BORSACA TRADER LIMITED TIME USE ONLYThis indicator does NOT REPAINT. If the signal occurs it will be forever. Easy and profitable strategy optimized for Crypto, Foreks and Stock Markets...
This indicator gives you Long and Exit signals all timeframes...
BORSACA TRADER is optimized to catch trend movements as soon as possible and maximize profitability.
Strategy tester results. 96% Profitable on BTCUSD Daily scale. Test other markets you want.
WE RELY ON OUR INDICATOR TO THE END. AND WE ASSURE YOU THERE IS NOTHING BETTER THAN THE BORSACA TRADER INDICATOR.
Best regards and happy trading.
Herif's winning strategy option. Check the strategy tester results success than %96
Safe Mode as optional parameter. You can enable this to prevent some riskier trades to happen at the cost of some profitability. Use it if you are more conservative in trading.
Normal Mode signals for Buy and Sell.
Trade Mode signals for buy and sell use with support and resistance levels.
Auto Support And Resistance..
Auto Fibonacci Levels...
BORSACA TRADER indicator is the best option for everybody in financial markets. Check my Profile Page for more information and follow me, like and favorite my indicator and support your positive response and take a message for 10 days trial.
Happy trading. Good luck :)
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Intelligent Exponential Moving Average Private AccessView the full documentation on this indicator here: www.kenzing.com
Note: This indicator is now intended for those who have been granted private access and may be more frequently updated than the previous versions.
Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The Exponential Moving Average ( EMA ) is one of the most used indicators on the planet, yet no one really knows what pair of exponential moving average lengths works best in combination with each other.
A reason for this is because no two EMA lengths are always going to be the best on every instrument, time-frame, and at any given point in time.
The " Intelligent Exponential Moving Average " solves the moving average problem by adapting the period length to match the most profitable combination of exponential moving averages in real time.
How does the Intelligent Exponential Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these exponential moving averages will be the most profitable.
Can we learn from the Intelligent Moving Average?
There are many lessons to be learned from the Intelligent EMA . Most will come with time as it is still a new concept. Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The exponential moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of exponential moving average lengths is between 5 to 40.
Additional coverage resulted in TradingView server errors.
Future Updates!
Soon, I will be publishing tools to test the AI and visualise what moving average combination the AI is currently using.
Follow and like for more content!
Intelligent Moving Average Private AccessNote: This indicator is intended for those who have been granted private access and may be more frequently updated than the previous versions.
Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The Moving Average is the most used indicator on the planet, yet no one really knows what pair of moving average lengths works best in combination with each other.
A reason for this is because no two moving averages are always going to be the best on every instrument, time-frame, and at any given point in time.
The " Intelligent Moving Average " solves the moving average problem by adapting the period length to match the most profitable combination of moving averages in real time.
How does the Intelligent Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these moving averages will be the most profitable.
Can we learn from the Intelligent Moving Average?
There are many lessons to be learned from the Intelligent Moving Average. Most will come with time as it is still a new concept.
Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of moving average lengths is between 5 to 40.
Additional coverage resulted in TradingView server errors.
Future Updates!
This indicator will be maintained and many updates will come in the near future! Stay tuned.
View the documentation on this indicator here: www.kenzing.com
kiska cloudskiska clouds: crypto twitter's next cloud meme
Crypto is a fast-paced, highly-volatile asset, therefore, many traditional strategies are thrown out of the window when applied to cryptocurrency markets. In trading, there are only two things known for sure: price and volume. Price and volume data is then manipulated using various math equations in an effort to discover patterns and/or make predictions. kiska clouds are no different.
The kiska clouds are a simple crossover strategy. The clouds are different because of the unique averages being used and the embedded momentum indicator.
To use the clouds is simple:
When the green line crosses above the pink line, you buy/long.
When the green line crosses below the pink line, you sell/short.
The clouds are indicative of the trend's momentum. Using the power of math, the larger the cloud indicates a higher amount of buying/selling pressure. As the cloud thins, momentum is slowing, and the trend may be reversing.
At the time of testing, the strategy had a profitability of 54.55% accuracy with 1133.41% net profit. While I think this could be automated into a bot, adding a human element with stop losses and further analysis will significantly improve the accuracy/profitability.
This indicator is a "Pay What You Want" model. For a trial or to purchase this indicator, send me a message on Twitter @moonkiska or here on TradingView. You will be granted a 2-3 day trial period to the backtesting strategy.
Tips:
The higher the time frame, the more accurate the strategy.
Personally, I do not short above the 200MA. I do not long below the 200MA.
Coming Soon:
Support/Resistance
Trend Lines
5X 15-min Momentum Scalper by SW9KThis is the alpha release-candidate study script with indicator alerts included. It is currently open for select individuals to test.
The core of this momentum scalper is primarily based on a modified Schaff Trend (which in itself is based on Stochastic elements and MACD) and a modified T3-CCI oscillator, specifically calibrated for 15-minute type movements -- do not apply to any other timeframes. Although it will take small scalps, it is designed to recognize when to ride out underwater positions so use maximum leverage or 5X or you may risk liquidation. Also, there is a stop loss setting feature, but it may reduce profits and win rate.
You can verify the highly accurate 75% win rate performance statistics with 100,000 XBTUSD contracts simulated at .
Features:
40% 3-month net profit, 74.48% win rate, 2.988 profit factor, 3.13% max drawdown, adjusted Sharpe ratio of ~3
Optimized for 15 minute timeframe scalping
Attempts to recognize when to keep position open and ride them out into profitable or breakeven
Profitable even with full Bitmex taker fees (0.075%)
Pyramiding Setting (default 3)
Aggressive Mode to increase entries and potential profits at higher risk
Easy-to-set binary Alerts
Follow SW9K at www.twitter.com
ALPHA: ReversalWhat is a divergence?
In the case of strength and momentum indicators, it is when the price deviates from the movement of the oscillator, it can have significant implications for trade management.
Divergences in an uptrend occurs when the price makes a higher high but the indicator does not. In a downtrend, divergence occurs when the price makes a lower low, but the indicator does not. When a divergence is spotted, there is a higher probability of a price reversal.
Divergences helps the trader recognize and react appropriately to a change in price action. It tells us something is changing and the trader must make a decision, such as tighten the stop-loss or take profit. Seeing divergences increases profitability by alerting the trader to protect profits or open a position.
Divergences indicate that something is changing, but it does not automatically mean the trend will reverse. It signals the trader must consider holding, tightening the stop loss, opening a position or take profit.
Introduction
The Alpha: Reversal is an indicator based off of the Stochastic, Relative Strength Index and Momentum indicator. Its sole purpose is to be able to identify divergences when they matter and identify high probability reversal areas. The formula used between the three indicators will be kept proprietary, in addition to the slight changes made on the Stochastic formula. The indicator plots the histogram with a divergence formula within a 14 period look-back on default. Additionally, there is a moving average of the histograms movement to identify the divergences when they matter.
Divergences exist on just about every candle, most of the time they are at a minuscule level. Rarely do the price and oscillator movement collude, the question becomes when do these divergences matter?
With that in mind I approached the task of finding a reliable reversal model. On default, the indicator has a moving average that measures the past histogram (the formula of the three indicators) movement to identify when a high potential trend shift may happen.
Keeping volatility in mind there is a feature called "Fixed Threshold" in settings. Various assets move at different speeds, so the indicator needs the ability to adjust to fit the assets speed. This "Threshold" option does not have a set of rules to use for each asset, the option is there though, so it may be adjusted by the analyst manually if the histogram moving average seems inaccurate due to volatility or lack thereof. In future publications (or possibly indicator updates) I plan on expanding on a fixed set of rules for various assets. This will take considerable time to research and backtest the various values needed for an asset's speed, so for now the default MA can be used until you are comfortable with adjusting the threshold level manually.
The look-back period on the histogram and threshold MA can be adjusted to whichever time period you would like. However, the default 14 is typically what is best considering the inputs of the three underlying indicators.
Analysis
The indicator is actually quite simple to read. When the price spikes blue, there is a high probability of reversal, same goes for red but in the opposite fashion. Now as always, you should use this indicator as an analysis tool and not rely on it by itself. Many times Cryptocurrencies couldn't care less about strength or oversold/overbought and volume explodes out of nowhere, I highly recommend you use price action in addition to Alpha: Exhaustion and Alpha: Volume with this tool. Oh wait, Alpha: Volume is not out yet.... SOON. :)
Point is, use proper analysis techniques with this indicator, nothing is perfect. NOTHING. But the Alpha: Reversal is a great tool to use for not only the beginner trader, but the advanced also. There is a ton of ways to use this indicator beyond the high probability reversal areas, I am discovering some really neat patterns within my new formula that I plan on expanding on in future publications, i.e. dead cat bounces and relief candles plus a few more.
Conclusion
The Alpha: Reversal is a great analysis tool that I now use on all my charts, as time goes on I plan on holding classes for its users on a regular basis to expand on the various techniques that can be implemented in addition to publishing research relevant to its purpose.
Access to the indicator can be purchased on my site www.thetradingwizard.com with either a monthly option for this & the Alpha: Exhaustion (), or a lifetime subscription independently. All updates and changes will be done automatically and included for every user. The Alpha series is designed to help you make your analysis easier to comprehend and more accurate, I really think this one will be enjoyed by many for years to come, I have enjoyed designing and using this immensely. As always, please make your own decisions when trading and use proper analysis techniques.
Note: The options within the Alpha: Reversal allow the indicator to be used on any timeframe & any asset. As with any indicator, the higher the timeframe, the higher the accuracy.
Disclaimer
Nothing in this post is to be used or construed as financial advice. This post is meant as an educational post to explain the functions of the indicator.
Bold PlotA remarkable algorithm creates entry, re-entry, take profit, safety exit signals. Nothing to set. There is only config code.All signals are being created when new candle opens. Ergo, never repaints. This also helps alarms to be set directly as "once per bar".
Now only for XBTUSD - Bitmex - 2h
Entries: When the algorithm creates an initial entry signal, it also follows the recent trend.
Re-Entries: If the algorithm senses a retracement or correction however the price movement within recent trend, the script creates re-entry signal.
Take Profit: Apart from the main entry algorithm, completely different algorithm has been developed for take profit signals. Expect maximum of 3 take profit signals after each initial entry and re-entries. Maximum of 3 TP signals aim to reach best profit levels rather than contingency.
Safety Exit Signals: Another individual algorithm apart from both entries and take profit signals. If the algorithm senses that the price movement might be in danger opposite to recent position, it creates safety exit signal for only once. This type of signals can also be considered as contingency signals. They can either be a take profit or stop loss. Be aware! This type of signals do not focus on exiting the position completely. They have designed to exit the position 60%-80% and re-enter if the the algorithm creates re-entry signals. There might be take profit signals following the safety exit signals as this situation does not affect take profits.
Current Config Codes:
XBTUSD - Bitmex - 2h / Config Code: 1
Greed Indicator | BennuQuantsGreed indicator. Applicable to traders who have issues taking profit at set targets.
This indicator has three inputs. Your entry, your profit target, and a margin % (if you are a degen). Given you entry price, you can see where (marked in gold) that you were in profit but didn't take profit. This is good feedback for psychological indicators which I think will be my next focus. Reasoning behind this was the many conversations that my old trading partner and I would have issues where we held positions for too long and they would reverse us out of profit. This should eliminate such behaviors or at least help to correct them.
I don't expect this to be that interesting to most, but its something. Will be publishing the script shortly
Green indicates proft, yellow marks greed periods, and red marks negative periods. Also an easy way to track a trades current profitability.
Efficient PriceTrading The Movements That Matters
Inspired by the Price Volume Trend indicator the Efficient Price aim to create a better version of the price containing only the information a trend trader must need.
Calculation
This indicator use the Efficiency Ratio as a smoothing constant, it is calculated as follow :
ER = abs(change(close,length))/sum(abs(change(close)),length)
The goal of the Efficiency Ratio is to show if the market is trending or ranging.If ER is high then the market is considered to be trending, if ER is low then the market is considered to be ranging.
Then the Efficient Price is calculated :
EP = cum(change(close)*ER)
When the price is trending, the indicator will show movements of the price with unchanged volatility, but if the price is not trending then the indicator will flatten those movements.Think of this indicator as both a filter and a compressor and the Efficient Price as some kind of threshold.
The Efficient Price As Input For Indicators/Strategies
If the indicator show the movement of the trending price, it can be interesting to use it as input in order to reduce the number of false signals in a strategy.
We will test 2 MACD strategy provided by tradingview, one using the closing price (In Red) and one with the efficient price (In White) as input
with both the following parameters :
fastLength = 50
slowlength = 200
MACDLength = 20
length = 50
Where length is the parameter of the Efficient Price.A spread of 2 pips is used.
Without Efficient Price : 26.88% of profitability, 69 pips of profit.
With Efficient Price : 38.46% of profitability, 336 pips of profit.
The difference of profitability is of 11.58%, the strategy with the Efficient Price made few trades and its equity have a lower variance than the equity of the MACD strategy using closing price.
Smoothed Version
It is possible to smooth the indicator output by using the following code :
EP = cum(change(close,length)*ER)
Hope you enjoy
For any questions/demands feel free to pm me, i would be happy to help you
Intelligent Volume-weighted Moving Average (AI)Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The volume-weighted moving average (VWMA) is one of the most used indicators on the planet, yet no one really knows what pair of volume-weighted moving average lengths works best in combination with each other. A reason for this is because no two VWMA lengths are always going to be the best on every instrument, time-frame, and at any given point in time.
The "Intelligent Volume-weighted Moving Average" solves the moving average problem by adapting the period length to match the most profitable combination of volume-weighted moving averages in real time.
How does the Intelligent Volume-weighted Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these volume-weighted moving averages will be the most profitable.
Can we learn from the Intelligent Volume-weighted Moving Average?
There are many lessons to be learned from the Intelligent VWMA. Most will come with time as it is still a new concept. Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
This indicator does not change what has already been plotted and does not repaint in any way shape or form which means it is excellent for trading in real-time!
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The volume-weighted moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of VWMA lengths is between 5 to 40.
The black crosses can be turned off in the settings panel.
Test this indicator!
I am also publishing tools that can be used to back-test this indicator and understand what period length is currently being used.
There will be many more updates to come so stay tuned!
Updated documentation and access to this indicator can be found at www.kenzing.com
Intelligent Exponential Moving Average (AI)Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The Exponential Moving Average (EMA) is one of the most used indicators on the planet, yet no one really knows what pair of exponential moving average lengths works best in combination with each other.
A reason for this is because no two EMA lengths are always going to be the best on every instrument, time-frame, and at any given point in time.
The "Intelligent Exponential Moving Average" solves the moving average problem by adapting the period length to match the most profitable combination of exponential moving averages in real time.
How does the Intelligent Exponential Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these exponential moving averages will be the most profitable.
Can we learn from the Intelligent Moving Average?
There are many lessons to be learned from the Intelligent EMA. Most will come with time as it is still a new concept. Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The exponential moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of exponential moving average lengths is between 5 to 40.
Additional coverage resulted in TradingView server errors.
Future Updates!
Soon, I will be publishing tools to test the AI and visualise what moving average combination the AI is currently using.
Intelligent Moving Average (AI)
Introduction
This indicator uses machine learning (Artificial Intelligence) to solve a real human problem.
The Moving Average is the most used indicator on the planet, yet no one really knows what pair of moving average lengths works best in combination with each other.
A reason for this is because no two moving averages are always going to be the best on every instrument, time-frame, and at any given point in time.
The " Intelligent Moving Average " solves the moving average problem by adapting the period length to match the most profitable combination of moving averages in real time.
How does the Intelligent Moving Average work?
The artificial intelligence that operates these moving average lengths was created by an algorithm that tests every single combination across the entire chart history of an instrument for maximum profitability in real-time.
No matter what happens, the combination of these moving averages will be the most profitable.
Can we learn from the Intelligent Moving Average?
There are many lessons to be learned from the Intelligent Moving Average. Most will come with time as it is still a new concept.
Adopting the usefulness of this AI will change how we perceive moving averages to work.
Limitations
Ultimately, there are no limiting factors within the range of combinations that has been programmed. The moving averages will operate normally, but may change lengths in unexpected ways - maybe it knows something we don't?
Thresholds
The range of moving average lengths is between 5 to 40.
Additional coverage resulted in TradingView server errors.
Future Updates!
Soon, I will be publishing tools to test the AI and visualise what moving average combination the AI is currently using.
BitcoinNinjas 'Ninja Signals' Buy/Sell Alert Trading Script v3.0Bitcoin Ninjas 'Ninja Signals' Buy/Sell Alerts & Backtesting TradingView Script v3.0
(for Cryptocurrencies, Forex, GunBot, ProfitTrailer, automatic trading software, and more)
This is version 3 of our popular Ninja Signals trading script, which is similar to version 2, but with a new hard-coded calibration (resolution) setting that automatically matches candle size (period) to ensure that no repainting occurs regardless of the number or type of indicators and filters traders apply when configuring the script.
'Ninja Signals' v3.0 (SCRIPT)
'Ninja Signals' v3.0 (STRATEGY)
'Ninja Signals' v2.0 (SCRIPT)
'Ninja Signals' v2.0 (STRATEGY)
'Ninja Signals' v1.0 (SCRIPT)
'Ninja Signals' v1.0 (STRATEGY)
-Allows users to easily set automated buy and sell alerts on TradingView for use with automatic and manual trading of cryptocurrencies, Forex securities, and more (alerts are compatible with automatic trading software such as GunBot, ProfitTrailer, and more).
-Synthesizes many powerful indicators [e.g. Relative Strength Index (RSI), stochastic RSI, Money Flow Index (MFI), Moving Average Convergence Divergence (MACD), etc.) into one super script to generate very precise buy and sell signals in almost any market condition.
-Buy arrows (blue) and sell arrows (red) can be changed or hidden for ease of viewing.
-No lag EMA trendline featuring trend-reversal color-coding (white uptrend, black downtrend).
-Adjustable ‘calibration’ setting allows users to customize the script to work for any currency or security available through TradingView, on any exchange, simply by adjusting a number.
-Complete with backtesting strategy version of script which allows users to test various buy and sell strategies based on the alerts the script generates (see info and screenshots below).
-Backtesting strategy incorporates a user-defined adjustable date range, so users can estimate the script’s performance over specific periods of time, such as the last day, week, or month.
-Backtesting strategy utilizes a minimum protective gain setting to help you never sell for a loss. Simply adjust your minimum profit (%) per trade, and the test results will update.
-Backtesting strategy allows for pyramid buying to test various average down / double up buying strategies. Simply adjust the number of pyramid buys and the quantity of each buy.
- Free 7-day trial available for TradingView users who join our free BitcoinNinjas community.
-Free 24/7 support via BitcoinNinjas Telegram GunBot support group with script purchase.
-Fully compatible with GunBot automatic trading software (TradingView plugin is required).
-Special discount available for traders who purchase GunBot automatic trading software and the GunBot TradingView plugin from BitcoinNinjas, allowing for fully automatic trading.
-Contact us via Email or Telegram for more information, to request additional / custom screenshots, or to start your free trial.
DISCLAIMER: By using our BitcoinNinjas ‘Ninja Signals’ planning script, you agree to the BitcoinNinjas 'Terms of Use', as presented on our website (www.BitcoinNinjas.org) and as stated here. No sharing, copying, reselling, modifying, or any other forms of use are authorized for our documents, script / strategy, and the information published with them. This informational planning script / strategy is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. Bitcoin Ninjas is not responsible for any losses you may incur. Please invest wisely.
MDTANOS EMA Spread Indicator [v2018-09-01]Built an indicator providing buy / sell signals for MDTANOS from the
ProfitTrailer discord discord.gg as an educational exercise to
show him and the rest of the profit trailer community how to create an indicator
on TradingView using PineScript.
He requested:
i would like to know how to see on tradingview a combination of EMASPREADS
on 5 min and 15 min time frame is it possible?
i have a buy strategy from A to D that combines several time frames
all using EMASPREAD
and the bot buys when all them are true
each of them uses a different time frame
5 min, 15 min, 30 min, 1hour 2 hours 4 hours and 1 day
is there a way to visualize thid condition on tradingview?
Rather than build directly to the requested strategy I made this a
generic and more flexible indicator that can be used and configured
to work on any market, timeframe and trading pair.
Note it is using the timeframes defined for the CandlePeriod parameter
rather than the chart resolution.
I first published the basis of this indicator on the ProfitTrailer discord.
The script uses an EMA spread as its main signal and displays the
spread values as lines on the indicator based on whatever input
criteria you provide.
Based on the buy value and buy limit values it works out buy signals.
The display of the buy signals is optional as displaying them altogether
would not be particularly useful.
This software is provided under a commercial license that grants
personal use only, please refer:
github.com
Copyright (c) 2018, Grant Cause aka CryptoCoyn
BitcoinNinjas Ninja Signals Buy/Sell Alert Trading Script v2.0Bitcoin Ninjas 'Ninja Signals' Buy/Sell Alerts & Backtesting TradingView Script v2.0
(for Cryptocurrencies, Forex, GunBot, ProfitTrailer, automatic trading software, and more)
'Ninja Signals' v2.0 (STRATEGY)
'Ninja Signals' v2.0 (SCRIPT)
'Ninja Signals' v1.0 (STRATEGY)
'Ninja Signals' v1.0 (SCRIPT)
-Allows users to easily set automated buy and sell alerts on TradingView for use with automatic and manual trading of cryptocurrencies, Forex securities, and more (alerts are compatible with automatic trading software such as GunBot, ProfitTrailer, and more).
-Synthesizes many powerful indicators [e.g. Relative Strength Index (RSI), stochastic RSI, Money Flow Index (MFI), Moving Average Convergence Divergence (MACD), etc.) into one super script to generate very precise buy and sell signals in almost any market condition.
-Buy arrows (blue) and sell arrows (red) can be changed or hidden for ease of viewing.
-No lag EMA trendline featuring trend-reversal color-coding (white uptrend, black downtrend).
-Adjustable ‘calibration’ setting allows users to customize the script to work for any currency or security available through TradingView, on any exchange, simply by adjusting a number.
-Complete with backtesting strategy version of script which allows users to test various buy and sell strategies based on the alerts the script generates (see info and screenshots below).
-Backtesting strategy incorporates a user-defined adjustable date range, so users can estimate the script’s performance over specific periods of time, such as the last day, week, or month.
-Backtesting strategy utilizes a minimum protective gain setting to help you never sell for a loss. Simply adjust your minimum profit (%) per trade, and the test results will update.
-Backtesting strategy allows for pyramid buying to test various average down / double up buying strategies. Simply adjust the number of pyramid buys and the quantity of each buy.
- Free 7-day trial available for TradingView users who join our free BitcoinNinjas community.
-Free 24/7 support via BitcoinNinjas Telegram GunBot support group with script purchase.
-Fully compatible with GunBot automatic trading software (TradingView plugin is required).
-Special discount available for traders who purchase GunBot automatic trading software and the GunBot TradingView plugin from BitcoinNinjas, allowing for fully automatic trading.
-Contact us via Email or Telegram for more information, to request additional / custom screenshots, or to start your free trial.
DISCLAIMER: By using this BitcoinNinjas document or ‘Ninja Signals’ planning script, you agree to the BitcoinNinjas 'Terms of Use', as presented on our website (www.BitcoinNinjas.org) and as stated here. No sharing, copying, reselling, modifying, or any other forms of use are authorized for our documents, script / strategy, and the information published with them. This informational document and planning script / strategy is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. BitcoinNinjas is not responsible for any losses you may incur. Please invest wisely.
BitcoinNinjas Ninja Signals Buy/Sell Alert Trading Strategy v2.0Bitcoin Ninjas 'Ninja Signals' Buy/Sell Alerts & Backtesting TradingView Script v2.0
(for Cryptocurrencies, Forex, GunBot, ProfitTrailer, automatic trading software, and more)
'Ninja Signals' v2.0 (SCRIPT)
'Ninja Signals' v2.0 (STRATEGY)
'Ninja Signals' v1.0 (SCRIPT)
'Ninja Signals' v1.0 (STRATEGY)
-Allows users to easily set automated buy and sell alerts on TradingView for use with automatic and manual trading of cryptocurrencies, Forex securities, and more (alerts are compatible with automatic trading software such as GunBot, ProfitTrailer, and more).
-Synthesizes many powerful indicators [e.g. Relative Strength Index (RSI), stochastic RSI, Money Flow Index (MFI), Moving Average Convergence Divergence (MACD), etc.) into one super script to generate very precise buy and sell signals in almost any market condition.
-Buy arrows (blue) and sell arrows (red) can be changed or hidden for ease of viewing.
-No lag EMA trendline featuring trend-reversal color-coding (white uptrend, black downtrend).
-Adjustable ‘calibration’ setting allows users to customize the script to work for any currency or security available through TradingView, on any exchange, simply by adjusting a number.
-Complete with backtesting strategy version of script which allows users to test various buy and sell strategies based on the alerts the script generates (see info and screenshots below).
-Backtesting strategy incorporates a user-defined adjustable date range, so users can estimate the script’s performance over specific periods of time, such as the last day, week, or month.
-Backtesting strategy utilizes a minimum protective gain setting to help you never sell for a loss. Simply adjust your minimum profit (%) per trade, and the test results will update.
-Backtesting strategy allows for pyramid buying to test various average down / double up buying strategies. Simply adjust the number of pyramid buys and the quantity of each buy.
- Free 7-day trial available for TradingView users who join our free BitcoinNinjas community.
-Free 24/7 support via BitcoinNinjas Telegram GunBot support group with script purchase.
-Fully compatible with GunBot automatic trading software (TradingView plugin is required).
-Special discount available for traders who purchase GunBot automatic trading software and the GunBot TradingView plugin from BitcoinNinjas, allowing for fully automatic trading.
-Contact us via Email or Telegram for more information, to request additional / custom screenshots, or to start your free trial.
DISCLAIMER: By using this BitcoinNinjas document or ‘Ninja Signals’ planning script, you agree to the BitcoinNinjas 'Terms of Use', as presented on our website (www.BitcoinNinjas.org) and as stated here. No sharing, copying, reselling, modifying, or any other forms of use are authorized for our documents, script / strategy, and the information published with them. This informational document and planning script / strategy is strictly for individual use and educational purposes only. This is not financial or investment advice. Investments are always made at your own risk and are based on your personal judgement. BitcoinNinjas is not responsible for any losses you may incur. Please invest wisely.
15 Minute Bitcoin Indicator 1.0Indicator Description:
This is a premium indicator that is intended for trading on the 15 minute time scale. This script uses ADX to judge the strength of trends. When a trend is confirmed by ADX, the indicator uses SRSI to find the optimal entry. The indicator works best on BITFINEX:BTCUSD .
Instructions:
Whenever there is a sell signal exit the current long and vice versa. If a close signal appears close the current position but do not open another trade in opposite direction. There is a indicator based stop loss system that is built into the signals, but no static stop loss based on % loss or pips moved in one direction.
Available Settings :
1. Buying and Selling Thresholds: These are the values that are used with SRSI to determine entries. The default values were experimentally determined
to be the most profitable.
2. Stacked Orders Allowed: This limits the amount of positions that can be entered in the same direction. This is useful for trading with leverage. This is defaulted to 2 because I limit myself to 2x leverage. Backtesting shows the more orders allowed, the more profitable, but also risk is increased.
3. ADX/DI Settings: These are settings the ADX smoothing and DI length.
Backtesting:
CLICK HERE
This is a strategy that enters and exits positions on the exact same criteria as this indicator. For the simulation the capital was 10,000 dollars and it was allowed to go up to 2x leverage. Each trade used 100% of available funds. The same simulation done from 1/1/2018 to 4/10/2018 resulted in:
3658.38 % Net Profit
316 Total Closed Trades
77.22 % Profitable
4.552 Profit Factor
24 % Max Drawdown
+11.58% Average Trade
20 15m candles in each trade on average.
Future Plans:
More robust stop loss system.
Factoring trend into trading signals.
EMA integration.
MULTI-TIMEFRAME SUPPORT
Availability
This indicator is currently in a testing stage of development with a full release planned for mid April. While the indicator is not completed, it currently is profitable for me to consider it ready for release. During this testing phase anyone can test it for free for three days, just comment below. Lifetime access currently costs .005 btc, and this price will increase once the full release occurs, if you are interested, DM me for further details.
Please comment with any ideas, suggestions, or criticisms.
Bitcoin Ninjas 'Ninja Signals' Buy & Sell Alert Trading ScriptBitcoin Ninjas 'Ninja Signals' Buy/Sell Alerts & Backtesting TradingView Script
(for Cryptocurrencies, Forex, GunBot, ProfitTrailer, automatic trading software, and more)
-Allows users to easily set automated buy and sell alerts on TradingView for use with automatic and manual trading of cryptocurrencies, Forex securities, and more (alerts are compatible with automatic trading software such as GunBot, ProfitTrailer, and more).
-Synthesizes many powerful indicators [e.g. Relative Strength Index (RSI), stochastic RSI, Money Flow Index (MFI), Moving Average Convergence Divergence (MACD), etc.) into one super script to generate very precise buy and sell signals in almost any market condition.
-Buy arrows (blue) and sell arrows (red) can be changed or hidden for ease of viewing.
-No lag EMA trendline featuring trend-reversal color-coding (white uptrend, black downtrend).
-Adjustable ‘calibration’ setting allows users to customize the script to work for any currency or security available through TradingView, on any exchange, simply by adjusting a number.
-Complete with backtesting strategy version of script which allows users to test various buy and sell strategies based on the alerts the script generates (see info and screenshots below).
-Backtesting strategy incorporates a user-defined adjustable date range, so users can estimate the script’s performance over specific periods of time, such as the last day, week, or month.
-Backtesting strategy utilizes a minimum protective gain setting to help you never sell for a loss. Simply adjust your minimum profit (%) per trade, and the test results will update.
-Backtesting strategy allows for pyramid buying to test various average down / double up buying strategies. Simply adjust the number of pyramid buys and the quantity of each buy.
-Free 7-day trial available for TradingView users who join our free BitcoinNinjas community.
-Free 24/7 support via BitcoinNinjas Telegram GunBot support group with script purchase.
-Fully compatible with GunBot automatic trading software (TradingView plugin is required).
-Special discount available for traders who purchase GunBot automatic trading software and the GunBot TradingView plugin from BitcoinNinjas, allowing for fully automatic trading.
-Contact us for more information, to request additional / custom screenshots, or to start your free trial.
DISCLAIMER: By viewing and/or using this TradingView script, you agree to the BitcoinNinjas 'Terms of Use', as presented on our website and as stated here. No sharing, copying, reselling, modifying, or any other forms of use, are authorized for this document. This document is strictly for individual use and informational purposes only. This is not financial or investment advice. Investments are always made at your own risk, and are ba
Atif's Liquidity Toolkit💎 GENERAL OVERVIEW:
Atif’s Liquidity Toolkit is a price-action-based indicator used to identify Buyside & Sellside Liquidity Levels, Liquidity Sweeps, FVG Sweeps, and Buy/Sell signals, following specific rules from Atif Hussain.
This indicator was developed by Flux Charts in collaboration with Atif Hussain.
🔹Purpose of this indicator:
The purpose of Atif’s Liquidity Toolkit is to help traders understand where liquidity is forming, when it’s being taken, and how momentum shifts immediately afterward. It automates the entire process of identifying buyside & sellside liquidity, detecting liquidity sweeps, and confirming whether displacement followed through a Fair Value Gap. The goal is to give traders a consistent, rule-based framework to interpret market structure.
🎯ATIF’S LIQUIDITY TOOLKIT FEATURES:
Atif’s Liquidity Toolkit indicator includes 6 main features:
Fair Value Gaps
Multi-Timeframe Liquidity Levels
Liquidity Sweeps
Fair Value Gap Sweeps
Buy & Sell Signals with Take-Profit & Stop-Loss Levels
Alerts
1️⃣Fair Value Gaps
🔹What is a Fair Value Gap?:
A Fair Value Gap (FVG) is an area where the market’s perception of fair value suddenly changes. On your chart, it appears as a three-candle pattern: a large candle in the middle, with smaller candles on each side that don’t fully overlap it. A bullish FVG forms when a bullish candle is between two smaller bullish/bearish candles, where the first and third candles’ wicks don’t overlap each other at all. A bearish FVG forms when a bearish candle is between two smaller bullish/bearish candles, where the first and third candles’ wicks don’t overlap each other at all.
Bullish & Bearish FVGs:
In the settings, you can toggle on/off FVGs, choose the invalidation method, adjust the sensitivity, and toggle on FVG Midline & Labels.
🔹Invalidation Method:
The Invalidation Method setting allows traders to choose how an FVG is invalidated. You can choose between Close and Wick.
Close: A candle must close below a bullish FVG or above a bearish FVG to invalidate it.
Wick: A candle’s wick must go below a bullish FVG or above a bearish FVG to invalidate it.
🔹Sensitivity:
The sensitivity setting determines the minimum gap size required for an FVG detection. A higher sensitivity will filter out smaller gaps, while a lower sensitivity will detect more frequent, smaller gaps. Setting the sensitivity to 0 will display all gaps, regardless of their size.
On the left, the sensitivity is 5. On the right, the sensitivity is 0.
🔹Midline:
When enabled, a dashed line is drawn at the center of the FVG.
🔹Labels:
When enabled, a text label will be plotted with the gap, clearly identifying the zone as a FVG.
2️⃣ Multi-Timeframe Liquidity Levels
The indicator automatically detects and plots Buyside Liquidity (BSL) & Sellside Liquidity (SSL) Levels across up to three timeframes simultaneously.
🔹What is Buyside Liquidity?
Buyside Liquidity (BSL) represents price levels where many buy stop orders are sitting, usually from traders holding short positions. When price moves into these areas, those stop-loss orders get triggered and short sellers are forced to buy back their positions. These zones often form above key highs such as the previous day, week, or month. Understanding BSL is important because when price reaches these levels, the sudden wave of buy orders can create sharp reactions or reversals as liquidity is taken from the market.
🔹What is Sellside Liquidity?
Sellside Liquidity (SSL) represents price levels where many sell stop orders are waiting, usually from traders holding long positions. When price drops into these areas, those stop-loss orders are triggered and long traders are forced to sell their positions. These zones often form below key lows such as the previous day, week, or month. Understanding SSL is important because when price reaches these levels, the surge of sell orders can cause sharp reactions or reversals as liquidity is taken from the market.
Atif’s Liquidity Toolkit indicator automatically plots Buyside & Sellside Liquidity levels using the following levels:
Previous Day High (PDH) & Previous Day Low (PDL)
Previous Week High (PWH) & Previous Week Low (PWL)
Previous Month High (PMH) & Previous Month Low (PML)
Asia Session Highs/Lows
London Session Highs/Lows
New York Session Highs/Lows
The session start and end times are not customizable. The following times in EST are used for each session:
Asia Session: 20:00-00:00
London Session: 02:00-05:00
New York Sessions:
NY AM: 09:30-11:00
NY Lunch: 12:00-13:00
NY PM: 14:00-16:00
Users can also plot swing highs/lows using a lookback period and choosing the higher timeframe. Users can choose two custom higher timeframes and also enable swing highs/lows from the current chart’s timeframe.
There are three settings to customize for the current chart’s timeframe and higher timeframes:
Current TF - when toggled on, swing highs/lows will be plotted from the chart’s timeframe using the pivot length input
HTF 1 - when toggled on, swing highs/lows will be plotted from the user-inputted timeframe using the pivot length input
HTF 2 - when toggled on, swing highs/lows will be plotted from the user-inputted timeframe using the pivot length input
The Pivot Length controls how far back the indicator checks to confirm whether a candle’s high or low is a true swing point (also called a “pivot”). When detecting a swing high, the indicator checks if that candle’s high is higher than the highs of the previous X candles and the next X candles. For a swing low, it checks if the candle’s low is lower than the lows of the previous X candles and the next X candles. The number X comes from your Pivot Length setting.
A lower Pivot Length input (for example, 3 or 4) means the indicator only looks at a few candles on each side, so it will detect more swing points, including smaller, less significant ones. A higher Pivot Length input (for example, 20 or 25) makes the indicator look at more candles on each side, so it only marks major turning points that stand out clearly on the chart.
In short:
Low Pivot Length = more frequent, smaller levels (short-term focus)
High Pivot Length = fewer, stronger levels (major swing focus)
The Pivot Length input for each setting (Current TF, HTF 1, and HTF 2) are displayed below in the red boxes:
Each liquidity level is plotted with a text label, making it easy to identify where a level came from. You can turn off the ‘Show Levels’ setting if you don’t want to see the levels on your chart.
Please note: Liquidity Levels play a key role in finding liquidity sweeps, FVG Sweeps, and Buy/Sell signals. Keeping the levels turned off will not stop the indicator from using the levels that are enabled from being used for the other features mentioned.
3️⃣Liquidity Sweeps:
The indicator automatically detects bullish and bearish liquidity sweeps using the liquidity levels you have enabled.
🔹What is a Liquidity Sweep?
A liquidity sweep is a market phenomenon where significant players, such as institutional traders, deliberately drive prices through key levels to trigger clusters of pending buy or sell orders. It’s how the market gathers the liquidity needed for larger participants to enter positions.
Traders often place stop-loss orders around obvious highs and lows, such as the previous day’s, week’s, or month’s levels. When price pushes through one of these areas, it triggers the stops placed there and generates a burst of volume. This often creates a short-term fake-out before the market reverses in the opposite direction.
By detecting these sweeps in real time, traders can identify potential reversal areas or “trap” areas where liquidity has been taken.
🔹Bullish Liquidity Sweep
These occur when price dips below a Sellside Liquidity (SSL) level, taking out the stop-loss orders placed by long traders below that low. The indicator marks a zone around the candle that swept the SSL to highlight where liquidity was removed from the market.
When this happens, it shows that the market just cleared out sell-side liquidity, meaning traders who were long had their stops hit. This is often followed by a reversal or strong reaction upward, because the market no longer has pending liquidity to fill below that level.
🔹Bearish Liquidity Sweep
These occur when price dips above a Buyside Liquidity (BSL) level, taking out the stop-loss orders placed by short seller traders above that high. The indicator marks a zone around the candle that swept the BSL to highlight where liquidity was removed from the market.
When this happens, it shows that the market just cleared out buyside liquidity, meaning short traders had their stops hit. This is often followed by a reversal or strong reaction downward, because the market no longer has pending liquidity to fill above that level.
Under the ‘Liquidity Sweeps’ section in the settings, you can toggle on/off Bullish Regular Sweeps and Bearish Regular Sweeps. You can also customize the line style and color of liquidity levels that have been swept.
🔹How to Use Liquidity Sweeps
Liquidity sweeps are not direct trade signals. They are best used as context when forming a directional bias. A sweep shows that the market has removed liquidity from one side, which can hint at where the next move may develop.
For example:
When Buyside Liquidity (BSL) is swept, it often signals that buy stops have been triggered and the market may be preparing to move lower. Traders may then begin looking for short opportunities.
When Sellside Liquidity (SSL) is swept, it often signals that sell stops have been triggered and the market may be preparing to move higher. Traders may then begin looking for long opportunities.
It’s common practice to use liquidity sweeps as the first step in building a trade idea. Many traders will wait for additional confirmation, such as a fair value gap forming after the sweep, before opening a position.
Under the ‘Liquidity Sweeps’ section in the settings, you can toggle on/off:
Bullish Regular Sweeps - when disabled, Bullish Regular Sweeps won’t appear on your chart.
Bearish Regular Sweeps - when disabled, Bearish Regular Sweeps won’t appear on your chart.
4️⃣Fair Value Gap Sweeps:
The indicator automatically detects bullish and bearish Fair Value Gap sweeps (FVG Sweep) using the liquidity levels you have enabled.
🔹What is a FVG Sweep?
A FVG Sweep is a specific type of liquidity sweep that not only clears liquidity above or below a key level, but also forms a Fair Value Gap (FVG) immediately afterward.
The liquidity sweep shows where stop orders were triggered, areas where the market aggressively took out one side’s liquidity. The formation of a Fair Value Gap right after the sweep confirms that displacement followed. This means that the sweep was not just a stop hunt, but a deliberate move backed by momentum.
In simple terms, a regular liquidity sweep only tells you that liquidity was taken. A FVG Sweep tells you that liquidity was taken and a strong directional move started immediately after, leaving an imbalance in price. That imbalance represents where aggressive buyers or sellers entered the market without enough opposite-side orders to keep price balanced. This combination adds a confirmation and intent behind regular liquidity sweeps.
🔹Bullish FVG Sweep
The indicator automatically detects bullish FVG Sweeps when price takes out a Sellside Liquidity (SSL) level and then forms a bullish FVG within the next few candles. This sequence shows that sellers were stopped out and buyers immediately entered the market with momentum.
🔹Bearish FVG Sweep
The indicator automatically detects bearish FVG Sweeps when price takes out a Buyside Liquidity (BSL) level and then forms a bearish FVG shortly after. This shows that short sellers’ stops were triggered, and new selling pressure entered the market right away.
🔹How to Use FVG Sweeps
Unlike regular liquidity sweeps, FVG Sweeps can be used as trade entries because they confirm both liquidity being cleared and immediate momentum. A regular sweep only shows that stop-losses were triggered, but an FVG Sweep proves that price not only cleared liquidity but also moved away with momentum, leaving behind an imbalance (Fair Value Gap). This shift often marks the start of a new short-term trend.
We’ll cover this in more detail in the Buy and Sell Signal section below, but in short, a bullish FVG Sweep can act as confirmation for a potential long entry after price takes out a low, while a bearish FVG Sweep can confirm a short entry after price takes out a high.
The strongest FVG Sweeps come from extremely sharp reversals. On the chart, they look like a “V” shape for bullish setups or an inverted “V” shape for bearish setups. This shape shows how quickly momentum shifted after liquidity was cleared. When price instantly reverses and leaves a Fair Value Gap behind, it’s a clear sign that buyers or sellers stepped in aggressively and absorbed all available liquidity on the opposite side.
In practice, traders often use FVG Sweeps as a trigger to align their bias. For example, after a bullish FVG Sweep, the focus shifts toward looking for long setups within the new imbalance or during a small retracement into the Fair Value Gap. After a bearish FVG Sweep, traders focus on short setups as price retraces back into the gap before continuing lower. The key takeaway is that FVG Sweeps show conviction.
Under the ‘Liquidity Sweeps’ section in the settings, you can toggle on/off:
Bullish FVG Sweeps - when disabled, Bullish FVG Sweeps won’t appear on your chart.
Bearish FVG Sweeps - when disabled, Bearish FVG Sweeps won’t appear on your chart.
Please Note: the settings you choose to use for Fair Value Gaps, under the ‘Fair Value Gaps’ section, will be used for FVG Sweeps. This is important because if you increase the sensitivity value for FVGs, not all FVG Sweeps will appear if the FVG’s size doesn’t meet the sensitivity threshold.
5️⃣Buy & Sell Signals:
This indicator also plots Buy & Sell signals. These signals follow logic based on Atif Hussain’s FVG trading model. The entry requirements for a Long & Short signal are outlined below.
🔹Buy Signal:
In order for a Buy Signal to generate, the following conditions must occur in order:
Bullish FVG Sweep
Price Retraces to the Bullish FVG
🔹Sell Signal:
In order for a Buy Signal to generate, the following conditions must occur in order:
Bearish FVG Sweep
Price Retraces to the FVG
🔹Require Retracement:
Under the ‘Signals’ section in the settings, you can toggle on/off the ‘Require Retracement’ setting. When disabled, a long/short signal will appear immediately after a Bullish or Bearish FVG Sweep, instead of waiting for price to retrace back to the gap.
Please Note: the liquidity levels you enable under the ‘Liquidity Levels’ section will be the levels used for signals. Thus, if you only have the Previous Day Highs/Lows enabled, then only those levels will be used to generate buy/sell signals. Also, long Signals will only appear if Bullish FVG Sweeps are enabled, and Short Signals will only appear if Bearish FVG Sweeps are enabled.
When a Buy Signal or Sell Signal is plotted, three suggested take-profit levels and one suggested stop-loss level are plotted. There are two different Take-Profit methods you can choose from within the indicator settings: Manual or Auto.
🔹Manual Take-Profit:
If you’re using manual take-profit levels, you can customize the Risk-to-Reward (RR) for Take-Profit 1, 2, and 3 by adjusting the “RR 1”, “RR 2”, and “RR 3” settings. Setting RR 1 to 1 means take-profit 1 is a 1:1 risk-to-reward ratio. The stop-loss will always be placed at the recent low for Buy Signals, and at the recent high for Sell Signals.
🔹Auto Take-Profit:
If you select to use Auto Take-Profit instead of Manual, then Take-Profit 1, 2, and 3 will be automatically determined based on nearby liquidity levels. The stop-loss will be placed at the recent low for Buy Signals, and at the recent high for Sell Signals. Take-Profit Levels 1, 2, and 3 will be placed at the three closest opposite liquidity levels. If the take-profit 2 and take-profit 3 levels are too far away, only one take-profit level will be displayed.
🔹Signal Settings:
Long Signals:
When enabled, long signals are shown. When disabled, long signals will not appear.
Short Signals:
When enabled, short signals are shown. When disabled, short signals will not appear.
Require Retracement:
When enabled, price must retrace to a FVG after a FVG Sweep in order for a signal to be generated.
Take-Profit Levels:
When enabled, take-profit levels (TP 1, TP 2, and TP 3) are shown with long/short signals. When disabled, take-profit levels and their price labels are not displayed.
Take-Profit Labels:
When enabled, take-profit labels are displayed when price reaches one of the three take-profit levels. When disabled, labels won’t appear when price reaches take-profit levels.
Stop-Loss Levels:
When enabled, stop-loss levels are shown for long/short signals. When disabled, the stop-loss level and its price label are not displayed.
Stop-Loss Labels:
When enabled, stop-loss levels are shown for long/short signals. When disabled, a label won’t appear when price reaches the stop-loss level.
6️⃣Alerts:
The indicator supports alerts, so you never miss a key market move. You can choose to receive alerts for each of the following conditions:
Bearish Liquidity Sweep
Bullish Liquidity Sweep
Bearish FVG Sweep
Bullish FVG Sweep
Long Signal
Short Signal
TP 1
TP 2
TP 3
Stop-Loss
‼️Important Notes:
TradingView has limitations when running features on multiple timeframes, such as the liquidity levels, which can result in the following error:
🔹Computation Error:
The computation of using MTF features are very intensive on TradingView. This can sometimes cause calculation timeouts. When this occurs, simply force the recalculation by modifying one indicator’s settings or by removing the indicator and adding it to your chart again.
🚩 UNIQUENESS:
This indicator is unique because it identifies a specific type of liquidity event referred to as FVG Sweeps, where price takes liquidity and then immediately forms a Fair Value Gap in the opposite direction. These FVG Sweeps serve as the foundation of the model, and the script uses them as the required condition for generating Buy and Sell signals. Once an FVG Sweep is confirmed, the indicator automatically produces a fully defined trade idea with a stop-loss and up to three take-profit targets, following a consistent rule-based execution approach.
chart Pattern & Candle sticks Strategy# **XAUUSD Pattern & Candle Strategy - Complete Description**
## **Overview**
This Pine Script indicator is a comprehensive multi-factor trading system specifically designed for **XAUUSD (Gold) scalping and swing trading**. It combines classical technical analysis methods including candlestick patterns, chart patterns, moving averages, and volume analysis to generate high-probability buy/sell signals with automatic stop-loss and take-profit levels.
***
## **Core Components**
### **1. Moving Average System (Triple MA)**
**Purpose:** Identifies trend direction and momentum
- **Fast MA (20-period)** - Short-term price action
- **Medium MA (50-period)** - Intermediate trend
- **Slow MA (200-period)** - Long-term trend direction
**How it works:**
- **Bullish alignment**: MA20 > MA50 > MA200 (all pointing up)
- **Bearish alignment**: MA20 < MA50 < MA200 (all pointing down)
- **Crossover signals**: When Fast MA crosses Medium MA, it triggers buy/sell signals
- **Choice of SMA or EMA**: Adjustable based on preference
**Visual indicators:**
- Blue line = Fast MA
- Orange line = Medium MA
- Light red line = Slow MA
- Green background tint = Bullish trend
- Red background tint = Bearish trend
---
### **2. Candlestick Pattern Recognition (13 Patterns)**
**Purpose:** Identifies reversal and continuation signals based on price action
#### **Bullish Patterns (Signal potential upward moves):**
1. **Hammer** 🔨
- Long lower wick (2x body size)
- Small body at top
- Indicates rejection of lower prices (buyers stepping in)
- Best at support levels
2. **Inverted Hammer**
- Long upper wick
- Small body at bottom
- Shows buying pressure despite initial selling
3. **Bullish Engulfing** 📈
- Green candle completely engulfs previous red candle
- Strong reversal signal
- Body must be 1.2x larger than previous
4. **Morning Star** ⭐
- 3-candle pattern
- Red candle → Small indecision candle → Large green candle
- Powerful reversal at bottoms
5. **Piercing Line** ⚡
- Green candle closes above 50% of previous red candle
- Indicates strong buying interest
6. **Bullish Marubozu**
- Almost no wicks (95% body)
- Very strong bullish momentum
- Body must be 1.3x average size
#### **Bearish Patterns (Signal potential downward moves):**
7. **Shooting Star** 💫
- Long upper wick
- Small body at bottom
- Indicates rejection of higher prices (sellers in control)
- Best at resistance levels
8. **Hanging Man**
- Similar to hammer but appears at top
- Warning of potential reversal down
9. **Bearish Engulfing** 📉
- Red candle completely engulfs previous green candle
- Strong reversal signal
10. **Evening Star** 🌙
- 3-candle pattern (opposite of Morning Star)
- Green → Small → Large red candle
- Powerful top reversal
11. **Dark Cloud Cover** ☁️
- Red candle closes below 50% of previous green candle
- Indicates strong selling pressure
12. **Bearish Marubozu**
- Almost no wicks, pure red body
- Very strong bearish momentum
#### **Neutral Pattern:**
13. **Doji**
- Open and close nearly equal (tiny body)
- Indicates indecision
- Often precedes major moves
**Detection Logic:**
- Compares body size, wick ratios, and position relative to previous candles
- Uses 14-period average body size as reference
- All patterns validated against volume confirmation
***
### **3. Chart Pattern Recognition**
**Purpose:** Identifies major support/resistance and reversal patterns
#### **Patterns Detected:**
**Double Bottom** 📊 (Bullish)
- Two lows at approximately same level
- Indicates strong support
- Breakout above neckline triggers buy signal
- Most reliable at major support zones
**Double Top** 📊 (Bearish)
- Two highs at approximately same level
- Indicates strong resistance
- Breakdown below neckline triggers sell signal
- Most reliable at major resistance zones
**Support & Resistance Levels**
- Automatically plots recent pivot highs (resistance)
- Automatically plots recent pivot lows (support)
- Uses 3-bar strength for validation
- Levels shown as dashed horizontal lines
**Price Action Patterns**
- **Uptrend detection**: Higher highs + higher lows
- **Downtrend detection**: Lower highs + lower lows
- Confirms overall market structure
***
### **4. Volume Analysis**
**Purpose:** Confirms signal strength and filters false signals
**Metrics tracked:**
- **Volume MA (20-period)**: Baseline average volume
- **High volume threshold**: 1.5x the volume average
- **Volume increase**: Current volume > previous 2 bars
**How it's used:**
- All buy/sell signals **require volume confirmation**
- High volume = institutional participation
- Low volume signals are filtered out
- Prevents whipsaw trades during quiet periods
**Visual indicator:**
- Dashboard shows "High" volume in orange when active
- "Normal" shown in gray during low volume
***
### **5. Signal Generation Logic**
**BUY SIGNALS triggered when ANY of these occur:**
1. **Candlestick + Volume**
- Bullish candle pattern detected
- High volume confirmation
- Price above Fast MA
2. **MA Crossover + Volume**
- Fast MA crosses above Medium MA
- High volume confirmation
3. **Double Bottom Breakout**
- Price breaks above support level
- Volume confirmation present
4. **Trend Continuation**
- Uptrend structure intact (higher highs/lows)
- All MAs in bullish alignment
- Price above Fast MA
- Volume confirmation
**SELL SIGNALS triggered when ANY of these occur:**
1. **Candlestick + Volume**
- Bearish candle pattern detected
- High volume confirmation
- Price below Fast MA
2. **MA Crossunder + Volume**
- Fast MA crosses below Medium MA
- High volume confirmation
3. **Double Top Breakdown**
- Price breaks below resistance level
- Volume confirmation present
4. **Trend Continuation**
- Downtrend structure intact (lower highs/lows)
- All MAs in bearish alignment
- Price below Fast MA
- Volume confirmation
***
### **6. Risk Management System**
**Automatic Stop Loss Calculation:**
- Based on ATR (Average True Range) - 14 periods
- **Formula**: Entry price ± (ATR × SL Multiplier)
- **Default multiplier**: 1.5 (adjustable)
- Adapts to market volatility automatically
**Automatic Take Profit Calculation:**
- **Formula**: Entry price ± (ATR × TP Multiplier)
- **Default multiplier**: 2.5 (adjustable)
- **Default Risk:Reward ratio**: 1:1.67
- Higher TP multiplier = more aggressive targets
**Position Management:**
- Tracks ONE position at a time (no pyramiding)
- Automatically closes position when:
- Stop loss is hit
- Take profit is reached
- Opposite MA crossover occurs
- Prevents revenge trading and over-leveraging
**Visual Representation:**
- **Red horizontal line** = Stop Loss level
- **Green horizontal line** = Take Profit level
- Lines remain on chart while position is active
- Automatically disappear when position closes
***
### **7. Visual Elements**
**On-Chart Displays:**
1. **Moving Average Lines**
- Fast MA (Blue, thick)
- Medium MA (Orange, thick)
- Slow MA (Red, thin)
2. **Support/Resistance**
- Green crosses = Support levels
- Red crosses = Resistance levels
3. **Buy/Sell Arrows**
- Large GREEN "BUY" label below bars
- Large RED "SELL" label above bars
4. **Pattern Labels** (Small markers)
- "Hammer", "Bull Engulf", "Morning Star" (green, below bars)
- "Shooting Star", "Bear Engulf", "Evening Star" (red, above bars)
- "Double Bottom" / "Double Top" (blue/orange)
5. **Signal Detail Labels** (Medium size)
- Shows signal reason (e.g., "Bullish Candle", "MA Cross Up")
- Displays Entry, SL, and TP prices
- Color-coded (green for long, red for short)
6. **Background Coloring**
- Light green tint = Bullish MA alignment
- Light red tint = Bearish MA alignment
***
### **8. Information Dashboard**
**Top-right corner table showing:**
| Metric | Description |
|--------|-------------|
| **Position** | Current trade status (LONG/SHORT/None) |
| **MA Trend** | Overall trend direction (Bullish/Bearish/Neutral) |
| **Volume** | Current volume status (High/Normal) |
| **Pattern** | Last detected candlestick pattern |
| **ATR** | Current volatility measurement |
**Purpose:**
- Quick at-a-glance market assessment
- Real-time position tracking
- No need to check multiple indicators
***
### **9. Alert System**
**Complete alert coverage for:**
✅ **Entry Alerts**
- "Buy Signal" - Triggers when buy conditions met
- "Sell Signal" - Triggers when sell conditions met
✅ **Exit Alerts**
- "Long TP Hit" - Take profit reached on long position
- "Long SL Hit" - Stop loss triggered on long position
- "Short TP Hit" - Take profit reached on short position
- "Short SL Hit" - Stop loss triggered on short position
**How to use:**
1. Click "Create Alert" button
2. Select desired alert from dropdown
3. Set notification method (popup, email, SMS, webhook)
4. Never miss a trade opportunity
***
## **Recommended Settings**
### **For Scalping (Quick trades):**
- **Timeframe**: 5-minute
- **Fast MA**: 9
- **Medium MA**: 21
- **Slow MA**: 50
- **SL Multiplier**: 1.0
- **TP Multiplier**: 2.0
- **Volume Threshold**: 1.5x
### **For Swing Trading (Longer holds):**
- **Timeframe**: 1-hour or 4-hour
- **Fast MA**: 20
- **Medium MA**: 50
- **Slow MA**: 200
- **SL Multiplier**: 2.0
- **TP Multiplier**: 3.0
- **Volume Threshold**: 1.3x
### **Best Trading Hours for XAUUSD:**
- **Asian Session**: 00:00 - 08:00 GMT (lower volatility)
- **London Session**: 08:00 - 16:00 GMT (high volatility) ⭐
- **New York Session**: 13:00 - 21:00 GMT (highest volume) ⭐
- **London-NY Overlap**: 13:00 - 16:00 GMT (BEST for scalping) 🔥
***
## **How to Use This Strategy**
### **Step 1: Setup**
1. Open TradingView
2. Load XAUUSD chart
3. Select timeframe (5m, 15m, 1H, or 4H)
4. Add indicator from Pine Editor
5. Adjust settings based on your trading style
### **Step 2: Wait for Signals**
- Watch for GREEN "BUY" or RED "SELL" labels
- Check the signal reason in the detail label
- Verify dashboard shows favorable conditions
- Confirm volume is "High" (not required but preferred)
### **Step 3: Enter Trade**
- Enter at market or limit order near signal price
- Note the displayed Entry, SL, and TP prices
- Set your broker's SL/TP to match indicator levels
### **Step 4: Manage Position**
- Watch for SL/TP lines on chart
- Monitor dashboard for trend changes
- Exit manually if opposite MA crossover occurs
- Let SL/TP do their job (don't move them!)
### **Step 5: Review & Learn**
- Track win rate over 20+ trades
- Adjust multipliers if needed
- Note which patterns work best for you
- Refine entry timing
***
## **Key Advantages**
✅ **Multi-confirmation approach** - Reduces false signals significantly
✅ **Automatic risk management** - No manual calculation needed
✅ **Adapts to volatility** - ATR-based SL/TP adjusts to market conditions
✅ **Volume filtered** - Ensures institutional participation
✅ **Visual clarity** - Easy to understand at a glance
✅ **Complete alert system** - Never miss opportunities
✅ **Pattern education** - Learn patterns as they appear
✅ **Works on all timeframes** - Scalping to swing trading
***
## **Limitations & Considerations**
⚠️ **Not a holy grail** - No strategy wins 100% of trades
⚠️ **Requires practice** - Demo trade first to understand signals
⚠️ **Market conditions matter** - Works best in trending or volatile markets
⚠️ **News events** - Avoid trading during major economic releases
⚠️ **Slippage on 5m** - Fast markets may have execution delays
⚠️ **Pattern subjectivity** - Some patterns may trigger differently than expected
***
## **Risk Management Rules**
1. **Never risk more than 1-2% per trade**
2. **Maximum 3 positions per day** (avoid overtrading)
3. **Don't trade during major news** (NFP, FOMC, etc.)
4. **Use proper position sizing** (0.01 lot per $100 for micro accounts)
5. **Keep trade journal** (track patterns, win rate, mistakes)
6. **Stop trading after 3 consecutive losses** (psychological reset)
7. **Don't move stop loss further away** (accept losses)
8. **Take partial profits** at 1:1 R:R if desired
***
## **Expected Performance**
**Realistic expectations:**
- **Win rate**: 50-65% (depending on market conditions and timeframe)
- **Risk:Reward**: 1:1.67 default (adjustable to 1:2 or 1:3)
- **Signals per day**: 3-8 on 5m, 1-3 on 1H
- **Best months**: High volatility periods (news events, economic uncertainty)
- **Drawdowns**: Expect 3-5 losing trades in a row occasionally
***
## **Customization Options**
All inputs are adjustable in settings panel:
**Moving Averages:**
- Type (SMA or EMA)
- All three period lengths
**Volume:**
- Volume MA length
- High volume multiplier threshold
**Chart Patterns:**
- Pattern strength (bars for pivot detection)
- Show/hide pattern labels
**Risk Management:**
- ATR period
- Stop loss multiplier
- Take profit multiplier
**Display:**
- Toggle pattern labels
- Customize colors (in code)
***
## **Conclusion**
This is a **professional-grade, multi-factor trading system** that combines the best of classical technical analysis with modern risk management. It's designed to give clear, actionable signals while automatically handling the complex calculations of stop loss and take profit levels.
**Best suited for traders who:**
- Understand basic technical analysis
- Can follow rules consistently
- Prefer systematic approach over gut feeling
- Want visual confirmation before entering trades
- Value proper risk management
**Start with demo trading** for at least 20-30 trades to understand how the signals work in different market conditions. Once comfortable and profitable on demo, transition to live trading with minimal risk per trade.
Happy trading! 📈🎯
0DTE Options - Iron Condor & ButterflyTo help options traders:
Plan and structure Iron Condor or Butterfly spreads in “Setup Mode.”
Track live trades, including P&L, breach risk, and strike distances, in “Live Mode.”
Visualize the trade on the price chart with profit zones, breakeven lines, strike markers, and alerts.
Evaluate market conditions using IV Rank, ATR-based range modeling, and modeled Delta approximation.
Essentially, it turns your TradingView chart into an options risk graph + planning terminal.
⚙️ Core Modes of Operation
🧱 1. Setup Mode
Used for planning new trades. It automatically suggests strikes based on:
ATR (volatility proxy)
IV Rank
Target Delta
Chosen risk tier (High / Mid / Low / Delta)
You can:
Preview recommended short and long strikes.
See estimated credit, width, and risk/reward ratios in a setup table.
Auto-feed these calculated strikes into the Live Mode to track them later.
Example Use:
Before market open, choose Setup Mode → Mid Risk Tier → see what strike widths and credits make sense for the day.
📈 2. Live Mode
Used to track real trades you’ve already opened.
You can:
Paste your real trade data (strikes, credits, etc.) into the 📋 paste field.
Or auto-feed from Setup Mode (if “Auto-Feed” is enabled).
The indicator then plots:
Short/long strikes
Breakevens
Profit/loss zone
Real-time breach detection and delta drift
Alerts when price nears your strikes or exits your safe zone.
Example Use:
After opening an Iron Condor on SPX, paste in 626,628,620,618,1.20,1, and the chart visually shows your safe range and warning zones.
🧮 Built-In Calculations
1. IV Rank (Volatility Environment)
Uses a 20-day log return volatility model to calculate IV Rank (percentile of volatility over the last 252 bars).
You can use this automatically or manually override it if you have data from your broker.
→ High IV Rank (>50) = better for selling Iron Condors (more premium).
2. ATR (Average True Range)
Measures short-term volatility to estimate expected daily price movement.
Used in Setup Mode to model distance between strikes.
3. Strike Calculations (Setup Mode)
Based on risk tier:
High Risk → wide wings, high credit, high potential drawdown
Mid Risk → balanced setup
Low Risk → narrow wings, safer but less credit
Delta Mode → based purely on target delta (e.g., 0.20)
Uses ATR × multiplier to determine how far short strikes should be from current price.
4. Credit Estimation
Based on strike width × IV Rank multiplier:
IV > 50 → 30% of width
IV 30–50 → 25%
IV < 30 → 20%
5. Profit & Loss Modeling
The indicator computes:
Max Profit:
Iron Condor → credit × 100 × contracts
Butterfly → (wing width − debit) × 100 × contracts
Max Loss:
Iron Condor → width − credit
Butterfly → debit × 100 × contracts
Breakevens:
Iron Condor → short strikes ± credit
Butterfly → body ± debit
Current P&L: Approximated by where the underlying is relative to the short/long strikes.
6. Delta Modeling
Estimates each short strike’s modeled delta based on how far it is from current price.
Displays total delta balance to show directional bias.
If Delta drifts too high → market imbalance → consider rolling or adjusting.
7. Breach Detection System
Automatically classifies your trade as:
🟢 In Range: Price between short strikes (safe zone).
🟠 Near Breach: Price close to short strike (risk zone).
🔴 Breached: Price outside long strike (stop or adjust zone).
This dynamically changes color in your profit box and info label.
🎨 Visual Components
Element Meaning Color
Red Line Put side strikes 🔻 Red
Green Line Call side strikes 🔺 Green
Yellow Dotted Lines Breakevens 🟡 Yellow
Green Box Profit zone 🟩 Light green
Orange Box Adjustment zone (near breach) 🟧 Orange
Red Box Breach zone 🟥 Red
White Line Current price ⚪ White
Optional labels display strike details and distances (e.g., “📉 Short Put: 620 – 5 pts away”).
📊 Setup Table (Setup Mode Only)
Displays a grid comparing all risk tiers:
Tier Short Call Short Put Width Est. Credit R:R
High 632 614 4.0 $1.20 0.43
Mid 630 616 3.0 $0.90 0.43
Low 628 618 2.0 $0.60 0.43
Highlighted row = selected risk tier.
This lets you compare how wide/narrow each setup is before committing to a trade.
🧾 Info Box (Live Mode)
Displays real-time stats such as:
🔶 IRON CONDOR | 1 Contract
📊 Calls: 626 / 628 | Puts: 620 / 618
💵 Credit: $1.20 | 💰 Profit: $120 | 🔴 Loss: $180
⬆️ BE: 627.2 | ⬇️ BE: 618.8
📍 Current: $623 | 💵 P&L: +$35.00 (+29.1%)
📏 To Short Call: 3 | To Short Put: 3
📊 Delta: 0.05 | IV Rank: 56% (FAVORABLE)
🔴 BREACH STATUS: In Range
🚨 Alerts
The indicator generates TradingView alerts for:
⚠️ Approaching Call Zone → nearing short call
⚠️ Approaching Put Zone → nearing short put
🛑 Stop Loss Triggered → current P&L exceeds loss threshold
🟠 Near Breach → price entering adjustment zone
🔴 Breached → price outside protection (long strikes)
These alerts can be used with TradingView notifications or webhooks.
🧠 How to Use It Step-by-Step
A. Planning (Setup Mode)
Set mode to “Setup.”
Adjust:
Risk Tier (High / Mid / Low / Delta)
Target Delta (0.15–0.30 recommended)
Strike Interval (e.g., 1.0 or 5.0)
Check Setup Table → see suggested strikes & credits.
Optionally toggle Auto-Feed → Live to send to live mode later.
B. Executing (Broker)
Confirm and enter your trade in your brokerage (use the strikes shown).
Record your strikes, net credit/debit, and number of contracts.
C. Tracking (Live Mode)
Switch to “Live” mode.
Paste your strikes in the 📋 Paste Data field:
Iron Condor Example: 626,628,620,618,1.20,1
Butterfly Example: 600,620,640,2.50,2
The chart updates:
Lines = your strikes
Boxes = profit/risk zones
Labels = strike info, distance to price
Info box = P&L, delta, IV rank, breach status
Set alerts for automatic notifications.
D. Managing the Trade
When the chart turns orange or red, you’re approaching or breaching a strike.
Use this signal to roll, hedge, or close your trade.
Monitor Gamma Risk: warning appears when price nears short strikes (explosive delta risk).
📌 Summary
Feature Description
Mode Switching Plan (Setup) or Track (Live)
IV Rank & ATR Modeling Estimates volatility environment
Auto Strike Planning Suggests strikes based on risk/delta
Visual Range Map Profit, breakeven, and adjustment zones
Real-Time Alerts Warns when nearing or breaching strikes
Trade Info Box Displays live risk, reward, delta, IV, and P&L
Setup Table Compares setups across risk tiers
Fully Configurable Works for Iron Condors or Butterflies
Buy/Sell Volume Tracker [wjdtks255]Indicator Description
Function: Separates buy and sell volume based on candle direction (close ≥ open) and displays the buy−sell difference (hist_val) as a histogram.
Visuals: Buy/sell bars are distinguished by user-selectable colors and opacity; two moving averages (MA1 and MA2) are shown to smooth the flow.
Meaning: A positive histogram indicates buy dominance; a negative histogram indicates sell dominance.
Limitation: The current separation is estimated from candle direction and may differ from execution-side (tick/trade-side) based data.
Trading Rules (Summary)
Conservative trend-following long
Entry: Enter long when hist_val turns above 0 and MA1 crosses MA2 from below.
Stop-loss: Exit if hist_val falls back below 0 or MA1 drops below MA2.
Take-profit: Use a risk:reward of 1:1.5 or set targets based on ATR.
Short-term rebound long
Entry: Enter a short-term long when a large negative histogram region begins to narrow and shows a recovery sign.
Stop-loss: Exit if hist_val drops below the previous low or bearish candles continue.
Take-profit: Prefer quick partial profit-taking.
Short (sell) strategy
Entry: Enter short when hist_val falls below 0 and MA1 crosses MA2 from above.
Stop-loss / Take-profit: Apply the inverse rules of the long strategy.
Filters and risk management
Volume filter: Only accept signals when volume exceeds a fraction of average volume to reduce noise.
Entry strength: Require |hist_val| to exceed a historical average threshold (e.g., avg(|hist_val|, N) × factor) to strengthen signals.
Position sizing: Size positions so that account risk per trade is within limits (e.g., 1–2% of account equity).
Timeframe: Use short timeframes for scalping and 1h+ for swing trading.
Manifold Singularity EngineManifold Singularity Engine: Catastrophe Theory Detection Through Multi-Dimensional Topology Analysis
The Manifold Singularity Engine applies catastrophe theory from mathematical topology to multi-dimensional price space analysis, identifying potential reversal conditions by measuring manifold curvature, topological complexity, and fractal regime states. Unlike traditional reversal indicators that rely on price pattern recognition or momentum oscillators, this system reconstructs the underlying geometric surface (manifold) that price evolves upon and detects points where this topology undergoes catastrophic folding—mathematical singularities that correspond to forced directional changes in price dynamics.
The indicator combines three analytical frameworks: phase space reconstruction that embeds price data into a multi-dimensional coordinate system, catastrophe detection that measures when this embedded manifold reaches critical curvature thresholds indicating topology breaks, and Hurst exponent calculation that classifies the current fractal regime to adaptively weight detection sensitivity. This creates a geometry-based reversal detection system with visual feedback showing topology state, manifold distortion fields, and directional probability projections.
What Makes This Approach Different
Phase Space Embedding Construction
The core analytical method reconstructs price evolution as movement through a three-dimensional coordinate system rather than analyzing price as a one-dimensional time series. The system calculates normalized embedding coordinates: X = normalize(price_velocity, window) , Y = normalize(momentum_acceleration, window) , and Z = normalize(volume_weighted_returns, window) . These coordinates create a trajectory through phase space where price movement traces a path across a geometric surface—the market manifold.
This embedding approach differs fundamentally from traditional technical analysis by treating price not as a sequential data stream but as a dynamical system evolving on a curved surface in multi-dimensional space. The trajectory's geometric properties (curvature, complexity, folding) contain information about impending directional changes that single-dimension analysis cannot capture. When this manifold undergoes rapid topological deformation, price must respond with directional change—this is the mathematical basis for catastrophe detection.
Statistical normalization using z-score transformation (subtracting mean, dividing by standard deviation over a rolling window) ensures the coordinate system remains scale-invariant across different instruments and volatility regimes, allowing identical detection logic to function on forex, crypto, stocks, or indices without recalibration.
Catastrophe Score Calculation
The catastrophe detection formula implements a composite anomaly measurement combining multiple topology metrics: Catastrophe_Score = 0.45×Curvature_Percentile + 0.25×Complexity_Ratio + 0.20×Condition_Percentile + 0.10×Gradient_Percentile . Each component measures a distinct aspect of manifold distortion:
Curvature (κ) is computed using the discrete Laplacian operator: κ = √ , which measures how sharply the manifold surface bends at the current point. High curvature values indicate the surface is folding or developing a sharp corner—geometric precursors to catastrophic topology breaks. The Laplacian measures second derivatives (rate of change of rate of change), capturing acceleration in the trajectory's path through phase space.
Topological Complexity counts sign changes in the curvature field over the embedding window, measuring how chaotically the manifold twists and oscillates. A smooth, stable surface produces low complexity; a highly contorted, unstable surface produces high complexity. This metric detects when the geometric structure becomes informationally dense with multiple local extrema, suggesting an imminent topology simplification event (catastrophe).
Condition Number measures the Jacobian matrix's sensitivity: Condition = |Trace| / |Determinant|, where the Jacobian describes how small changes in price produce changes in the embedding coordinates. High condition numbers indicate numerical instability—points where the coordinate transformation becomes ill-conditioned, suggesting the manifold mapping is approaching a singularity.
Each metric is converted to percentile rank within a rolling window, then combined using weighted sum. The percentile transformation creates adaptive thresholds that automatically adjust to each instrument's characteristic topology without manual recalibration. The resulting 0-100% catastrophe score represents the current bar's position in the distribution of historical manifold distortion—values above the threshold (default 65%) indicate statistically extreme topology states where reversals become geometrically probable.
This multi-metric ensemble approach prevents false signals from isolated anomalies: all four geometric features must simultaneously indicate distortion for a high catastrophe score, ensuring only true manifold breaks trigger detection.
Hurst Exponent Regime Classification
The Hurst exponent calculation implements rescaled range (R/S) analysis to measure the fractal dimension of price returns: H = log(R/S) / log(n) , where R is the range of cumulative deviations from mean and S is the standard deviation. The resulting value classifies market behavior into three fractal regimes:
Trending Regime (H > 0.55) : Persistent price movement where future changes are positively correlated with past changes. The manifold exhibits directional momentum with smooth topology evolution. In this regime, catastrophe signals receive 1.2× confidence multiplier because manifold breaks in trending conditions produce high-magnitude directional changes.
Mean-Reverting Regime (H < 0.45) : Anti-persistent price movement where future changes tend to oppose past changes. The manifold exhibits oscillatory topology with frequent small-scale distortions. Catastrophe signals receive 0.8× confidence multiplier because reversal significance is diminished in choppy conditions where the manifold constantly folds at minor scales.
Random Walk Regime (H ≈ 0.50) : No statistical correlation in returns. The manifold evolution is geometrically neutral with moderate topology stability. Standard 1.0× confidence multiplier applies.
This adaptive weighting system solves a critical problem in reversal detection: the same geometric catastrophe has different trading implications depending on the fractal regime. A manifold fold in a strong trend suggests a significant reversal opportunity; the same fold in mean-reversion suggests a minor oscillation. The Hurst-based regime filter ensures detection sensitivity automatically adjusts to market character without requiring trader intervention.
The implementation uses logarithmic price returns rather than raw prices to ensure
stationarity, and applies the calculation over a configurable window (default 5 bars) to balance responsiveness with statistical validity. The Hurst value is then smoothed using exponential moving average to reduce noise while maintaining regime transition detection.
Multi-Layer Confirmation Architecture
The system implements five independent confirmation filters that must simultaneously validate
before any singularity signal generates:
1. Catastrophe Threshold : The composite anomaly score must exceed the configured threshold (default 0.65 on 0-1 scale), ensuring the manifold distortion is statistically extreme relative to recent history.
2. Pivot Structure Confirmation : Traditional swing high/low patterns (using ta.pivothigh and ta.pivotlow with configurable lookback) must form at the catastrophe bar. This ensures the geometric singularity coincides with observable price structure rather than occurring mid-swing where interpretation is ambiguous.
3. Swing Size Validation : The pivot magnitude must exceed a minimum threshold measured in ATR units (default 1.5× Average True Range). This filter prevents signals on insignificant price jiggles that lack meaningful reversal potential, ensuring only substantial swings with adequate risk/reward ratios generate signals.
4. Volume Confirmation : Current volume must exceed 1.3× the 20-period moving average, confirming genuine market participation rather than low-liquidity price noise. Manifold catastrophes without volume support often represent false topology breaks that don't translate to sustained directional change.
5. Regime Validity : The market must be classified as either trending (ADX > configured threshold, default 30) or volatile (ATR expansion > configured threshold, default 40% above 30-bar average), and must NOT be in choppy/ranging state. This critical filter prevents trading during geometrically unfavorable conditions where edge deteriorates.
All five conditions must evaluate true simultaneously for a signal to generate. This conjunction-based logic (AND not OR) dramatically reduces false positives while preserving true reversal detection. The architecture recognizes that geometric catastrophes occur frequently in noisy data, but only those catastrophes that align with confirming evidence across price structure, participation, and regime characteristics represent tradable opportunities.
A cooldown mechanism (default 8 bars between signals) prevents signal clustering at extended pivot zones where the manifold may undergo multiple small catastrophes during a single reversal process.
Direction Classification System
Unlike binary bull/bear systems, the indicator implements a voting mechanism combining four
directional indicators to classify each catastrophe:
Pivot Vote : +1 if pivot low, -1 if pivot high, 0 otherwise
Trend Vote : Based on slow frequency (55-period EMA) slope—+1 if rising, -1 if falling, 0 if flat
Flow Vote : Based on Y-gradient (momentum acceleration)—+1 if positive, -1 if negative, 0 if neutral
Mid-Band Vote : Based on price position relative to medium frequency (21-period EMA)—+1 if above, -1 if below, 0 if at
The total vote sum classifies the singularity: ≥2 votes = Bullish , ≤-2 votes = Bearish , -1 to +1 votes = Neutral (skip) . This majority-consensus approach ensures directional classification requires alignment across multiple timeframes and analysis dimensions rather than relying on a single indicator. Neutral signals (mixed voting) are displayed but should not be traded, as they represent geometric catastrophes without clear directional resolution.
Core Calculation Methodology
Embedding Coordinate Generation
Three normalized phase space coordinates are constructed from price data:
X-Dimension (Velocity Space):
price_velocity = close - close
X = (price_velocity - mean) / stdev over hurstWindow
Y-Dimension (Acceleration Space):
momentum = close - close
momentum_accel = momentum - momentum
Y = (momentum_accel - mean) / stdev over hurstWindow
Z-Dimension (Volume-Weighted Space):
vol_normalized = (volume - mean) / stdev over embedLength
roc = (close - close ) / close
Z = (roc × vol_normalized - mean) / stdev over hurstWindow
These coordinates define a point in 3D phase space for each bar. The trajectory connecting these points is the reconstructed manifold.
Gradient Field Calculation
First derivatives measure local manifold slope:
dX/dt = X - X
dY/dt = Y - Y
Gradient_Magnitude = √
The gradient direction indicates where the manifold is "pushing" price. Positive Y-gradient suggests upward topological pressure; negative Y-gradient suggests downward pressure.
Curvature Tensor Components
Second derivatives measure manifold bending using discrete Laplacian:
Laplacian_X = X - 2×X + X
Laplacian_Y = Y - 2×Y + Y
Laplacian_Magnitude = √
This is then normalized:
Curvature_Normalized = (Laplacian_Magnitude - mean) / stdev over embedLength
High normalized curvature (>1.5) indicates sharp manifold folding.
Complexity Accumulation
Sign changes in curvature field are counted:
Sign_Flip = 1 if sign(Curvature ) ≠ sign(Curvature ), else 0
Topological_Complexity = sum(Sign_Flip) over embedLength window
This measures oscillation frequency in the geometry. Complexity >5 indicates chaotic topology.
Condition Number Stability Analysis
Jacobian matrix sensitivity is approximated:
dX/dp = dX/dt / (price_change + epsilon)
dY/dp = dY/dt / (price_change + epsilon)
Jacobian_Determinant = (dX/dt × dY/dp) - (dX/dp × dY/dt)
Jacobian_Trace = dX/dt + dY/dp
Condition_Number = |Trace| / (|Determinant| + epsilon)
High condition numbers indicate numerical instability near singularities.
Catastrophe Score Assembly
Each metric is converted to percentile rank over embedLength window, then combined:
Curvature_Percentile = percentrank(abs(Curvature_Normalized), embedLength)
Gradient_Percentile = percentrank(Gradient_Magnitude, embedLength)
Condition_Percentile = percentrank(abs(Condition_Z_Score), embedLength)
Complexity_Ratio = clamp(Topological_Complexity / embedLength, 0, 1)
Final score:
Raw_Anomaly = 0.45×Curvature_P + 0.25×Complexity_R + 0.20×Condition_P + 0.10×Gradient_P
Catastrophe_Score = Raw_Anomaly × Hurst_Multiplier
Values are clamped to range.
Hurst Exponent Calculation
Rescaled range analysis on log returns:
Calculate log returns: r = log(close) - log(close )
Compute cumulative deviations from mean
Find range: R = max(cumulative_dev) - min(cumulative_dev)
Calculate standard deviation: S = stdev(r, hurstWindow)
Compute R/S ratio
Hurst = log(R/S) / log(hurstWindow)
Clamp to and smooth with 5-period EMA
Regime Classification Logic
Volatility Regime:
ATR_MA = SMA(ATR(14), 30)
Vol_Expansion = ATR / ATR_MA
Is_Volatile = Vol_Expansion > (1.0 + minVolExpansion)
Trend Regime (Corrected ADX):
Calculate directional movement (DM+, DM-)
Smooth with Wilder's RMA(14)
Compute DI+ and DI- as percentages
Calculate DX = |DI+ - DI-| / (DI+ + DI-) × 100
ADX = RMA(DX, 14)
Is_Trending = ADX > (trendStrength × 100)
Chop Detection:
Is_Chopping = NOT Is_Trending AND NOT Is_Volatile
Regime Validity:
Regime_Valid = (Is_Trending OR Is_Volatile) AND NOT Is_Chopping
Signal Generation Logic
For each bar:
Check if catastrophe score > topologyStrength threshold
Verify regime is valid
Confirm Hurst alignment (trending or mean-reverting with pivot)
Validate pivot quality (price extended outside spectral bands then re-entered)
Confirm volume/volatility participation
Check cooldown period has elapsed
If all true: compute directional vote
If vote ≥2: Bullish Singularity
If vote ≤-2: Bearish Singularity
If -1 to +1: Neutral (display but skip)
All conditions must be true for signal generation.
Visual System Architecture
Spectral Decomposition Layers
Three harmonic frequency bands visualize entropy state:
Layer 1 (Surface Frequency):
Center: EMA(8)
Width: ±0.3 × 0.5 × ATR
Transparency: 75% (most visible)
Represents fast oscillations
Layer 2 (Mid Frequency):
Center: EMA(21)
Width: ±0.5 × 0.5 × ATR
Transparency: 85%
Represents medium cycles
Layer 3 (Deep Frequency):
Center: EMA(55)
Width: ±0.7 × 0.5 × ATR
Transparency: 92% (most transparent)
Represents slow baseline
Convergence of layers indicates low entropy (stable topology). Divergence indicates high entropy (catastrophe building). This decomposition reveals how different frequency components of price movement interact—when all three align, the manifold is in equilibrium; when they separate, topology is unstable.
Energy Radiance Fields
Concentric boxes emanate from each singularity bar:
For each singularity, 5 layers are generated:
Layer n: bar_index ± (n × 1.5 bars), close ± (n × 0.4 × ATR)
Transparency gradient: inner 75% → outer 95%
Color matches signal direction
These fields visualize the "energy well" of the catastrophe—wider fields indicate stronger topology distortion. The exponential expansion creates a natural radiance effect.
Singularity Node Geometry
N-sided polygon (default hexagon) at each signal bar:
Vertices calculated using polar coordinates
Rotation angle: bar_index × 0.1 (creates animation)
Radius: ATR × singularity_strength × 2
Connects vertices with colored lines
The rotating geometric primitive marks the exact catastrophe bar with visual prominence.
Gradient Flow Field
Directional arrows display manifold slope:
Spawns every 3 bars when gradient_magnitude > 0.1
Symbol: "↗" if dY/dt > 0.1, "↘" if dY/dt < -0.1, "→" if neutral
Color: Bull/bear/neutral based on direction
Density limited to flowDensity parameter
Arrows cluster when gradient is strong, creating intuitive topology visualization.
Probability Projection Cones
Forward trajectory from each singularity:
Projects 10 bars forward
Direction based on vote classification
Center line: close + (direction × ATR × 3)
Uncertainty width: ATR × singularity_strength × 2
Dashed boundaries, solid center
These are mathematical projections based on current gradient, not price targets. They visualize expected manifold evolution if topology continues current trajectory.
Dashboard Metrics Explanation
The real-time control panel displays six core metrics plus regime status:
H (Hurst Exponent):
Value: Current Hurst (0-1 scale)
Label: TREND (>0.55), REVERT (<0.45), or RANDOM (0.45-0.55)
Icon: Direction arrow based on regime
Purpose: Shows fractal character—only trade when favorable
Σ (Catastrophe Score):
Value: Current composite anomaly (0-100%)
Bar gauge shows relative strength
Icon: ◆ if above threshold, ○ if below
Purpose: Primary signal strength indicator
κ (Curvature):
Value: Normalized Laplacian magnitude
Direction arrow shows sign
Color codes severity (green<0.8, yellow<1.5, red≥1.5)
Purpose: Shows manifold bending intensity
⟳ (Topology Complexity):
Value: Count of sign flips in curvature
Icon: ◆ if >3, ○ otherwise
Color codes chaos level
Purpose: Indicates geometric instability
V (Volatility Expansion):
Value: ATR expansion percentage above 30-bar average
Icon: ● if volatile, ○ otherwise
Purpose: Confirms energy present for reversal
T (Trend Strength):
Value: ADX reading (0-100)
Icon: ● if trending, ○ otherwise
Purpose: Shows directional bias strength
R (Regime):
Label: EXPLOSIVE / TREND / VOLATILE / CHOP / NEUTRAL
Icon: ✓ if valid, ✗ if invalid
Purpose: Go/no-go filter for trading
STATE (Bottom Display):
Shows: "◆ BULL SINGULARITY" (green), "◆ BEAR SINGULARITY" (red), "◆ WEAK/NEUTRAL" (orange), or "— Monitoring —" (gray)
Purpose: Current signal status at a glance
How to Use This Indicator
Initial Setup and Configuration
Apply the indicator to your chart with default settings as a starting point. The default parameters (21-bar embedding, 5-bar Hurst window, 2.5σ singularity threshold, 0.65 topology confirmation) are optimized for balanced detection across most instruments and timeframes. For very fast markets (scalping crypto, 1-5min charts), consider reducing embedding depth to 13-15 bars and Hurst window to 3 bars for more responsive detection. For slower markets (swing trading stocks, 4H-Daily charts), increase embedding depth to 34-55 bars and Hurst window to 8-10 bars for more stable topology measurement.
Enable the dashboard (top right recommended) to monitor real-time metrics. The control panel is your primary decision interface—glancing at the dashboard should instantly communicate whether conditions favor trading and what the current topology state is. Position and size the dashboard to remain visible but not obscure price action.
Enable regime filtering (strongly recommended) to prevent trading during choppy/ranging conditions where geometric edge deteriorates. This single setting can dramatically improve overall performance by eliminating low-probability environments.
Reading Dashboard Metrics for Trade Readiness
Before considering any trade, verify the dashboard shows favorable conditions:
Hurst (H) Check:
The Hurst Exponent reading is your first filter. Only consider trades when H > 0.50 . Ideal conditions show H > 0.60 with "TREND" label—this indicates persistent directional price movement where manifold catastrophes produce significant reversals. When H < 0.45 (REVERT label), the market is mean-reverting and catastrophes represent minor oscillations rather than substantial pivots. Do not trade in mean-reverting regimes unless you're explicitly using range-bound strategies (which this indicator is not optimized for). When H ≈ 0.50 (RANDOM label), edge is neutral—acceptable but not ideal.
Catastrophe (Σ) Monitoring:
Watch the Σ percentage build over time. Readings consistently below 50% indicate stable topology with no imminent reversals. When Σ rises above 60-65%, manifold distortion is approaching critical levels. Signals only fire when Σ exceeds the configured threshold (default 65%), so this metric pre-warns you of potential upcoming catastrophes. High-conviction setups show Σ > 75%.
Regime (R) Validation:
The regime classification must read TREND, VOLATILE, or EXPLOSIVE—never trade when it reads CHOP or NEUTRAL. The checkmark (✓) must be present in the regime cell for trading conditions to be valid. If you see an X (✗), skip all signals until regime improves. This filter alone eliminates most losing trades by avoiding geometrically unfavorable environments.
Combined High-Conviction Profile:
The strongest trading opportunities show simultaneously:
H > 0.60 (strong trending regime)
Σ > 75% (extreme topology distortion)
R = EXPLOSIVE or TREND with ✓
κ (Curvature) > 1.5 (sharp manifold fold)
⟳ (Complexity) > 4 (chaotic geometry)
V (Volatility) showing elevated ATR expansion
When all metrics align in this configuration, the manifold is undergoing severe distortion in a favorable fractal regime—these represent maximum-conviction reversal opportunities.
Signal Interpretation and Entry Logic
Bullish Singularity (▲ Green Triangle Below Bar):
This marker appears when the system detects a manifold catastrophe at a price low with bullish directional consensus. All five confirmation filters have aligned: topology score exceeded threshold, pivot low structure formed, swing size was significant, volume/volatility confirmed participation, and regime was valid. The green color indicates the directional vote totaled +2 or higher (majority bullish).
Trading Approach: Consider long entry on the bar immediately following the signal (bar after the triangle). The singularity bar itself is where the geometric catastrophe occurred—entering after allows you to see if price confirms the reversal. Place stop loss below the singularity bar's low (with buffer of 0.5-1.0 ATR for volatility). Initial target can be the previous swing high, or use the probability cone projection as a guide (though not a guarantee). Monitor the dashboard STATE—if it flips to "◆ BEAR SINGULARITY" or Hurst drops significantly, consider exiting even if target not reached.
Bearish Singularity (▼ Red Triangle Above Bar):
This marker appears when the system detects a manifold catastrophe at a price high with bearish directional consensus. Same five-filter confirmation process as bullish signals. The red color indicates directional vote totaled -2 or lower (majority bearish).
Trading Approach: Consider short entry on the bar following the signal. Place stop loss above the singularity bar's high (with buffer). Target previous swing low or use cone projection as reference. Exit if opposite signal fires or Hurst deteriorates.
Neutral Signal (● Orange Circle at Price Level):
This marker indicates the catastrophe detection system identified a topology break that passed catastrophe threshold and regime filters, but the directional voting system produced a mixed result (vote between -1 and +1). This means the four directional components (pivot, trend, flow, mid-band) are not in agreement about which way the reversal should resolve.
Trading Approach: Skip these signals. Neutral markers are displayed for analytical completeness but should not be traded. They represent geometric catastrophes without clear directional resolution—essentially, the manifold is breaking but the direction of the break is ambiguous. Trading neutral signals dramatically increases false signal rate. Only trade green (bullish) or red (bearish) singularities.
Visual Confirmation Using Spectral Layers
The three colored ribbons (spectral decomposition layers) provide entropy visualization that helps confirm signal quality:
Divergent Layers (High Entropy State):
When the three frequency bands (fast 8-period, medium 21-period, slow 55-period) are separated with significant gaps between them, the manifold is in high entropy state—different frequency components of price movement are pulling in different directions. This geometric tension precedes catastrophes. Strong signals often occur when layers are divergent before the signal, then begin reconverging immediately after.
Convergent Layers (Low Entropy State):
When all three ribbons are tightly clustered or overlapping, the manifold is in equilibrium—all frequency components agree. This stable geometry makes catastrophe detection more reliable because topology breaks clearly stand out against the baseline stability. If you see layers converge, then a singularity fires, then layers diverge, this pattern suggests a genuine regime transition.
Signal Quality Assessment:
High-quality singularity signals should show:
Divergent layers (high entropy) in the 5-10 bars before signal
Singularity bar occurs when price has extended outside at least one of the spectral bands (shows pivot extended beyond equilibrium)
Close of singularity bar re-enters the spectral band zone (shows mean reversion starting)
Layers begin reconverging in 3-5 bars after signal (shows new equilibrium forming)
This pattern visually confirms the geometric narrative: manifold became unstable (divergence), reached critical distortion (extended outside equilibrium), broke catastrophically (singularity), and is now stabilizing in new direction (reconvergence).
Using Energy Fields for Trade Management
The concentric glowing boxes around each singularity visualize the topology distortion
magnitude:
Wide Energy Fields (5+ Layers Visible):
Large radiance indicates strong catastrophe with high manifold curvature. These represent significant topology breaks and typically precede larger price moves. Wide fields justify wider profit targets and longer hold times. The outer edge of the largest box can serve as a dynamic support/resistance zone—price often respects these geometric boundaries.
Narrow Energy Fields (2-3 Layers):
Smaller radiance indicates moderate catastrophe. While still valid signals (all filters passed), expect smaller follow-through. Use tighter profit targets and be prepared for quicker exit if momentum doesn't develop. These are valid but lower-conviction trades.
Field Interaction Zones:
When energy fields from consecutive signals overlap or touch, this indicates a prolonged topology distortion region—often corresponds to consolidation zones or complex reversal patterns (head-and-shoulders, double tops/bottoms). Be more cautious in these areas as the manifold is undergoing extended restructuring rather than a clean catastrophe.
Probability Cone Projections
The dashed cone extending forward from each singularity is a mathematical projection, not a
price target:
Cone Direction:
The center line direction (upward for bullish, downward for bearish, flat for neutral) shows the expected trajectory based on current manifold gradient and singularity direction. This is where the topology suggests price "should" go if the catastrophe completes normally.
Cone Width:
The uncertainty band (upper and lower dashed boundaries) represents the range of outcomes given current volatility (ATR-based). Wider cones indicate higher uncertainty—expect more price volatility even if direction is correct. Narrower cones suggest more constrained movement.
Price-Cone Interaction:
Price following near the center line = catastrophe resolving as expected, geometric projection accurate
Price breaking above upper cone = stronger-than-expected reversal, consider holding for larger targets
Price breaking below lower cone (for bullish signal) = catastrophe failing, manifold may be re-folding in opposite direction, consider exit
Price oscillating within cone = normal reversal process, hold position
The 10-bar projection length means cones show expected behavior over the next ~10 bars. Don't confuse this with longer-term price targets.
Gradient Flow Field Interpretation
The directional arrows (↗, ↘, →) scattered across the chart show the manifold's Y-gradient (vertical acceleration dimension):
Upward Arrows (↗):
Positive Y-gradient indicates the momentum acceleration dimension is pushing upward—the manifold topology has upward "slope" at this location. Clusters of upward arrows suggest bullish topological pressure building. These often appear before bullish singularities fire.
Downward Arrows (↘):
Negative Y-gradient indicates downward topological pressure. Clusters precede bearish singularities.
Horizontal Arrows (→):
Neutral gradient indicates balanced topology with no strong directional pressure.
Using Flow Field:
The arrows provide real-time topology state information even between singularity signals. If you're in a long position from a bullish singularity and begin seeing increasing downward arrows appearing, this suggests manifold gradient is shifting—consider tightening stops. Conversely, if arrows remain upward or neutral, topology supports continuation.
Don't confuse arrow direction with immediate price direction—arrows show geometric slope, not price prediction. They're confirmatory context, not entry signals themselves.
Parameter Optimization for Your Trading Style
For Scalping / Fast Trading (1m-15m charts):
Embedding Depth: 13-15 bars (faster topology reconstruction)
Hurst Window: 3 bars (responsive fractal detection)
Singularity Threshold: 2.0-2.3σ (more sensitive)
Topology Confirmation: 0.55-0.60 (lower barrier)
Min Swing Size: 0.8-1.2 ATR (accepts smaller moves)
Pivot Lookback: 3-4 bars (quick pivot detection)
This configuration increases signal frequency for active trading but requires diligent monitoring as false signal rate increases. Use tighter stops.
For Day Trading / Standard Approach (15m-4H charts):
Keep default settings (21 embed, 5 Hurst, 2.5σ, 0.65 confirmation, 1.5 ATR, 5 pivot)
These are balanced for quality over quantity
Best win rate and risk/reward ratio
Recommended for most traders
For Swing Trading / Position Trading (4H-Daily charts):
Embedding Depth: 34-55 bars (stable long-term topology)
Hurst Window: 8-10 bars (smooth fractal measurement)
Singularity Threshold: 3.0-3.5σ (only extreme catastrophes)
Topology Confirmation: 0.75-0.85 (high conviction only)
Min Swing Size: 2.5-4.0 ATR (major moves only)
Pivot Lookback: 8-13 bars (confirmed swings)
This configuration produces infrequent but highly reliable signals suitable for position sizing and longer hold times.
Volatility Adaptation:
In extremely volatile instruments (crypto, penny stocks), increase Min Volatility Expansion to 0.6-0.8 to avoid over-signaling during "always volatile" conditions. In stable instruments (major forex pairs, blue-chip stocks), decrease to 0.3 to allow signals during moderate volatility spikes.
Trend vs Range Preference:
If you prefer trading only strong trends, increase Min Trend Strength to 0.5-0.6 (ADX > 50-60). If you're comfortable with volatility-based trading in weaker trends, decrease to 0.2 (ADX > 20). The default 0.3 balances both approaches.
Complete Trading Workflow Example
Step 1 - Pre-Session Setup:
Load chart with MSE indicator. Check dashboard position is visible. Verify regime filter is enabled. Review recent signals to gauge current instrument behavior.
Step 2 - Market Assessment:
Observe dashboard Hurst reading. If H < 0.45 (mean-reverting), consider skipping this session or using other strategies. If H > 0.50, proceed. Check regime shows TREND, VOLATILE, or EXPLOSIVE with checkmark—if CHOP, wait for regime shift alert.
Step 3 - Signal Wait:
Monitor catastrophe score (Σ). Watch for it climbing above 60%. Observe spectral layers—look for divergence building. If you see curvature (κ) rising above 1.0 and complexity (⟳) increasing, catastrophe is building. Do not anticipate—wait for the actual signal marker.
Step 4 - Signal Recognition:
▲ Bullish or ▼ Bearish triangle appears at a bar. Dashboard STATE changes to "◆ BULL/BEAR SINGULARITY". Energy field appears around the signal bar. Check signal quality:
Was Σ > 70% at signal? (Higher quality)
Are energy fields wide? (Stronger catastrophe)
Did layers diverge before and reconverge after? (Clean break)
Is Hurst still > 0.55? (Good regime)
Step 5 - Entry Decision:
If signal is green/red (not orange neutral), all confirmations look strong, and no immediate contradicting factors appear, prepare entry on next bar open. Wait for confirmation bar to form—ideally it should close in the signal direction (bullish signal → bar closes higher, bearish signal → bar closes lower).
Step 6 - Position Entry:
Enter at open or shortly after open of bar following signal bar. Set stop loss: for bullish signals, place stop at singularity_bar_low - (0.75 × ATR); for bearish signals, place stop at singularity_bar_high + (0.75 × ATR). The buffer accommodates volatility while protecting against catastrophe failure.
Step 7 - Trade Management:
Monitor dashboard continuously:
If Hurst drops below 0.45, consider reducing position
If opposite singularity fires, exit immediately (manifold has re-folded)
If catastrophe score drops below 40% and stays there, topology has stabilized—consider partial profit taking
Watch gradient flow arrows—if they shift to opposite direction persistently, tighten stops
Step 8 - Profit Taking:
Use probability cone as a guide—if price reaches outer cone boundary, consider taking partial profits. If price follows center line cleanly, hold for larger target. Traditional technical targets work well: previous swing high/low, round numbers, Fibonacci extensions. Don't expect precision—manifold projections give direction and magnitude estimates, not exact prices.
Step 9 - Exit:
Exit on: (a) opposite signal appears, (b) dashboard shows regime became invalid (checkmark changes to X), (c) technical target reached, (d) Hurst deteriorates significantly, (e) stop loss hit, or (f) time-based exit if using session limits. Never hold through opposite singularity signals—the manifold has broken in the other direction and your trade thesis is invalidated.
Step 10 - Post-Trade Review:
After exit, review: Did the probability cone projection align with actual price movement? Were the energy fields proportional to move size? Did spectral layers show expected reconvergence? Use these observations to calibrate your interpretation of signal quality over time.
Best Performance Conditions
This topology-based approach performs optimally in specific market environments:
Favorable Conditions:
Well-Developed Swing Structure: Markets with clear rhythm of advances and declines where pivots form at regular intervals. The manifold reconstruction depends on swing formation, so instruments that trend in clear waves work best. Stocks, major forex pairs during active sessions, and established crypto assets typically exhibit this characteristic.
Sufficient Volatility for Topology Development: The embedding process requires meaningful price movement to construct multi-dimensional coordinates. Extremely quiet markets (tight consolidations, holiday trading, after-hours) lack the volatility needed for manifold differentiation. Look for ATR expansion above average—when volatility is present, geometry becomes meaningful.
Trending with Periodic Reversals: The ideal environment is not pure trend (which rarely reverses) nor pure range (which reverses constantly at small scale), but rather trending behavior punctuated by occasional significant counter-trend reversals. This creates the catastrophe conditions the system is designed to detect: manifold building directional momentum, then undergoing sharp topology break at extremes.
Liquid Instruments Where EMAs Reflect True Flow: The spectral layers and frequency decomposition require that moving averages genuinely represent market consensus. Thinly traded instruments with sporadic orders don't create smooth manifold topology. Prefer instruments with consistent volume where EMA calculations reflect actual capital flow rather than random tick sequences.
Challenging Conditions:
Extremely Choppy / Whipsaw Markets: When price oscillates rapidly with no directional persistence (Hurst < 0.40), the manifold undergoes constant micro-catastrophes that don't translate to tradable reversals. The regime filter helps avoid these, but awareness is important. If you see multiple neutral signals clustering with no follow-through, market is too chaotic for this approach.
Very Low Volatility Consolidation: Tight ranges with ATR below average cause the embedding coordinates to compress into a small region of phase space, reducing geometric differentiation. The manifold becomes nearly flat, and catastrophe detection loses sensitivity. The regime filter's volatility component addresses this, but manually avoiding dead markets improves results.
Gap-Heavy Instruments: Stocks that gap frequently (opening outside previous close) create discontinuities in the manifold trajectory. The embedding process assumes continuous evolution, so gaps introduce artifacts. Most gaps don't invalidate the approach, but instruments with daily gaps >2% regularly may show degraded performance. Consider using higher timeframes (4H, Daily) where gaps are less proportionally significant.
Parabolic Moves / Blowoff Tops: When price enters an exponential acceleration phase (vertical rally or crash), the manifold evolves too rapidly for the standard embedding window to track. Catastrophe detection may lag or produce false signals mid-move. These conditions are rare but identifiable by Hurst > 0.75 combined with ATR expansion >2.0× average. If detected, consider sitting out or using very tight stops as geometry is in extreme distortion.
The system adapts by reducing signal frequency in poor conditions—if you notice long periods with no signals, the topology likely lacks the geometric structure needed for reliable catastrophe detection. This is a feature, not a bug: it prevents forced trading during unfavorable environments.
Theoretical Justification for Approach
Why Manifold Embedding?
Traditional technical analysis treats price as a one-dimensional time series: current price is predicted from past prices in sequential order. This approach ignores the structure of price dynamics—the relationships between velocity, acceleration, and participation that govern how price actually evolves.
Dynamical systems theory (from physics and mathematics) provides an alternative framework: treat price as a state variable in a multi-dimensional phase space. In this view, each market condition corresponds to a point in N-dimensional space, and market evolution is a trajectory through this space. The geometry of this space (its topology) constrains what trajectories are possible.
Manifold embedding reconstructs this hidden geometric structure from observable price data. By creating coordinates from velocity, momentum acceleration, and volume-weighted returns, we map price evolution onto a 3D surface. This surface—the manifold—reveals geometric relationships that aren't visible in price charts alone.
The mathematical theorem underlying this approach (Takens' Embedding Theorem from dynamical systems theory) proves that for deterministic or weakly stochastic systems, a state space reconstruction from time-delayed observations of a single variable captures the essential dynamics of the full system. We apply this principle: even though we only observe price, the embedded coordinates (derivatives of price) reconstruct the underlying dynamical structure.
Why Catastrophe Theory?
Catastrophe theory, developed by mathematician René Thom (Fields Medal 1958), describes how continuous systems can undergo sudden discontinuous changes when control parameters reach critical values. A classic example: gradually increasing force on a beam causes smooth bending, then sudden catastrophic buckling. The beam's geometry reaches a critical curvature where topology must break.
Markets exhibit analogous behavior: gradual price changes build tension in the manifold topology until critical distortion is reached, then abrupt directional change occurs (reversal). Catastrophes aren't random—they're mathematically necessary when geometric constraints are violated.
The indicator detects these geometric precursors: high curvature (manifold bending sharply), high complexity (topology oscillating chaotically), high condition number (coordinate mapping becoming singular). These metrics quantify how close the manifold is to a catastrophic fold. When all simultaneously reach extreme values, topology break is imminent.
This provides a logical foundation for reversal detection that doesn't rely on pattern recognition or historical correlation. We're measuring geometric properties that mathematically must change when systems reach critical states. This is why the approach works across different instruments and timeframes—the underlying geometry is universal.
Why Hurst Exponent?
Markets exhibit fractal behavior: patterns at different time scales show statistical self-similarity. The Hurst exponent quantifies this fractal structure by measuring long-range dependence in returns.
Critically for trading, Hurst determines whether recent price movement predicts future direction (H > 0.5) or predicts the opposite (H < 0.5). This is regime detection: trending vs mean-reverting behavior.
The same manifold catastrophe has different trading implications depending on regime. In trending regime (high Hurst), catastrophes represent significant reversal opportunities because the manifold has been building directional momentum that suddenly breaks. In mean-reverting regime (low Hurst), catastrophes represent minor oscillations because the manifold constantly folds at small scales.
By weighting catastrophe signals based on Hurst, the system adapts detection sensitivity to the current fractal regime. This is a form of meta-analysis: not just detecting geometric breaks, but evaluating whether those breaks are meaningful in the current fractal context.
Why Multi-Layer Confirmation?
Geometric anomalies occur frequently in noisy market data. Not every high-curvature point represents a tradable reversal—many are artifacts of microstructure noise, order flow imbalances, or low-liquidity ticks.
The five-filter confirmation system (catastrophe threshold, pivot structure, swing size, volume, regime) addresses this by requiring geometric anomalies to align with observable market evidence. This conjunction-based logic implements the principle: extraordinary claims require extraordinary evidence .
A manifold catastrophe (extraordinary geometric event) alone is not sufficient. We additionally require: price formed a pivot (visible structure), swing was significant (adequate magnitude), volume confirmed participation (capital backed the move), and regime was favorable (trending or volatile, not chopping). Only when all five dimensions agree do we have sufficient evidence that the geometric anomaly represents a genuine reversal opportunity rather than noise.
This multi-dimensional approach is analogous to medical diagnosis: no single test is conclusive, but when multiple independent tests all suggest the same condition, confidence increases dramatically. Each filter removes a different category of false signals, and their combination creates a robust detection system.
The result is a signal set with dramatically improved reliability compared to any single metric alone. This is the power of ensemble methods applied to geometric analysis.
Important Disclaimers
This indicator applies mathematical topology and catastrophe theory to multi-dimensional price space reconstruction. It identifies geometric conditions where manifold curvature, topological complexity, and coordinate singularities suggest potential reversal zones based on phase space analysis. It should not be used as a standalone trading system.
The embedding coordinates, catastrophe scores, and Hurst calculations are deterministic mathematical formulas applied to historical price data. These measurements describe current and recent geometric relationships in the reconstructed manifold but do not predict future price movements. Past geometric patterns and singularity markers do not guarantee future market behavior will follow similar topology evolution.
The manifold reconstruction assumes certain mathematical properties (sufficient embedding dimension, quasi-stationarity, continuous dynamics) that may not hold in all market conditions. Gaps, flash crashes, circuit breakers, news events, and other discontinuities can violate these assumptions. The system attempts to filter problematic conditions through regime classification, but cannot eliminate all edge cases.
The spectral decomposition, energy fields, and probability cones are visualization aids that represent mathematical constructs, not price predictions. The probability cone projects current gradient forward assuming topology continues current trajectory—this is a mathematical "if-then" statement, not a forecast. Market topology can and does change unexpectedly.
All trading involves substantial risk. The singularity markers represent analytical conditions where geometric mathematics align with threshold criteria, not certainty of directional change. Use appropriate risk management for every trade: position sizing based on account risk tolerance (typically 1-2% maximum risk per trade), stop losses placed beyond recent structure plus volatility buffer, and never risk capital needed for living expenses.
The confirmation filters (pivot, swing size, volume, regime) are designed to reduce false signals but cannot eliminate them entirely. Markets can produce geometric anomalies that pass all filters yet fail to develop into sustained reversals. This is inherent to probabilistic systems operating on noisy real-world data.
No indicator can guarantee profitable trades or eliminate losses. The catastrophe detection provides an analytical framework for identifying potential reversal conditions, but actual trading outcomes depend on numerous factors including execution, slippage, spreads, position sizing, risk management, psychological discipline, and market conditions that may change after signal generation.
Use this tool as one component of a comprehensive trading plan that includes multiple forms of analysis, proper risk management, emotional discipline, and realistic expectations about win rates and drawdowns. Combine catastrophe signals with additional confirmation methods such as support/resistance analysis, volume patterns, multi-timeframe alignment, and broader market context.
The spacing filter, cooldown mechanism, and regime validation are designed to reduce noise and over-signaling, but market conditions can change rapidly and render any analytical signal invalid. Always use stop losses and never risk capital you cannot afford to lose. Past performance of detection accuracy does not guarantee future results.
Technical Implementation Notes
All calculations execute on closed bars only—signals and metric values do not repaint after bar close. The indicator does not use any lookahead bias in its calculations. However, the pivot detection mechanism (ta.pivothigh and ta.pivotlow) inherently identifies pivots with a lag equal to the lookback parameter, meaning the actual pivot occurred at bar but is recognized at bar . This is standard behavior for pivot functions and is not repainting—once recognized, the pivot bar never changes.
The normalization system (z-score transformation over rolling windows) requires approximately 30-50 bars of historical data to establish stable statistics. Values in the first 30-50 bars after adding the indicator may show instability as the rolling means and standard deviations converge. Allow adequate warmup period before relying on signals.
The spectral layer arrays, energy field boxes, gradient flow labels, and node geometry lines are subject to TradingView drawing object limits (500 lines, 500 boxes, 500 labels per indicator as specified in settings). The system implements automatic cleanup by deleting oldest objects when limits approach, but on very long charts with many signals, some historical visual elements may be removed to stay within limits. This does not affect signal generation or dashboard metrics—only historical visual artifacts.
Dashboard and visual rendering update only on the last bar to minimize computational overhead. The catastrophe detection logic executes on every bar, but table cells and drawing objects refresh conditionally to optimize performance. If experiencing chart lag, reduce visual complexity: disable spectral layers, energy fields, or flow field to improve rendering speed. Core signal detection continues to function with all visual elements disabled.
The Hurst calculation uses logarithmic returns rather than raw price to ensure stationarity, and implements clipping to range to handle edge cases where R/S analysis produces invalid values (which can occur during extended periods of identical prices or numerical overflow). The 5-period EMA smoothing reduces noise while maintaining responsiveness to regime transitions.
The condition number calculation adds epsilon (1e-10) to denominators to prevent division by zero when Jacobian determinant approaches zero—which is precisely the singularity condition we're detecting. This numerical stability measure ensures the indicator doesn't crash when detecting the very phenomena it's designed to identify.
The indicator has been tested across multiple timeframes (5-minute through daily) and multiple asset classes (forex majors, stock indices, individual equities, cryptocurrencies, commodities, futures). It functions identically across all instruments due to the adaptive normalization approach and percentage-based metrics. No instrument-specific code or parameter sets are required.
The color scheme system implements seven preset themes plus custom mode. Color assignments are applied globally and affect all visual elements simultaneously. The opacity calculation system multiplies component-specific transparency with master opacity to create hierarchical control—adjusting master opacity affects all visuals proportionally while maintaining their relative transparency relationships.
All alert conditions trigger only on bar close to prevent false alerts from intrabar fluctuations. The regime transition alerts (VALID/INVALID) are particularly useful for knowing when trading edge appears or disappears, allowing traders to adjust activity levels accordingly.
— Dskyz, Trade with insight. Trade with anticipation.
