disparate global sessions, this tool employs session-specific calibration to target the distinct liquidity characteristics of the NY trading day: Pre-Market structural formation (08:00-09:30), the Morning breakout window (09:30-12:00), and the Afternoon Killzone (13:30-16:00)—periods when institutional order flow exhibits the highest concentration and most definable technical structure. By restricting its operational scope to these statistically significant time windows, the indicator focuses on signal relevance while filtering the noise inherent in lower-liquidity overnight or extended-hours trading environments.
I. TECHNICAL RATIONALE: THE PRINCIPLE OF CONTEXTUAL FUSION
1. The Limitation of Acontextual Indicators
Traditional technical indicators often fail because they treat every bar and every market session equally, applying static thresholds (e.g., RSI > 70) without regard for the underlying market structure or liquidity environment. However, institutional volume and market volatility are highly dependent on the time of day (session) and the prevailing long-term risk environment.
This indicator was developed to address this "contextual deficit" by fusing three distinct yet interdependent analytical layers:
• Time and Structure (Macro): Identifying high-probability trading windows (Killzones) and critical structural levels (Pre-Market Range, PDH/PDL).
• Volatility and Scoring (Engine): Normalizing intraday momentum against annual volatility data to create an objective, statistically grounded AI Score.
• Risk Management (Execution): Implementing dynamic, volatility-adjusted Stop Loss (SL) and Take Profit (TP) parameters based on the Average True Range (ATR).
2. The Mandate for 252-Day Normalization (Z-Score)
What makes this tool unique is its 252-day Z-Score normalization engine that transforms raw momentum readings into statistically grounded probability scores, allowing the same indicator to deliver consistent, context-aware signals across any timeframe—from 1-minute scalping to 1-hour swing trades—without manual recalibration.
THE PROBLEM OF SCALE INVARIANCE
A high Relative Strength Index (RSI) reading on a 1-minute chart has a completely different market implication than a high RSI reading on a Daily chart. Simple percentage-based thresholds (like 70 or 30) do not provide true contextual significance. A sudden spike in momentum may look extreme on a 5-minute chart, but if it is statistically insignificant compared to the overall volatility of the last year, it may be a poor signal.
THE SOLUTION: CROSS-TIMEFRAME Z-SCORE NORMALIZATION
This indicator utilizes the Pine Script function request.security to reference the Daily timeframe for calculating the mean (μ) and standard deviation (σ) of a momentum oscillator (RSI) over the past 252 trading days (one year).
The indicator then calculates the Z-Score (Z) for the current bar's raw momentum (x): Z = (x - μ) / σ
Core Implementation: float raw_rsi = ta.rsi(close, 14) // x
= request.security(syminfo.tickerid, "D",
, // σ (252 days)
lookahead=barmerge.lookahead_on)
float cur_rsi_norm = d_rsi_std != 0 ? (raw_rsi - d_rsi_mean) / d_rsi_std : 0.0 // Z
This score provides an objective measurement of current intraday momentum significance by evaluating its statistical extremity against the yearly baseline of daily momentum. This standardized approach provides the scoring engine with consistent, global contextual information, independent of the chart's current viewing timeframe.
II. CORE COMPONENTS AND TECHNICAL ANALYSIS BREAKDOWN
1. TIME AND SESSION ANALYSIS (KILLZONES AND BIAS)
The indicator visually segments the trading day based on New York (NY) trading sessions, aligning the analysis with periods of high institutional liquidity events.
Pre-Market (PRE)
• Function: Defines the range before the core market opens. This range establishes structural support and resistance levels (PMH/PML).
• Technical Implementation: Uses a dedicated Session input (ny_pre_sess). The High and Low values (pm_h_val/pm_l_val) within this session are stored and plotted for structural reference.
• Smart Extension Logic: PMH/PML lines are automatically extended until the next Pre-Market session begins, providing continuous support/resistance references overnight.
NY Killzones (AM/PM)
• Function: Highlights high-probability volatility windows where institutional liquidity is expected to be highest (e.g., NY open, lunch, NY close).
• Technical Implementation: Separate session inputs (kz_ny_am, kz_ny_pm) are utilized to draw translucent background fills, providing a clear visual cue for timing.
Market Regime Bias
• Function: Determines the initial directional premise for the trading day. The bias is confirmed when the price breaks either the Pre-Market High (PMH) or the Pre-Market Low (PML).
• Technical Implementation: Involves the comparison of the close price against the predefined structural levels (check_h for PMH, check_l for PML). The variable active_bias is set to Bullish or Bearish upon confirmed breakout.
Trend Bar Coloring
• Function: Applies a visual cue to the bars based on the established regime (Bullish=Cyan, Bearish=Red). This visual filter helps mitigate noise from counter-trend candles.
• Technical Implementation: The Pine Script barcolor() function is tied directly to the value of the determined active_bias.
2. VOLATILITY NORMALIZED SCORING ENGINE
The internal scoring mechanism accumulates points from multiple market factors to determine the strength and validity of a signal. The purpose is to apply a robust filtering mechanism before generating an entry.
The score accumulation logic is based on the following factors:
• Market Bias Alignment (+3 Points): Points are awarded for conformance with the determined active_bias (Bullish/Bearish).
• VWAP Alignment (+2 Points): Assesses the position of the current price relative to the Volume-Weighted Average Price (VWAP). Alignment suggests conformity with the average institutional transaction price.
• Volume Anomaly (+2 Points): Detects a price move accompanied by an abnormally high relative volume (odd_vol_spike). This suggests potential institutional participation or significant order flow.
• VIX Integration (+2 Points): A score derived from the CBOE VIX index, assessing overall market stability and stress. Stable VIX levels add points, while high VIX levels (stress regimes) remove points or prevent signal generation entirely.
• ML Probability Score (+3 Points): This is the core predictive engine. It utilizes a Log-Manhattan Distance Kernel to compare the current market state against historical volatility patterns. The script implements a Log-linear distance formula (log(1 + |Δ|) ). This approach mathematically dampens the impact of extreme volatility spikes (outliers), ensuring that the similarity score reflects true structural alignment rather than transient market noise.
Core Technical Logic (Z-Score Normalization)
float cur_rsi_norm = d_rsi_std != 0 ? (raw_rsi - d_rsi_mean) / d_rsi_std : 0.0
• Technical Purpose: This line calculates the Z-Score (cur_rsi_norm) of the current momentum oscillator reading (raw_rsi) by normalizing it against the mean (d_rsi_mean) and standard deviation (d_rsi_std) derived from 252 days of Daily momentum data. If the standard deviation is zero (market is perfectly flat), it safely returns 0.0 to prevent division by zero runtime errors. This allows the AI's probability score to be based on the current signal's significance within the context of the entire trading year.
3. EXECUTION AND RISK MANAGEMENT (ATR MODEL)
The indicator utilizes the Average True Range (ATR) volatility model. This helps risk management scale dynamically with market volatility by allowing users to define TP/SL distances independently based on the current ATR.
Stop Loss Multiplier (sl_mult)
• Function: Sets the Stop Loss (SL) distance as a configurable multiple of the current ATR (e.g., 1.5 × ATR).
• Technical Logic: The price level is calculated as: last_sl_price := close - (atr_val * sl_mult). The mathematical sign is reversed for short trades.
Take Profit Multiplier (tp_mult)
• Function: Sets the Take Profit (TP) distance as a configurable multiple of the current ATR (e.g., 3.0 × ATR).
• Technical Logic: The price level is calculated as: last_tp_price := close + (atr_val * tp_mult). The mathematical sign is reversed for short trades.
Structural SL Option
• Function: Provides an override to the ATR-based SL calculation. When enabled, it forces the Stop Loss to the Pre-Market High/Low (PMH/PML) level, aligning the stop with a key institutional structural boundary.
• Technical Logic: The indicator checks the use_struct_sl input. If true, the calculated last_sl_price is overridden with either pm_h_val or pm_l_val, dependent on the specific trade direction.
Trend Continuation Logic
• Function: Enables signal generation in established, strong trends (typically in the Afternoon session) based on follow-through momentum (a new high/low of the previous bar) combined with a high Signal Score, rather than exclusively relying on the initial PMH/PML breakout.
• Technical Logic: For a long signal, the is_cont_long logic specifically requires checks like active_bias == s_bull AND close > high , confirming follow-through momentum within the established regime.
Smart Snapping & Cleanup (16:00 Market Close)
• Function: To maintain chart cleanliness, all trade boxes (TP/SL), AI Prediction zones, Killzone overlays (NY AM/PM), and Liquidity lines (PDH/PDL) are automatically "snapped" and cut off precisely at 16:00 NY Time (Market Close).
• Technical Logic: When is_market_close condition is met (hour == 16 and minute == 0), the script executes cleanup logic that:
◦ Closes active trades and evaluates final P&L
◦ Snaps all TP/SL box widths to current bar
◦ Truncates AI Prediction ghost boxes at market close
◦ Cuts off NY AM/PM Killzone background fills
◦ Terminates PDH/PDL line extensions
◦ Prevents visual clutter from extending into post-market sessions
4. LIQUIDITY AND STRUCTURAL ANALYSIS
The indicator plots key structural levels that serve as high-probability magnet zones or areas of potential liquidity absorption.
• Pre-Market High/Low (PMH/PML): These are the high and low established during the configured pre-market session (ny_pre_sess). They define the primary structural breakout level for the day, often serving as the initial market inflection point or the key entry level for the morning session.
• PDH (Previous Day High): The high of the calendar day immediately preceding the current bar. This represents a key Liquidity Pool; large orders are often placed above this level, making it a frequent target for stop hunts or liquidity absorption by market makers.
• PDL (Previous Day Low): The low of the calendar day immediately preceding the current bar. This also represents a key Liquidity Pool and a high-probability reversal or accumulation point, particularly during the Killzones.
FIFO Array Management
The indicator uses FIFO (First-In-First-Out) array structures to manage liquidity lines and labels, automatically deleting the oldest objects when the count exceeds 500 to comply with drawing object limits.
5. AI PREDICTION BOX (PREDICTIVE MODEL)
Function: Analyzes AI scores and volatility to project predicted killzone ranges and duration with asymmetric directional bias.
A. DIRECTIONAL BIAS (ASYMMETRIC EXPANSION)
The prediction model calculates directional probability using the ML kernel's 252-day Normalized RSI (Z-Score) and Relative Volume (RVOL). The prediction box dynamically adjusts its range based on this probability to provide immediate visual feedback on high-probability direction.
Bullish Scenario (ml_prob > 1.0):
• Upper Range: Expands significantly (1.5x multiplier) to show the aggressive upside target
• Lower Range: Tightens (0.5x multiplier) to show the invalidation level
• Visual Intent: The box is visibly skewed upward, immediately communicating bullish bias without requiring numerical analysis.
Bearish Scenario (ml_prob < -1.0):
• Upper Range: Tightens (0.5x multiplier) to show the invalidation level
• Lower Range: Expands significantly (1.5x multiplier) to show the aggressive downside target
• Visual Intent: The box is visibly skewed downward, immediately communicating bearish bias.
Neutral Scenario (-1.0 < ml_prob < 1.0):
Both ranges use balanced multipliers, creating a symmetrical box that indicates uncertainty.
B. DYNAMIC VOLATILITY BOOSTER (SESSION-BASED ADAPTATION)
The prediction box adjusts its volatility multiplier based on the current session and market conditions to account for intraday volatility patterns.
AM Session (Morning: 07:00-12:00):
• Base Multiplier: 1.0x (Neutral Base)
• Logic: Morning sessions often contain false breakouts and noise. The base multiplier starts neutral to avoid over-projecting during consolidation.
• Trend Booster: Multiplier jumps to 1.5x when:
Price > London Session Open AND AI is Bullish (ml_prob > 0), OR
Price < London Session Open AND AI is Bearish (ml_prob < 0)
• Logic: When the London trend (typically 03:00-08:00 NY time) aligns with the AI model's directional conviction, the indicator aggressively targets higher volatility expansion. This filters for "institutional follow-through" rather than random morning chop.
PM Session (Afternoon: 13:00-16:00):
• Fixed Multiplier: 1.8x
• Logic: The PM session, particularly the 13:30-16:00 ICT Silver Bullet window, often contains the "True Move" of the day. A higher baseline multiplier is applied to emphasize this session's significance over morning noise.
Safety Floor:
A minimum range of 0.2% of the current price is enforced regardless of volatility conditions.
• Purpose: Maintains the prediction box visibility during extreme low-volatility consolidation periods where ATR might collapse to near-zero values.
Volatility Clamp Protection:
Maximum volatility is capped at three times the current ATR value. During flash crashes, circuit breaker halts, or large overnight gaps, raw volatility calculations can spike to extreme levels. This clamp prevents prediction boxes from expanding to unrealistic widths.
Technical Implementation:
f_get_ai_multipliers(float _prob) =>
float _abs_prob = math.abs(_prob)
float _range_mult = 1.0
float _dur_mult = 1.0
if _abs_prob > 30
_range_mult := 1.8
else if _abs_prob > 10
_range_mult := 1.2
else
_range_mult := 0.7
C. PRACTICAL INTERPRETATION
• Wide Upper Range + Tight Lower Range: Strong bullish conviction. The model expects significant upside with limited downside risk.
• Tight Upper Range + Wide Lower Range: Strong bearish conviction. The model expects significant downside with limited upside.
• Symmetrical Range: Neutral/uncertain market. Wait for directional confirmation before entry.
• Large Box (Extended Duration): High-confidence prediction expecting sustained movement.
• Small Box (Short Duration): Low-confidence or choppy conditions. Expect quick resolution.
III. PRACTICAL USAGE GUIDE: METHODOLOGY AND EXECUTION
A. ESTABLISHING TRADING CONTEXT (THE THREE CHECKS)
The primary goal of the dashboard is to filter out low-probability trade setups before they occur.
• Timeframe Selection: Although the core AI is normalized to the Daily context, the indicator performs optimally on intraday timeframes (e.g., 5m, 15m) where session-based volatility is most pronounced.
• PHASE Check (Timing): Always confirm the current phase. The highest probability signals typically occur within the visually highlighted NY AM/PM Killzones because this is when institutional liquidity and volume are at their peak. Signals outside these zones should be treated with skepticism.
• MARKET REGIME Check (Bias): Ensure the signal (BUY/SELL arrow) aligns with the established MARKET REGIME bias (BULLISH/BEARISH). Counter-bias signals are technically allowed if the score is high, but they represent a higher risk trade.
• VIX REGIME Check (Risk): Review the VIX REGIME for overall market stress. Periods marked DANGER (high VIX) indicate elevated volatility and market uncertainty. During DANGER regimes, reducing position size or choosing a wider SL Multiplier is advisable.
B. DASHBOARD INTERPRETATION (THE REAL-TIME STATUS DISPLAY)
The indicator features a non-intrusive dashboard that provides real-time, context-aware information based on the core analytical engines.
PHASE: (PRE-MARKET, NY-AM, LUNCH, NY-PM)
• Meaning: Indicates the current institutional session time. This is derived from the customizable session inputs.
• Interpretation: Signals generated during NY-AM or NY-PM (Killzones) are generally considered higher-probability due to increased institutional participation and liquidity.
MARKET REGIME: (BULLISH, BEARISH, NEUTRAL)
• Meaning: The established directional bias for the trading day, confirmed by the price breaking above the Pre-Market High (PMH) or below the Pre-Market Low (PML).
• Interpretation: Trading with the established regime (e.g., taking a BUY signal when the regime is BULLISH) is the primary method. NEUTRAL indicates that the PMH/PML boundary has not yet been broken, suggesting market ambiguity.
VIX REGIME: (STABLE, DANGER)
• Meaning: A measure of overall market stress and stability, based on the CBOE VIX index integration. The thresholds (20.0 and 35.0 default) are customizable by the user.
• Interpretation: STABLE indicates stable volatility, favoring momentum trades. DANGER (VIX > 35.0) indicates extreme stress; signals generated in this environment require caution and often necessitate smaller position sizing.
SIGNAL SCORE: (0 to 10+ Points)
• Meaning: The accumulated score derived from the VOLATILITY NORMALIZED AI SCORING ENGINE, factoring in bias, VWAP alignment, volume, and the Z-Score probability.
• Interpretation: The indicator generates a signal when this score meets or exceeds the Minimum Entry Score (default 3). A higher score (e.g., 7+) indicates greater statistical confluence and a stronger potential entry.
AI PROBABILITY: (Bull/Bear %)
• Meaning: Directional probability derived from the ML kernel, expressed as a percentage with Bull/Bear label.
• Interpretation: Higher absolute values (>20%) indicate stronger directional conviction from the ML model.
LIVE METRICS SECTION:
• STATUS: Shows current trade state (LONG, SHORT, or INACTIVE)
• ENTRY: Displays the entry price for active trades
• TARGET: Shows the calculated Take Profit level
• ROI | KILL ZONE:
◦ For Active Trades: Displays real-time P&L percentage during NY session hours.
◦ At Market Close (16:00 NY): Since this is a NY session-specific indicator, any active position is automatically evaluated and closed at 16:00. The final result (VALIDATED or INVALIDATED) is determined based on whether the trade reached profit or loss at market close.
◦ Result Persistence: The killzone result (VALIDATED/INVALIDATED) remains displayed on the dashboard until the next NY AM KILLZONE session begins, providing a clear performance reference for the previous trading day.
Note: If a trade is still trending at 16:00, it will be force-closed and evaluated at that moment, as the indicator operates strictly within NY trading hours.
C. SIGNAL GENERATION AND ENTRY LOGIC
The indicator generates signals based on two distinct technical setups, both of which require the accumulated SIGNAL SCORE to be above the configured Minimum Entry Score.
Breakout Entry
• Trigger Condition: Price closes beyond the Pre-Market High (PMH) or Low (PML).
• Rationale: This setup targets the initial directional movement for the day. A breakout confirms the institutional bias by decisively breaking the first major structural boundary, making the signal high-probability.
Continuation Entry
• Trigger Condition: The market is already in an established regime (e.g., BULLISH), and the price closes above the high (or below the low) of the previous bar, while the SIGNAL SCORE remains high. Requires the Allow Trend Continuation parameter to be active.
• Rationale: This setup targets follow-through trades, typically in the afternoon session, capturing momentum after the morning's direction has been confirmed. This filters for sustainability in the established trend.
Execution: Execute the trade immediately upon the close of the bar that prints the BUY or SELL signal arrow.
D. MANAGING RISK AND EXITS
1. RISK PARAMETER SELECTION
The indicator immediately draws the dynamic TP/SL zones upon entry.
• Volatility-Based (Recommended Default): By setting the SL Multiplier (e.g., 1.5) and the TP Multiplier (e.g., 3.0), the indicator enforces a constant, dynamically sized risk-to-reward ratio (e.g., 1:2 in this example). This helps that risk management scales proportionally with the current market volatility (ATR).
• Structural Override: Selecting the Use Structural SL parameter fixes the stop-loss not to the ATR calculation, but to the more significant structural level of the PMH or PML. This is utilized by traders who favor institutional entry rules where the stop is placed behind the liquidity boundary.
2. EXIT METHODS
• Hard Exit: Price hits the visual TP or SL box boundary.
• Soft Exit (Momentum Decay Filter): If the trade is active and the SIGNAL SCORE drops below the Exit Score Threshold (default 3), it indicates that the momentum supporting the trade has significantly collapsed. This serves as a momentum decay filter, prompting the user to consider a manual early exit even if the SL/TP levels have not been hit, thereby preserving capital during low-momentum consolidation.
• Market Close Auto-Exit: At 16:00 NY time, any active trade is automatically closed and classified as VALIDATED (profit) or INVALIDATED (loss) based on current price vs. entry price.
IV. PARAMETER REFERENCE AND CONFIGURATION
A. GLOBAL SETTINGS
• Language (String, Default: English): Selects the language for the dashboard and notification text. Options: English, Korean, Chinese, Spanish, Portuguese, Russian, Ukrainian, Vietnamese.
B. SESSION TIMES (3 BOX SYSTEM)
• PRE-MARKET (Session, Default: 0800-0930): Defines the session range used for Pre-Market High/Low (PMH/PML) structural calculation.
• REGULAR (Morning) (Session, Default: 0930-1200): Defines the core Morning trading session.
• AFTERNOON (PM) (Session, Default: 1300-1600): Defines the main Afternoon trading session.
• Timezone (String, Default: America/New_York): Sets the timezone for all session and time-based calculations.
C. NY KILLZONES (OVERLAYS)
• Show NY Killzones (Bool, Default: True): Toggles the translucent background fills that highlight high-probability trading times (Killzones).
• NY AM Killzone (Session, Default: 0700-1000): Defines the specific time window for the first key liquidity surge (Open overlap).
• NY PM Killzone (Session, Default: 1330-1600): Defines the afternoon liquidity window, aligned with the ICT Silver Bullet and PM Trend entry timing.
• Allow Entry in Killzones (Bool, Default: True): Enables or disables signal generation specifically during the defined Killzone hours.
• Activate AI Prediction Box (Bool, Default: True): Toggles the drawing of the predicted target range boxes on the chart.
D. CORE SCORING ENGINE
• Minimum Entry Score (Int, Default: 3): The lowest accumulated score required for a Buy/Sell signal to be generated and plotted.
• Allow Trend Continuation (Bool, Default: True): Enables the secondary entry logic that fires signals based on momentum in an established trend.
• Force Ignore Volume (Bool, Default: False): Overrides the volume checks in the scoring engine. Useful for markets where volume data is unreliable or nonexistent.
• Force Show Signals (Ignore Score) (Bool, Default: False): Debug mode that displays all signals regardless of score threshold.
• Integrate CBOE:VIX (Bool, Default: True): Enables the connection to the VIX index for market stress assessment.
• Stable VIX (<) (Float, Default: 20.0): VIX level below which market stress is considered low (increases score).
• Stress VIX (>) (Float, Default: 35.0): VIX level above which market stress is considered high (decreases score/flags DANGER).
• Use ML Probability (Bool, Default: True): Activates the volatility-normalized AI Z-Score kernel. Disabling this removes the cross-timeframe normalization filter.
• Max Learning History (Int, Default: 2000): Maximum number of bars stored in the ML training arrays.
• Normalization Lookback (252 Days) (Int, Default: 252): The number of DAILY bars used to calculate the Z-Score mean and standard deviation (representing approximately 1 year of data).
E. RISK MANAGEMENT (ATR MODEL)
• Use Structural SL (Bool, Default: False): Overrides the ATR-based Stop Loss distance to use the Pre-Market High/Low as the fixed stop level.
• Stop Loss Multiplier (x ATR) (Float, Default: 1.5): Defines the Stop Loss distance in multiples of the current Average True Range (ATR).
• Take Profit Multiplier (x ATR) (Float, Default: 3.0): Defines the Take Profit distance in multiples of the current Average True Range (ATR).
• Exit Score Threshold (<) (Int, Default: 3): The minimum score below which an active trade is flagged for a Soft Exit due to momentum collapse.
F. VISUAL SETTINGS
• Show Dashboard (Bool, Default: True): Toggles the real-time data panel.
• Show NY Killzones (Bool, Default: True): Toggles killzone background fills.
• Show TP/SL Zones (Bool, Default: True): Toggles the drawing of Take Profit and Stop Loss boxes.
• Show Pre-Market Extensions (Bool, Default: True): Extends PM High/Low lines across the entire chart for support/resistance reference.
• Activate AI Prediction Box (Bool, Default: True): Enable or disable the predictive range projection.
• Light Mode Optimization (Bool, Default: True): Toggles dashboard and plot colors for optimal visibility on white (light) chart backgrounds.
• Enforce Trend Coloring (Bool, Default: True): Forces candle colors based on Market Regime (Bullish=Cyan, Bearish=Pink) to emphasize trend direction.
• Label Size (String, Default: Normal): Options: Tiny, Small, Normal.
G. LIQUIDITY POOLS (PDH/PDL)
• Show Liquidity Lines (Bool, Default: True): Toggles the display of the Previous Day High (PDH) and Low (PDL) lines.
• Liquidity High Color (Color, Default: Green): Color setting for the PDH line.
• Liquidity Low Color (Color, Default: Red): Color setting for the PDL line.
🔔 ALERT CONFIGURATION GUIDE
The indicator is equipped with specific alert conditions.
How to Set Up an Alert:
Click the "Alert" (Clock icon) in the top TradingView toolbar.
Select "Market Regime NY Session " from the Condition dropdown menu.
Choose one of the specific trigger conditions below depending on your strategy:
🚀 Available Alert Conditions
1. BUY (Long Entry)
Trigger: Fires immediately when a confirmed Bullish Setup is detected.
Conditions: Market Bias is Bullish (or valid Continuation) + Signal Score ≥ Minimum Entry Score.
Usage: Use this alert to open new Long positions or close existing Short positions.
2. SELL (Short Entry)
Trigger: Fires immediately when a confirmed Bearish Setup is detected.
Conditions: Market Bias is Bearish (or valid Continuation) + Signal Score ≥ Minimum Entry Score.
Usage: Use this alert to open new Short positions or close existing Long positions.
V. IMPORTANT TECHNICAL LIMITATIONS
⚠️ Intraday Only (Timeframe Compatibility)
This indicator is strictly designed for Intraday Timeframes (1m to 4h).
Daily/Weekly Charts: The session logic (e.g., "09:30-16:00") cannot function on Daily bars because a single bar encompasses the entire session. Session boxes, TP/SL zones, and AI prediction boxes will NOT draw on the Daily timeframe. Only the PDH/PDL liquidity lines remain visible on Daily charts. This is expected behavior, not a limitation.
Maximum Supported Timeframe: All visual components (session boxes, killzone overlays, TP/SL zones, AI prediction boxes) are displayed up to the 4-hour timeframe. Above this timeframe, only PDH/PDL lines and the dashboard remain functional.
⚠️ Drawing Object Limit (Max 500)
A single script can display a maximum of 500 drawing objects (boxes/lines) simultaneously.
On lower timeframes (e.g., 1-minute), where many signals and session boxes are generated, older history (typically beyond 10-14 days) will automatically disappear to make room for new real-time data.
For deeper historical backtesting visualization, switch to higher timeframes (e.g., 15m, 1h).
The indicator implements FIFO array management to comply with this limit while maintaining the most recent and relevant visual data.
VI. PRACTICAL TRADING TIPS AND BEST PRACTICES
• Killzone Confirmation: The highest statistical validity is observed when a high-score signal occurs directly within a visible NY AM/PM Killzone. Use the Killzones as a strict time filter.
• Liquidity Awareness (PDH/PDL): Treat the Previous Day High (PDH) and Low (PDL) lines as magnets. If your dynamic Take Profit (TP) is placed just above PDH, consider adjusting your target slightly below PDH or utilizing the Soft Exit, as liquidity absorption at these levels often results in sudden, sharp reversals that stop out a trade just before the target is reached.
• VIX as a Position Sizer: During DANGER VIX regimes, the resulting high volatility means the ATR value will be large. It is prudent to either reduce the SL Multiplier or, more commonly, reduce the overall position size to maintain a constant currency risk exposure per trade.
• Continuation Filter Timing: Trend Continuation signals are most effective during the Afternoon (PM) session when the morning's directional breakout has had time to establish a strong, clear, and sustainable trend. Avoid using them in the initial AM session when the direction is still being contested.
• 16:00 Market Close Rule: All trades, boxes, and lines are automatically cleaned up at 16:00 NY time. This prevents overnight chart clutter and maintains visual clarity.
VII. 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 "ROI" and trade results) 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.
Delta Reaction Zones [BOSWaves]Delta Reaction Zones - Cumulative Delta-Based Supply and Demand Identification with Flow-Weighted Zone Construction
Overview
Delta Reaction Zones is a volume flow-aware supply and demand detection system that identifies price levels where significant buying or selling pressure accumulated, constructing adaptive zones around cumulative delta extremes with intelligent flow composition analysis.
Instead of relying on traditional price-based support and resistance or fixed pivot structures, zone placement, thickness, and directional characterization are determined through delta accumulation patterns, volatility-adaptive sizing, and the proportional composition of positive versus negative volume flow.
This creates dynamic reaction boundaries that reflect actual order flow imbalances rather than arbitrary price levels - contracting during low volatility environments, expanding during elevated volatility periods, and incorporating flow composition statistics to reveal whether zones formed under buying or selling dominance.
Price is therefore evaluated relative to zones anchored at delta extremes rather than conventional technical levels.
Conceptual Framework
Delta Reaction Zones is founded on the principle that meaningful support and resistance emerge where cumulative volume flow reaches local extremes rather than where price alone forms patterns.
Traditional support and resistance methods identify turning points through price structure, which often ignores the underlying order flow dynamics that drive those reversals. This framework replaces price-centric logic with delta-driven zone construction informed by actual buying and selling pressure.
Three core principles guide the design:
Zone placement should correspond to cumulative delta extremes, not price pivots alone.
Zone thickness must adapt to current market volatility conditions.
Flow composition context reveals whether zones formed under accumulation or distribution.
This shifts supply and demand analysis from static price levels into adaptive, flow-anchored reaction boundaries.
Theoretical Foundation
The indicator combines delta proxy methodology, cumulative volume tracking, adaptive volatility measurement, and flow decomposition analysis.
A signed volume delta proxy estimates directional order flow on each bar, which accumulates into a running cumulative delta series. Pivot detection identifies local extremes in either cumulative delta or its rate of change, marking levels where flow momentum reached inflection points. Average True Range (ATR) provides volatility-responsive zone sizing, while impulse window analysis decomposes recent flow into positive and negative components with percentage weighting.
Four internal systems operate in tandem:
Delta Accumulation Engine : Computes smoothed signed volume and maintains cumulative delta tracking for directional flow measurement.
Pivot Detection System : Identifies significant turning points in cumulative delta or delta rate of change to anchor zone placement.
Adaptive Zone Construction : Scales zone thickness dynamically using ATR-based volatility measurement around pivot anchors.
Flow Composition Analysis : Calculates positive and negative flow percentages over a configurable impulse window to characterize zone formation context.
This design allows zones to reflect actual order flow behavior rather than reacting mechanically to price formations.
How It Works
Delta Reaction Zones evaluates price through a sequence of flow-aware processes:
Signed Volume Delta Calculation : Each bar's volume is directionally signed based on close-open relationship, creating a proxy for buying versus selling pressure.
Cumulative Delta Tracking : Signed volume accumulates into a running total, revealing sustained directional flow over time.
Pivot Identification : Local highs and lows in cumulative delta (or its rate of change) mark significant flow inflection points where zones anchor.
Volatility-Adaptive Sizing : ATR multiplier determines zone half-width, automatically adjusting thickness to current market conditions.
Flow Decomposition : Positive and negative volume components are separated and percentage-weighted over the impulse window to reveal dominant flow direction.
Intelligent Zone Merging : Overlapping zones of the same type automatically merge into broader reaction areas, with flow statistics blended proportionally.
Dynamic Extension and Visualization : Zones extend forward with gradient-filled composition segments showing buy versus sell flow proportions.
Breach Detection and Cleanup : Zones invalidate automatically when price closes beyond their boundaries, maintaining chart clarity.
Together, these elements form a continuously updating supply and demand framework anchored in order flow reality.
Interpretation
Delta Reaction Zones should be interpreted as flow-anchored supply and demand boundaries:
Support Zones (Green) : Form at cumulative delta lows, marking levels where selling exhaustion or buying accumulation occurred.
Resistance Zones (Red) : Establish at cumulative delta highs, identifying areas where buying exhaustion or selling distribution dominated.
Flow Composition Segments : Visual gradient within each zone reveals the buy/sell flow proportion during zone formation. The upper segment (red tint) represents negative (selling) flow percentage while the lower segment (green tint) represents positive (buying) flow percentage.
BUY FLOW / SELL FLOW / MIXED Labels : Indicate dominant flow character when one direction exceeds 60% of total impulse window activity.
Net Delta Statistics : Display cumulative flow totals (Δ) alongside percentage breakdowns for immediate context.
Zone Thickness : Reflects current volatility environment - wider zones in volatile conditions, tighter zones in calm markets.
Zone Merging : Multiple nearby pivots consolidate into broader reaction areas, weighted by their respective flow magnitudes.
Flow composition, volatility context, and delta magnitude outweigh isolated price reactions.
Signal Logic & Visual Cues
Delta Reaction Zones presents two primary interaction signals:
Support Reclaim (RC) : Green label appears when price crosses back above a support zone's midline after trading below it, suggesting renewed buying interest.
Resistance Re-enter (RE) : Red label displays when price crosses back below a resistance zone's midline after trading above it, indicating resumed selling pressure.
Alert generation covers zone creation and midline reclaim/re-entry events for systematic monitoring.
Strategy Integration
Delta Reaction Zones fits within order flow-informed and supply/demand trading approaches:
Flow-Anchored Entry Zones : Use zones as high-probability reaction areas where historical order flow imbalances occurred.
Composition-Based Bias : Favor trades aligning with dominant flow character - long setups near zones formed under buying dominance, short setups near selling-dominated zones.
Volatility-Aware Targeting : Expect wider reaction ranges when ATR expands zones, tighter ranges when ATR contracts them.
Merge-Informed Conviction : Broader merged zones represent multiple flow inflection points, potentially offering stronger support/resistance.
Midline Reclaim Validation : Use RC/RE signals as confirmation of zone respect rather than standalone entry triggers.
Multi-Timeframe Flow Context : Apply higher-timeframe delta zones to inform lower-timeframe entry precision.
Technical Implementation Details
Core Engine : Signed volume delta proxy with EMA smoothing
Accumulation Model : Persistent cumulative delta tracking with optional rate-of-change pivot detection
Zone Construction : ATR-scaled thickness around pivot anchors
Flow Analysis : Positive/negative decomposition over configurable impulse window
Visualization : Gradient-filled zones with embedded flow statistics and percentage segments
Signal Logic : Midline crossover detection with breach-based invalidation
Merge System : Proximity-based consolidation with weighted flow blending
Performance Profile : Optimized for real-time execution with configurable zone limits
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Micro-structure flow zones for scalping and short-term reversals
15 - 60 min : Intraday supply/demand identification with flow context
4H - Daily : Swing-level reaction zones with macro flow characterization
Suggested Baseline Configuration:
Delta Smoothing Length : 3
Pivot Length : 12
Pivot Source : Cumulative Delta
Impulse Window : 100
ATR Length : 14
ATR Multiplier : 0.35 (reduce for lower timeframes)
Maximum Zones : 8
Merge Overlapping Zones : Enabled
Merge Gap : 20 ticks
These suggested parameters should be used as a baseline; their effectiveness depends on the asset's volume profile, tick structure, and preferred zone density, so fine-tuning is expected for optimal performance.
Parameter Calibration Notes
Use the following adjustments to refine behavior without altering the core logic:
Zones appearing oversized : Reduce ATR Multiplier to tighten zone thickness, especially on lower timeframes.
Excessive zone clutter : Increase Pivot Length to demand stronger delta extremes before zone creation.
Unstable delta readings : Increase Delta Smoothing Length to reduce bar-to-bar noise in flow calculation.
Missing significant levels : Decrease Pivot Length or switch Pivot Source to "Cumulative Delta RoC" for flow acceleration sensitivity.
Flow percentages feel stale : Reduce Impulse Window Length to emphasize more recent buying/selling composition.
Too many merged zones : Decrease Merge Gap (ticks) or disable merging to preserve individual pivot zones.
Adjustments should be incremental and evaluated across multiple session types rather than isolated market conditions.
Performance Characteristics
High Effectiveness:
Markets with consistent volume and order flow characteristics
Instruments where delta proxy correlates well with actual tape reading
Mean-reversion strategies targeting flow exhaustion zones
Trend continuation entries at zones aligned with dominant flow direction
Reduced Effectiveness:
Extremely low volume environments where delta proxy becomes unreliable
News-driven or gapped markets with discontinuous flow
Highly manipulated or illiquid instruments with erratic volume patterns
Integration Guidelines
Confluence : Combine with BOSWaves structure, market profile, or traditional supply/demand analysis
Flow Respect : Trust zones formed with strong net delta magnitude and clear flow dominance
Context Awareness : Consider whether current market regime matches zone formation conditions
Merge Recognition : Treat merged zones as higher-conviction areas due to multiple flow inflections
Breach Discipline : Exit zone-based setups cleanly when price invalidates boundaries
Disclaimer
Delta Reaction Zones is a professional-grade order flow and supply/demand analysis tool. It uses a volume-based delta proxy that estimates directional pressure but does not access true order book data. Results depend on market conditions, volume reliability, parameter selection, and disciplined execution. BOSWaves recommends deploying this indicator within a broader analytical framework that incorporates price structure, volatility context, and comprehensive risk management.
