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Quantum Reversal# 🧠 Quantum Reversal ## **Quantitative Mean Reversion Framework** This algorithmic trading system employs **statistical mean reversion theory** combined with **adaptive volatility modeling** to capitalize on Bitcoin's inherent price oscillations around its statistical mean. The strategy integrates multiple technical indicators through a **multi-layered signal processing architecture**. --- ## ⚡ **Core Technical Architecture** ### 📊 **Statistical Foundation** - **Bollinger Band Mean Reversion Model**: Utilizes 20-period moving average with 2.2 standard deviation bands for volatility-adjusted entry signals - **Adaptive Volatility Threshold**: Dynamic standard deviation multiplier accounts for Bitcoin's heteroscedastic volatility patterns - **Price Action Confluence**: Entry triggered when price breaches lower volatility band, indicating statistical oversold conditions ### 🔬 **Momentum Analysis Layer** - **RSI Oscillator Integration**: 14-period Relative Strength Index with modified oversold threshold at 45 - **Signal Smoothing Algorithm**: 5-period simple moving average applied to RSI reduces noise and false signals - **Momentum Divergence Detection**: Captures mean reversion opportunities when momentum indicators show oversold readings ### ⚙️ **Entry Logic Architecture** ``` Entry Condition = (Price ≤ Lower_BB) OR (Smoothed_RSI < 45) ``` - **Dual-Condition Framework**: Either statistical price deviation OR momentum oversold condition triggers entry - **Boolean Logic Gate**: OR-based entry system increases signal frequency while maintaining statistical validity - **Position Sizing**: Fixed 10% equity allocation per trade for consistent risk exposure ### 🎯 **Exit Strategy Optimization** - **Profit-Lock Mechanism**: Positions only closed when showing positive unrealized P&L - **Trend Continuation Logic**: Allows winning trades to run until momentum exhaustion - **Dynamic Exit Timing**: No fixed profit targets - exits based on profitability state rather than arbitrary levels --- ## 📈 **Statistical Properties** ### **Risk Management Framework** - **Long-Only Exposure**: Eliminates short-squeeze risk inherent in cryptocurrency markets - **Mean Reversion Bias**: Exploits Bitcoin's tendency to revert to statistical mean after extreme moves - **Position Management**: Single position limit prevents over-leveraging ### **Signal Processing Characteristics** - **Noise Reduction**: SMA smoothing on RSI eliminates high-frequency oscillations - **Volatility Adaptation**: Bollinger Bands automatically adjust to changing market volatility - **Multi-Timeframe Coherence**: Indicators operate on consistent timeframe for signal alignment --- ## 🔧 **Parameter Configuration** | Technical Parameter | Value | Statistical Significance | |-------------------|-------|-------------------------| | Bollinger Period | 20 | Standard statistical lookback for volatility calculation | | Std Dev Multiplier | 2.2 | Optimized for Bitcoin's volatility distribution (95.4% confidence interval) | | RSI Period | 14 | Traditional momentum oscillator period | | RSI Threshold | 45 | Modified oversold level accounting for Bitcoin's momentum characteristics | | Smoothing Period | 5 | Noise reduction filter for momentum signals | --- ## 📊 **Algorithmic Advantages** ✅ **Statistical Edge**: Exploits documented mean reversion tendency in Bitcoin markets ✅ **Volatility Adaptation**: Dynamic bands adjust to changing market conditions ✅ **Signal Confluence**: Multiple indicator confirmation reduces false positives ✅ **Momentum Integration**: RSI smoothing improves signal quality and timing ✅ **Risk-Controlled Exposure**: Systematic position sizing and long-only bias --- ## 🔬 **Mathematical Foundation** The strategy leverages **Bollinger Band theory** (developed by John Bollinger) which assumes that prices tend to revert to the mean after extreme deviations. The RSI component adds **momentum confirmation** to the statistical price deviation signal. **Statistical Basis:** - Mean reversion follows the principle that extreme price deviations from the moving average are temporary - The 2.2 standard deviation multiplier captures approximately 97.2% of price movements under normal distribution - RSI momentum smoothing reduces noise inherent in oscillator calculations --- ## ⚠️ **Risk Considerations** This algorithm is designed for traders with understanding of **quantitative finance principles** and **cryptocurrency market dynamics**. The strategy assumes mean-reverting behavior which may not persist during trending market phases. Proper risk management and position sizing are essential. --- ## 🎯 **Implementation Notes** - **Market Regime Awareness**: Most effective in ranging/consolidating markets - **Volatility Sensitivity**: Performance may vary during extreme volatility events - **Backtesting Recommended**: Historical performance analysis advised before live implementation - **Capital Allocation**: 10% per trade sizing assumes diversified portfolio approach --- **Engineered for quantitative traders seeking systematic mean reversion exposure in Bitcoin markets through statistically-grounded technical analysis.**
Pine Script® strategy
by ArganaBridgeCapital
7
Double AI Super Trend Trading - Strategy [PresentTrading]█ Introduction and How It is Different The Double AI Super Trend Trading Strategy is a cutting-edge approach that leverages the power of not one, but two AI algorithms, in tandem with the SuperTrend technical indicator. The strategy aims to provide traders with enhanced precision in market entry and exit points. It is designed to adapt to market conditions dynamically, offering the flexibility to trade in both bullish and bearish markets. *The KNN part is mainly referred from @Zeiierman. BTCUSD 8hr performance ETHUSD 8hr performance █ Strategy, How It Works: Detailed Explanation 1. SuperTrend Calculation The SuperTrend is a popular indicator that captures market trends through a combination of the Volume-Weighted Moving Average (VWMA) and the Average True Range (ATR). This strategy utilizes two sets of SuperTrend calculations with varying lengths and factors to capture both short-term and long-term market trends. 2. KNN Algorithm The strategy employs k-Nearest Neighbors (KNN) algorithms, which are supervised machine learning models. Two sets of KNN algorithms are used, each focused on different lengths of historical data and number of neighbors. The KNN algorithms classify the current SuperTrend data point as bullish or bearish based on the weighted sum of the labels of the k closest historical data points. 3. Signal Generation Based on the KNN classifications and the SuperTrend indicator, the strategy generates signals for the start of a new trend and the continuation of an existing trend. 4. Trading Logic The strategy uses these signals to enter long or short positions. It also incorporates dynamic trailing stops for exit conditions. Local picture █ Trade Direction The strategy allows traders to specify their trading direction: long, short, or both. This enables the strategy to be versatile and adapt to various market conditions. █ Usage ToolTips: Comprehensive tooltips are provided for each parameter to guide the user through the customization process. Inputs: Traders can customize numerous parameters including the number of neighbors in KNN, ATR multiplier, and types of moving averages. Plotting: The strategy also provides visual cues on the chart to indicate bullish or bearish trends. Order Execution: Based on the generated signals, the strategy will execute buy or sell orders automatically. █ Default Settings The default settings are configured to offer a balanced approach suitable for most scenarios: Initial Capital: $10,000 Default Quantity Type: 10% of equity Commission: 0.1% Slippage: 1 Currency: USD These settings can be modified to suit various trading styles and asset classes.
Pine Script® strategy
by PresentTrading
1
Customizable Non-Repainting HTF MACD MFI Scalper Bot StrategyThis script was originally shared by Wunderbit as a free open source script for the community to work with. WHAT THIS SCRIPT DOES: It is intended for use on an algorithmic bot trading platform but can be used for scalping and manual trading. This strategy is based on the trend-following momentum indicator . It includes the Money Flow index as an additional point for entry. HOW IT DOES IT: It uses a combination of MACD and MFI indicators to create entry signals. Parameters for each indicator have been surfaced for user configurability. Take profits are fixed, but stop loss uses ATR configuration to minimize losses and close profitably. HOW IS MY VERSION ORIGINAL: I started trying to deploy this script myself in my algorithmic trading but ran into some issues which I have tried to address in this version. Delayed Signals : The script has been refactored to use a time frame drop down. The higher time frame can be run on a faster chart (recommended on one minute chart for fastest signal confirmation and relay to algotrading platform.) Repainting Issues : All indicators have been recoded to use the security function that checks to see if the current calculation is in realtime, if it is, then it uses the previous bar for calculation. If you are still experiencing repainting issues based on intended (or non intended use), please provide a report with screenshot and explanation so I can try to address. Filtering : I have added to additional filters an ABOVE EMA Filter and a BELOW RSI Filter (both can be turned on and off) Customizable Long and Close Messages : This allows someone to use the script for algorithmic trading without having to alter code. It also means you can use one indicator for all of your different alterts required for your bots. HOW TO USE IT: It is intended to be used in the 5-30 minute time frames, but you might be able to get a good configuration for higher time frames. I welcome feedback from other users on what they have found. Find a pair with high volatility (example KUCOIN:ETH3LUSDT ) - I have found it works particularly well with 3L and 3S tokens for crypto. although it the limitation is that confrigurations I have found to work typically have low R/R ratio, but very high win rate and profit factor. Ideally set one minute chart for bots, but you can use other charts for manual trading. The signal will be delayed by one bar but I have found configurations that still test well. Select a time frame in configuration for your indicator calculations. Select the strategy config for time frame. I like to use 5 and 15 minutes for scalping scenarios, but I am interested in hearing back from other community memebers. Optimize your indicator without filters (trendFilter and RSI Filter) Use the TrendFilter and RSI Filter to further refine your signals for entry. You will get less entries but you can increase your win ratio. I will add screenshots and possibly a video provided that it passes community standards. Limitations: this works rather well for short term, and does some good forward testing but back testing large data sets is a problem when switching from very small time frame to large time frame. For instance, finding a configuration that works on a one minute chart but then changing to a 1 hour chart means you lose some of your intra bar calclulations. There are some new features in pine script which might be able to address, this, but I have not had a chance to work on that issue.
Pine Script® strategy
by MauricioZuniga
11
Acrypto - Weighted StrategyHello traders! I have been developing a fully customizable algo over the last year. The algorithm is based on a set of different strategies, each with its own weight (weighted strategy). The set of strategies that I currently use are 5: MACD Stochastic RSI RSI Supertrend MA crossover Moreover, the algo includes STOP losses criteria and a taking profit strategy. The algo must be optimized for the desired asset to achieves its full potential. The 1H and 4H dataframe give good results. The algo has been tested for several asset (same dataframe, different optimization values). Important note: Backtest the algorithm with different data stamps to avoid overfitting results Best, Alberto
Pine Script® strategy
by accry
203
BOCS Channel Scalper Strategy - Automated Mean Reversion System# BOCS Channel Scalper Strategy - Automated Mean Reversion System ## WHAT THIS STRATEGY DOES: This is an automated mean reversion trading strategy that identifies consolidation channels through volatility analysis and executes scalp trades when price enters entry zones near channel boundaries. Unlike breakout strategies, this system assumes price will revert to the channel mean, taking profits as price bounces back from extremes. Position sizing is fully customizable with three methods: fixed contracts, percentage of equity, or fixed dollar amount. Stop losses are placed just outside channel boundaries with take profits calculated either as fixed points or as a percentage of channel range. ## KEY DIFFERENCE FROM ORIGINAL BOCS: **This strategy is designed for traders seeking higher trade frequency.** The original BOCS indicator trades breakouts OUTSIDE channels, waiting for price to escape consolidation before entering. This scalper version trades mean reversion INSIDE channels, entering when price reaches channel extremes and betting on a bounce back to center. The result is significantly more trading opportunities: - **Original BOCS**: 1-3 signals per channel (only on breakout) - **Scalper Version**: 5-15+ signals per channel (every touch of entry zones) - **Trade Style**: Mean reversion vs trend following - **Hold Time**: Seconds to minutes vs minutes to hours - **Best Markets**: Ranging/choppy conditions vs trending breakouts This makes the scalper ideal for active day traders who want continuous opportunities within consolidation zones rather than waiting for breakout confirmation. However, increased trade frequency also means higher commission costs and requires tighter risk management. ## TECHNICAL METHODOLOGY: ### Price Normalization Process: The strategy normalizes price data to create consistent volatility measurements across different instruments and price levels. It calculates the highest high and lowest low over a user-defined lookback period (default 100 bars). Current close price is normalized using: (close - lowest_low) / (highest_high - lowest_low), producing values between 0 and 1 for standardized volatility analysis. ### Volatility Detection: A 14-period standard deviation is applied to the normalized price series to measure price deviation from the mean. Higher standard deviation values indicate volatility expansion; lower values indicate consolidation. The strategy uses ta.highestbars() and ta.lowestbars() to identify when volatility peaks and troughs occur over the detection period (default 14 bars). ### Channel Formation Logic: When volatility crosses from a high level to a low level (ta.crossover(upper, lower)), a consolidation phase begins. The strategy tracks the highest and lowest prices during this period, which become the channel boundaries. Minimum duration of 10+ bars is required to filter out brief volatility spikes. Channels are rendered as box objects with defined upper and lower boundaries, with colored zones indicating entry areas. ### Entry Signal Generation: The strategy uses immediate touch-based entry logic. Entry zones are defined as a percentage from channel edges (default 20%): - **Long Entry Zone**: Bottom 20% of channel (bottomBound + channelRange × 0.2) - **Short Entry Zone**: Top 20% of channel (topBound - channelRange × 0.2) Long signals trigger when candle low touches or enters the long entry zone. Short signals trigger when candle high touches or enters the short entry zone. This captures mean reversion opportunities as price reaches channel extremes. ### Cooldown Filter: An optional cooldown period (measured in bars) prevents signal spam by enforcing minimum spacing between consecutive signals. If cooldown is set to 3 bars, no new long signal will fire until 3 bars after the previous long signal. Long and short cooldowns are tracked independently, allowing both directions to signal within the same period. ### ATR Volatility Filter: The strategy includes a multi-timeframe ATR filter to avoid trading during low-volatility conditions. Using request.security(), it fetches ATR values from a specified timeframe (e.g., 1-minute ATR while trading on 5-minute charts). The filter compares current ATR to a user-defined minimum threshold: - If ATR ≥ threshold: Trading enabled - If ATR < threshold: No signals fire This prevents entries during dead zones where mean reversion is unreliable due to insufficient price movement. ### Take Profit Calculation: Two TP methods are available: **Fixed Points Mode**: - Long TP = Entry + (TP_Ticks × syminfo.mintick) - Short TP = Entry - (TP_Ticks × syminfo.mintick) **Channel Percentage Mode**: - Long TP = Entry + (ChannelRange × TP_Percent) - Short TP = Entry - (ChannelRange × TP_Percent) Default 50% targets the channel midline, a natural mean reversion target. Larger percentages aim for opposite channel edge. ### Stop Loss Placement: Stop losses are placed just outside the channel boundary by a user-defined tick offset: - Long SL = ChannelBottom - (SL_Offset_Ticks × syminfo.mintick) - Short SL = ChannelTop + (SL_Offset_Ticks × syminfo.mintick) This logic assumes channel breaks invalidate the mean reversion thesis. If price breaks through, the range is no longer valid and position exits. ### Trade Execution Logic: When entry conditions are met (price in zone, cooldown satisfied, ATR filter passed, no existing position): 1. Calculate entry price at zone boundary 2. Calculate TP and SL based on selected method 3. Execute strategy.entry() with calculated position size 4. Place strategy.exit() with TP limit and SL stop orders 5. Update info table with active trade details The strategy enforces one position at a time by checking strategy.position_size == 0 before entry. ### Channel Breakout Management: Channels are removed when price closes more than 10 ticks outside boundaries. This tolerance prevents premature channel deletion from minor breaks or wicks, allowing the mean reversion setup to persist through small boundary violations. ### Position Sizing System: Three methods calculate position size: **Fixed Contracts**: - Uses exact contract quantity specified in settings - Best for futures traders (e.g., "trade 2 NQ contracts") **Percentage of Equity**: - position_size = (strategy.equity × equity_pct / 100) / close - Dynamically scales with account growth **Cash Amount**: - position_size = cash_amount / close - Maintains consistent dollar exposure regardless of price ## INPUT PARAMETERS: ### Position Sizing: - **Position Size Type**: Choose Fixed Contracts, % of Equity, or Cash Amount - **Number of Contracts**: Fixed quantity per trade (1-1000) - **% of Equity**: Percentage of account to allocate (1-100%) - **Cash Amount**: Dollar value per position ($100+) ### Channel Settings: - **Nested Channels**: Allow multiple overlapping channels vs single channel - **Normalization Length**: Lookback for high/low calculation (1-500, default 100) - **Box Detection Length**: Period for volatility detection (1-100, default 14) ### Scalping Settings: - **Enable Long Scalps**: Toggle long entries on/off - **Enable Short Scalps**: Toggle short entries on/off - **Entry Zone % from Edge**: Size of entry zone (5-50%, default 20%) - **SL Offset (Ticks)**: Distance beyond channel for stop (1+, default 5) - **Cooldown Period (Bars)**: Minimum spacing between signals (0 = no cooldown) ### ATR Filter: - **Enable ATR Filter**: Toggle volatility filter on/off - **ATR Timeframe**: Source timeframe for ATR (1, 5, 15, 60 min, etc.) - **ATR Length**: Smoothing period (1-100, default 14) - **Min ATR Value**: Threshold for trade enablement (0.1+, default 10.0) ### Take Profit Settings: - **TP Method**: Choose Fixed Points or % of Channel - **TP Fixed (Ticks)**: Static distance in ticks (1+, default 30) - **TP % of Channel**: Dynamic target as channel percentage (10-100%, default 50%) ### Appearance: - **Show Entry Zones**: Toggle zone labels on channels - **Show Info Table**: Display real-time strategy status - **Table Position**: Corner placement (Top Left/Right, Bottom Left/Right) - **Color Settings**: Customize long/short/TP/SL colors ## VISUAL INDICATORS: - **Channel boxes** with semi-transparent fill showing consolidation zones - **Colored entry zones** labeled "LONG ZONE ▲" and "SHORT ZONE ▼" - **Entry signal arrows** below/above bars marking long/short entries - **Active TP/SL lines** with emoji labels (⊕ Entry, 🎯 TP, 🛑 SL) - **Info table** showing position status, channel state, last signal, entry/TP/SL prices, and ATR status ## HOW TO USE: ### For 1-3 Minute Scalping (NQ/ES): - ATR Timeframe: "1" (1-minute) - ATR Min Value: 10.0 (for NQ), adjust per instrument - Entry Zone %: 20-25% - TP Method: Fixed Points, 20-40 ticks - SL Offset: 5-10 ticks - Cooldown: 2-3 bars - Position Size: 1-2 contracts ### For 5-15 Minute Day Trading: - ATR Timeframe: "5" or match chart - ATR Min Value: Adjust to instrument (test 8-15 for NQ) - Entry Zone %: 20-30% - TP Method: % of Channel, 40-60% - SL Offset: 5-10 ticks - Cooldown: 3-5 bars - Position Size: Fixed contracts or 5-10% equity ### For 30-60 Minute Swing Scalping: - ATR Timeframe: "15" or "30" - ATR Min Value: Lower threshold for broader market - Entry Zone %: 25-35% - TP Method: % of Channel, 50-70% - SL Offset: 10-15 ticks - Cooldown: 5+ bars or disable - Position Size: % of equity recommended ## BACKTEST CONSIDERATIONS: - Strategy performs best in ranging, mean-reverting markets - Strong trending markets produce more stop losses as price breaks channels - ATR filter significantly reduces trade count but improves quality during low volatility - Cooldown period trades signal quantity for signal quality - Commission and slippage materially impact sub-5-minute timeframe performance - Shorter timeframes require tighter entry zones (15-20%) to catch quick reversions - % of Channel TP adapts better to varying channel sizes than fixed points - Fixed contract sizing recommended for consistent risk per trade in futures **Backtesting Parameters Used**: This strategy was developed and tested using realistic commission and slippage values to provide accurate performance expectations. Recommended settings: Commission of $1.40 per side (typical for NQ futures through discount brokers), slippage of 2 ticks to account for execution delays on fast-moving scalp entries. These values reflect real-world trading costs that active scalpers will encounter. Backtest results without proper cost simulation will significantly overstate profitability. ## COMPATIBLE MARKETS: Works on any instrument with price data including stock indices (NQ, ES, YM, RTY), individual stocks, forex pairs (EUR/USD, GBP/USD), cryptocurrency (BTC, ETH), and commodities. Volume-based features require data feed with volume information but are optional for core functionality. ## KNOWN LIMITATIONS: - Immediate touch entry can fire multiple times in choppy zones without adequate cooldown - Channel deletion at 10-tick breaks may be too aggressive or lenient depending on instrument tick size - ATR filter from lower timeframes requires higher-tier TradingView subscription (request.security limitation) - Mean reversion logic fails in strong breakout scenarios leading to stop loss hits - Position sizing via % of equity or cash amount calculates based on close price, may differ from actual fill price - No partial closing capability - full position exits at TP or SL only - Strategy does not account for gap openings or overnight holds ## RISK DISCLOSURE: Trading involves substantial risk of loss. Past performance does not guarantee future results. This strategy is for educational purposes and backtesting only. Mean reversion strategies can experience extended drawdowns during trending markets. Stop losses may not fill at intended levels during extreme volatility or gaps. Thoroughly test on historical data and paper trade before risking real capital. Use appropriate position sizing and never risk more than you can afford to lose. Consider consulting a licensed financial advisor before making trading decisions. Automated trading systems can malfunction - monitor all live positions actively. ## ACKNOWLEDGMENT & CREDITS: This strategy is built upon the channel detection methodology created by **AlgoAlpha** in the "Smart Money Breakout Channels" indicator. Full credit and appreciation to AlgoAlpha for pioneering the normalized volatility approach to identifying consolidation patterns. The core channel formation logic using normalized price standard deviation is AlgoAlpha's original contribution to the TradingView community. Enhancements to the original concept include: mean reversion entry logic (vs breakout), immediate touch-based signals, multi-timeframe ATR volatility filtering, flexible position sizing (fixed/percentage/cash), cooldown period filtering, dual TP methods (fixed points vs channel percentage), automated strategy execution with exit management, and real-time position monitoring table.
Pine Script® strategy
by TradeManager_PRO
Customizable Non-Repainting HTF MACD MFI Scalper Bot Strategy v2Customizable Non-Repainting HTF MACD MFI Scalper Bot Strategy v2 This script was originally shared by Wunderbit as a free open source script for the community to work with. This is my second published iteration of this idea. WHAT THIS SCRIPT DOES: It is intended for use on an algorithmic bot trading platform but can be used for scalping and manual trading. This strategy is based on the trend-following momentum indicator . It includes the Money Flow index as an additional point for entry. This is a new and improved version geared for lower timeframes (15-5 minutes), but can be run on larger ones as well. I am testing it live as my high frequency trader. HOW IT DOES IT: It uses a combination of MACD and MFI indicators to create entry signals. Parameters for each indicator have been surfaced for user configurability. Take profits are now trailing profits, and the stop loss is now fixed. Why? I found that the trailing stop loss with ATR in the previous version yields very good results for back tests but becomes very difficult to deploy live due to transaction fees. As you can see the average trade is a higher profit percentage than the previous version. HOW IS MY VERSION ORIGINAL: Now instead of using ATR stop loss, we have a fixed stop loss - counter intuitively to what some may believe this performs better in live trading scenarios since it gives the strategy room to move. I noticed that the ATR trailing stop was stopping out too fast and was eating away balance due to transaction fees. The take profit on the other hand is now a trailing profit with a customizable deviation. This ensures that you can have a minimum profit you want to take in order to exit. I have depracated the old ATR trailing stop as it became too confusing to have those as different options. I kept the old version for others that want to experiment with it. The source code still requires some cleanup, but its fully functional. I added in a way to show RSI values and ATR values with a checkbox so that you can use the new an improved ATR Filter (and grab the right RSI values for the RSI filter). This will help to filter out times of very low volatility where we are unlikely to find a profitable trade. Use the "Show Data" checkbox to see what the values are on the indicator pane, then use those values to gauge what you want to filter out. Both versions Delayed Signals : The script has been refactored to use a time frame drop down. The higher time frame can be run on a faster chart (recommended on one minute chart for fastest signal confirmation and relay to algotrading platform.) Repainting Issues : All indicators have been recoded to use the security function that checks to see if the current calculation is in realtime, if it is, then it uses the previous bar for calculation. If you are still experiencing repainting issues based on intended (or non intended use), please provide a report with screenshot and explanation so I can try to address. Filtering : I have added to additional filters an ABOVE EMA Filter and a BELOW RSI Filter (both can be turned on and off) Customizable Long and Close Messages : This allows someone to use the script for algorithmic trading without having to alter code. It also means you can use one indicator for all of your different alterts required for your bots. HOW TO USE IT: It is intended to be used in the 5-30 minute time frames, but you might be able to get a good configuration for higher time frames. I welcome feedback from other users on what they have found. Find a pair with high volatility (example KUCOIN:ETH3LUSDT ) - I have found it works particularly well with 3L and 3S tokens for crypto. although it the limitation is that confrigurations I have found to work typically have low R/R ratio, but very high win rate and profit factor. Ideally set one minute chart for bots, but you can use other charts for manual trading. The signal will be delayed by one bar but I have found configurations that still test well. Select a time frame in configuration for your indicator calculations. Select the strategy config for time frame (resolution). I like to use 5 and 15 minutes for scalping scenarios, but I am interested in hearing back from other community memebers. Optimize your indicator without filters : customize your settings for MACD and MFI that are profitable with your chart and selected time frame calculation. Try different Take Profits (try about 2-5%) and stop loss (try about 5-8%). See if your back test is profitable and continue to optimize. Use the Trend, RSI, ATR Filter to further refine your signals for entry. You will get less entries but you can increase your win ratio. You can use the open and close messages for a platform integration, but I choose to set mine up on the destination platform and let the platform close it. With certain platforms you cannot be sure what your entry point actually was compared to Trading View due to slippage and timing, so I let the platform decide when it is actually profitable. Limitations: this works rather well for short term, and does some good forward testing but back testing large data sets is a problem when switching from very small time frame to large time frame. For instance, finding a configuration that works on a one minute chart but then changing to a 1 hour chart means you lose some of your intra bar calclulations. There are some new features in pine script which might be able to address, this, but I have not had a chance to work on that issue.
Pine Script® strategy
by MauricioZuniga
14
Webhook Starter Kit [HullBuster] Introduction This is an open source strategy which provides a framework for webhook enabled projects. It is designed to work out-of-the-box on any instrument triggering on an intraday bar interval. This is a full featured script with an emphasis on actual trading at a brokerage through the TradingView alert mechanism and without requiring browser plugins. The source code is written in a self documenting style with clearly defined sections. The sections “communicate” with each other through state variables making it easy for the strategy to evolve and improve. This is an excellent place for Pine Language beginners to start their strategy building journey. The script exhibits many Pine Language features which will certainly ad power to your script building abilities. This script employs a basic trend follow strategy utilizing a forward pyramiding technique. Trend detection is implemented through the use of two higher time frame series. The market entry setup is a Simple Moving Average crossover. Positions exit by passing through conditional take profit logic. The script creates ten indicators including a Zscore oscillator to measure support and resistance levels. The indicator parameters are exposed through 47 strategy inputs segregated into seven sections. All of the inputs are equipped with detailed tool tips to help you get started. To improve the transition from simulation to execution, strategy.entry and strategy.exit calls show enhanced message text with embedded keywords that are combined with the TradingView placeholders at alert time. Thereby, enabling a single JSON message to generate multiple execution events. This is genius stuff from the Pine Language development team. Really excellent work! This document provides a sample alert message that can be applied to this script with relatively little modification. Without altering the code, the strategy inputs can alter the behavior to generate thousands of orders or simply a few dozen. It can be applied to crypto, stocks or forex instruments. A good way to look at this script is as a webhook lab that can aid in the development of your own endpoint processor, impress your co-workers and have hours of fun. By no means is a webhook required or even necessary to benefit from this script. The setups, exits, trend detection, pyramids and DCA algorithms can be easily replaced with more sophisticated versions. The modular design of the script logic allows you to incrementally learn and advance this script into a functional trading system that you can be proud of. Design This is a trend following strategy that enters long above the trend line and short below. There are five trend lines that are visible by default but can be turned off in Section 7. Identified, in frequency order, as follows: 1. - EMA in the chart time frame. Intended to track price pressure. Configured in Section 3. 2. - ALMA in the higher time frame specified in Section 2 Signal Line Period. 3. - Linear Regression in the higher time frame specified in Section 2 Signal Line Period. 4. - Linear Regression in the higher time frame specified in Section 2 Signal Line Period. 5. - DEMA in the higher time frame specified in Section 2 Trend Line Period. The Blue, Green and Orange lines are signal lines are on the same time frame. The time frame selected should be at least five times greater than the chart time frame. The Purple line represents the trend line for which prices above the line suggest a rising market and prices below a falling market. The time frame selected for the trend should be at least five times greater than the signal lines. Three oscillators are created as follows: 1. Stochastic - In the chart time frame. Used to enter forward pyramids. 2. Stochastic - In the Trend period. Used to detect exit conditions. 3. Zscore - In the Signal period. Used to detect exit conditions. The Stochastics are configured identically other than the time frame. The period is set in Section 2. Two Simple Moving Averages provide the trade entry conditions in the form of a crossover. Crossing up is a long entry and down is a short. This is in fact the same setup you get when you select a basic strategy from the Pine editor. The crossovers are configured in Section 3. You can see where the crosses are occurring by enabling Show Entry Regions in Section 7. The script has the capacity for pyramids and DCA. Forward pyramids are enabled by setting the Pyramid properties tab with a non zero value. In this case add on trades will enter the market on dips above the position open price. This process will continue until the trade exits. Downward pyramids are available in Crypto and Range mode only. In this case add on trades are placed below the entry price in the drawdown space until the stop is hit. To enable downward pyramids set the Pyramid Minimum Span In Section 1 to a non zero value. This implementation of Dollar Cost Averaging (DCA) triggers off consecutive losses. Each loss in a run increments a sequence number. The position size is increased as a multiple of this sequence. When the position eventually closes at a profit the sequence is reset. DCA is enabled by setting the Maximum DCA Increments In Section 1 to a non zero value. It should be noted that the pyramid and DCA features are implemented using a rudimentary design and as such do not perform with the precision of my invite only scripts. They are intended as a feature to stress test your webhook endpoint. As is, you will need to buttress the logic for it to be part of an automated trading system. It is for this reason that I did not apply a Martingale algorithm to this pyramid implementation. But, hey, it’s an open source script so there is plenty of room for learning and your own experimentation. How does it work The overall behavior of the script is governed by the Trading Mode selection in Section 1. It is the very first input so you should think about what behavior you intend for this strategy at the onset of the configuration. As previously discussed, this script is designed to be a trend follower. The trend being defined as where the purple line is predominately heading. In BiDir mode, SMA crossovers above the purple line will open long positions and crosses below the line will open short. If pyramiding is enabled add on trades will accumulate on dips above the entry price. The value applied to the Minimum Profit input in Section 1 establishes the threshold for a profitable exit. This is not a hard number exit. The conditional exit logic must be satisfied in order to permit the trade to close. This is where the effort put into the indicator calibration is realized. There are four ways the trade can exit at a profit: 1. Natural exit. When the blue line crosses the green line the trade will close. For a long position the blue line must cross under the green line (downward). For a short the blue must cross over the green (upward). 2. Alma / Linear Regression event. The distance the blue line is from the green and the relative speed the cross is experiencing determines this event. The activation thresholds are set in Section 6 and relies on the period and length set in Section 2. A long position will exit on an upward thrust which exceeds the activation threshold. A short will exit on a downward thrust. 3. Exponential event. The distance the yellow line is from the blue and the relative speed the cross is experiencing determines this event. The activation thresholds are set in Section 3 and relies on the period and length set in the same section. 4. Stochastic event. The purple line stochastic is used to measure overbought and over sold levels with regard to position exits. Signal line positions combined with a reading over 80 signals a long profit exit. Similarly, readings below 20 signal a short profit exit. Another, optional, way to exit a position is by Bale Out. You can enable this feature in Section 1. This is a handy way to reduce the risk when carrying a large pyramid stack. Instead of waiting for the entire position to recover we exit early (bale out) as soon as the profit value has doubled. There are lots of ways to implement a bale out but the method I used here provides a succinct example. Feel free to improve on it if you like. To see where the Bale Outs occur, enable Show Bale Outs in Section 7. Red labels are rendered below each exit point on the chart. There are seven selectable Trading Modes available from the drop down in Section 1: 1. Long - Uses the strategy.risk.allow_entry_in to execute long only trades. You will still see shorts on the chart. 2. Short - Uses the strategy.risk.allow_entry_in to execute short only trades. You will still see long trades on the chart. 3. BiDir - This mode is for margin trading with a stop. If a long position was initiated above the trend line and the price has now fallen below the trend, the position will be reversed after the stop is hit. Forward pyramiding is available in this mode if you set the Pyramiding value in the Properties tab. DCA can also be activated. 4. Flip Flop - This is a bidirectional trading mode that automatically reverses on a trend line crossover. This is distinctively different from BiDir since you will get a reversal even without a stop which is advantageous in non-margin trading. 5. Crypto - This mode is for crypto trading where you are buying the coins outright. In this case you likely want to accumulate coins on a crash. Especially, when all the news outlets are talking about the end of Bitcoin and you see nice deep valleys on the chart. Certainly, under these conditions, the market will be well below the purple line. No margin so you can’t go short. Downward pyramids are enabled for Crypto mode when two conditions are met. First the Pyramiding value in the Properties tab must be non zero. Second the Pyramid Minimum Span in Section 1 must be non zero. 6. Range - This is a counter trend trading mode. Longs are entered below the purple trend line and shorts above. Useful when you want to test your webhook in a market where the trend line is bisecting the signal line series. Remember that this strategy is a trend follower. It’s going to get chopped out in a range bound market. By turning on the Range mode you will at least see profitable trades while stuck in the range. However, when the market eventually picks a direction, this mode will sustain losses. This range trading mode is a rudimentary implementation that will need a lot of improvement if you want to create a reliable switch hitter (trend/range combo). 7. No Trade. Useful when setting up the trend lines and the entry and exit is not important. Once in the trade, long or short, the script tests the exit condition on every bar. If not a profitable exit then it checks if a pyramid is required. As mentioned earlier, the entry setups are quite primitive. Although they can easily be replaced by more sophisticated algorithms, what I really wanted to show is the diminished role of the position entry in the overall life of the trade. Professional traders spend much more time on the management of the trade beyond the market entry. While your trade entry is important, you can get in almost anywhere and still land a profitable exit. If DCA is enabled, the size of the position will increase in response to consecutive losses. The number of times the position can increase is limited by the number set in Maximum DCA Increments of Section 1. Once the position breaks the losing streak the trade size will return the default quantity set in the Properties tab. It should be noted that the Initial Capital amount set in the Properties tab does not affect the simulation in the same way as a real account. In reality, running out of money will certainly halt trading. In fact, your account would be frozen long before the last penny was committed to a trade. On the other hand, TradingView will keep running the simulation until the current bar even if your funds have been technically depleted. Entry and exit use the strategy.entry and strategy.exit calls respectfully. The alert_message parameter has special keywords that the endpoint expects to properly calculate position size and message sequence. The alert message will embed these keywords in the JSON object through the {{strategy.order.alert_message}} placeholder. You should use whatever keywords are expected from the endpoint you intend to webhook in to. Webhook Integration The TradingView alerts dialog provides a way to connect your script to an external system which could actually execute your trade. This is a fantastic feature that enables you to separate the data feed and technical analysis from the execution and reporting systems. Using this feature it is possible to create a fully automated trading system entirely on the cloud. Of course, there is some work to get it all going in a reliable fashion. Being a strategy type script place holders such as {{strategy.position_size}} can be embedded in the alert message text. There are more than 10 variables which can write internal script values into the message for delivery to the specified endpoint. Entry and exit use the strategy.entry and strategy.exit calls respectfully. The alert_message parameter has special keywords that my endpoint expects to properly calculate position size and message sequence. The alert message will embed these keywords in the JSON object through the {{strategy.order.alert_message}} placeholder. You should use whatever keywords are expected from the endpoint you intend to webhook in to. Here is an excerpt of the fields I use in my webhook signal: "broker_id": "kraken", "account_id": "XXX XXXX XXXX XXXX", "symbol_id": "XMRUSD", "action": "{{strategy.order.action}}", "strategy": "{{strategy.order.id}}", "lots": "{{strategy.order.contracts}}", "price": "{{strategy.order.price}}", "comment": "{{strategy.order.alert_message}}", "timestamp": "{{time}}" Though TradingView does a great job in dispatching your alert this feature does come with a few idiosyncrasies. Namely, a single transaction call in your script may cause multiple transmissions to the endpoint. If you are using placeholders each message describes part of the transaction sequence. A good example is closing a pyramid stack. Although the script makes a single strategy.close() call, the endpoint actually receives a close message for each pyramid trade. The broker, on the other hand, only requires a single close. The incongruity of this situation is exacerbated by the possibility of messages being received out of sequence. Depending on the type of order designated in the message, a close or a reversal. This could have a disastrous effect on your live account. This broker simulator has no idea what is actually going on at your real account. Its just doing the job of running the simulation and sending out the computed results. If your TradingView simulation falls out of alignment with the actual trading account lots of really bad things could happen. Like your script thinks your are currently long but the account is actually short. Reversals from this point forward will always be wrong with no one the wiser. Human intervention will be required to restore congruence. But how does anyone find out this is occurring? In closed systems engineering this is known as entropy. In practice your webhook logic should be robust enough to detect these conditions. Be generous with the placeholder usage and give the webhook code plenty of information to compare states. Both issuer and receiver. Don’t blindly commit incoming signals without verifying system integrity. Setup The following steps provide a very brief set of instructions that will get you started on your first configuration. After you’ve gone through the process a couple of times, you won’t need these anymore. It’s really a simple script after all. I have several example configurations that I used to create the performance charts shown. I can share them with you if you like. Of course, if you’ve modified the code then these steps are probably obsolete. There are 47 inputs divided into seven sections. For the most part, the configuration process is designed to flow from top to bottom. Handy, tool tips are available on every field to help get you through the initial setup. Step 1. Input the Base Currency and Order Size in the Properties tab. Set the Pyramiding value to zero. Step 2. Select the Trading Mode you intend to test with from the drop down in Section 1. I usually select No Trade until I’ve setup all of the trend lines, profit and stop levels. Step 3. Put in your Minimum Profit and Stop Loss in the first section. This is in pips or currency basis points (chart right side scale). Remember that the profit is taken as a conditional exit not a fixed limit. The actual profit taken will almost always be greater than the amount specified. The stop loss, on the other hand, is indeed a hard number which is executed by the TradingView broker simulator when the threshold is breached. Step 4. Apply the appropriate value to the Tick Scalar field in Section 1. This value is used to remove the pipette from the price. You can enable the Summary Report in Section 7 to see the TradingView minimum tick size of the current chart. Step 5. Apply the appropriate Price Normalizer value in Section 1. This value is used to normalize the instrument price for differential calculations. Basically, we want to increase the magnitude to significant digits to make the numbers more meaningful in comparisons. Though I have used many normalization techniques, I have always found this method to provide a simple and lightweight solution for less demanding applications. Most of the time the default value will be sufficient. The Tick Scalar and Price Normalizer value work together within a single calculation so changing either will affect all delta result values. Step 6. Turn on the trend line plots in Section 7. Then configure Section 2. Try to get the plots to show you what’s really happening not what you want to happen. The most important is the purple trend line. Select an interval and length that seem to identify where prices tend to go during non-consolidation periods. Remember that a natural exit is when the blue crosses the green line. Step 7. Enable Show Event Regions in Section 7. Then adjust Section 6. Blue background fills are spikes and red fills are plunging prices. These measurements should be hard to come by so you should see relatively few fills on the chart if you’ve set this up as intended. Section 6 includes the Zscore oscillator the state of which combines with the signal lines to detect statistically significant price movement. The Zscore is a zero based calculation with positive and negative magnitude readings. You want to input a reasonably large number slightly below the maximum amplitude seen on the chart. Both rise and fall inputs are entered as a positive real number. You can easily use my code to create a separate indicator if you want to see it in action. The default value is sufficient for most configurations. Step 8. Turn off Show Event Regions and enable Show Entry Regions in Section 7. Then adjust Section 3. This section contains two parts. The entry setup crossovers and EMA events. Adjust the crossovers first. That is the Fast Cross Length and Slow Cross Length. The frequency of your trades will be shown as blue and red fills. There should be a lot. Then turn off Show Event Regions and enable Display EMA Peaks. Adjust all the fields that have the word EMA. This is actually the yellow line on the chart. The blue and red fills should show much less than the crossovers but more than event fills shown in Step 7. Step 9. Change the Trading Mode to BiDir if you selected No Trades previously. Look on the chart and see where the trades are occurring. Make adjustments to the Minimum Profit and Stop Offset in Section 1 if necessary. Wider profits and stops reduce the trade frequency. Step 10. Go to Section 4 and 5 and make fine tuning adjustments to the long and short side. Example Settings To reproduce the performance shown on the chart please use the following configuration: (Bitcoin on the Kraken exchange) 1. Select XBTUSD Kraken as the chart symbol. 2. On the properties tab set the Order Size to: 0.01 Bitcoin 3. On the properties tab set the Pyramiding to: 12 4. In Section 1: Select “Crypto” for the Trading Model 5. In Section 1: Input 2000 for the Minimum Profit 6. In Section 1: Input 0 for the Stop Offset (No Stop) 7. In Section 1: Input 10 for the Tick Scalar 8. In Section 1: Input 1000 for the Price Normalizer 9. In Section 1: Input 2000 for the Pyramid Minimum Span 10. In Section 1: Check mark the Position Bale Out 11. In Section 2: Input 60 for the Signal Line Period 12. In Section 2: Input 1440 for the Trend Line Period 13. In Section 2: Input 5 for the Fast Alma Length 14. In Section 2: Input 22 for the Fast LinReg Length 15. In Section 2: Input 100 for the Slow LinReg Length 16. In Section 2: Input 90 for the Trend Line Length 17. In Section 2: Input 14 Stochastic Length 18. In Section 3: Input 9 Fast Cross Length 19. In Section 3: Input 24 Slow Cross Length 20. In Section 3: Input 8 Fast EMA Length 21. In Section 3: Input 10 Fast EMA Rise NetChg 22. In Section 3: Input 1 Fast EMA Rise ROC 23. In Section 3: Input 10 Fast EMA Fall NetChg 24. In Section 3: Input 1 Fast EMA Fall ROC 25. In Section 4: Check mark the Long Natural Exit 26. In Section 4: Check mark the Long Signal Exit 27. In Section 4: Check mark the Long Price Event Exit 28. In Section 4: Check mark the Long Stochastic Exit 29. In Section 5: Check mark the Short Natural Exit 30. In Section 5: Check mark the Short Signal Exit 31. In Section 5: Check mark the Short Price Event Exit 32. In Section 5: Check mark the Short Stochastic Exit 33. In Section 6: Input 120 Rise Event NetChg 34. In Section 6: Input 1 Rise Event ROC 35. In Section 6: Input 5 Min Above Zero ZScore 36. In Section 6: Input 120 Fall Event NetChg 37. In Section 6: Input 1 Fall Event ROC 38. In Section 6: Input 5 Min Below Zero ZScore In this configuration we are trading in long only mode and have enabled downward pyramiding. The purple trend line is based on the day (1440) period. The length is set at 90 days so it’s going to take a while for the trend line to alter course should this symbol decide to node dive for a prolonged amount of time. Your trades will still go long under those circumstances. Since downward accumulation is enabled, your position size will grow on the way down. The performance example is Bitcoin so we assume the trader is buying coins outright. That being the case we don’t need a stop since we will never receive a margin call. New buy signals will be generated when the price exceeds the magnitude and speed defined by the Event Net Change and Rate of Change. Feel free to PM me with any questions related to this script. Thank you and happy trading! CFTC RULE 4.41 These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.
Pine Script® strategy
by tradingtudi
11
(IK) Base Break BuyThis strategy first calculates areas of support (bases), and then enters trades if that support is broken. The idea is to profit off of retracement. Dollar-cost-averaging safety orders are key here. This strategy takes into account a .1% commission, and tests are done with an initial capital of 100.00 USD. This only goes long. The strategy is highly customizable. I've set the default values to suit ETH/USD 15m. If you're trading this on another ticker or timeframe, make sure to play around with the settings. There is an explanation of each input in the script comments. I found this to be profitable across most 'common sense' values for settings, but tweaking led to some pretty promising results. I leaned more towards high risk/high trade volume. Always remember though: historical performance is no guarantee of future behavior . Keep settings within your personal risk tolerance, even if it promises better profit. Anyone can write a 100% profitable script if they assume price always eventually goes up. Check the script comments for more details, but, briefly, you can customize: -How many bases to keep track of at once -How those bases are calculated -What defines a 'base break' -Order amounts -Safety order count -Stop loss Here's the basic algorithm: -Identify support. --Have previous candles found bottoms in the same area of the current candle bottom? --Is this support unique enough from other areas of support? -Determine if support is broken. --Has the price crossed under support quickly and with certainty? -Enter trade with a percentage of initial capital. -Execute safety orders if price continues to drop. -Exit trade at profit target or stop loss. Take profit is dynamic and calculated on order entry. The bigger the 'break', the higher your take profit percentage. This target percentage is based on average position size, so as safety orders are filled, and average position size comes down, the target profit becomes easier to reach. Stop loss can be calculated one of two ways, either a static level based on initial entry, or a dynamic level based on average position size. If you use the latter (default), be aware, your real losses will be greater than your stated stop loss percentage . For example: -stop loss = 15%, capital = 100.00, safety order threshold = 10% -you buy $50 worth of shares at $1 - price average is $1 -you safety $25 worth of shares at $0.9 - price average is $0.966 -you safety $25 worth of shares at $0.8. - price average is $0.925 -you get stopped out at 0.925 * (1-.15) = $0.78625, and you're left with $78.62. This is a realized loss of ~21.4% with a stop loss set to 15%. The larger your safety order threshold, the larger your real loss in comparison to your stop loss percentage, and vice versa. Indicator plots show the calculated bases in white. The closest base below price is yellow. If that base is broken, it turns purple. Once a trade is entered, profit target is shown in silver and stop loss in red.
Pine Script® strategy
by tapRoot_coding
14
(IK) Grid ScriptThis is my take on a grid trading strategy. From Investopedia: "Grid trading is most commonly associated with the foreign exchange market. Overall the technique seeks to capitalize on normal price volatility in an asset by placing buy and sell orders at certain regular intervals above and below a predefined base price." This strategy is best used on sideways markets, without a definitive up or down major trend. Because it doesn't rely on huge vertical movement, this strategy is great for small timeframes. It only goes long. I've set initial_capital to 100 USD. default_qty_value should be your initial capital divided by your amount of grid lines. I'm also assuming a 0.1% commission per trade. Here's the basic algorithm: - Create a grid based on an upper-bound (strong resistance) and a lower-bound (strong support) - Grid lines are spaced evenly between these two bounds. (I recommend anywhere between 5-10 grid lines, but this script lets you use up to 15. More gridlines = more/smaller trades) - Identify nearest gridline above and below current price (ignoring the very closest grid line) - If price crosses under a near gridline, buy and recalculate near gridlines - If price crosses over a near gridline, sell and recalculate near gridlines - Trades are entered and exited based on a FIFO system. So if price falls 3 grid lines (buy-1, buy-2, buy-3), and subsequently crosses above one grid line, only the first trade will exit (sell-1). If it falls again, it will enter a new trade (buy-4), and if it crosses above again it will sell the original second trade (sell-2). The amount of trades you can be in at once are based on the amount of grid lines you have. This strategy has no built-in stop loss! This is not a 'set-it-and-forget-it" script. Make sure that price remains within the bounds of your grid. If prices exits above the grid, you're in the money, but you won't be making any more trades. If price exits below the grid, you're 100% staked in whatever you happen to be trading. This script is more complicated than my last one, but should be more user friendly. Make sure to correctly set your lower-bound and upper-bound based on strong support and resistance (the default values for these are probably going to be meaningless). If you change your "Grid Quantity" (amount of grid lines) make sure to also change your 'Order Size' property under settings for proper test results (or default_qty_value in the strategy() declaration).
Pine Script® strategy
by tapRoot_coding
20
Gyspy Bot Trade Engine - V1.2B - Strategy 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Ultimate Strategy & Backtest Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙 1. Executive Summary & Architecture Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script environment. While most strategies rely on a single dominant indicator (like an RSI cross or a MACD flip) to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm. The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only executes a trade entry when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction before capital is committed. Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to force-exit positions, overriding standard stops to preserve capital during Black Swan events. 2. ⚠️ The Philosophy of "Curve Fitting" (Must Read) One must be careful when applying Gypsy Bot to new pairs or charts. To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the backtest shows a 100% win rate, only to have the strategy fail immediately in live markets because it was tuned to historical noise rather than market structure. To use this engine successfully, you must adopt a specific optimization mindset: Ignore Raw Net Profit: Do not tune for the highest dollar amount. A strategy that makes $1M in the backtest but has a 40% drawdown is useless. Prioritize Stability: Look for a high Profit Factor (1.5+), a high Percent Profitable, and a smooth equity curve. Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Parameters that worked perfectly in 2021 may fail in 2024. Gypsy Bot settings should be reviewed and adjusted at regular intervals (e.g., quarterly) to ensure the voting logic remains aligned with current market volatility. Timeframe Recommendations: Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets. 3. The Voting Mechanism: How Entries Are Generated The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings). The engine constantly monitors the output of all enabled Modules. Long Votes: GoLongCount Short Votes: GoShortCount If you have 10 Modules enabled, and you set ActivateOrders to 7: The engine will ONLY trigger a Buy Entry if 7 or more modules return a valid "Buy" signal on the same closed candle. If only 6 modules agree, the trade is rejected. This allows you to mix "Leading" indicators (Oscillators) with "Lagging" indicators (Moving Averages) to create a high-probability entry signal that requires momentum, volume, and trend to all be in alignment. 4. Technical Deep Dive: The 12 Modules Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading. Module 1: Modified Slope Angle (MSA) Logic: Calculates the geometric angle of a moving average relative to the timeline. Function: It filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold. This helps avoid entering trades during weak drifts that often precede a reversal. Module 2: Correlation Trend Indicator (CTI) Logic: Based on John Ehlers' work, this measures how closely the current price action correlates to a straight line (a perfect trend). Function: It outputs a confidence score (-1 to 1). Gypsy Bot uses this to ensure that we are not just moving up, but moving up with high statistical correlation, reducing fake-outs. Module 3: Ehlers Roofing Filter Logic: A sophisticated spectral filter that combines a High-Pass filter (to remove long-term drift) with a Super Smoother (to remove high-frequency noise). Function: It attempts to isolate the "Roof" of the price action. It is excellent at catching cyclical turning points before standard moving averages react. Module 4: Forecast Oscillator Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is. Function: When the Forecast Oscillator crosses its zero line, it indicates that the regression trend has flipped. We offer both "Aggressive" and "Conservative" calculation modes for this module. Module 5: Chandelier ATR Stop Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from the highest high (for longs) or lowest low (for shorts). Function: Used here as an entry filter. If price is above the Chandelier line, the trend is Bullish. It also includes a "Bull/Bear Qualifier" check to ensure structural support. Module 6: Crypto Market Breadth (CMB) Logic: This is a macro-filter. It pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts) across different exchanges. Function: It calculates a "Market Health" percentage. If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade, ensuring you don't buy into a "fake" rally driven by a single asset. Module 7: Directional Index Convergence (DIC) Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices. Function: Identifies when trend strength is expanding. A buy signal is generated only when the positive directional movement overpowers the negative movement with expanding momentum. Module 8: Market Thrust Indicator (MTI) Logic: A volume-weighted breadth indicator. It uses Advance/Decline data and Up/Down Volume data. Function: This is one of the most powerful modules. It confirms that price movement is supported by actual volume flow. We recommend using the "SSMA" (Super Smoother) MA Type for the cleanest signals on the 4H chart. Module 9: Simple Ichimoku Cloud Logic: Traditional Japanese trend analysis using the Tenkan-sen and Kijun-sen. Function: Checks for a "Kumo Breakout." Price must be fully above the Cloud (for longs) or below it (for shorts). This is a classic "trend confirmation" module. Module 10: Simple Harmonic Oscillator Logic: Analyzes the harmonic wave properties of price action to detect cyclical tops and bottoms. Function: Serves as a counter-trend or early-reversal detector. It tries to identify when a cycle has bottomed out (for buys) or topped out (for sells) before the main trend indicators catch up. Module 11: HSRS Compression / Super AO Logic: Two options in one. HSRS: Hirashima Sugita Resistance Support. Detects volatility compression (squeezes) relative to dynamic support/resistance bands. Super AO: A combination of the Awesome Oscillator and SuperTrend logic. Function: Great for catching explosive moves that result from periods of low volatility (consolidation). Module 12: Fisher Transform (MTF) Logic: Converts price data into a Gaussian normal distribution. Function: Identifies extreme price deviations. This module uses Multi-Timeframe (MTF) logic to look at higher-timeframe trends (e.g., looking at the Daily Fisher while trading the 4H chart) to ensure you aren't trading against the major trend. 5. Global Inhibitors (The Veto Power) Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors. If any of these are triggered, the trade is blocked. Bitcoin Halving Logic: Hardcoded dates for past and projected future Bitcoin halvings (up to 2040). Trading is inhibited or restricted during the chaotic weeks immediately surrounding a Halving event to avoid volatility crushes. Miner Capitulation: Uses Hash Rate Ribbons (Moving averages of Hash Rate). If miners are capitulating (Shutting down rigs due to unprofitability), the engine flags a "Bearish" regime and can flip logic to Short-only or flat. ADX Filter (Flat Market Protocol): If the Average Directional Index (ADX) is below a specific threshold (e.g., 20), the market is deemed "Flat/Choppy." The bot will refuse to open trend-following trades in a flat market. CryptoCap Trend: Checks the total Crypto Market Cap chart. If the broad market is in a downtrend, it can inhibit Long entries on individual altcoins. 6. Risk Management & The Dump Protection Team (DPT) Gypsy Bot separates "Entry Logic" from "Risk Management Logic." Dump Protection Team (DPT) This is a specialized logic branch designed to save the account during Black Swan events. Nuke Protection: If the DPT detects a volatility signature consistent with a flash crash, it overrides all other logic and forces an immediate exit. Moon Protection: If a parabolic pump is detected that violates statistical probability (Bollinger deviations), DPT can force a profit take before the inevitable correction. Advanced Adaptive Trailing Stop (AATS) Unlike a static trailing stop (e.g., "trail by 5%"), AATS is dynamic. Penthouse Level: If price is at the top of the HSRS channel (High Volatility), the stop loosens to allow for wicks. Dungeon Level: If price is compressed at the bottom, the stop tightens to protect capital. Staged Take Profits TP1: Scalp a portion (e.g., 10%) to cover fees and secure a win. TP2: Take the bulk of profit. TP3: Leave a "Runner" position with a loose trailing stop to catch "Moon" moves. 7. Recommended Setup Guide When applying Gypsy Bot to a new chart, follow this sequence: Set Timeframe: 4 Hours (4H). Reset: Turn OFF Trailing Stop, Stop Loss, and Take Profits. (We want to see raw entry performance first). Tune DPT: Adjust "Dump/Moon Protection" inputs first. These have the highest impact on net performance. Tune Module 8 (MTI): This module is a heavy filter. Experiment with the MA Type (SSMA is recommended). Select Modules: Enable/Disable modules 1-12 based on the asset's personality (Trending vs. Ranging). Voting Threshold: Adjust ActivateOrders. A lower number = More Trades (Aggressive). A higher number = Fewer, higher conviction trades (Conservative). Final Polish: Re-enable Stop Losses, Trailing Stops, and Staged Take Profits to smooth the equity curve and define your max risk per trade. 8. Technical Specs Engine Version: Pine Script V6 Repainting: This strategy uses Closed Candle data for all Risk Management and Entry decisions. This ensures that Backtest results align closely with real-time behavior (no repainting of historical signals). Alerts: This script generates Strategy alerts. If you require visual-only alerts, see the source code header for instructions on switching to "Study" (Indicator) mode. Disclaimer: This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Use this tool to assist your own decision-making, not to replace it. 9. About Signal Lynx Automation for the Night-Shift Nation 🌙 Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management. We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to: Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search. License: Mozilla Public License 2.0 (Open Source). If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Pine Script® strategy
by SignalLynx
The Oracle: Dip & Top Adaptive Sniper [Hakan Yorganci]█ OVERVIEW The Oracle: Dip & Top Adaptive Sniper is a precision-focused trend trading strategy designed to solve the biggest problem in swing trading: Timing. Most trend-following strategies chase price ("FOMO"), buying when the asset is already overextended. The Oracle takes a different approach. It adopts a "Sniper" mentality: it identifies a strong macro trend but patiently waits for a Mean Reversion (pullback) to execute an entry at a discounted price. By combining the structural strength of Moving Averages (SMA 50/200) with the momentum precision of RSI and the volatility filtering of ADX, this script filters out noise and targets high-probability setups. █ HOW IT WORKS This strategy operates on a strictly algorithmic protocol known as "The Yorganci Protocol," which involves three distinct phases: Filter, Target, and Execute. 1. The Macro Filter (Trend Identification) * SMA 200 Rule: By default, the strategy only scans for buy signals when the price is trading above the 200-period Simple Moving Average. This ensures we are always trading in the direction of the long-term bull market. * Adaptive Switch: A new feature allows users to toggle the Only Buy Above SMA 200? filter OFF. This enables the strategy to hunt for oversold bounces (dead cat bounces) even during bearish or neutral market structures. 2. The Volatility Filter (ADX Integration) * Sideways Protection: One of the main weaknesses of moving average strategies is "whipsaw" losses during choppy, ranging markets. * Solution: The Oracle utilizes the ADX (Average Directional Index). It will BLOCK any trade entry if the ADX is below the threshold (Default: 20). This ensures capital is only deployed when a genuine trend is present. 3. The Sniper Entry (Buying the Dip) * Instead of buying on breakout strength (e.g., RSI > 60), The Oracle waits for the RSI Moving Average to dip into the "Value Zone" (Default: 45) and cross back up. This technique allows for tighter stops and higher Risk/Reward ratios compared to traditional breakout systems. █ EXIT STRATEGY The Oracle employs a dynamic dual-exit mechanism to maximize gains and protect capital: * Take Profit (The Peak): The strategy monitors RSI heat. When the RSI Moving Average breaches the Overbought Threshold (Default: 75), it signals a "Take Profit", securing gains near the local top before a potential reversal. * Stop Loss (Trend Invalidated): If the market structure fails and the price closes below the 50-period SMA, the position is immediately closed to prevent deep drawdowns. █ SETTINGS & CONFIGURATION * Moving Averages: Fully customizable lengths for Support (SMA 50) and Trend (SMA 200). * Trend Filter: Checkbox to enable/disable the "Bull Market Only" rule. * RSI Thresholds: * Sniper Buy Level: Adjustable (Default: 45). Lower values = Deeper dips, fewer trades. * Peak Sell Level: Adjustable (Default: 75). Higher values = Longer holds, potentially higher profit. * ADX Filter: Checkbox to enable/disable volatility filtering. █ BEST PRACTICES * Timeframe: Designed primarily for 4H (4-Hour) charts for swing trading. It can also be used on 1H for more frequent signals. * Assets: Highly effective on trending assets such as Bitcoin (BTC), Ethereum (ETH), and high-volume Altcoins. * Risk Warning: This strategy is designed for "Long Only" spot or leverage trading. Always use proper risk management. █ CREDITS * Original Concept: Inspired by the foundational work of Murat Besiroglu (@muratkbesiroglu). * Algorithm Development & Enhancements: Developed by Hakan Yorganci (@hknyrgnc). * Modifications include: Integration of ADX filters, Mean Reversion entry logic (RSI Dip), and Dynamic Peak Profit taking.
Pine Script® strategy
by hknyrgnc
EMA 12-26-100 Momentum Strategy# Triple EMA Multi-Signal Momentum Strategy ## 📊 Overview **Triple EMA Multi-Signal** is a comprehensive trend-following momentum strategy designed specifically for cryptocurrency markets. It combines multiple technical indicators and signal types to identify high-probability trading opportunities while maintaining strict risk management protocols. The strategy excels in trending markets and uses adaptive position sizing with trailing stops to maximize profits during strong trends while protecting capital during choppy conditions. ## 🎯 Core Algorithm ### Triple EMA System The strategy employs a three-layer EMA system to identify trend direction and strength: - **Fast EMA (12)**: Quick response to price changes - **Slow EMA (26)**: Confirmation of trend direction - **Trend EMA (100)**: Overall market bias filter Trades are only taken when all three EMAs align in the same direction, ensuring we trade with the dominant trend. ### Multi-Signal Confirmation (8 Signal Types) The strategy requires at least 1-2 confirmed signals from multiple independent sources before entering a position: 1. **EMA Crossover** - Fast EMA crossing Slow EMA (primary signal) 2. **MACD Cross** - MACD line crossing signal line (momentum confirmation) 3. **RSI Reversal** - RSI bouncing from oversold/overbought zones 4. **Price Action** - Strong bullish/bearish candles (>60% of range) 5. **Volume Spike** - Above-average volume confirmation 6. **Breakout** - Price breaking 20-period high/low with volume 7. **Pullback to EMA** - Trend continuation after healthy retracement 8. **Bollinger Bounce** - Price bouncing from BB bands This multi-signal approach significantly reduces false signals and improves win rate. ## 💰 Risk Management ### Position Sizing - Default: 20-25% of equity per trade - Adjustable based on risk tolerance - Smaller positions recommended for leveraged trading ### Stop Loss & Take Profit - **Stop Loss**: 2.0% (tight control of risk) - **Take Profit**: 5.5% (2.75:1 reward-to-risk ratio) - Both levels are fixed at entry to avoid emotional decisions ### Trailing Stop System - Activates after 1.8% profit - Trails at 1.3% below current price - Locks in profits during extended trends - Automatically adjusts as price moves in your favor ### Maximum Hold Time - 36-48 hours maximum (configurable) - Designed to minimize funding rate costs on futures - Forces position closure to avoid excessive exposure - Helps maintain capital velocity ## 📈 Key Features ### Trend Filters - **ADX Filter**: Ensures sufficient trend strength (threshold: 20) - **EMA Alignment**: All three EMAs must confirm trend direction - **RSI Boundaries**: Avoids extreme overbought/oversold entries ### Volume Analysis - Volume must exceed 20-period moving average - Configurable multiplier (default: 1.0x) - Helps identify institutional participation ### Automatic Exit Conditions 1. Take Profit target reached 2. Stop Loss triggered 3. Trailing stop activated 4. Trend reversal (EMA cross in opposite direction) 5. Maximum hold time exceeded ## 🎮 Recommended Settings ### For Spot Trading (Conservative) ``` Position Size: 15-20% Stop Loss: 2.5% Take Profit: 6.0% Max Hold: 72 hours Leverage: 1x ``` ### For Futures 3-5x Leverage (Balanced) ``` Position Size: 12-15% Stop Loss: 2.0% Take Profit: 5.5% Max Hold: 36 hours Trailing: Active ``` ### For Aggressive Trading 5-10x (High Risk) ``` Position Size: 8-12% Stop Loss: 1.5% Take Profit: 4.5% Max Hold: 24 hours ADX Filter: Disabled ``` ## 📊 Performance Metrics ### Backtested Results (BTC/USDT 1H, 2 years) - **Total Return**: ~19% (spot) / ~75% (5x leverage)* - **Total Trades**: 240-300 - **Win Rate**: 49-52% - **Profit Factor**: 1.25-1.50 - **Max Drawdown**: ~18-22% - **Average Trade**: 0.5-3 days *Leverage results exclude funding rates and real-world slippage ### Optimal Timeframes - **1 Hour**: Best for active trading (recommended) - **4 Hour**: More stable, fewer signals - **15 Min**: High frequency (requires monitoring) ### Best Performing Assets - BTC/USDT (most tested) - ETH/USDT - Major altcoins with good liquidity - Not recommended for low-cap or illiquid pairs ## ⚙️ How to Use 1. **Add to Chart**: Apply strategy to 1H BTC/USDT chart 2. **Adjust Settings**: Configure risk parameters based on your preference 3. **Review Signals**: Green = Long, Red = Short, labels show signal count 4. **Monitor Performance**: Check strategy tester for detailed statistics 5. **Optimize**: Use strategy optimization to find best parameters for your market ## 🎨 Visual Indicators The strategy provides clear visual feedback: - **EMA Lines**: Blue (Fast), Red (Slow), Orange (Trend) - **BUY/SELL Labels**: Show entry points with signal count - **Stop/Target Lines**: Red (SL), Green (TP) displayed during active trades - **Background Color**: Light green (long), light red (short) when in position - **Info Panel**: Shows current trend, RSI, ADX, and volume status ## ⚠️ Important Notes ### Risk Disclaimer - This strategy is for educational purposes only - Past performance does not guarantee future results - Cryptocurrency trading involves substantial risk - Only trade with capital you can afford to lose - Always use proper position sizing and risk management ### Limitations - Performs poorly in sideways/choppy markets - Requires sufficient liquidity for best execution - Backtests do not include: - Real-world slippage (especially during volatility) - Funding rates (for perpetual futures) - Exchange downtime or connection issues - Emotional trading decisions ### For Futures Trading If using this strategy on futures with leverage: - Reduce position size proportionally to leverage - Account for funding rates (~0.01% per 8h) - Set max hold time to minimize funding costs - Use lower leverage (3-5x max recommended) - Monitor liquidation price carefully ## 🔧 Customization All parameters are fully customizable: - EMA periods (fast/slow/trend) - MACD settings (12/26/9) - RSI levels (30/70) - Stop Loss / Take Profit percentages - Trailing stop activation and offset - Volume multiplier - ADX threshold - Maximum hold time ## 📚 Strategy Logic The strategy follows this decision tree: ``` 1. Check Trend Direction (EMA alignment) ↓ 2. Scan for Entry Signals (8 types) ↓ 3. Confirm with Filters (ADX, Volume, RSI) ↓ 4. Enter Position with Fixed SL/TP ↓ 5. Monitor for Exit Conditions: - TP Hit → Close with profit - SL Hit → Close with loss - Trailing Active → Follow price - Trend Reversal → Close position - Max Time → Force close ``` ## 🎓 Best Practices 1. **Start Conservative**: Use smaller position sizes initially 2. **Track Performance**: Monitor actual vs backtested results 3. **Optimize Regularly**: Market conditions change, adapt parameters 4. **Combine with Analysis**: Don't rely solely on automated signals 5. **Manage Emotions**: Stick to the system, avoid manual overrides 6. **Paper Trade First**: Test on demo before risking real capital ## 📞 Support & Updates This strategy is actively maintained and updated based on: - Market condition changes - User feedback and suggestions - Performance optimization - Bug fixes and improvements ## 🏆 Conclusion Triple EMA Multi-Signal Strategy offers a robust, systematic approach to cryptocurrency trading by combining trend following, momentum indicators, and strict risk management. Its multi-signal confirmation system helps filter false signals while the trailing stop mechanism captures extended trends. The strategy is suitable for both manual traders looking for high-probability setups and algorithmic traders seeking a proven systematic approach. **Remember**: No strategy wins 100% of the time. Success comes from consistent application, proper risk management, and continuous adaptation to changing market conditions. --- *Version: 1.0* *Last Updated: November 2025* *Tested on: BTC/USDT, ETH/USDT (1H, 4H timeframes)* *Recommended Capital: $5,000+ for optimal position sizing*
Pine Script® strategy
by RomanEnlil
Aurum DCX AVE Gold and Silver StrategySummary in one paragraph Aurum DCX AVE is a volatility break strategy for gold and silver on intraday and swing timeframes. It aligns a new Directional Convexity Index with an Adaptive Volatility Envelope and an optional USD/DXY bias so trades appear only when direction quality and expansion agree. It is original because it fuses three pieces rarely combined in one model for metals: a convexity aware trend strength score, a percentile based envelope that widens with regime heat, and an intermarket DXY filter. Scope and intent • Markets. Gold and silver futures or spot, other liquid commodities, major indices • Timeframes. Five minutes to one day. Defaults to 30min for swing pace • Default demo used in this publication. TVC:GOLD on 30m • Purpose. Enter confirmed volatility breaks while muting chop using regime heat and USD bias • Limits. This is a strategy. Orders are simulated on standard candles only Originality and usefulness • Unique fusion. DCX combines DI strength with path efficiency and curvature. AVE blends ATR with a high TR percentile and widens with DCX heat. DXY adds an intermarket bias • Failure mode addressed. False starts inside compression and unconfirmed breakouts during USD swings • Testability. Each component has a named input. Entry names L and S are visible in the list of trades • Portable yardstick. Weekly ATR for stops and R multiples for targets • Open source. Method and implementation are disclosed for community review Method overview in plain language You score direction quality with DCX, size an adaptive envelope with a blend of ATR and a high TR percentile, and only allow breaks that clear the band while DCX is above a heat threshold in the same direction. An optional DXY filter favors long when USD weakens and short when USD strengthens. Orders are bracketed with a Weekly ATR stop and an R multiple target, with optional trailing to the envelope. Base measures • Range basis. True Range and ATR over user windows. A high TR percentile captures expansion tails used by AVE • Return basis. Not required Components • Directional Convexity Index DCX. Measures directional strength with DX, multiplies by path efficiency, blends a curvature term from acceleration, scales to 0 to 100, and uses a rise window • Adaptive Volatility Envelope AVE. Midline ALMA or HMA or EMA plus bands sized by a blend of ATR and a high TR percentile. The blend weight follows volatility of volatility. Band width widens with DCX heat • DXY Bias optional. Daily EMA trend of DXY. Long bias when USD weakens. Short bias when USD strengthens • Risk block. Initial stop equals Weekly ATR times a multiplier. Target equals an R multiple of the initial risk. Optional trailing to AVE band Fusion rule • All gates must pass. DCX above threshold and rising. Directional lead agrees. Price breaks the AVE band in the same direction. DXY bias agrees when enabled Signal rule • Long. Close above AVE upper and DCX above threshold and DCX rising and plus DI leads and DXY bias is bearish • Short. Close below AVE lower and DCX above threshold and DCX falling and minus DI leads and DXY bias is bullish • Exit and flip. Bracket exit at stop or target. Optional trailing to AVE band Inputs with guidance Setup • Symbol. Default TVC:GOLD (Correlation Asset for internal logic) • Signal timeframe. Blank follows the chart • Confirm timeframe. Default 1 day used by the bias block Directional Convexity Index • DCX window. Typical 10 to 21. Higher filters more. Lower reacts earlier • DCX rise bars. Typical 3 to 6. Higher demands continuation • DCX entry threshold. Typical 15 to 35. Higher avoids soft moves • Efficiency floor. Typical 0.02 to 0.06. Stability in quiet tape • Convexity weight 0..1. Typical 0.25 to 0.50. Higher gives curvature more influence Adaptive Volatility Envelope • AVE window. Typical 24 to 48. Higher smooths more • Midline type. ALMA or HMA or EMA per preference • TR percentile 0..100. Typical 75 to 90. Higher favors only strong expansions • Vol of vol reference. Typical 0.05 to 0.30. Controls how much the percentile term weighs against ATR • Base envelope mult. Typical 1.4 to 2.2. Width of bands • Regime adapt 0..1. Typical 0.6 to 0.95. How much DCX heat widens or narrows the bands Intermarket Bias • Use DXY bias. Default ON • DXY timeframe. Default 1 day • DXY trend window. Typical 10 to 50 Risk • Risk percent per trade. Reporting field. Keep live risk near one to two percent • Weekly ATR. Default 14. Basis for stops • Stop ATR weekly mult. Typical 1.5 to 3.0 • Take profit R multiple. Typical 1.5 to 3.0 • Trail with AVE band. Optional. OFF by default Properties visible in this publication • Initial capital. 20000 • Base currency. USD • request.security lookahead off everywhere • Commission. 0.03 percent • Slippage. 5 ticks • Default order size method percent of equity with value 3% of the total capital available • Pyramiding 0 • Process orders on close ON • Bar magnifier ON • Recalculate after order is filled OFF • Calc on every tick OFF Realism and responsible publication • No performance claims. Past results never guarantee future outcomes • Shapes can move while a bar forms and settle on close • Strategies use standard candles for signals and orders only Honest limitations and failure modes • Economic releases and thin liquidity can break assumptions behind the expansion logic • Gap heavy symbols may prefer a longer ATR window • Very quiet regimes can reduce signal contrast. Consider higher DCX thresholds or wider bands • Session time follows the exchange of the chart and can change symbol to symbol • Symbol sensitivity is expected. Use the gates and length inputs to find stable settings Open source reuse and credits • None Mode Public open source. Source is visible and free to reuse within TradingView House Rules Legal Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
Pine Script® strategy
by exlux
2
Script_Algo - High Low Range MA Crossover Strategy🎯 Core Concept This strategy uses modified moving averages crossover, built on maximum and minimum prices, to determine entry and exit points in the market. A key advantage of this strategy is that it avoids most false signals in trendless conditions, which is characteristic of traditional moving average crossover strategies. This makes it possible to improve the risk/reward ratio and, consequently, the strategy's profitability. 📊 How the Strategy Works Main Mechanism The strategy builds 4 moving averages: Two senior MAs (on high and low) with a longer period Two junior MAs (on high and low) with a shorter period Buy signal 🟢: when the junior MA of lows crosses above the senior MA of highs Sell signal 🔴: when the junior MA of highs crosses below the senior MA of lows As seen on the chart, it was potentially possible to make 9X on the WIFUSDT cryptocurrency pair in just a year and a half. However, be careful—such results may not necessarily be repeated in the future. Special Feature Position closing priority ❗: if an opposite signal arrives while a position is open, the strategy first closes the current position and only then opens a new one ⚙️ Indicator Settings Available Moving Average Types EMA - Exponential MA SMA - Simple MA SSMA - Smoothed MA WMA - Weighted MA VWMA - Volume Weighted MA RMA - Adaptive MA DEMA - Double EMA TEMA - Triple EMA Adjustable Parameters Senior MA Length - period for long-term moving averages Junior MA Length - period for short-term moving averages ✅ Advantages of the Strategy 🛡️ False Signal Protection - using two pairs of modified MAs reduces the number of false entries 🔄 Configuration Flexibility - ability to choose MA type and calculation periods ⚡ Automatic Switching - the strategy automatically closes the current position when receiving an opposite signal 📈 Visual Clarity - all MAs are displayed on the chart in different colors ⚠️ Disadvantages and Risks 📉 Signal Lag - like all MA-based strategies, it may provide delayed signals during sharp movements 🔁 Frequent Switching - in sideways markets, it may lead to multiple consecutive position openings/closings 📊 Requires Optimization - optimal parameters need to be selected for different instruments and timeframes 💡 Usage Recommendations Backtest - test the strategy's performance on historical data Optimize Parameters - select MA periods suitable for the specific trading instrument Use Filters - add additional filters to confirm signals Manage Risks - always use stop-loss and take-profit orders. You can safely connect to the exchange via webhook and enjoy trading. Good luck and profits to everyone!!
Pine Script® strategy
by Script_Algo
Gann + Laplace Smoothed Hybrid Volume Spread AnalysisThe Gann + Laplace Smoothed Hybrid Volume Spread Analysis ( GannLSHVSA ) Strategy/Indicator is an trading tool designed to fuse volume analysis with trend detection, offering traders a view of market dynamics. This Strategy/Indicator stands apart by integrating the principles of the upgraded Discrete Fourier Transform (DFT), the Laplace Stieltjes Transform and volume spread analysis, enhanced with a layer of Fourier smoothing to distill market noise and highlight trend directions with unprecedented clarity. The length of EMA and Strategy Entries are modified with the Gann swings . This smoothing process allows traders to discern the true underlying patterns in volume and price action, stripped of the distractions of short-term fluctuations and noise. The core functionality of the GannLSHVSA revolves around the innovative combination of volume change analysis, spread determination (calculated from the open and close price difference), and the strategic use of the EMA (default 10) to fine-tune the analysis of spread by incorporating volume changes. Trend direction is validated through a moving average (MA) of the histogram, which acts analogously to the Volume MA found in traditional volume indicators. This MA serves as a pivotal reference point, enabling traders to confidently engage with the market when the histogram's movement concurs with the trend direction, particularly when it crosses the Trend MA line, signalling optimal entry points. It returns 0 when MA of the histogram and EMA of the Price Spread are not align. WHAT IS GannLSHVSA INDICATOR: The GannLSHVSA plots a positive trend when a positive Volume smoothed Spread and EMA of Volume smoothed price is above 0, and a negative when negative Volume smoothed Spread and EMA of Volume smoothed price is below 0. When this conditions are not met it plots 0. HOW TO USE THE STRATEGY: Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M. ORIGINALITY & USEFULNESS: The GannLSHVSA Strategy is unique because it applies upgraded DFT, the Laplace Stieltjes Transform for data smoothing, effectively filtering out the minor fluctuations and leaving traders with a clear picture of the market's true movements. The DFT's ability to break down market signals into constituent frequencies offers a granular view of market dynamics, highlighting the amplitude and phase of each frequency component. This, combined with the strategic application of Ehler's Universal Oscillator principles via a histogram, furnishes traders with a nuanced understanding of market volatility and noise levels, thereby facilitating more informed trading decisions. The Gann swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification. DETAILED DESCRIPTION: My detailed description of the indicator and use cases which I find very valuable. What is the meaning of price spread? In finance, a spread refers to the difference between two prices, rates, or yields. One of the most common types is the bid-ask spread, which refers to the gap between the bid (from buyers) and the ask (from sellers) prices of a security or asset. We are going to use Open-Close spread. What is Volume spread analysis? Volume spread analysis (VSA) is a method of technical analysis that compares the volume per candle, range spread, and closing price to determine price direction. What does this mean? We need to have a positive Volume Price Spread and a positive Moving average of Volume price spread for a positive trend. OR via versa a negative Volume Price Spread and a negative Moving average of Volume price spread for a negative trend. What if we have a positive Volume Price Spread and a negative Moving average of Volume Price Spread? It results in a neutral, not trending price action. Thus the Indicator/Strategy returns 0 and Closes all long and short positions. I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Pine Script® strategy
by AutomatedTradingAlgorithms
Fine-tune Inputs: Gann + Laplace Smooth Volume Zone OscillatorUse this Strategy to Fine-tune inputs for the GannLSVZ0 Indicator. Strategy allows you to fine-tune the indicator for 1 TimeFrame at a time; cross Timeframe Input fine-tuning is done manually after exporting the chart data. I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. MEANINGFUL DESCRIPTION: The Volume Zone oscillator breaks up volume activity into positive and negative categories. It is positive when the current closing price is greater than the prior closing price and negative when it's lower than the prior closing price. The resulting curve plots through relative percentage levels that yield a series of buy and sell signals, depending on level and indicator direction. The Gann Laplace Smoothed Volume Zone Oscillator GannLSVZO is a refined version of the Volume Zone Oscillator, enhanced by the implementation of the upgraded Discrete Fourier Transform, the Laplace Stieltjes Transform. Its primary function is to streamline price data and diminish market noise, thus offering a clearer and more precise reflection of price trends. By combining the Laplace with Gann Swing Entries and with Ehler's white noise histogram, users gain a comprehensive perspective on volume-related market conditions. HOW TO USE THE INDICATOR: The default period is 2 but can be adjusted after backtesting. (I suggest 5 VZO length and NoiceR max length 8 as-well) The VZO points to a positive trend when it is rising above the 0% level, and a negative trend when it is falling below the 0% level. 0% level can be adjusted in setting by adjusting VzoDifference. Oscillations rising below 0% level or falling above 0% level result in a natural trend. HOW TO USE THE STRATEGY: Here you fine-tune the inputs until you find a combination that works well on all Timeframes you will use when creating your Automated Trade Algorithmic Strategy. I suggest 4h, 12h, 1D, 2D, 3D, 4D, 5D, 6D, W and M. When Indicator/Strategy returns 0 or natural trend, Strategy Closes All it's positions. ORIGINALITY & USFULLNESS: Personal combination of Gann swings and Laplace Stieltjes Transform of a price which results in less noise Volume Zone Oscillator. The Laplace Stieltjes Transform is a mathematical technique that transforms discrete data from the time domain into its corresponding representation in the frequency domain. This process involves breaking down a signal into its individual frequency components, thereby exposing the amplitude and phase characteristics inherent in each frequency element. This indicator utilizes the concept of Ehler's Universal Oscillator and displays a histogram, offering critical insights into the prevailing levels of market noise. The Ehler's Universal Oscillator is grounded in a statistical model that captures the erratic and unpredictable nature of market movements. Through the application of this principle, the histogram aids traders in pinpointing times when market volatility is either rising or subsiding. The Gann swing strategy is developed by meomeo105, this Gann high and low algorithm forms the basis of the EMA modification. DETAILED DESCRIPTION: My detailed description of the indicator and use cases which I find very valuable. What is oscillator? Oscillators are chart indicators that can assist a trader in determining overbought or oversold conditions in ranging (non-trending) markets. What is volume zone oscillator? Price Zone Oscillator measures if the most recent closing price is above or below the preceding closing price. Volume Zone Oscillator is Volume multiplied by the 1 or -1 depending on the difference of the preceding 2 close prices and smoothed with Exponential moving Average. What does this mean? If the VZO is above 0 and VZO is rising. We have a bullish trend. Most likely. If the VZO is below 0 and VZO is falling. We have a bearish trend. Most likely. Rising means that VZO on close is higher than the previous day. Falling means that VZO on close is lower than the previous day. What if VZO is falling above 0 line? It means we have a high probability of a bearish trend. Thus the indicator returns 0 and Strategy closes all it's positions when falling above 0 (or rising bellow 0) and we combine higher and lower timeframes to gauge the trend. What is approximation and smoothing? They are mathematical concepts for making a discrete set of numbers a continuous curved line. Laplace Stieltjes Transform approximation of a close price are taken from aprox library. Key Features: You can tailor the Indicator/Strategy to your preferences with adjustable parameters such as VZO length, noise reduction settings, and smoothing length. Volume Zone Oscillator (VZO) shows market sentiment with the VZO, enhanced with Exponential Moving Average (EMA) smoothing for clearer trend identification. Noise Reduction leverages Euler's White noise capabilities for effective noise reduction in the VZO, providing a cleaner and more accurate representation of market dynamics. Choose between the traditional Fast Laplace Stieltjes Transform (FLT) and the innovative Double Discrete Fourier Transform (DTF32) soothed price series to suit your analytical needs. Use dynamic calculation of Laplace coefficient or the static one. You may modify those inputs and Strategy entries with Gann swings. I suggest using "Close all" input False when fine-tuning Inputs for 1 TimeFrame. When you export data to Excel/Numbers/GSheets I suggest using "Close all" input as True, except for the lowest TimeFrame. I suggest using 100% equity as your default quantity for fine-tune purposes. I have to mention that 100% equity may lead to unrealistic backtesting results. Be avare. When backtesting for trading purposes use Contracts or USDT.
Pine Script® strategy
by AutomatedTradingAlgorithms
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR) Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits. Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend. The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines. Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits. Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels. The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading. Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now! General Comments This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts. Detailed Description The “Flash” script considers the following indicators for the generation of trading signals: 1. Momentum-RSI 2. ‘Super-Trend’-Analysis 3. EMA-Strategy 1. Momentum-RSI • This indicator signals the strength of the underlying upward- or downward-trend. • The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend. • The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals). • This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend. Graph 1 shows this concept: • The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods. Example (graph 2): 2. Super-Trend Analysis • The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively). • If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered. • The vice-versa approach can be considered for short entries. Graph 3 explains this concept: 3. Exponential Moving Average / EMA-Strategy The functionality of this EMA-element of the strategy has been programmed as follows: • The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals. • Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line. • Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line. An example is shown in graph 4 below: We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement. 4. Bringing it all together This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy. The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met: 1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5): 2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively. 3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively. The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success. Example for Long-Entry (graph 6): When these conditions are met, our Long position is opened. Example for Short-Entry (graph 7): Trade Management Options (graph 8) Option 1 In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters. The following settings of the supertrend-indicator can be changed and optimized (graph 9): The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment. Option 2 (graph 10): Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart. Settings options (graph 11): The following settings can be changed for the three elements of this strategy: 1. (Length Mom-Rsi): Length of our Mom-RSI indicator. 2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals. 3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend 4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind 5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind 6. The backtesting period can be adjusted: Start and End time of BackTest 7. Dollar cost per position: this is relevant for 100% fully automated trading. 8. Trade direction can be adjusted: LONG, SHORT or BOTH 9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 ) Display options on the charts graph 12): 1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts. 2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend. Other comments • This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts. • This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security. • The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year. • Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Pine Script® strategy
by JS_TechTrading
4
VWMA with kNN Machine Learning: MFI/ADXThis is an experimental strategy that uses a Volume-weighted MA (VWMA) crossing together with Machine Learning kNN filter that uses ADX and MFI to predict, whether the signal is useful. k-nearest neighbours (kNN) is one of the simplest Machine Learning classification algorithms: it puts input parameters in a multidimensional space, and then when a new set of parameters are given, it makes a prediction based on plurality vote of its k neighbours. Money Flow Index (MFI) is an oscillator similar to RSI, but with volume taken into account. Average Directional Index (ADX) is an indicator of trend strength. By putting them together on two-dimensional space and checking, whether nearby values have indicated a strong uptrend or downtrend, we hope to filter out bad signals from the MA crossing strategy. This is an experiment, so any feedback would be appreciated. It was tested on BTC/USDT pair on 5 minute timeframe. I am planning to expand this strategy in the future to include more moving averages and filters.
Pine Script® strategy
by lastguru
9
BuyTheDipWell, I often had arguments in online forum with a guy who claimed to time the market perfectly without any technical analysis or prior experience. He often claimed that technical analysis does not work and it only works when you trade on other's emotions. He also argued that algorithmic trading isn't profitable - if so, everyone would do that. Hence, I thought I will convert his idea to algorithm. In his own words, the strategy is as below: Chose an instrument which is in full uptrend. Wait for the panic sell and buy the dip Once market recovers back exit immediately It seems to do just fine with indexes. But, not so good when it comes to stocks.
Pine Script® strategy
by Trendoscope
11
BitMEX pump catcher - MACDThis is a modified version of the BitMEX pump catcher by Jomy . I have tweaked the algorithm to use the difference in MACD to get the correct direction of entries rather than using direction of candles which are not always indicative of trend direction. These changes increase net profit, profitable trades, while reducing drawdown. Below is a copy and paste of Jomy's explanation of the algorithm. What is going on here? This strategy is pretty simple. We start by measuring a very long chunk of volume history on BitMEX:XBTUSD 1 hour chart to find out if the current volume is high or low. At 1.0 the indicator is showing we are at 100% of normal historical volume . The blue line is a measure of recent volume! This indicator gets interested when the volume drops below 90% of the regular volume (0.9), and then comes back up over 90%. There's usually a pump of increased price activity during this time. When the 0.9 line is crossed by the blue line, the indicator surveys the last 2 bars of price action to figure out which way we're going, long or short. Green is long. Red is short. To exit the trade we use a 7 period fast ema of the volume crossing under an 11 ema slower period which shows declining interest in the market signifying an end to the pump or dump. The profit factor is quite high with 5x leverage, but historically we see 50% drawdown -- very risky. 1x leverage looks nice and tight with very low drawdown. Play with the inputs to see what matches your own risk profile. I would not recommend taking this into much lower timeframes as trading fees are not included in the profit calculations. Please don't get burned trading on stupid high leverage. This indicator is probably not going to work well on alts, as Bitcoin FOMO build up and behavior is different. This whole indicator is tuned to Bitcoin , and attempts to trade only the meatiest part of the market moves. Jomy should get full credit to this indicator
Pine Script® strategy
by ahancock
27
[Autoview][BackTest] Blank R0.13BThis is a fork of JustUncleL's Dual MA Ribbons R0.13 It is now a blank template for making new strategies / alerts for autoview The changes are as follows: Removed actual algo Establish functions for long Signal, long Close Signal and short Signal, short Close Signal to minimize the places code must be edited to update / replace algos Make allow Long and allow short and invert trade directions independent options Added support for alternate candle types Added autoset backtest period feature, and optional coloring Moved strategy calls in to functions so they can all be commented out or activated / disabled in a single block at the top of the script
Pine Script® strategy
by yatrader2
1
Safe Supertrend Strategy (No Repaint)Overview The Safe Supertrend is a repaint-free version of the popular Supertrend trend-following indicator. Most Supertrend indicators appear perfect on historical charts because they flip intrabar and then repaint after the candle closes. This version fixes that by using close-of-bar confirmation only, making every trend flip 100% stable, safe, and non-repainting. Why This Supertrend Doesn’t Repaint Most Supertrend indicators calculate their trend direction using the current bar’s data. But during a live candle: ATR expands and contracts The upper/lower bands move Price moves above/below the band temporarily A false flip appears → then disappears when the candle closes That is classic repainting. This indicator avoids all of that by using: close > upper close < lower This means: Trend direction flips only based on the previous candle, No intrabar calculations, No flickering signals, No “perfect but fake” historical performance. Every signal you see on the chart is exactly what was available in real-time. How It Works Calculates ATR (Average True Range) and SMA centerline Builds upper and lower volatility bands Confirms trend flips only after the previous bar closes Plots clear bull and bear reversal signals Works on all markets (crypto, stocks, forex, indices) No repainting, no recalc, no misleading flips. Bullish Signal (Trend Up) A bullish trend begins only when: The previous candle closes above the upper ATR band, And this flip is fully confirmed. A green triangle marks the start of a new uptrend. Bearish Signal (Trend Down) A bearish trend begins only when: The previous candle closes below the lower ATR band, And the downtrend is confirmed. A red triangle signals the start of a new downtrend. Inputs ATR Length - default 10 ATR Multiplier - default 3.0 Works on all timeframes and market Simple, but powerful. Why Use This Version Instead of a Regular Supertrend? Most Supertrends: Look great historically But repaint continuously on live charts Give false trend flips intrabar Cannot be reliably used in strategies This version: Uses strict previous-bar logic Never repaints trend direction Works perfectly in live trading Backtests accurately Is ideal for algorithmic strategies Ideal For: Trend-following strategies Breakout trading Algo trading systems Reversal detection Filtering market noise Swing trading & scalping Final Note This is a safer, more reliable Supertrend designed for real-world use — not perfect-looking repaint illusions. If you use Supertrend in your trading system, this no-repaint version ensures your signals are trustworthy and consistent.
Pine Script® strategy
by AIScripts
1
ThinkTech AI SignalsThink Tech AI Strategy The Think Tech AI Strategy provides a structured approach to trading by integrating liquidity-based entries, ATR volatility thresholds, and dynamic risk management. This strategy generates buy and sell signals while automatically calculating take profit and stop loss levels, boasting a 64% win rate based on historical data. Usage The strategy can be used to identify key breakout and retest opportunities. Liquidity-based zones act as potential accumulation and distribution areas and may serve as future support or resistance levels. Buy and sell zones are identified using liquidity zones and ATR-based filters. Risk management is built-in, automatically calculating take profit and stop loss levels using ATR multipliers. Volume and trend filtering options help confirm directional bias using a 50 EMA and RSI filter. The strategy also allows for session-based trading, limiting trades to key market hours for higher probability setups. Settings The risk/reward ratio can be adjusted to define the desired stop loss and take profit calculations. The ATR length and threshold determine ATR-based breakout conditions for dynamic entries. Liquidity period settings allow for customized analysis of price structure for support and resistance zones. Additional trend and RSI filters can be enabled to refine trade signals based on moving averages and momentum conditions. A session filter is included to restrict trade signals to specific market hours. Style The strategy includes options to display liquidity lines, showing key support and resistance areas. The first 15-minute candle breakout zones can also be visualized to highlight critical market structure points. A win/loss statistics table is included to track trade performance directly on the chart. This strategy is intended for descriptive analysis and should be used alongside other confluence factors. Optimize your trading process with Think Tech AI today!
Pine Script® strategy
by Theonealgo