Combo Backtest 123 Reversal and Accelerator Oscillator (AC) This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Second strategy
The Accelerator Oscillator has been developed by Bill Williams
as the development of the Awesome Oscillator. It represents the
difference between the Awesome Oscillator and the 5-period moving
average, and as such it shows the speed of change of the Awesome
Oscillator, which can be useful to find trend reversals before the
Awesome Oscillator does.
WARNING:
- For purpose educate only
- This script to change bars colors.
Cerca negli script per "the strat"
Combo Backtest 123 Reversal and Absolute Price Oscillator (APO) This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Secon strategy
The Absolute Price Oscillator displays the difference between two exponential
moving averages of a security's price and is expressed as an absolute value.
How this indicator works
APO crossing above zero is considered bullish, while crossing below zero is bearish.
A positive indicator value indicates an upward movement, while negative readings
signal a downward trend.
Divergences form when a new high or low in price is not confirmed by the Absolute Price
Oscillator (APO). A bullish divergence forms when price make a lower low, but the APO
forms a higher low. This indicates less downward momentum that could foreshadow a bullish
reversal. A bearish divergence forms when price makes a higher high, but the APO forms a
lower high. This shows less upward momentum that could foreshadow a bearish reversal.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Strategies 123 Reversal and 3-Bar-Reversal-Pattern This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Secon strategy
This startegy based on 3-day pattern reversal described in "Are Three-Bar
Patterns Reliable For Stocks" article by Thomas Bulkowski, presented in
January,2000 issue of Stocks&Commodities magazine.
That pattern conforms to the following rules:
- It uses daily prices, not intraday or weekly prices;
- The middle day of the three-day pattern has the lowest low of the three days, with no ties allowed;
- The last day must have a close above the prior day's high, with no ties allowed;
- Each day must have a nonzero trading range.
WARNING:
- For purpose educate only
- This script to change bars colors.
Combo Backtest 123 Reversal and 2/20 EMA This is combo strategies for get
a cumulative signal. Result signal will return 1 if two strategies
is long, -1 if all strategies is short and 0 if signals of strategies is not equal.
First strategy
This System was created from the Book "How I Tripled My Money In The
Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies.
The strategy buys at market, if close price is higher than the previous close
during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50.
The strategy sells at market, if close price is lower than the previous close price
during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50.
Secon strategy
This indicator plots 2/20 exponential moving average. For the Mov
Avg X 2/20 Indicator, the EMA bar will be painted when the Alert criteria is met.
Please, use it only for learning or paper trading. Do not for real trading.
WARNING:
- For purpose educate only
- This script to change bars colors.
XPloRR MA-Trailing-Stop StrategyXPloRR MA-Trailing-Stop Strategy
Long term MA-Trailing-Stop strategy with Adjustable Signal Strength to beat Buy&Hold strategy
None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy.
Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade.
My buy strategy is triggered by the fast buy EMA (blue) crossing over the slow buy SMA curve (orange) and the fast buy EMA has a certain up strength.
My sell strategy is triggered by either one of these conditions:
the EMA(6) of the close value is crossing under the trailing stop value (green) or
the fast sell EMA (navy) is crossing under the slow sell SMA curve (red) and the fast sell EMA has a certain down strength.
The trailing stop value (green) is set to a multiple of the ATR(15) value.
ATR(15) is the SMA(15) value of the difference between the high and low values.
The scripts shows a lot of graphical information:
The close value is shown in light-green. When the close value is lower then the buy value, the close value is shown in light-red. This way it is possible to evaluate the virtual losses during the trade.
the trailing stop value is shown in dark-green. When the sell value is lower then the buy value, the last color of the trade will be red (best viewed when zoomed)(in the example, there are 2 trades that end in gain and 2 in loss (red line at end))
the EMA and SMA values for both buy and sell signals are shown as a line
the buy and sell(close) signals are labeled in blue
How to use this strategy?
Every stock has it's own "DNA", so first thing to do is tune the right parameters to get the best strategy values voor EMA , SMA, Strength for both buy and sell and the Trailing Stop (#ATR).
Look in the strategy tester overview to optimize the values Percent Profitable and Net Profit (using the strategy settings icon, you can increase/decrease the parameters)
Then keep using these parameters for future buy/sell signals only for that particular stock.
Do the same for other stocks.
Important : optimizing these parameters is no guarantee for future winning trades!
Here are the parameters:
Fast EMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 10-20)
Slow SMA Buy: buy trigger when Fast EMA Buy crosses over the Slow SMA Buy value (use values between 30-100)
Minimum Buy Strength: minimum upward trend value of the Fast SMA Buy value (directional coefficient)(use values between 0-120)
Fast EMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 10-20)
Slow SMA Sell: sell trigger when Fast EMA Sell crosses under the Slow SMA Sell value (use values between 30-100)
Minimum Sell Strength: minimum downward trend value of the Fast SMA Sell value (directional coefficient)(use values between 0-120)
Trailing Stop (#ATR): the trailing stop value as a multiple of the ATR(15) value (use values between 2-20)
Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now) compared to the Buy&Hold Strategy(=do nothing):
BEKB(Bekaert): EMA-Buy=12, SMA-Buy=44, Strength-Buy=65, EMA-Sell=12, SMA-Sell=55, Strength-Sell=120, Stop#ATR=20
NetProfit: 996%, #Trades: 6, %Profitable: 83%, Buy&HoldProfit: 78%
BAR(Barco): EMA-Buy=16, SMA-Buy=80, Strength-Buy=44, EMA-Sell=12, SMA-Sell=45, Strength-Sell=82, Stop#ATR=9
NetProfit: 385%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 55%
AAPL(Apple): EMA-Buy=12, SMA-Buy=45, Strength-Buy=40, EMA-Sell=19, SMA-Sell=45, Strength-Sell=106, Stop#ATR=8
NetProfit: 6900%, #Trades: 7, %Profitable: 71%, Buy&HoldProfit: 2938%
TNET(Telenet): EMA-Buy=12, SMA-Buy=45, Strength-Buy=27, EMA-Sell=19, SMA-Sell=45, Strength-Sell=70, Stop#ATR=14
NetProfit: 129%, #Trade
XPloRR MA-Buy ATR-Trailing-Stop Long Term Strategy Beating B&HXPloRR MA-Buy ATR-MA-Trailing-Stop Strategy
Long term MA Trailing Stop strategy to beat Buy&Hold strategy
None of the strategies that I tested can beat the long term Buy&Hold strategy. That's the reason why I wrote this strategy.
Purpose: beat Buy&Hold strategy with around 10 trades. 100% capitalize sold trade into new trade.
My buy strategy is triggered by the EMA(blue) crossing over the SMA curve(orange).
My sell strategy is triggered by another EMA(lime) of the close value crossing the trailing stop(green) value.
The trailing stop value(green) is set to a multiple of the ATR(15) value.
ATR(15) is the SMA(15) value of the difference between high and low values.
Every stock has it's own "DNA", so first thing to do is find the right parameters to get the best strategy values voor EMA, SMA and Trailing Stop.
Then keep using these parameter for future buy/sell signals only for that particular stock.
Do the same for other stocks.
Here are the parameters:
Exponential MA: buy trigger when crossing over the SMA value (use values between 11-50)
Simple MA: buy trigger when EMA crosses over the SMA value (use values between 20 and 200)
Stop EMA: sell trigger when Stop EMA of close value crosses under the trailing stop value (use values between 8 and 16)
Trailing Stop #ATR: defines the trailing stop value as a multiple of the ATR(15) value
Example parameters for different stocks (Start capital: 1000, Order=100% of equity, Period 1/1/2005 to now):
BAR(Barco): EMA=11, SMA=82, StopEMA=12, Stop#ATR=9
Buy&HoldProfit: 45.82%, NetProfit: 294.7%, #Trades:8, %Profit:62.5%, ProfitFactor: 12.539
AAPL(Apple): EMA=12, SMA=45, StopEMA=12, Stop#ATR=6
Buy&HoldProfit: 2925.86%, NetProfit: 4035.92%, #Trades:10, %Profit:60%, ProfitFactor: 6.36
BEKB(Bekaert): EMA=12, SMA=42, StopEMA=12, Stop#ATR=7
Buy&HoldProfit: 81.11%, NetProfit: 521.37%, #Trades:10, %Profit:60%, ProfitFactor: 2.617
SOLB(Solvay): EMA=12, SMA=63, StopEMA=11, Stop#ATR=8
Buy&HoldProfit: 43.61%, NetProfit: 151.4%, #Trades:8, %Profit:75%, ProfitFactor: 3.794
PHIA(Philips): EMA=11, SMA=80, StopEMA=8, Stop#ATR=10
Buy&HoldProfit: 56.79%, NetProfit: 198.46%, #Trades:6, %Profit:83.33%, ProfitFactor: 23.07
I am very curious to see the parameters for your stocks and please make suggestions to improve this strategy.
Intraday Momentum StrategyExplanation of the StrategyIndicators:Fast and Slow EMA: A crossover of the 9-period EMA over the 21-period EMA signals a bullish trend (long entry), while a crossunder signals a bearish trend (short entry).
RSI: Ensures entries are not in overbought (RSI > 70) or oversold (RSI < 30) conditions to avoid reversals.
VWAP: Acts as a dynamic support/resistance. Long entries require the price to be above VWAP, and short entries require it to be below.
Trading Session:The strategy only trades during a user-defined session (e.g., 9:30 AM to 3:45 PM, typical for US markets).
All positions are closed at the session end to avoid overnight risk.
Risk Management:Stop Loss: 1% below/above the entry price for long/short positions.
Take Profit: 2% above/below the entry price for long/short positions.
These can be adjusted via inputs for optimization.
Position Sizing:Fixed lot size of 1 for simplicity. Adjust based on your account size during backtesting.
PRO Investing - Quant AlphaCentauri D |XLF|PRO Investing - Quant AlphaCentauri D |XLF|
1. Summary and Core Concept
This is a quantitative backtesting strategy engineered specifically for the Financial Select Sector SPDR Fund (XLF) on the Daily (1D) timeframe. The name "AlphaCentauri" reflects its goal: to seek alpha by identifying statistically significant opportunities through rigorous time series analysis.
The strategy's core principle is to move beyond conventional technical indicators and instead analyze the underlying structure and character of price data. It is designed to methodically identify conditions that have historically preceded sustained directional trends in the financial sector.
2. The Analytical Process: How It Works
This strategy employs a multi-stage quantitative process to filter for high-probability setups. It is a "mashup" of statistical concepts applied to price action.
Structural Pattern Recognition: The engine's primary function is to analyze the historical price series of XLF to identify specific, recurring structural patterns. It examines price geometry and cyclical behavior to find formations that often act as the foundation for a new, emerging trend.
Signal Execution: A signal to enter a trade is only generated when the findings from both the structural analysis and the validation stages are in agreement. This disciplined, multi-layered approach ensures the strategy remains flat during periods of high uncertainty and only engages when its quantitative criteria are fully met.
3. How to Use This Strategy
Timeframe: This strategy has been designed, tested, and optimized exclusively for the Daily (1D) timeframe on the XLF ticker. Its logic is not intended for other timeframes or assets and may produce unreliable results if used differently.
On-Chart Signals: The strategy's operation is transparent. It plots all historical buy and sell entries, along with their corresponding exits, directly on the chart for easy performance review and analysis.
4. Risk Management: The Strategy's Foundation
This strategy is built upon a foundation of strict, non-negotiable risk management, which is reflected in its code and backtesting parameters. This design complies with TradingView's guidelines for publishing realistic and responsible strategies.
Dynamic Stop-Loss and Position Sizing: A stop-loss is dynamically calculated for each trade based on recent market volatility. The strategy then automatically adjusts the position size for that trade to target a defined risk percentage. In cases of extreme market volatility, the maximum potential loss on a single trade may approach, but is designed not to exceed, 5% of total account equity. Under normal market conditions, the risk for most trades will be below this maximum threshold.
Realistic Backtesting Parameters:
Initial Capital: The backtest defaults to an initial capital of $100,000.
Commission: A realistic fee of $5.00 per order is included to simulate broker costs.
5. Disclaimer
This strategy is an educational tool provided for informational and research purposes. It is not financial advice. All trading carries a high level of risk, and past performance is not a guarantee of future results. You are solely responsible for your own trading decisions and risk management. Always conduct your own due diligence before deploying any trading strategy in a live account.
Strategy Chameleon [theUltimator5]Have you ever looked at an indicator and wondered to yourself "Is this indicator actually profitable?" Well now you can test it out for yourself with the Strategy Chameleon!
Strategy Chameleon is a versatile, signal-agnostic trading strategy designed to adapt to any external indicator or trading system. Like a chameleon changes colors to match its environment, this strategy adapts to match any buy/sell signals you provide, making it the ultimate backtesting and automation tool for traders who want to test multiple strategies without rewriting code.
🎯 Key Features
1) Connects ANY external indicator's buy/sell signals
Works with RSI, MACD, moving averages, custom indicators, or any Pine Script output
Simply connect your indicator's signal output to the strategy inputs
2) Multiple Stop Loss Types:
Percentage-based stops
ATR (Average True Range) dynamic stops
Fixed point stops
3) Advanced Trailing Stop System:
Percentage trailing
ATR-based trailing
Fixed point trailing
4) Flexible Take Profit Options:
Risk:Reward ratio targeting
Percentage-based profits
ATR-based profits
Fixed point profits
5) Trading Direction Control
Long Only - Bull market strategies
Short Only - Bear market strategies
Both - Full market strategies
6) Time-Based Filtering
Optional trading session restrictions
Customize active trading hours
Perfect for day trading strategies
📈 How It Works
Signal Detection: The strategy monitors your connected buy/sell signals
Entry Logic: Executes trades when signals trigger during valid time periods
Risk Management: Automatically applies your chosen stop loss and take profit levels
Trailing System: Dynamically adjusts stops to lock in profits
Performance Tracking: Real-time statistics table showing win rate and performance
⚙️ Setup Instructions
0) Add indicator you want to test, then add the Strategy to your chart
Connect Your Signals:
imgur.com
Go to strategy settings → Signal Sources
1) Set "Buy Signal Source" to your indicator's buy output
2) Set "Sell Signal Source" to your indicator's sell output
3) Choose table position - This simply changes the table location on the screen
4) Set trading direction preference - Buy only? Sell only? Both directions?
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5) Set your preferred stop loss type and level
You can set the stop loss to be either percentage based or ATR and fully configurable.
6) Enable trailing stops if desired
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7) Configure take profit settings
8) Toggle time filter to only consider specific time windows or trading sessions.
🚀 Use Cases
Test various indicators to determine feasibility and/or profitability.
Compare different signal sources quickly
Validate trading ideas with consistent risk management
Portfolio Management
Apply uniform risk management across different strategies
Standardize stop loss and take profit rules
Monitor performance consistently
Automation Ready
Built-in alert conditions for automated trading
Compatible with trading bots and webhooks
Easy integration with external systems
⚠️ Important Notes
This strategy requires external signals to function
Default settings use 10% of equity per trade
Pyramiding is disabled (one position at a time)
Strategy calculates on bar close, not every tick
🔗 Integration Examples
Works perfectly with:
RSI strategies (connect RSI > 70 for sells, RSI < 30 for buys)
Moving average crossovers
MACD signal line crosses
Bollinger Band strategies
Custom oscillators and indicators
Multi-timeframe strategies
📋 Default Settings
Position Size: 10% of equity
Stop Loss: 2% percentage-based
Trailing Stop: 1.5% percentage-based (enabled)
Take Profit: Disabled (optional)
Trade Direction: Both long and short
Time Filter: Disabled
Vortex Hunter X - Strategy | SUI Signal (Binance)⚙️ Vortex Hunter X - Strategy | SUI Signal (Binance)
🚨 To test the strategy and get more guidance, contact me via my communication channels! 🚨
👉 For more details, please refer to the contact sections in my profile.
This strategy is designed for executing trades on the SUI/USDT pair in the Futures market on Binance and on the TradingView platform. However, trades can be executed on any preferred exchange.
💡 This strategy is perfectly optimized and configured, and requires no additional settings!
All parameters and settings are pre-optimized, and you just need to follow the instructions to run the strategy.
For each position:
Target (TP): Exactly 4% profit
Stop Loss (SL): Exactly 2% loss
These values are fixed in the code (not dynamic).
🔎 Signal Accuracy | No Repainting
Signals are completely non-repainting; once a signal is issued, it does not change.
Backtesting and live execution on TradingView are exactly the same, demonstrating the high reliability of the strategy.
🔁 Note about Replay Mode
In Replay mode on TradingView, there may be discrepancies compared to live execution or backtesting.
These differences arise due to how data is processed in Replay mode and the limitation of some filters accessing past data.
✅ However, this is NOT a sign of repainting;
Signals in live mode and backtesting are issued exactly the same without any difference.
🔄 Important Note: Correct Script Loading
Due to complex logic and multi-layer filters, sometimes browser cache may prevent the script from fully loading.
✅ To ensure accurate performance:
Before first run and every few days:
Clear your browser cache
Or use Ctrl + F5 for a full refresh.
⚠️ Important Usage Notes
This strategy is designed ONLY for the following conditions:
Symbol: SUIUSDT
Exchange: Binance
Market: Futures
Timeframe: 3 minutes (3m)
Chart Type: Candlestick (Candles)
To receive valid signals, be sure to run it only on the SUIUSDT chart (Futures | 3m | Binance | Standard Candles) on TradingView.
⚠️ Critical and Important Note:
Signals are valid ONLY on the above chart and settings on TradingView.
However, you can execute real trades on any preferred exchange (Binance, Bybit, OKX, etc.)!
⚡️ Signal generation must be done only on TradingView with exact settings,
but order execution and trading have no restrictions on the exchange used.
⚠️ Running the strategy on wrong symbol or timeframe will lead to incorrect signals.
✅ Strategy execution and signal reception must be done exactly with the above settings on TradingView, but trades can be executed on different exchanges.
ℹ️ Strategy Naming Convention
The currency name is clearly stated in each strategy name:
Vortex Hunter X - Strategy | SUI Signal (Binance) → for SUI
Vortex Hunter X - Strategy | PEPE Signal (Binance) → for PEPE
📌 Currently, this strategy is active for the following two pairs:
SUIUSDT (Futures – Binance)
PEPEUSDT (Futures – Binance)
🪙 By purchasing one subscription, you will have access to both versions.
🚀 New currencies will be added soon and subscribers will have access to future versions.
✅ Settings Summary
🔧 Required settings on TradingView (by user):
⏱️ Timeframe: 3 minutes
📈 Chart Type: Candlestick (Candles)
🧪 Market: Futures – Symbol: SUIUSDT – Exchange: Binance
⚠️ Final and Important Note:
Due to the use of complex logic and multi-layer filters in this strategy, sometimes the number of signals, performance stats, or other details may not display correctly. These changes may be caused by issues like browser cache or incomplete page loading, which prevent accurate data display.
✅ If you notice such an issue, please follow these steps:
Remove the strategy from the chart
Completely close the browser
Reopen the browser and go back to TradingView
Refresh the page fully using Ctrl + F5
Apply the strategy to the chart again
This method ensures all data and filters load correctly and full information is displayed.
❗️ Note: This issue is NOT related to repainting. Signals remain fixed and unchanged; sometimes they may display incorrectly due to cache or incomplete loading.
Multi-Pair Matrix📊 Multi-Pair Matrix — Strategy Overview
This invite-only strategy works across five major crypto pairs: BTC, ETH, XRP, DOT, and SOL. It combines multiple confirmation signals and risk-management tools into one unified script.
🔍 Core Logic
The strategy uses a combination of proven technical tools:
Price Action Patterns: Breakouts, rejections, and reversal zones
EMA Crossovers: Short- and long-term trend confirmation
Stochastic Oscillator: Identifies exhaustion and entry opportunities
MACD Histogram: Filters entries by confirming directional momentum
Dynamic SL/TP Logic: Each trade has an independent stop-loss and take-profit based on market conditions
Delayed Entry System: Prevents immediate re-entry after closing in the opposite direction
Smart Trailing Stop-Loss: Adjusts as price moves to secure gains
⚙️ Capital Allocation & Pyramiding
The strategy uses strategy.percent_of_equity = 100, but only ~10% margin is used per position
This leaves headroom for controlled pyramiding without risking full account exposure
🔁 Recommended Pyramiding Settings per Pair
Pair -Pyramiding
BTC - 6
ETH - 6
XRP - 8
DOT - 5
SOL - 7
🧪 Backtest Conditions
Commission: 0.1% per trade
Slippage: 3 ticks
Capital: realistic margin use per trade
Pair displayed in this publication: XRP
This pair is shown in the current backtest example due to platform limitations
The remaining pairs follow the same internal logic and backtest methodology, but are not visible in a single report
⚠️ Usage Instructions
To use this script for real-time alerts:
Open the Inputs tab and enable “Live Trading Mode”
Choose your desired pair from the dropdown — this will automatically apply the correct settings
The script is designed for lower timeframe markets and is optimized for high-activity, volatile periods
All logic is contained in a single script as required — no suite publishing or duplicated variations
Vortex Hunter X - Strategy (3-Min TF) | PEPE Signal (Binance)⚙️ Vortex Hunter X - Strategy (3-Min TF) | PEPE Signal (Binance)
This strategy is designed for analyzing the PEPE/USDT pair on Binance Futures within the TradingView platform, and can be used to execute trades on any exchange of your choice.
Each position has a fixed 4% profit target and a fixed 2% stop loss. These parameters are hard-coded and do not change dynamically. The risk-to-reward ratio is fixed at 1:2.
🔎 Non-Repainting Signals and Consistency Between Backtest and Live Trading
The signals generated by this strategy are completely non-repainting, meaning once a signal is issued, it will not be altered or modified later.
Backtesting results and live trading performance on TradingView are exactly consistent, demonstrating the high reliability of the strategy.
🔁 Note About Replay Mode on TradingView
When running the strategy in Replay mode on TradingView (historical playback of the chart), you may notice some differences compared to live or backtest results.
These differences arise due to the way data is processed in Replay mode and delays in how certain filters access past information.
✅ However, it is important to understand that these differences do not indicate any repainting of signals. In live and backtest modes, signals are generated exactly according to the strategy’s logic without any changes.
🔄 Important Recommendation for Proper Script Loading
Due to the use of complex filters, multi-stage processing, and sensitive conditions in the signal logic, sometimes the browser cache may cause the script not to load fully or precisely, or some components may load with delays.
This can lead to signals not displaying correctly or minor issues in the strategy’s performance.
✅ Therefore, it is strongly recommended to clear your browser cache or press Ctrl + F5 for a full refresh on the TradingView chart page before the first use and periodically (e.g., every few days).
This ensures the script loads freshly and completely from TradingView servers, enabling accurate and smooth strategy operation.
⚠️ Important Usage Notes:
🔸 This strategy is specifically designed and optimized only for the following conditions:
Symbol: PEPEUSDT
Exchange: BINANCE
Market: Futures
Timeframe: 3 minutes (3m)
🔸 For accurate signals, please ensure the strategy runs only on the PEPE/USDT Futures chart on Binance with a 3-minute timeframe in TradingView.
🔸 ⚠️ Note: For actual trading execution, you may use any exchange (e.g., Binance, Bybit, OKX, etc.), but analysis and strategy operation must be performed strictly within TradingView with the exact above settings.
Using the strategy on incorrect symbols, timeframes, or markets may result in invalid signals.
ℹ️ Strategy Naming:
Each strategy’s name clearly indicates the asset it is configured for.
For example:
Vortex Hunter X - Strategy (3-Min TF) | PEPE Signal (Binance) for PEPE
Vortex Hunter X - Strategy (3-Min TF) | SUI Signal (Binance) for SUI
Currently, the strategy is configured and optimized for only these two pairs:
PEPEUSDT (Binance Futures)
SUIUSDT (Binance Futures)
📌 Purchasing a single subscription grants you access to both strategies (PEPE and SUI).
📈 More assets will be added to this strategy in the future, and subscribers will gain access to new versions automatically.
✅ Summary of Settings:
🎯 Take Profit (TP): 4%
⛔ Stop Loss (SL): 2%
📊 Risk-to-Reward Ratio: 1:2
⏱️ Timeframe: 3 minutes
🧪 Target Market: PEPE Futures on Binance
📩 For access or support, contact:
Break and Retest High Probability StrategyWhat does the script Do:
Script uses Break and Retest strategy on Key Levels like PMH, PDH, PMH, PML and ORB levels. Based on the strength of the candle at these key levels a position is taken and based on Dynamic stop loss, we scale out of the position at key levels. Scale out can also happen based on the QQQ trend.
How it does it:
First the script identifies No Trade Zone - which is higher of PMH and PDH for Highest position of No Trade Zone, and lower of PML and PDL. Any trades within this doesnt take any Trade entries.
Entries are taken in only Regular Trading Hours.
Candle strength is constantly tracked for break out these levels and then wait for retest levels based on Volatality on that day with ATR levels. If it fails to come back to retest - it is ignored else at retest levels strength of the bar is tracked. Scaling out can be done based on various Input parameters given in the strategy. VWAP and 9 EMA is also tracked for taking an entry or not.
How to use it:
Make sure to use various parameters within Inputs like Candle Strength at vwap, QQQ confluence to tweak and see what works best for the time frame and stock.
In the Multi Time frame construct - if you are on 5min time frame the candle stregth can be tracked in lower time frame which can be 1, 2, 3 min etc. This is also configurable within the Inputs.
Make sure to use the levels and values displayed in the table to see real time data.
Also, You can just have the Long entry, Short Entry and Plot variables selected in Style section to declutter the chart. Feel free to reuse the chart
what makes it original.
Strategy Parameters
• Is representative of real world trading conditions.
Break and Retest at key levels while following various confluence set ups makes it completely real world and battle tested indicator. All the parameters used within Inputs and Style are completely known Market variables.
• Is compatible with the markets their strategy is written for.
This is best for doing scalping where momentum and volatality is the king.
• Produces realistic results.
Like any strategy nothing is 100% guaranteed. But the key is to monitor the Profit factor and exit at right positions even if it means lesser number of trades.
This strategy is tested against lot of Tech stocks like nvidia, tesla, amazon against QQQ confluence.
. to help traders interpret the results they publish with their strategy,
Please feel free to tweak the parameters to tweak the strategy and see what works best for the stock you are placing this indicator on.
I primarily take the default parameters of this strategy to do scalping. The Multitime frame restest ( which goes to lower timeframe to check the strength of bars - which is again configurable by Fixed Retest bars and Retest Time Frame. I would recommend you to use Enable candle pattern filter to further refine the trades to be high probability.
This is a high probability set up - so please dont expect many trades from each stock. The strategy only gets triggered when it sees valid signal as per parameters set on the strategy.
Buy Dip Multiple Positions🎯 Objective
This strategy aims to capture aggressive dip-buying opportunities during volume-confirmed price reversals in short term downtrending markets. It is optimized for multi-entry precision, adaptive stop management, and real-time trade monitoring.
It allows traders to execute multiple long entries and dynamically trail stops to maximize gains while capping risk. Designed with modular inputs, this strategy is ideal for intraday momentum scalping and swing trading alike.
🔧 How It Operates
The strategy triggers buy entries when three conditions align:
Reversal Candle: Current close < prior low × 0.998
Volume Confirmation: Current volume exceeds average of prior 2 bars × 1.2
Price Surge Threshold: Current close below user-defined % of close from N bars ago
Once a reversal candle is confirmed, the strategy:
Calculates position size based on user-defined risk parameters
Allows up to a max number of simultaneous trades
Trailing Stop kicks in 2 bars after entry, climbing by a user-defined % each bar
Exit occurs when price hits either the trailing stop or target price
🛠️ Inputs
Users can customize all major aspects of the strategy:
Max Simultaneous Trades: Default 20
Trailing Stop Increase per Bar (%): Default 1%
Initial Stop (% of Reversal Low): Default 85%
Target Price (% Above Reversal Low): Default 60%
Price Surge Threshold (% of Past Close): Default 89%
Surge Lookback Bars: Default 14
Show Active Trade Dot: Toggle to display green trade status dot
📊 Visual Overlays
The chart displays the following:
Marker Description
🟢 Green Dot Active trade (toggleable)
🔴 Red Dot Max trades reached
📈 Trailing Stop Applied internally but not plotted (can be added)
📊 Metrics Plots of win rate, winning/losing trade counts
📎 Notes
Strategy uses strategy.cash allocation logic
Entry size adapts to account equity and risk per trade
All parameters are accessible via the settings panel
Built entirely in Pine Script v5
This strategy balances flexibility and precision, giving traders control over entry timing, capital allocation, and stop behavior. Ideal for those looking to automate dip-buy setups with tactical overlays and visual alerts.
WaveSurfer StrategyThis is a quant trading strategy that can be used to automate your trading. The first thing you will see in the settings popup is blocks where text can be entered. You can enter your automated trading messages here that will be sent to your exchange or third party application. Check with them to identify exactly how the buy and sell text should be configured. Put this {{strategy.order.alert_message}} in the alert message box and it will pull the buy and sell text from these settings boxes.
This trading strategy is designed to trade cryptocurrencies on the 1 hour timeframe. Other timeframes can be used but this is where I have found success. It uses a fairly complex algorithm to determine Long Buy and Sell opportunities. Each assets settings need to be optimized using back testing due to differences in volatility, volume, and risk. I provide optimized settings for the coins I trade here . As with any trading strategy, no amount of gains can be guaranteed. There is always risk of taking losses. Do not trade more than you are willing to lose.
The backbone of the strategy uses Bollinger Bands to measure the market trend. Bollinger Band Width(BBW) moves in waves. Waves over 0.2 are considered strong movements. Bollinger Band Percent(BB%) is used to determine wave direction, Bullish or Bearish. The strategy calculates BBW Slope and it is critical in determining status of the Bullish or Bearish wave. For example, if a strong Bullish wave is above 0.2 and slope is positive, this means to hold as the wave continues to accumulate gains. When slope turns negative, it is a signal that the wave is ending and opens more opportunities for the strategy to sell. Under certain conditions the waves can be considered neutral, especially when BBW is under 0.2.
BBW waves are given a score -5 through 5. These scores are used throughout the strategy to determine which Buy and Sell limits to use. Here is what the scores mean:
0 = Neutral, 1->3 = Beginning of Bullish wave, 4 = Strong Bullish wave, 5 = End of Bullish wave
0 = Neutral, -1->-3 = Beginning of Bearish wave, -4 = Strong Bearish wave, -5 = End of Bearish wave
During each of these trends the strategy offers different buy and sell opportunities that can be configured in settings. Hull moving averages are used for determining Buy/Sell crossovers and the Phase of the trade. The Phase of a trade if telling the strategy which Sell limits to use to determine when to sell. Phase 1 represents Bearish trend sell limits, Phase 2 represents Neutral trend sell limits, and Phase 3 represents Bullish trend sell limits. For example, if a Buy is triggered during a Bear trend, the trade will start in Phase 1. As the price moves up to Neutral within the Bollinger Bands it will move to Phase 2 and sell limits will move up. If price continues to rise into Bullish BBW trend it will change to Phase 3 and use Sell limits that will allow price to grow while the wave remains bullish.
Bearish Buys: Bearish Buys are designed to buy at a low peak. It uses Bollinger Band Mid line slope(Generally below -0.3), BB% very low(Generally below 0.0), and the trigger is RSI crossing up around 25-30. There are three different types of Bear Buys but they are all slight variations of this same technique. Again, all these settings need to be optimized using back testing. A more volatile coin will drop lower and with more intensity than a more stable coin. All Bear Buys will start in phase 1 with tight stop loss limits to protect against further drops. If prices does not recover quickly and moves sideways the sell limit will adjust(typically moving up) with each low pivot(assuming it is still above the original low that triggered the buy). There are also emergency sell options that can be configured.
Neutral Buys: Neutral Buys trigger when the Hull Moving Average crosses above the Bollinger Bands mid-point, generally want to use around 0.6. There is an option to buy only when BBW is below 0.2, meaning weak trend/Neutral. Neutral Buys will start with Phase 3 Sell limits.
Bullish Buys: There are a few different Bullish Buy options but these can be risky due to false breakouts which can result in higher losses if price reverses and drops quickly. All Bullish Buys start with Phase 3 Sell limits. One type of Bullish Buy is Level breakout. The recent high is always calculated using the pivot function and is displayed on the screen with the thick red dotted line. If you are using the Level buy option it will buy when the price breaks above this high level for consecutive candles. But the best bullish Buy option is Cycle Buy Late. This will buy when cycle crosses above 2, into Bull trend 3 or 4.
These examples shows the gold sell line adjust during the pivot and the Phase changes. It maintains decent gain even as price fails to move up in Phase 3. The thin yellow line is a Cycle Sell option that sells during cycles 5(Wave ending) and 0(Neutral). All these limits can be adjusted in settings:
This example shows Phase 3 sell limits allowing price to grow. The thin yellow line is an additional sell line that is higher than standard sell in this example but only triggers when Cycle is 5(wave ending) or 0(Wave Neutral):
Divergence Strategy [Trendoscope®]🎲 Overview
The Divergence Strategy is a sophisticated TradingView strategy that enhances the Divergence Screener by adding automated trade signal generation, risk management, and trade visualization. It leverages the screener’s robust divergence detection to identify bullish, bearish, regular, and hidden divergences, then executes trades with precise entry, stop-loss, and take-profit levels. Designed for traders seeking automated trading solutions, this strategy offers customizable trade parameters and visual feedback to optimize performance across various markets and timeframes.
For core divergence detection features, including oscillator options, trend detection methods, zigzag pivot analysis, and visualization, refer to the Divergence Screener documentation. This description focuses on the strategy-specific enhancements for automated trading and risk management.
🎲 Strategy Features
🎯Automated Trade Signal Generation
Trade Direction Control : Restrict trades to long-only or short-only to align with market bias or strategy goals, preventing conflicting orders.
Divergence Type Selection : Choose to trade regular divergences (bullish/bearish), hidden divergences, or both, targeting reversals or trend continuations.
Entry Type Options :
Cautious : Enters conservatively at pivot points and exits quickly to minimize risk exposure.
Confident : Enters aggressively at the latest price and holds longer to capture larger moves.
Mixed : Combines conservative entries with delayed exits for a balanced approach.
Market vs. Stop Orders: Opt for market orders for instant execution or stop orders for precise price entry.
🎯 Enhanced Risk Management
Risk/Reward Ratio : Define a risk-reward ratio (default: 2.0) to set profit targets relative to stop-loss levels, ensuring consistent trade sizing.
Bracket Orders : Trades include entry, stop-loss, and take-profit levels calculated from divergence pivot points, tailored to the entry type and risk-reward settings.
Stop-Loss Placement : Stops are strategically set (e.g., at recent pivot or last price point) based on entry type, balancing risk and trade validity.
Order Cancellation : Optionally cancel pending orders when a divergence is broken (e.g., price moves past the pivot in the wrong direction), reducing invalid trades. This feature is toggleable for flexibility.
🎯 Trade Visualization
Target and Stop Boxes : Displays take-profit (lime) and stop-loss (orange) levels as boxes on the price chart, extending 10 bars forward for clear visibility.
Dynamic Trade Updates : Trade visualizations are added, updated, or removed as trades are executed, canceled, or invalidated, ensuring accurate feedback.
Overlay Integration : Trade levels overlay the price chart, complementing the screener’s oscillator-based divergence lines and labels.
🎯 Strategy Default Configuration
Capital and Sizing : Set initial capital (default: $1,000,000) and position size (default: 20% of equity) for realistic backtesting.
Pyramiding : Allows up to 4 concurrent trades, enabling multiple divergence-based entries in trending markets.
Commission and Margin : Accounts for commission (default: 0.01%) and margin (100% for long/short) to reflect trading costs.
Performance Optimization : Processes up to 5,000 bars dynamically, balancing historical analysis and real-time execution.
🎲 Inputs and Configuration
🎯Trade Settings
Direction : Select Long or Short (default: Long).
Divergence : Trade Regular, Hidden, or Both divergence types (default: Both).
Entry/Exit Type : Choose Cautious, Confident, or Mixed (default: Cautious).
Risk/Reward : Set the risk-reward ratio for profit targets (default: 2.0).
Use Market Order : Enable market orders for immediate entry (default: false, uses limit orders).
Cancel On Break : Cancel pending orders when divergence is broken (default: true).
🎯Inherited Settings
The strategy inherits all inputs from the Divergence Screener, including:
Oscillator Settings : Oscillator type (e.g., RSI, CCI), length, and external oscillator option.
Trend Settings : Trend detection method (Zigzag, MA Difference, External), MA type, and length.
Zigzag Settings : Zigzag length (fixed repaint = true).
🎲 Entry/Exit Types for Divergence Scenarios
The Divergence Strategy offers three Entry/Exit Type options—Cautious, Confident, and Mixed—which determine how trades are entered and exited based on divergence pivot points. This section explains how these settings apply to different divergence scenarios, with placeholders for screenshots to illustrate each case.
The divergence pattern forms after 3 pivots. The stop and entry levels are formed on one of these levels based on Entry/Exit types.
🎯Bullish Divergence (Reversal)
A bullish divergence occurs when price forms a lower low, but the oscillator forms a higher low, signaling a potential upward reversal.
💎 Cautious:
Entry : At the pivot high point for a conservative entry.
Exit : Stop-loss at the last pivot point (previous low that is higher than the current pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Entry : At the last pivot low, (previous low which is higher than the current pivot low) for an aggressive entry.
Exit : Stop-loss at recent pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
💎Mixed:
Entry : At the pivot high point (conservative).
Exit : Stop-loss at the recent pivot point that has resulted in lower low (lazy exit). Canceled if price breaks below the pivot.
Behavior : Balances entry caution with extended holding for trend continuation.
🎯Bearish Divergence (Reversal)
A bearish divergence occurs when price forms a higher high, but the oscillator forms a lower high, indicating a potential downward reversal.
💎Cautious:
Entry : At the pivot low point (lower high) for a conservative short entry.
Exit : Stop-loss at the previous pivot high point (previous high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident:
Entry : At the last price point (previous high) for an aggressive short entry.
Exit : Stop-loss at the pivot point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Enters early to maximize trend continuation, holding longer.
💎Mixed:
Entry : At the previous piot high point (conservative).
Exit : Stop-loss at the last price point (delayed exit). Canceled if price breaks above the pivot.
Behavior : Combines conservative entry with extended holding for downtrend gains.
🎯Bullish Hidden Divergence (Continuation)
A bullish hidden divergence occurs when price forms a higher low, but the oscillator forms a lower low, suggesting uptrend continuation. In case of Hidden bullish divergence, b]Entry is always on the previous pivot high (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the recent pivot low point (higher than previous pivot low); take-profit at risk-reward ratio. Canceled if price breaks below the pivot (if Cancel On Break is enabled).
Behavior : Enters after confirmation and exits quickly to limit downside risk.
💎Confident:
Exit : Stop-loss at previous pivot low, which is the lowest point; take-profit at risk-reward ratio. Canceled if price breaks below the pivot. (lazy exit)
Behavior : Enters early to capture trend continuation, holding longer for gains.
🎯Bearish Hidden Divergence (Continuation)
A bearish hidden divergence occurs when price forms a lower high, but the oscillator forms a higher high, suggesting downtrend continuation. In case of Hidden Bearish divergence, b]Entry is always on the previous pivot low (unless it is a market order)
💎Cautious:
Exit : Stop-loss at the latest pivot high point (which is a lower high); take-profit at risk-reward ratio. Canceled if price breaks above the pivot (if Cancel On Break is enabled).
Behavior : Enters conservatively and exits quickly to minimize risk.
💎Confident/Mixed:
Exit : Stop-loss at the previous pivot high point; take-profit at risk-reward ratio. Canceled if price breaks above the pivot.
Behavior : Uses the late exit point to hold longer.
🎲 Usage Instructions
🎯Add to Chart:
Add the Divergence Strategy to your TradingView chart.
The oscillator and divergence signals appear in a separate pane, with trade levels (target/stop boxes) overlaid on the price chart.
🎯Configure Settings:
Adjust trade settings (direction, divergence type, entry type, risk-reward, market orders, cancel on break).
Modify inherited Divergence Screener settings (oscillator, trend method, zigzag length) as needed.
Enable/disable alerts for divergence notifications.
🎯Interpret Signals:
Long Trades: Triggered on bullish or bullish hidden divergences (if allowed), shown with green/lime lines and labels.
Short Trades: Triggered on bearish or bearish hidden divergences (if allowed), shown with red/orange lines and labels.
Monitor lime (target) and orange (stop) boxes for trade levels.
Review strategy performance metrics (e.g., profit/loss, win rate) in the strategy tester.
🎯Backtest and Optimize:
Use TradingView’s strategy tester to evaluate performance on historical data.
Fine-tune risk-reward, entry type, position sizing, and cancellation settings to suit your market and timeframe.
For questions, suggestions, or support, contact Trendoscope via TradingView or official support channels. Stay tuned for updates and enhancements to the Divergence Strategy!
Strategi FVG 09:31 (Pro)FVG 09:31 Strategy (Pro)
In short, this is an automated trading strategy (bot) for TradingView designed to execute buy or sell orders based on a Fair Value Gap (FVG) pattern. The strategy is highly specific, as it only triggers on the 1-minute timeframe and looks for an FVG that forms precisely at 09:32 AM New York time.
Main Purpose of the Strategy
The primary goal of this script is to identify and capitalize on short-term price imbalances, known as Fair Value Gaps (FVGs). It operates during a specific, high-volatility window right after the U.S. stock market opens, often referred to by traders as the "Silver Bullet" session. By automating the detection and execution, it aims to trade these fleeting opportunities with precision.
How the Strategy Works
The strategy follows a clear, step-by-step logical flow on your chart.
1. Time & Timeframe Restriction
1-Minute Timeframe: The strategy is hard-coded to work only on the 1-minute (1m) chart. A warning label will appear on your chart if you apply it to any other timeframe.
Specific Time Window: The core logic activates only between 09:32 and 09:33 AM New York time. It searches for an FVG pattern formed by the three candles from 09:29, 09:30, and 09:31, with the pattern confirmation happening on the close of the 09:31 candle.
2. Fair Value Gap (FVG) Detection
An FVG is a three-candle pattern that signals a price imbalance.
Bullish FVG (Potential Buy): Occurs when the low of the first candle is higher than the high of the third candle. The space between these two prices is the FVG zone.
Bearish FVG (Potential Sell): Occurs when the high of the first candle is lower than the low of the third candle. The space between these two prices is the FVG zone.
If this pattern is detected at the target time, the strategy draws a colored box on the chart to visualize the FVG zone (aqua for bullish, fuchsia for bearish).
3. Entry Logic
The strategy provides two user-selectable methods for entering a trade:
Retracement (Immediate Entry): The strategy will open a position with a market order as soon as the price retraces back into the identified FVG zone.
For a Bullish FVG, a Long (buy) position is opened when the price drops to touch the upper boundary of the FVG.
For a Bearish FVG, a Short (sell) position is opened when the price rises to touch the lower boundary of the FVG.
Limit Order (Pending Entry): The strategy places a pending limit order at the edge of the FVG zone.
For a Bullish FVG, a Buy Limit order is placed at the upper boundary of the FVG.
For a Bearish FVG, a Sell Limit order is placed at the lower boundary of the FVG.
Order Expiration: If the limit order is not filled within a specified number of candles (default is 15), it is automatically canceled to avoid chasing a stale setup.
4. Exit Logic
Once a position is active, the strategy automatically manages the exit by setting a Take Profit (TP) and Stop Loss (SL) level. You can choose between two types:
Ticks (Fixed Points): You define a fixed profit target and loss limit in ticks (the smallest price movement). For example, a 200-tick TP and a 100-tick SL.
Last Swing (Dynamic Levels): The TP and SL are set dynamically based on the most recent swing high or swing low.
For a Long position: Take Profit is set at the last swing high; Stop Loss is at the last swing low.
For a Short position: Take Profit is set at the last swing low; Stop Loss is at the last swing high.
5. Daily Management
At the start of each new trading day, the script performs a reset. All variables, including any FVG data from the previous day, are cleared. This ensures the strategy only acts on fresh signals from the current day and cancels any pending orders from the day before.
Explanation of Settings (Inputs)
Here is what each user-configurable setting does:
Entry Type: Choose your preferred entry method: Retracement or Limit Order.
Order Expiration (Candles): Applies only to the Limit Order type. Sets how many candles an unfilled order will remain active before being canceled.
Stop Loss Type: Choose Ticks for a fixed-distance stop loss or Last Swing for a dynamic level.
Take Profit Type: Choose Ticks for a fixed-distance profit target or Last Swing for a dynamic level.
Pivot Lookback (SL/TP Swing): Defines how many candles the script looks back to identify the most recent swing high/low for the Last Swing SL/TP type.
Contract Size: The quantity or lot size for each trade.
Take Profit (in Ticks): The profit target distance if using the Ticks type.
Stop Loss (in Ticks): The maximum loss distance if using the Ticks type.
Holy GrailThis is a long-only educational strategy that simulates what happens if you keep adding to a position during pullbacks and only exit when the asset hits a new All-Time High (ATH). It is intended for learning purposes only — not for live trading.
🧠 How it works:
The strategy identifies pullbacks using a simple moving average (MA).
When price dips below the MA, it begins monitoring for the first green candle (close > open).
That green candle signals a potential bottom, so it adds to the position.
If price goes lower, it waits for the next green candle and adds again.
The exit happens after ATH — it sells on each red candle (close < open) once a new ATH is reached.
You can adjust:
MA length (defines what’s considered a pullback)
Initial buy % (how much to pre-fill before signals start)
Buy % per signal (after pullback green candle)
Exit % per red candle after ATH
📊 Intended assets & timeframes:
This strategy is designed for broad market indices and long-term appreciating assets, such as:
SPY, NASDAQ, DAX, FTSE
Use it only on 1D or higher timeframes — it’s not meant for scalping or short-term trading.
⚠️ Important Limitations:
Long-only: The script does not short. It assumes the asset will eventually recover to a new ATH.
Not for all assets: It won't work on assets that may never recover (e.g., single stocks or speculative tokens).
Slow capital deployment: Entries happen gradually and may take a long time to close.
Not optimized for returns: Buy & hold can outperform this strategy.
No slippage, fees, or funding costs included.
This is not a performance strategy. It’s a teaching tool to show that:
High win rate ≠ high profitability
Patience can be deceiving
Many signals = long capital lock-in
🎓 Why it exists:
The purpose of this strategy is to demonstrate market psychology and risk overconfidence. Traders often chase strategies with high win rates without considering holding time, drawdowns, or opportunity cost.
This script helps visualize that phenomenon.
Bollinger Band Breakout With Volatility StoplossDetailed Explanation of the Bollinger Band Breakout With Volatility Stoploss System
Introduction
The "Bollinger Band Breakout With Volatility Stoploss" system is a trading strategy designed to exploit price volatility in financial markets using the Bollinger Bands indicator, a widely recognized tool developed by John Bollinger. This system adapts the traditional Bollinger Bands framework into a Volatility Breakout strategy, focusing on capturing significant price movements by leveraging customized parameters and precise trading rules. The system operates exclusively on long positions, employs a daily timeframe, and incorporates dynamic risk management techniques to optimize trade outcomes while preserving capital.
System Parameters
The system modifies the standard Bollinger Bands configuration to suit its breakout methodology:
Standard Deviation (SD): Set to 1x, determining the width of the bands relative to the central moving average. This tighter setting enhances sensitivity to price movements, making the system responsive to smaller volatility shifts compared to the conventional 2x SD.
Period: A 30-day (1-month) lookback period is used to calculate the bands, providing a balance between capturing medium-term price trends and avoiding excessive noise from shorter timeframes.
Moving Average Type: The system uses an Exponential Moving Average (EMA) instead of the Simple Moving Average (SMA). The EMA places greater weight on recent price data, making it more responsive to current market conditions and better suited for detecting breakout opportunities in dynamic markets.
Core Concept
The Bollinger Band Breakout system is built on the principle of Volatility Breakout, which seeks to capitalize on significant price movements when the price breaks out of a defined volatility range. The Bollinger Bands, consisting of an EMA as the central line and two bands (Upper and Lower) calculated as the EMA plus or minus 1x SD, define this range. The system operates on a Daily Chart (D) timeframe, making it suitable for traders who prefer analyzing and executing trades based on daily price action. By focusing solely on Long Positions (buying low and selling high), the system avoids short-selling, aligning with strategies that capitalize on upward price momentum.
The core idea is to use the 1x SD multiplier over a 30-day period to establish a dynamic price range that reflects recent market volatility. Breakouts above the Upper Band signal potential buying opportunities, while penetrations below the Lower Band indicate exits, ensuring trades are aligned with significant price movements.
Trading Signals
The system generates clear entry and exit signals based on price interactions with the Bollinger Bands:
Buy Signal: A buy signal is triggered when the closing price of a daily candle exceeds the Upper Bollinger Band (EMA + 1x SD over 30 days). The trade is entered at the opening price of the subsequent candle, ensuring the breakout is confirmed by the close of the prior day. This approach minimizes false signals by waiting for a definitive breach of the volatility threshold.
Sell Signal: A sell signal occurs when the closing price falls below the Lower Bollinger Band (EMA - 1x SD over 30 days). The position is exited at the opening price of the next candle, allowing the trader to lock in profits or limit losses when the price reverses or loses momentum.
Risk Management
Risk management is a cornerstone of the system, ensuring capital preservation and disciplined trade execution:
Initial Stoploss: The stoploss is set at the Lower Bollinger Band of the candle that triggered the buy signal. This level acts as a volatility-based threshold, below which the trade is deemed invalid, prompting an immediate exit to protect capital. Traders have two options for implementing the stoploss:
Pending Stoploss: A predefined stoploss order placed at the Lower Band level.
Conditional Exit: Using the sell signal condition (price closing below the Lower Band) as the exit trigger, effectively aligning the stoploss with the system’s exit rules.
Position Sizing: The system employs Fixed Fractional Position Sizing with a risk per trade capped at 3% of the account balance. The position size is calculated based on the distance between the entry price and the Initial Stoploss, incorporating Volatility Position Sizing. This method adjusts the trade size according to the market’s volatility, ensuring that risk remains consistent across varying market conditions. Two options are available for managing capital:
Gear Up Option: Profits from previous trades are reinvested into the account’s capital, increasing the base for calculating the next position size. This compounding approach can amplify returns but also increases risk exposure.
Fixed Equity Option: Profits from previous trades are withdrawn, and only the remaining capital is used for calculating the next position size. This conservative approach prioritizes capital preservation by not compounding gains.
Trailing Stop: The system uses the Lower Bollinger Band as a dynamic trailing stop, which adjusts with price movements and volatility. This ensures that profits are protected during favorable trends while allowing the trade to remain open as long as the price stays above the Lower Band. The trailing stop aligns with the sell signal condition, maintaining consistency in the system’s exit strategy.
Supporting Indicators
The system incorporates two additional indicators to enhance market analysis and decision-making:
Bollinger Band Width (BBW): BBW measures the distance between the Upper and Lower Bollinger Bands relative to the EMA, serving as a proxy for market volatility.
A high BBW indicates significant price volatility, often associated with strong trends or large price movements, which may confirm the strength of a breakout.
A low BBW suggests low volatility, potentially signaling a period of consolidation or "squeeze" that could precede a breakout. This can help traders anticipate potential trade setups.
The BBW calculation uses the EMA to maintain consistency with the system’s core parameters.
Bollinger Band Ratio (BBR) or %B: BBR measures the price’s position relative to the Bollinger Bands, providing insight into market conditions.
BBR > 1: The price is above the Upper Band, indicating potential overbought conditions or strong upward momentum, which aligns with the system’s buy signal.
BBR < 0: The price is below the Lower Band, suggesting oversold conditions or downward momentum, corresponding to the sell signal or stoploss trigger.
BBR between 0 and 1: The price is within the bands, indicating a neutral state where no immediate action is required.
Like BBW, BBR is calculated using the EMA for consistency.
Backtesting and Implementation
To evaluate the system’s performance, traders can utilize the Backtest Parameter function, which allows for testing the strategy across user-defined time periods. This feature enables traders to assess the system’s effectiveness under various market conditions, optimize parameters, and refine their approach based on historical data.
Conclusion
The Bollinger Band Breakout With Volatility Stoploss system is a robust, volatility-driven trading strategy that combines the predictive power of Bollinger Bands with disciplined risk management. By focusing on long positions, using a 1x SD multiplier, and incorporating EMA-based calculations, the system is designed to capture significant price breakouts while minimizing risk through dynamic stoplosses and volatility-adjusted position sizing. The inclusion of BBW and BBR indicators provides additional context for assessing market conditions, enhancing the trader’s ability to make informed decisions. With its structured approach and backtesting capabilities, this system is well-suited for traders seeking a systematic, data-driven method to trade in volatile markets.
DVPOOverview
The DVPO (Dynamic Volume Profile Oscillator) Strategy is a comprehensive and highly customizable trading tool designed for precision and control. It is built around a unique, volume-driven oscillator that identifies potential market entries by analyzing the relationship between price, volume, and volatility.
This strategy is not just another signal generator; it's a complete framework that includes dynamic entry logic, adaptive risk management (ATR Stop Loss and R:R-based Take Profit), and a powerful dashboard of 10+ optional confirmation filters to help you tailor the strategy to your specific instrument, timeframe, and trading style.
The Core Concept: The DVPO Oscillator
The heart of this strategy is the DVPO oscillator. Unlike standard oscillators like RSI or Stochastics, the DVPO's primary goal is to quantify how far the current price has deviated from its recent volume-weighted "fair value."
Here’s how it works conceptually:
Micro Volume Profile: The indicator first analyzes a recent period of bars (defined by Lookback Period) to build a mini-profile of price and volume.
Volume-Weighted Mean: From this profile, it calculates a volume-weighted average price (VWAP) and the average deviation from that mean. This establishes the central point of value for the recent period.
Deviation Measurement: The oscillator's value is derived from how far the current price is from this calculated mean, scaled by the observed price deviation and a user-defined Sensitivity. A value above the midline suggests the price is trading at a premium, while a value below suggests it's at a discount.
Adaptive Volatility Zones: Instead of using fixed overbought/oversold levels (e.g., 70/30), the DVPO calculates dynamic upper and lower zones using the standard deviation of the oscillator itself. These zones expand and contract based on recent market volatility.
An entry signal is triggered not just when the oscillator is "overbought" or "oversold," but when it breaks out of these adaptive volatility zones, signaling that a statistically significant price movement is underway.
📈 Long Entry Condition : The oscillator crosses above the dynamic upper zone.
📉 Short Entry Condition : The oscillator crosses below the dynamic lower zone.
Integrated Risk & Trade Management
A signal is useless without proper risk management. This strategy has professional-grade risk management built directly into its logic.
Stop Loss (ATR-Based): The Stop Loss is not a fixed percentage. It is calculated using the Average True Range (ATR), allowing it to adapt automatically to the market's current volatility. In volatile periods, the stop will be wider; in quiet periods, it will be tighter.
Take Profit (Risk/Reward Ratio): The Take Profit level is calculated based on a user-defined Risk/Reward Ratio. If you set a ratio of 2.0, the Take Profit target will be placed at twice the distance of the Stop Loss from your entry price.
Dynamic Position Sizing: The strategy can automatically calculate the trade quantity for you. It determines the position size based on your specified Capital Size and the % Risk Per Trade you are willing to accept, ensuring disciplined risk control on every trade.
The Filter Dashboard : Enhance Your Signal Quality
To help reduce false signals and adapt to different market conditions, the strategy includes a comprehensive dashboard of optional confirmation filters. An entry signal will only be executed if it aligns with all the filters you have activated.
Trend & Momentum Filters :
T3, VMA, & VWAP Trend Filters: Utilize a suite of advanced moving averages (T3, Variable Moving Average, and a session-based VWAP) to ensure your trades are aligned with the dominant trend.
ADX Filter: Confirms that the market has sufficient directional strength for a trend-following trade, helping to avoid entries during choppy conditions.
Kaufman Efficiency Filter: Uses the Kaufman Efficiency Ratio to measure market noise. It only allows trades when the market is trending efficiently.
Volume & Market State Filters :
Volume Flow (VFI): A sophisticated volume-based filter that confirms whether volume is supporting the price move.
TDFI (Trader's Dynamic Index): A market state indicator designed to identify when the market is primed for a strong, directional move.
Flat Market Detector: A unique filter that identifies and avoids trading in sideways or ranging markets where trend strategies typically underperform.
Trade Condition Filters :
Min TP / Max SL %: Filter out trades where the risk/reward profile doesn't meet your minimum requirements (e.g., ignore a trade if the ATR-based stop loss is more than 10% away from the price).
Session Filters: Allows you to enable or disable trading on specific days of the week and to set a Cooldown Period (a set number of bars to wait after a trade closes before looking for a new entry).
How To Use This Strategy
Start with the Core: Begin by configuring the DVPO Oscillator settings (Lookback Period, Sensitivity, Zone Width) and your Risk Management parameters (ATR Multiplier, RR Ratio, % Risk Per Trade). These form the foundation of the strategy.
Backtest and Observe: Use TradingView's Strategy Tester to see how the core signals perform on your chosen asset and timeframe.
Layer Filters Intelligently: Enable the confirmation filters one by one and re-run your backtest. Observe how each filter impacts performance (e.g., does the T3 filter increase profitability but reduce the number of trades?). The goal is to find the optimal balance between signal quality and frequency.
Visualize and Analyze: Use the Show Risk/Reward Area option to plot your entry, stop loss, and take profit levels directly on the chart for every trade, providing a clear visual representation of your trade plan.
Disclaimer: This strategy is provided for educational and analytical purposes only. Past performance is not indicative of future results. All trading involves risk, and you should conduct your own thorough backtesting and analysis before deploying any strategy in a live market.
Anomalous Holonomy Field Theory🌌 Anomalous Holonomy Field Theory (AHFT) - Revolutionary Quantum Market Analysis
Where Theoretical Physics Meets Trading Reality
A Groundbreaking Synthesis of Differential Geometry, Quantum Field Theory, and Market Dynamics
🔬 THEORETICAL FOUNDATION - THE MATHEMATICS OF MARKET REALITY
The Anomalous Holonomy Field Theory represents an unprecedented fusion of advanced mathematical physics with practical market analysis. This isn't merely another indicator repackaging old concepts - it's a fundamentally new lens through which to view and understand market structure .
1. HOLONOMY GROUPS (Differential Geometry)
In differential geometry, holonomy measures how vectors change when parallel transported around closed loops in curved space. Applied to markets:
Mathematical Formula:
H = P exp(∮_C A_μ dx^μ)
Where:
P = Path ordering operator
A_μ = Market connection (price-volume gauge field)
C = Closed price path
Market Implementation:
The holonomy calculation measures how price "remembers" its journey through market space. When price returns to a previous level, the holonomy captures what has changed in the market's internal geometry. This reveals:
Hidden curvature in the market manifold
Topological obstructions to arbitrage
Geometric phase accumulated during price cycles
2. ANOMALY DETECTION (Quantum Field Theory)
Drawing from the Adler-Bell-Jackiw anomaly in quantum field theory:
Mathematical Formula:
∂_μ j^μ = (e²/16π²)F_μν F̃^μν
Where:
j^μ = Market current (order flow)
F_μν = Field strength tensor (volatility structure)
F̃^μν = Dual field strength
Market Application:
Anomalies represent symmetry breaking in market structure - moments when normal patterns fail and extraordinary opportunities arise. The system detects:
Spontaneous symmetry breaking (trend reversals)
Vacuum fluctuations (volatility clusters)
Non-perturbative effects (market crashes/melt-ups)
3. GAUGE THEORY (Theoretical Physics)
Markets exhibit gauge invariance - the fundamental physics remains unchanged under certain transformations:
Mathematical Formula:
A'_μ = A_μ + ∂_μΛ
This ensures our signals are gauge-invariant observables , immune to arbitrary market "coordinate changes" like gaps or reference point shifts.
4. TOPOLOGICAL DATA ANALYSIS
Using persistent homology and Morse theory:
Mathematical Formula:
β_k = dim(H_k(X))
Where β_k are the Betti numbers describing topological features that persist across scales.
🎯 REVOLUTIONARY SIGNAL CONFIGURATION
Signal Sensitivity (0.5-12.0, default 2.5)
Controls the responsiveness of holonomy field calculations to market conditions. This parameter directly affects the threshold for detecting quantum phase transitions in price action.
Optimization by Timeframe:
Scalping (1-5min): 1.5-3.0 for rapid signal generation
Day Trading (15min-1H): 2.5-5.0 for balanced sensitivity
Swing Trading (4H-1D): 5.0-8.0 for high-quality signals only
Score Amplifier (10-200, default 50)
Scales the raw holonomy field strength to produce meaningful signal values. Higher values amplify weak signals in low-volatility environments.
Signal Confirmation Toggle
When enabled, enforces additional technical filters (EMA and RSI alignment) to reduce false positives. Essential for conservative strategies.
Minimum Bars Between Signals (1-20, default 5)
Prevents overtrading by enforcing quantum decoherence time between signals. Higher values reduce whipsaws in choppy markets.
👑 ELITE EXECUTION SYSTEM
Execution Modes:
Conservative Mode:
Stricter signal criteria
Higher quality thresholds
Ideal for stable market conditions
Adaptive Mode:
Self-adjusting parameters
Balances signal frequency with quality
Recommended for most traders
Aggressive Mode:
Maximum signal sensitivity
Captures rapid market moves
Best for experienced traders in volatile conditions
Dynamic Position Sizing:
When enabled, the system scales position size based on:
Holonomy field strength
Current volatility regime
Recent performance metrics
Advanced Exit Management:
Implements trailing stops based on ATR and signal strength, with mode-specific multipliers for optimal profit capture.
🧠 ADAPTIVE INTELLIGENCE ENGINE
Self-Learning System:
The strategy analyzes recent trade outcomes and adjusts:
Risk multipliers based on win/loss ratios
Signal weights according to performance
Market regime detection for environmental adaptation
Learning Speed (0.05-0.3):
Controls adaptation rate. Higher values = faster learning but potentially unstable. Lower values = stable but slower adaptation.
Performance Window (20-100 trades):
Number of recent trades analyzed for adaptation. Longer windows provide stability, shorter windows increase responsiveness.
🎨 REVOLUTIONARY VISUAL SYSTEM
1. Holonomy Field Visualization
What it shows: Multi-layer quantum field bands representing market resonance zones
How to interpret:
Blue/Purple bands = Primary holonomy field (strongest resonance)
Band width = Field strength and volatility
Price within bands = Normal quantum state
Price breaking bands = Quantum phase transition
Trading application: Trade reversals at band extremes, breakouts on band violations with strong signals.
2. Quantum Portals
What they show: Entry signals with recursive depth patterns indicating momentum strength
How to interpret:
Upward triangles with portals = Long entry signals
Downward triangles with portals = Short entry signals
Portal depth = Signal strength and expected momentum
Color intensity = Probability of success
Trading application: Enter on portal appearance, with size proportional to portal depth.
3. Field Resonance Bands
What they show: Fibonacci-based harmonic price zones where quantum resonance occurs
How to interpret:
Dotted circles = Minor resonance levels
Solid circles = Major resonance levels
Color coding = Resonance strength
Trading application: Use as dynamic support/resistance, expect reactions at resonance zones.
4. Anomaly Detection Grid
What it shows: Fractal-based support/resistance with anomaly strength calculations
How to interpret:
Triple-layer lines = Major fractal levels with high anomaly probability
Labels show: Period (H8-H55), Price, and Anomaly strength (φ)
⚡ symbol = Extreme anomaly detected
● symbol = Strong anomaly
○ symbol = Normal conditions
Trading application: Expect major moves when price approaches high anomaly levels. Use for precise entry/exit timing.
5. Phase Space Flow
What it shows: Background heatmap revealing market topology and energy
How to interpret:
Dark background = Low market energy, range-bound
Purple glow = Building energy, trend developing
Bright intensity = High energy, strong directional move
Trading application: Trade aggressively in bright phases, reduce activity in dark phases.
📊 PROFESSIONAL DASHBOARD METRICS
Holonomy Field Strength (-100 to +100)
What it measures: The Wilson loop integral around price paths
>70: Strong positive curvature (bullish vortex)
<-70: Strong negative curvature (bearish collapse)
Near 0: Flat connection (range-bound)
Anomaly Level (0-100%)
What it measures: Quantum vacuum expectation deviation
>70%: Major anomaly (phase transition imminent)
30-70%: Moderate anomaly (elevated volatility)
<30%: Normal quantum fluctuations
Quantum State (-1, 0, +1)
What it measures: Market wave function collapse
+1: Bullish eigenstate |↑⟩
0: Superposition (uncertain)
-1: Bearish eigenstate |↓⟩
Signal Quality Ratings
LEGENDARY: All quantum fields aligned, maximum probability
EXCEPTIONAL: Strong holonomy with anomaly confirmation
STRONG: Good field strength, moderate anomaly
MODERATE: Decent signals, some uncertainty
WEAK: Minimal edge, high quantum noise
Performance Metrics
Win Rate: Rolling performance with emoji indicators
Daily P&L: Real-time profit tracking
Adaptive Risk: Current risk multiplier status
Market Regime: Bull/Bear classification
🏆 WHY THIS CHANGES EVERYTHING
Traditional technical analysis operates on 100-year-old principles - moving averages, support/resistance, and pattern recognition. These work because many traders use them, creating self-fulfilling prophecies.
AHFT transcends this limitation by analyzing markets through the lens of fundamental physics:
Markets have geometry - The holonomy calculations reveal this hidden structure
Price has memory - The geometric phase captures path-dependent effects
Anomalies are predictable - Quantum field theory identifies symmetry breaking
Everything is connected - Gauge theory unifies disparate market phenomena
This isn't just a new indicator - it's a new way of thinking about markets . Just as Einstein's relativity revolutionized physics beyond Newton's mechanics, AHFT revolutionizes technical analysis beyond traditional methods.
🔧 OPTIMAL SETTINGS FOR MNQ 10-MINUTE
For the Micro E-mini Nasdaq-100 on 10-minute timeframe:
Signal Sensitivity: 2.5-3.5
Score Amplifier: 50-70
Execution Mode: Adaptive
Min Bars Between: 3-5
Theme: Quantum Nebula or Dark Matter
💭 THE JOURNEY - FROM IMPOSSIBLE THEORY TO TRADING REALITY
Creating AHFT was a mathematical odyssey that pushed the boundaries of what's possible in Pine Script. The journey began with a seemingly impossible question: Could the profound mathematical structures of theoretical physics be translated into practical trading tools?
The Theoretical Challenge:
Months were spent diving deep into differential geometry textbooks, studying the works of Chern, Simons, and Witten. The mathematics of holonomy groups and gauge theory had never been applied to financial markets. Translating abstract mathematical concepts like parallel transport and fiber bundles into discrete price calculations required novel approaches and countless failed attempts.
The Computational Nightmare:
Pine Script wasn't designed for quantum field theory calculations. Implementing the Wilson loop integral, managing complex array structures for anomaly detection, and maintaining computational efficiency while calculating geometric phases pushed the language to its limits. There were moments when the entire project seemed impossible - the script would timeout, produce nonsensical results, or simply refuse to compile.
The Breakthrough Moments:
After countless sleepless nights and thousands of lines of code, breakthrough came through elegant simplifications. The realization that market anomalies follow patterns similar to quantum vacuum fluctuations led to the revolutionary anomaly detection system. The discovery that price paths exhibit holonomic memory unlocked the geometric phase calculations.
The Visual Revolution:
Creating visualizations that could represent 4-dimensional quantum fields on a 2D chart required innovative approaches. The multi-layer holonomy field, recursive quantum portals, and phase space flow representations went through dozens of iterations before achieving the perfect balance of beauty and functionality.
The Balancing Act:
Perhaps the greatest challenge was maintaining mathematical rigor while ensuring practical trading utility. Every formula had to be both theoretically sound and computationally efficient. Every visual had to be both aesthetically pleasing and information-rich.
The result is more than a strategy - it's a synthesis of pure mathematics and market reality that reveals the hidden order within apparent chaos.
📚 INTEGRATED DOCUMENTATION
Once applied to your chart, AHFT includes comprehensive tooltips on every input parameter. The source code contains detailed explanations of the mathematical theory, practical applications, and optimization guidelines. This published description provides the overview - the indicator itself is a complete educational resource.
⚠️ RISK DISCLAIMER
While AHFT employs advanced mathematical models derived from theoretical physics, markets remain inherently unpredictable. No mathematical model, regardless of sophistication, can guarantee future results. This strategy uses realistic commission ($0.62 per contract) and slippage (1 tick) in all calculations. Past performance does not guarantee future results. Always use appropriate risk management and never risk more than you can afford to lose.
🌟 CONCLUSION
The Anomalous Holonomy Field Theory represents a quantum leap in technical analysis - literally. By applying the profound insights of differential geometry, quantum field theory, and gauge theory to market analysis, AHFT reveals structure and opportunities invisible to traditional methods.
From the holonomy calculations that capture market memory to the anomaly detection that identifies phase transitions, from the adaptive intelligence that learns and evolves to the stunning visualizations that make the invisible visible, every component works in mathematical harmony.
This is more than a trading strategy. It's a new lens through which to view market reality.
Trade with the precision of physics. Trade with the power of mathematics. Trade with AHFT.
I hope this serves as a good replacement for Quantum Edge Pro - Adaptive AI until I'm able to fix it.
— Dskyz, Trade with insight. Trade with anticipation.
SDR Market Structure (liv3) 1.0🧠 SDR Market Structure (LIV3) v1.0
Precision-Based Market Structure & Momentum Scalping
Strategy Type: Market Structure-Based Scalping
Built For: Intraday, Scalping, Trend-Following or Reversal entries with confirmation filters
Assets: All (optimized for FX and indices)
Timeframes: 1min to 15min (ideal for scalping); higher TFs can be used for structure alignment
🎯 Strategy Overview
SDR Market Structure is a robust scalping strategy that combines structural market context (Change-of-Character, Break of Structure) with a modular system of technical filters that advanced traders can toggle on/off. The strategy is adaptable and surgical, designed to find high-probability trade entries during momentum shifts, liquidity grabs, and trend continuations.
This script supports fine-tuned risk management, multiple confirmation layers, and intraday session filtering, allowing experienced traders to tailor it for precision-based trading in varying volatility regimes.
🔍 Core Logic: CHoCH and Market Structure
At the heart of SDR Scalper is Change-of-Character (CHoCH) detection:
Bullish CHoCH: Occurs when price breaks above a recent swing high (pivot) after making a lower low, implying a potential reversal or continuation.
Bearish CHoCH: Triggers when price breaks below a recent swing low after making a higher high.
Once a CHoCH is identified:
Entry is confirmed only if all selected filters pass, ensuring high-confidence setups.
SL is placed at the most recent swing low/high or an optional looser SL based on fractals.
Break-even logic moves SL to entry upon hitting 1R.
Risk-Reward ratio is fully customizable.
🛠️ Advanced Filter Modules
Each filter module below can be toggled independently, allowing for custom filtering strategies based on trading conditions.
1️⃣ HTF EMA Filter
Purpose: Confirms trend bias using a higher timeframe EMA (e.g., 55 EMA on 15-min TF).
Logic:
Longs: Entry only allowed if price > HTF EMA
Shorts: Entry only allowed if price < HTF EMA
Why Use It: Prevents counter-trend trades. Excellent when used during trending sessions.
Best Paired With: EMA crossover filter or RSI for intraday trend alignment.
2️⃣ EMA Crossover Filter
Inputs: Fast EMA (default 10), Slow EMA (default 50)
Logic:
Longs: Fast EMA must be above Slow EMA
Shorts: Fast EMA below Slow EMA
Enhancement: Adds a moving average structure filter to CHoCH. Good for filtering false breakouts during sideways markets.
Combo Tip: Use alongside RSI/MACD filters to confirm trend momentum.
3️⃣ RSI Filter
Default Period: 14
Logic:
Longs: RSI > threshold (default 50)
Shorts: RSI < threshold
Edge: Useful for momentum confirmation in trending conditions.
Advanced Use:
Raise thresholds to 60/40 in strong trends.
Combine with MACD to filter momentum exhaustion.
4️⃣ MACD Histogram Filter
MACD Histogram > 0: Long entries only
MACD Histogram < 0: Short entries only
Purpose: Measures positive/negative momentum shifts, helpful in volatile breakouts.
Pro Tip: Combine with ROC filter in fast-moving markets for maximum edge.
5️⃣ Rate of Change (ROC) Filter
Default: 9-period
Logic:
Longs: ROC > threshold (default 0.0)
Shorts: ROC < threshold
Why It Works: Captures short bursts of momentum often missed by other lagging indicators.
Combos That Work:
MACD + ROC: Double momentum filter
ROC + EMA crossover: Catch high-speed trend continuations
6️⃣ Stochastic RSI Filter
Parameters: Customizable %K and %D smoothing
Logic:
Longs: StochRSI > threshold and K > D
Shorts: StochRSI < threshold and K < D
Use Case: Effective for mean-reversion and momentum crossovers near S/R zones.
Advanced Tip: Use in ranging markets or to fade extended trends.
7️⃣ Time Filter
Customize Start/End Time: Default is 09:30 - 16:00 (New York session)
Supports Time Zones: Input via string (e.g., GMT+0, EST, etc.)
Visual Aid: Background shading for valid sessions.
Benefits:
Avoids low-liquidity or overnight trading periods.
Prevents false signals in pre/post-market sessions.
8️⃣ Loose Stop-Loss Option
If Enabled: SL placed 1 fractal beyond the last pivot.
Why: Helps in volatile assets like crypto where swing points are commonly breached before reversals.
Note: Should be used with tight risk controls or lower position sizing.
💼 Risk Management & Break-Even Logic
Risk-to-Reward Ratio: Adjustable via input
Auto TP & SL: Based on defined RR and recent structure
Break-Even Feature: Moves SL to entry after 1R is reached to protect capital
📈 Strategy Display Elements
CHoCH & BoS Labels: Visual confirmation of structure breaks
Liquidity Sweep (✖): Optional display for potential stop hunts
Trend Color Candles: Highlights bullish or bearish candle clusters
Session Overlay: Displays active time window on chart
⚙️ Recommended Configurations
Objective Suggested Filters
Trend Scalping HTF EMA + EMA Crossover + RSI
Volatility Breakouts ROC + MACD Histogram + Time Filter
Mean Reversion Stochastic RSI + RSI
Structure-Only Mode Disable all filters except Time Filter
Conservative Mode Enable all filters with tightened thresholds
📌 Final Notes
This script is highly modular and is not a one-size-fits-all strategy. It is a framework that allows advanced traders to apply contextual judgment and optimize entries based on confluence. Extensive backtesting per asset and timeframe is highly recommended.
🛠️ Strategy Parameters Summary
✅ Market Structure Entry (CHoCH)
✅ Smart SL & Break-Even Logic
✅ Modular Momentum Filters (RSI, MACD, ROC, StochRSI)
✅ Trend Filters (HTF EMA, EMA Cross)
✅ Session Filtering & Visualization
✅ Liquidity Sweeps (optional)
pinescript version5
System 0530 - Stoch RSI Strategy with ATR filterStrategy Description: System 0530 - Multi-Timeframe Stochastic RSI with ATR Filter
Overview:
This strategy, "System 0530," is designed to identify trading opportunities by leveraging the Stochastic RSI indicator across two different timeframes: a shorter timeframe for initial signal triggers (assumed to be the chart's current timeframe, e.g., 5-minute) and a longer timeframe (15-minute) for signal confirmation. It incorporates an ATR (Average True Range) filter to help ensure trades are taken during periods of adequate market volatility and includes a cooldown mechanism to prevent rapid, successive signals in the same direction. Trade exits are primarily handled by reversing signals.
How It Works:
1. Signal Initiation (e.g., 5-Minute Timeframe):
Long Signal Wait: A potential long entry is considered when the 5-minute Stochastic RSI %K line crosses above its %D line, AND the %K value at the time of the cross is at or below a user-defined oversold level (default: 30).
Short Signal Wait: A potential short entry is considered when the 5-minute Stochastic RSI %K line crosses below its %D line, AND the %K value at the time of the cross is at or above a user-defined overbought level (default: 70). When these conditions are met, the strategy enters a "waiting state" for confirmation from the 15-minute timeframe.
2. Signal Confirmation (15-Minute Timeframe):
Once in a waiting state, the strategy looks for confirmation on the 15-minute Stochastic RSI within a user-defined number of 5-minute bars (wait_window_5min_bars, default: 5 bars).
Long Confirmation:
The 15-minute Stochastic RSI %K must be greater than or equal to its %D line.
The 15-minute Stochastic RSI %K value must be below a user-defined threshold (stoch_15min_long_entry_level, default: 40).
Short Confirmation:
The 15-minute Stochastic RSI %K must be less than or equal to its %D line.
The 15-minute Stochastic RSI %K value must be above a user-defined threshold (stoch_15min_short_entry_level, default: 60).
3. Filters:
ATR Volatility Filter: If enabled, trades are only confirmed if the current ATR value (converted to ticks) is above a user-defined minimum threshold (min_atr_value_ticks). This helps to avoid taking signals during periods of very low market volatility. If the ATR condition is not met, the strategy continues to wait for the condition to be met within the confirmation window, provided other conditions still hold.
Signal Cooldown Filter: If enabled, after a signal is generated, the strategy will wait for a minimum number of bars (min_bars_between_signals) before allowing another signal in the same direction. This aims to reduce overtrading.
4. Entry and Exit Logic:
Entry: A strategy.entry() order is placed when all trigger, confirmation, and filter conditions are met.
Exit: This strategy primarily uses reversing signals for exits. For example, if a long position is open, a confirmed short signal will close the long position and open a new short position. There are no explicit take profit or stop loss orders programmed into this version of the script.
Key User-Adjustable Parameters:
Stochastic RSI Parameters: RSI Length, Stochastic RSI Length, %K Smoothing, %D Smoothing.
Signal Trigger & Confirmation:
5-minute %K trigger levels for long and short.
15-minute %K confirmation thresholds for long and short.
Wait window (in 5-minute bars) for 15-minute confirmation.
Filters:
Enable/disable and configure the Signal Cooldown filter (minimum bars between signals).
Enable/disable and configure the ATR Volatility filter (ATR period, minimum ATR value in ticks).
Strategy Parameters:
Leverage Multiplier (Note: This primarily affects theoretical position sizing for backtesting calculations in TradingView and does not simulate actual leveraged trading risks).
Recommendations for Users:
Thorough Backtesting: Test this strategy extensively on historical data for the instruments and timeframes you intend to trade.
Parameter Optimization: Experiment with different parameter settings to find what works best for your trading style and chosen markets. The default values are starting points and may not be optimal for all conditions.
Understand the Logic: Ensure you understand how each component (Stochastic RSI on different timeframes, ATR filter, cooldown) interacts to generate signals.
Risk Management: Since this version does not include explicit stop-loss orders, ensure you have a clear risk management plan in place if trading this strategy live. You might consider manually adding stop-loss orders through your broker or using TradingView's separate strategy order settings for stop-loss if applicable.
Disclaimer:
This strategy description is for informational purposes only and does not constitute financial advice. Past performance is not indicative of future results. Trading involves significant risk of loss. Always do your own research and understand the risks before trading.
