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Recherche dans les scripts pour "macd strategy"

MACD StrategyThis script sends buy and sell signals as alerts to 3Commas (online software with trading bots in cryptocurreny) It's based on 2 indicators: - MACD - 12 EMA and 26 EMA When the 12 EMA and 26 EMA crossover, the MACD line crosses above 0. The goal here is to look for buy signals when the MACD and Signal are below 0, the histogram is positive, and there was or will be a 12 EMA and 26 EMA crossover. I struggle with the following: - There are multiple ways to use this as a crossover signal. I want to calculate the win rate of every posibility. - What should be my take profit and my stoploss? I think a 2:1 R/R,and a 60% win rate would make a great strategy! I could use some advice.
Indicateur Pine Script®
par Atumkaya
5
MACD Strategy- Script Example how to use % SL in your script ** Tired of Script showing a trade that you stopped out on but is still long on your script? Not any more** I used Pine script to create realistic trading scenarios for SL users. Now your scripts will reflect what you see on the order book. a=0.0 a := (*Insert buy condition*)? close: nz(a ) plot(0.98*a, color= green) //2%SL for BUY b=0.0 b:= (*Insert Short condition*) ? close: nz(b ) plot(1.02*b, color= red) //2% SL for Short Please check the script on how to implement this :)
Stratégie Pine Script®
par UnknownUnicorn1178563
Dual MACD StrategyThis strategy Multi Time Frame Macd Indicator We take the first long position when we have a buy signal in Weekly Macd (Macd line crosses above Signal line). This open a trading window, showed with green background color We close the first position when either Weekly or Daily Macd give us a sell signal ((Macd line crosses below Signal line)) Enable Profit and Stop in strategy settings with different percentage to backtest the strategy. Also if it is better to use a Traditional Stop Loss or a Trailing Stop Loss based on a percentage from low prices Change macd resolution in settings for other time frames to test the strategy This Strategy was tested on Crypto Market with good results in assets as BTC, ETH, BNB, ADA, LTC, XLM, BCH, among others
Stratégie Pine Script®
par Trading_Solutions_
1
TST Signals & AlertsThis is an unofficial script for strategies tested on Trading Strategy Testing Youtube channel. Over time, most successful strategies will be added with an option to set strategy-specific alerts . TST Signals & Alerts will draw signals on the chart when the entry conditions are met. You can also opt for displaying indicators . My script is meant for beginners but can be used by veterans too. Just pick one or two strategies, you don't want to flood your chart with conflicting signals. You may want to support your trades with a proper analysis. Is the market trending? Is there a fundament around the corner? If a new signal occurs when there is still an open position, you are not supposed to take another. The current version includes MACD and ADX + BB and BB strategies. MACD strategy: ►Buy, when MACD crosses below the signal line when it is negative. The price must also be above 200 EMA. ►Sell, when MACD crosses above the signal line when it is positive. The price must also be below 200 EMA. ►This strategy was tested on 15-minute charts of EURUSD with reward-to-risk ratio 1,5 and win rate of 61% over 100 trades. ►►►MACD has to be added to your chart separately because it needs a new window. Ticking display indicators will not add MACD to your chart. ►►►MACD was also tested by a different channel I made a script for. You can view the results and the script here: ADX + BB strategy: ►Buy, when the price is above 200 EMA and ADX becomes higher than 25. ►Sell, when the price is below 200 EMA and ADX becomes higher than 25. ►Stop-loss is either 200 EMA or Bollinger Bands level. Check the channel for more information. ►This strategy was tested on 5-minute charts of EURUSD, USDJPY, AUDUSD with reward-to-risk ratio 1,2 and win rate of 56% over 100 trades in total. BB strategy: ►Buy, when the price is above 200 EMA and candle's low is below the lower Bollinger Band. ►Sell, when the price is below 200 EMA and candle's high is above the upper Bollinger Band. ►This strategy was tested on 15-minute charts of EURUSD with reward-to-risk ratio 1,5 and win rate of 52% over 100 trades in total. ►►►Due to the relatively low win rate of this strategy, you need to filter out potentially harmful signals with a proper analysis. Bear in mind that backtesting performance doesn't guarantee future profitability. • Most systematic strategies are not suitable for each timeframe - if you use the different timeframe than the one it was tested on, the result can differ significantly. • You should perform your own backtest to base your trades on more data & to establish confidence in the selected strategy. • This script is not a replacement for proper analysis. New strategies will be added when I have time. If I see multiple people asking for the same feature, I might agree to release it with a new version. I am not going to add input options in this script, it could come as a separate script though. I am in no way affiliated with the Youtube channel, so if you find the script helpful, shot me a message or send me some TradingView coins >) If you encounter any bug, you can report it in a message or in comments. Support it with screenshot and relevant information such as a time when it occurred and what options were on etc.
Indicateur Pine Script®
par OrcChieftain
8
Trading Rush Signals & AlertsThis is an unofficial script for strategies tested on TRADING RUSH Youtube channel. Over time, most successful strategies will be added with an option to set strategy-specific alerts . Trading Rush Signals & Alerts will draw signals on the chart when the entry conditions are met. You can also opt for displaying indicators . My script is meant for beginners but can be used by veterans too. Just pick only one or two strategies, you don't want to flood your chart with conflicting signals. You may want to support your trades with a proper analysis. If a new signal occurs when there is still an open position, you are not supposed to take another. The current version includes MACD and Donchian Channels. MACD strategy: ►Buy, when MACD crosses below the signal line when it is negative. The price must also be above 200 EMA. ►Sell, when MACD crosses above the signal line when it is positive. The price must also be below 200 EMA. ►This strategy was tested on 30-minute charts of EURUSD and EURJPY with reward-to-risk ratio 1,5 and win rate of 62% over 100 trades . ►►►MACD has to be added to your chart separately because it needs a new window. Indicators displaying will not add this indicator to the chart. Donchian Channels strategy: ►Buy, when the price breaches Donchian to the upside after making a new low. The price must also be above 200 EMA. ►Sell, when the price breaches Donchian to the downside after making a new high. The price must also be below 200 EMA. ►Stop-loss is Donchian bottom for long and Donchian top for shorts. Check the channel for more information. ►This strategy was tested on 30-minute charts of EURUSD with reward-to-risk ratio 1,5 and win rate of 58% over 100 trades . ►►►I programmed alerts for Donchians to come ahead of an actual breach. If you often leave the screen when trading, this will help you. The necessary downside for that is the alerts might come when the signal doesn't trigger in the end. You will see a mark on the chart if the conditions are truly met. Bear in mind that backtesting performance doesn't guarantee future profitability. • Most systematic strategies are not suitable for any timeframe. • You should perform your own backtest to base your trades on more data & to establish confidence in the selected strategy. New strategies will be added when I have time. If I see multiple people asking for the same new feature, I might agree to release it with a new version. I am not going to add input options in this script, it could come as a separate script though. I am in no way affiliated with the Youtubechannel , so if you find the script helpful, shot me a message or send me some TradingView coins >) If you encounter any bug, you can report it in a message or in comments. Support it with screenshot and relevant information such as a time when it occurred and what options were on etc.
Indicateur Pine Script®
par OrcChieftain
27
Confluence Buy-Sell Indicator with Fibonacci The script is a "Confluence Indicator with Fibonacci" designed to work on the TradingView platform. This indicator combines multiple technical analysis strategies to generate buy and sell signals based on user-defined confluence criteria. Here's a breakdown of its features: Confluence Criteria: Users can enable or disable various strategies like MACD, RSI, Bollinger Bands, Divergence, Fibonacci, and Moving Average. The number of strategies that need to align for a signal to be generated can be set by the user. Strategies Included: MACD Strategy: Uses the Moving Average Convergence Divergence method to identify buy/sell opportunities. RSI Strategy: Utilizes the Relative Strength Index to detect overbought or oversold conditions. Bollinger Bands Strategy: Incorporates Bollinger Bands to identify volatility and potential buy/sell signals. Divergence Strategy: A basic implementation that detects bullish and bearish divergences using the RSI. Fibonacci Strategy: Uses Fibonacci retracement levels to determine potential support and resistance levels. Moving Average Strategy: Employs a crossover system between the 50-period and 200-period simple moving averages. Additional Features: Support & Resistance: Identifies major support and resistance levels from the last 50 bars. Pivot Points: Calculates pivot points to determine potential turning points. Stop Loss Levels: Automatically calculates and plots stop-loss levels for buy and sell signals. NYC Midnight Level: Option to display the New York City midnight price level. Visualization: Plots buy and sell signals on the chart with green and red markers respectively. Adequate Category: "Technical Analysis Indicators & Overlays" or "Strategy & Scripting Tools".
Indicateur Pine Script®
par CallmeNegan108
3
CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy WHAT THIS STRATEGY IS CryptoFlux Dynamo is an open-source Pine Script v6 strategy designed for momentum-based scalping on cryptocurrency perpetual futures. It combines multiple technical analysis methods into a unified system that adapts its behavior based on current market volatility conditions. This script is published open-source so you can read, understand, and modify the complete logic. The description below explains everything the strategy does so that traders who cannot read Pine Script can fully understand how it works before using it. HOW THIS STRATEGY IS ORIGINAL AND WHY THE INDICATORS ARE COMBINED This strategy uses well-known indicators (MACD, EMA, RSI, MFI, Bollinger Bands, Keltner Channels, ATR). The originality is not in the individual indicators themselves, but in the specific way they are integrated into a regime-adaptive system. Here is the detailed justification for why these components are combined and how they work together: The Problem Being Solved: Standard indicator-based strategies use fixed thresholds. For example, a typical MACD strategy might enter when the histogram crosses above zero. However, in cryptocurrency markets, volatility changes dramatically throughout the day and week. A MACD crossover during a low-volatility consolidation period has very different implications than the same crossover during a high-volatility trending period. Using the same entry thresholds and stop distances in both conditions leads to either: Too many false signals during consolidation (if thresholds are loose) Missing valid opportunities during expansion (if thresholds are tight) Stops that are too tight during volatility spikes (causing premature exits) Stops that are too wide during compression (giving back profits) The Solution Approach: This strategy first classifies the current volatility regime using normalized ATR (ATR as a percentage of price), then dynamically adjusts ALL other parameters based on that classification. This creates a context-aware system rather than a static threshold comparison. How Each Component Contributes to the System: ATR-Based Regime Classification (The Foundation) The strategy calculates ATR over 21 periods, smooths it with a 13-period EMA to reduce noise from wicks, then divides by price to get a normalized percentage. This ATR% is classified into three regimes: - Compression (ATR% < 0.8%): Market is consolidating, breakouts are more likely but false signals are common - Expansion (ATR% 0.8% - 1.6%): Normal trending conditions - Velocity (ATR% > 1.6%): High volatility, larger moves but also larger adverse excursions This regime classification then controls stop distances, profit targets, trailing stop offsets, and signal strength requirements. The regime acts as a "meta-parameter" that tunes the entire system. EMA Ribbon (8/21/34) - Trend Structure Detection The three EMAs establish trend direction and structure. When EMA 8 > EMA 21 > EMA 34, the trend structure is bullish. The slope of the middle EMA (21) is calculated over 8 bars and converted to degrees using arctangent. This slope measurement quantifies trend strength, not just direction. Why these specific periods? The 8/21/34 sequence follows Fibonacci-like spacing and provides good separation on 5-minute cryptocurrency charts. The fast EMA (8) responds to immediate price action, the mid EMA (21) represents the short-term trend, and the slow EMA (34) acts as a trend filter. The EMA ribbon works with the regime classification: during compression regimes, the strategy requires stronger ribbon alignment before entry because false breakouts are more common. MACD (8/21/5) - Momentum Measurement The MACD uses faster parameters (8/21/5) than the standard (12/26/9) because cryptocurrency markets move faster than traditional markets. The histogram is smoothed with a 5-period EMA to reduce noise. The key innovation is the adaptive histogram baseline. Instead of using a fixed threshold, the strategy calculates a rolling baseline from the smoothed absolute histogram value, then multiplies by a sensitivity factor (1.15). This means the threshold for "significant momentum" automatically adjusts based on recent momentum levels. The MACD works with the regime classification: during velocity regimes, the histogram baseline is effectively higher because recent momentum has been stronger, preventing entries on relatively weak momentum. RSI (21 period) and MFI (21 period) - Independent Momentum Confirmation RSI measures momentum using price changes only. MFI (Money Flow Index) measures momentum using price AND volume. By requiring both to confirm, the strategy filters out price moves that lack volume support. The 21-period length is longer than typical (14) to reduce noise on 5-minute charts. The trigger threshold (55 for longs, 45 for shorts) is slightly offset from 50 to require momentum in the trade direction, not just neutral readings. These indicators work together: a signal requires RSI > 55 AND MFI > 55 for longs. This dual confirmation reduces false signals from price manipulation or low-volume moves. Bollinger Bands (1.5 mult) and Keltner Channels (1.8 mult) - Squeeze Detection When Bollinger Bands contract inside Keltner Channels, volatility is compressing and a breakout is likely. This is the "squeeze" condition. When the bands expand back outside the channels, the squeeze "releases." The strategy uses a 1.5 multiplier for Bollinger Bands (tighter than standard 2.0) and 1.8 for Keltner Channels. These values were chosen to identify meaningful squeezes on 5-minute cryptocurrency charts without triggering too frequently. The squeeze detection works with the regime classification: squeeze releases during compression regimes receive additional signal strength points because breakouts from consolidation are more significant. Volume Impulse Detection - Institutional Participation Filter The strategy calculates a volume baseline (34-period SMA) and standard deviation. A "volume impulse" is detected when current volume exceeds the baseline by 1.15x OR when the volume z-score exceeds 0.5. This filter ensures entries occur when there is meaningful market participation, not during low-volume periods where price moves are less reliable. Volume impulse is required for all entries and adds points to the composite signal strength score. Cycle Oscillator - Trend Alignment Filter The strategy calculates a 55-period EMA as a cycle basis, then measures price deviation from this basis as a percentage. When price is more than 0.15% above the cycle basis, the cycle is bullish. When more than 0.15% below, the cycle is bearish. This filter prevents counter-trend entries. Long signals require bullish cycle alignment; short signals require bearish cycle alignment. BTC Dominance Filter (Optional) - Market Regime Filter The strategy can optionally use BTC.D (Bitcoin Dominance) as a market regime filter. When BTC dominance is rising (slope > 0.12), the market is in "risk-off" mode and long entries on altcoins are filtered. When dominance is falling (slope < -0.12), short entries are filtered. This filter is optional because the BTC.D data feed may lag during low-liquidity periods. How The Components Work Together (The Mashup Justification): The strategy uses a composite scoring system where each signal pathway contributes points: Trend Break pathway (30 points): Requires EMA ribbon alignment + positive slope + price breaks above recent structure high Momentum Surge pathway (30 points): Requires MACD histogram > adaptive baseline + MACD line > signal + RSI > 55 + MFI > 55 + volume impulse Squeeze Release pathway (25 points): Requires BB inside KC (squeeze) then release + momentum bias + histogram confirmation Micro Pullback pathway (15 points): Requires shallow retracement to fast EMA within established trend + histogram confirmation + volume impulse Additional modifiers: +5 points if volume impulse is present, -5 if absent +5 points in velocity regime, -2 in compression regime +5 points if cycle is aligned, -5 if counter-trend A trade only executes when the composite score reaches the minimum threshold (default 55) AND all filters agree (session, cycle bias, BTC dominance if enabled). This scoring system is the core innovation: instead of requiring ALL conditions to be true (which would generate very few signals) or ANY condition to be true (which would generate too many false signals), the strategy requires ENOUGH conditions to be true, with different conditions contributing different weights based on their reliability. HOW THE STRATEGY CALCULATES ENTRIES AND EXITS Entry Logic: 1. Calculate current volatility regime from ATR% 2. Calculate all indicator values (MACD, EMA, RSI, MFI, squeeze, volume) 3. Evaluate each signal pathway and sum points 4. Check all filters (session, cycle, dominance, kill switch) 5. If composite score >= 55 AND all filters pass, generate entry signal 6. Calculate position size based on risk per trade and regime-adjusted stop distance 7. Execute entry with regime name as comment Position Sizing Formula: RiskCapital = Equity * (0.65 / 100) StopDistance = ATR * StopMultiplier(regime) RawQuantity = RiskCapital / StopDistance MaxQuantity = Equity * (12 / 100) / Price Quantity = min(RawQuantity, MaxQuantity) Quantity = round(Quantity / 0.001) * 0.001 This ensures each trade risks approximately 0.65% of equity regardless of volatility, while capping total exposure at 12% of equity. Stop Loss Calculation: Stop distance is ATR multiplied by a regime-specific multiplier: Compression regime: 1.05x ATR (tighter stops because moves are smaller) Expansion regime: 1.55x ATR (standard stops) Velocity regime: 2.1x ATR (wider stops to avoid premature exits during volatility) Take Profit Calculation: Target distance is ATR multiplied by regime-specific multiplier and base risk/reward: Compression regime: 1.6x ATR * 1.8 base R:R * 0.9 regime bonus = approximately 2.6x ATR Expansion regime: 2.05x ATR * 1.8 base R:R * 1.0 regime bonus = approximately 3.7x ATR Velocity regime: 2.8x ATR * 1.8 base R:R * 1.15 regime bonus = approximately 5.8x ATR Trailing Stop Logic: When adaptive trailing is enabled, the strategy calculates a trailing offset based on ATR and regime: Compression regime: 1.1x base offset (looser trailing to avoid noise) Expansion regime: 1.0x base offset (standard) Velocity regime: 0.8x base offset (tighter trailing to lock in profits during fast moves) The trailing stop only activates when it would be tighter than the initial stop. Momentum Fail-Safe Exits: The strategy closes positions early if momentum reverses: Long positions close if MACD histogram turns negative OR EMA ribbon structure breaks (fast EMA crosses below mid EMA) Short positions close if MACD histogram turns positive OR EMA ribbon structure breaks This prevents holding through momentum reversals even if stop loss hasn't been hit. Kill Switch: If maximum drawdown exceeds 6.5%, the strategy disables new entries until manually reset. This prevents continued trading during adverse conditions. HOW TO USE THIS STRATEGY Step 1: Apply to Chart Use a 5-minute chart of a high-liquidity cryptocurrency perpetual (BTC/USDT, ETH/USDT recommended) Ensure at least 200 bars of history are loaded for indicator stabilization Use standard candlestick charts only (not Heikin Ashi, Renko, or other non-standard types) Step 2: Understand the Visual Elements EMA Ribbon: Three lines (8/21/34 periods) showing trend structure. Bullish when stacked upward, bearish when stacked downward. Background Color: Shows current volatility regime - Indigo/dark blue = Compression (low volatility) - Purple = Expansion (normal volatility) - Magenta/pink = Velocity (high volatility) Bar Colors: Reflect signal strength divergence. Brighter colors indicate stronger directional bias. Triangle Markers: Entry signals. Up triangles below bars = long entry. Down triangles above bars = short entry. Dashboard (top-right): Real-time display of regime, ATR%, signal strengths, position status, stops, targets, and risk metrics. Step 3: Interpret the Dashboard Regime: Current volatility classification (Compression/Expansion/Velocity) ATR%: Normalized volatility as percentage of price Long/Short Strength: Current composite signal scores (0-100) Cycle Osc: Price deviation from 55-period EMA as percentage Dominance: BTC.D slope and filter status Position: Current position direction or "Flat" Stop/Target: Current stop loss and take profit levels Kill Switch: Status of drawdown protection Volume Z: Current volume z-score Impulse: Whether volume impulse condition is met Step 4: Adjust Parameters for Your Needs For more conservative trading: Increase "Minimum Composite Signal Strength" to 65 or higher For more aggressive trading: Decrease to 50 (but expect more false signals) For higher timeframes (15m+): Increase "Structure Break Window" to 12-15, increase "RSI Momentum Trigger" to 58 For lower liquidity pairs: Increase "Volume Impulse Multiplier" to 1.3, increase slippage in strategy properties To disable short selling: Uncheck "Enable Short Structure" To disable BTC dominance filter: Uncheck "BTC Dominance Confirmation" STRATEGY PROPERTIES (BACKTEST SETTINGS) These are the exact settings used in the strategy's Properties dialog box. You must use these same settings when evaluating the backtest results shown in the publication: Initial Capital: $100,000 Justification: This amount is higher than typical retail accounts. I chose this value to demonstrate percentage-based returns that scale proportionally. The strategy uses percentage-based position sizing (0.65% risk per trade), so a $10,000 account would see the same percentage returns with 10x smaller position sizes. The absolute dollar amounts in the backtest should be interpreted as percentages of capital. Commission: 0.04% (commission_value = 0.04) Justification: This reflects typical perpetual futures exchange fees. Major exchanges charge between 0.02% (maker) and 0.075% (taker). The 0.04% value is a reasonable middle estimate. If your exchange charges different fees, adjust this value accordingly. Higher fees will reduce net profitability. Slippage: 1 tick Justification: This is conservative for liquid pairs like BTC/USDT on major exchanges during normal conditions. For less liquid altcoins or during high volatility, actual slippage may be higher. If you trade less liquid pairs, increase this value to 2-3 ticks for more realistic results. Pyramiding: 1 Justification: No position stacking. The strategy holds only one position at a time. This simplifies risk management and prevents overexposure. calc_on_every_tick: true Justification: The strategy evaluates on every price update, not just bar close. This is necessary for scalping timeframes where waiting for bar close would miss opportunities. Note that this setting means backtest results may differ slightly from bar-close-only evaluation. calc_on_order_fills: true Justification: The strategy recalculates immediately after order fills for faster response to position changes. RISK PER TRADE JUSTIFICATION The default risk per trade is 0.65% of equity. This is well within the TradingView guideline that "risking more than 5-10% on a trade is not typically considered viable." With the 12% maximum exposure cap, even if the strategy takes multiple consecutive losses, the total risk remains manageable. The kill switch at 6.5% drawdown provides additional protection by halting new entries during adverse conditions. The position sizing formula ensures that stop distance (which varies by regime) is accounted for, so actual risk per trade remains approximately 0.65% regardless of volatility conditions. SAMPLE SIZE CONSIDERATIONS For statistically meaningful backtest results, you should select a dataset that generates at least 100 trades. On 5-minute BTC/USDT charts, this typically requires: 2-3 months of data during normal market conditions 1-2 months during high-volatility periods 3-4 months during low-volatility consolidation periods The strategy's selectivity (requiring 55+ composite score plus all filters) means it generates fewer signals than less filtered approaches. If your backtest shows fewer than 100 trades, extend the date range or reduce the minimum signal strength threshold. Fewer than 100 trades produces statistically unreliable results. Win rate, profit factor, and other metrics can vary significantly with small sample sizes. STRATEGY DESIGN COMPROMISES AND LIMITATIONS Every strategy involves trade-offs. Here are the compromises made in this design and the limitations you should understand: Selectivity vs. Opportunity Trade-off The 55-point minimum threshold filters many potential trades. This reduces false signals but also misses valid setups that don't meet all criteria. Lowering the threshold increases trade frequency but decreases win rate. There is no "correct" threshold; it depends on your preference for fewer higher-quality signals vs. more signals with lower individual quality. Regime Classification Lag The ATR-based regime detection uses historical data (21 periods + 13-period smoothing). It cannot predict sudden volatility spikes. During flash crashes or black swan events, the strategy may be classified in the wrong regime for several bars before the classification updates. This is an inherent limitation of any lagging indicator. Indicator Parameter Sensitivity The default parameters (MACD 8/21/5, EMA 8/21/34, RSI 21, etc.) are tuned for BTC/ETH perpetuals on 5-minute charts during 2024 market conditions. Different assets, timeframes, or market regimes may require different parameters. There is no guarantee that parameters optimized on historical data will perform similarly in the future. BTC Dominance Filter Limitations The CRYPTOCAP:BTC.D data feed may lag during low-liquidity periods or weekends. The dominance slope calculation uses a 5-bar SMA, adding additional delay. If you notice the filter behaving unexpectedly, consider disabling it. Backtest vs. Live Execution Differences TradingView backtesting does not replicate actual broker execution. Key differences: Backtests assume perfect fills at calculated prices; real execution involves order book depth, latency, and partial fills The calc_on_every_tick setting improves backtest realism but still cannot capture sub-bar price action or order book dynamics Commission and slippage settings are estimates; actual costs vary by exchange, time of day, and market conditions Funding rates on perpetual futures are not modeled in backtests and can significantly impact profitability over time Exchange-specific limitations (position limits, liquidation mechanics, order types) are not modeled Market Condition Dependencies This strategy is designed for trending and breakout conditions. During extended sideways consolidation with no clear direction, the strategy may generate few signals or experience whipsaws. No strategy performs well in all market conditions. Cryptocurrency-Specific Risks Cryptocurrency markets operate 24/7 without session boundaries. This means: No natural "overnight" risk reduction Volatility can spike at any time Liquidity varies significantly by time of day Exchange outages or issues can occur at any time WHAT THIS STRATEGY DOES NOT DO To be straightforward about limitations: This strategy does not guarantee profits. Past backtest performance does not indicate future results. This strategy does not predict the future. It reacts to current conditions based on historical patterns. This strategy does not account for funding rates, which can significantly impact perpetual futures profitability. This strategy does not model exchange-specific execution issues (partial fills, requotes, outages). This strategy does not adapt to fundamental news events or black swan scenarios. This strategy is not optimized for all market conditions. It may underperform during extended consolidation. IMPORTANT RISK WARNINGS Past performance does not guarantee future results. The backtest results shown reflect specific historical market conditions and parameter settings. Markets change constantly, and strategies that performed well historically may underperform or lose money in the future. A single backtest run does not constitute proof of future profitability. Trading involves substantial risk of loss. Cryptocurrency derivatives are highly volatile instruments. You can lose your entire investment. Only trade with capital you can afford to lose completely. This is not financial advice. This strategy is provided for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or any form of financial guidance. The author is not a licensed financial advisor. You are responsible for your own decisions. Before using this strategy with real capital: Thoroughly understand the code and logic by reading the open-source implementation Forward test with paper trading or very small positions for an extended period Verify that commission, slippage, and execution assumptions match your actual trading environment Understand that live results will differ from backtest results Consider consulting with a qualified financial advisor No guarantees or warranties. This strategy is provided "as is" without any guarantees of profitability, accuracy, or suitability for any purpose. The author is not responsible for any losses incurred from using this strategy. OPEN-SOURCE CODE STRUCTURE The strategy code is organized into these sections for readability: Configuration Architecture: Input parameters organized into logical groups (Core Controls, Optimization Constants, Regime Intelligence, Signal Pathways, Risk Architecture, Visualization) Helper Functions: calcQty() for position sizing, clamp01() and normalize() for value normalization, calcMFI() for Money Flow Index calculation Core Indicator Engine: EMA ribbon, ATR and regime classification, MACD with adaptive baseline, RSI, MFI, volume analytics, cycle oscillator, BTC dominance filter, squeeze detection Signal Pathway Logic: Trend break, momentum surge, squeeze release, micro pullback pathways with composite scoring Entry/Exit Orchestration: Signal filtering, position sizing, entry execution, stop/target calculation, trailing stop logic, momentum fail-safe exits Visualization Layer: EMA plots, regime background, bar coloring, signal labels, dashboard table You can read and modify any part of the code. Understanding the logic before deployment is strongly recommended. - Made with passion by officialjackofalltrades
Stratégie Pine Script®
par officialjackofalltrades
Cycles StrategyThis is back-testable strategy is a modified version of the Stochastic strategy. It is meant to accompany the modified Stochastic indicator: "Cycles". Modifications to the Stochastic strategy include; 1. Programmable settings for the Stochastic Periods (%K, %D and Smooth %K). 2. Programmable settings for the MACD Periods (Fast, Slow, Smoothing) 3. Programmable thresholds for %K, to qualify a potential entry strategy. 4. Programmable thresholds for %D, to qualify a potential exit strategy. 5. Buttons to choose which components to use in the trading algorithm. 6. Choose the month and year to back test. The trading algorithm: 1. When %K exceeds the upper/lower threshold and then hooks down/up, in the direction of the Moving Average (MA). This is the minimum entry qualification. 2. When %D exceeds the lower/upper threshold and angled in the direction of the trade, is the exit qualification. 3. Additional entry filters include the direction of MACD, Signal and %D. Also, the "cliff", being a long entry is a higher high or a short entry is a lower low. 4. Strategy can only go "Long" or "Short" depending on the selected setting. 5. By matching the settings in the "Cycles" indicator, you can (almost) see what the strategy is doing. 6. Be sure to select the "Recalculate" buttons, to recalculate on every new Tick, for best results. Please click the Like button and leave a comment if you appreciate this script. Improvements will be implemented as time goes on. I am not a licensed trade advisor. This strategy is for entertainment only. Use at your own risk!
Stratégie Pine Script®
par FXEngineering
Filtered MACD with Backtest [UAlgo]The "Filtered MACD with Backtest " indicator is an advanced trading tool designed for the TradingView platform. It combines the Moving Average Convergence Divergence (MACD) with additional filters such as Moving Average (MA) and Average Directional Index (ADX) to enhance trading signals. This indicator aims to provide more reliable entry and exit points by filtering out noise and confirming trends. Additionally, it includes a comprehensive backtesting module to simulate trading strategies and assess their performance based on historical data. The visual backtest module allows traders to see potential trades directly on the chart, making it easier to evaluate the effectiveness of the strategy. 🔶 Customizable Parameters : Price Source Selection: Users can choose their preferred price source for calculations, providing flexibility in analysis. Filter Parameters: MA Filter: Option to use a Moving Average filter with types such as EMA, SMA, WMA, RMA, and VWMA, and a customizable length. ADX Filter: Option to use an ADX filter with adjustable length and threshold to determine trend strength. MACD Parameters: Customizable fast length, slow length, and signal smoothing for the MACD indicator. Backtest Module: Entry Type: Supports "Buy and Sell", "Buy", and "Sell" strategies. Stop Loss Types: Choose from ATR-based, fixed point, or X bar high/low stop loss methods. Reward to Risk Ratio: Set the desired take profit level relative to the stop loss. Backtest Visuals: Display entry, stop loss, and take profit levels directly on the chart with colored backgrounds. Alerts: Configurable alerts for buy and sell signals. 🔶 Filtered MACD : Understanding How Filters Work with ADX and MA ADX Filter: The Average Directional Index (ADX) measures the strength of a trend. The script calculates ADX using the user-defined length and applies a threshold value. Trading Signals with ADX Filter: Buy Signal: A regular MACD buy signal (crossover of MACD line above the signal line) is only considered valid if the ADX is above the set threshold. This suggests a stronger uptrend to potentially capitalize on. Sell Signal: Conversely, a regular MACD sell signal (crossunder of MACD line below the signal line) is only considered valid if the ADX is above the threshold, indicating a stronger downtrend for potential shorting opportunities. Benefits: The ADX filter helps avoid whipsaws or false signals that might occur during choppy market conditions with weak trends. MA Filter: You can choose from various Moving Average (MA) types (EMA, SMA, WMA, RMA, VWMA) for the filter. The script calculates the chosen MA based on the user-defined length. Trading Signals with MA Filter: Buy Signal: A regular MACD buy signal is only considered valid if the closing price is above the MA value. This suggests a potential uptrend confirmed by the price action staying above the moving average. Sell Signal: Conversely, a regular MACD sell signal is only considered valid if the closing price is below the MA value. This suggests a potential downtrend confirmed by the price action staying below the moving average. Benefits: The MA filter helps identify potential trend continuation opportunities by ensuring the price aligns with the chosen moving average direction. Combining Filters: You can choose to use either the ADX filter, the MA filter, or both depending on your strategy preference. Using both filters adds an extra layer of confirmation for your signals. 🔶 Backtesting Module The backtesting module in this script allows you to visually assess how the filtered MACD strategy would have performed on historical data. Here's a deeper dive into its features: Backtesting Type: You can choose to backtest for buy signals only, sell signals only, or both. This allows you to analyze the strategy's effectiveness in different market conditions. Stop-Loss Types: You can define how stop-loss orders are placed: ATR (Average True Range): This uses a volatility measure (ATR) multiplied by a user-defined factor to set the stop-loss level. Fixed Point: This allows you to specify a fixed dollar amount or percentage value as the stop-loss. X bar High/Low: This sets the stop-loss at a certain number of bars (defined by the user) above/below the bar's high (for long positions) or low (for short positions). Reward-to-Risk Ratio: Define the desired ratio between your potential profit and potential loss on each trade. The backtesting module will calculate take-profit levels based on this ratio and the stop-loss placement. 🔶 Disclaimer: Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals. Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator. Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies. Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses. No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Indicateur Pine Script®
par UAlgo
2
MACD EMA - TradingRush StrategyHey there! Today I present you a rather simple, but very profitable MACD strategy. Since I trade it with cryptocurrencies, the settings have been adjusted. I discovered the strategy on a YouTube channel and tried to transfer it as a strategy into a script. Tested with the crypto pair ETH/USDT in the 15 minute chart. There is the possibility to switch between short and long positions. ----------------------------------------------------------------------------------- How does the strategy work? ENTRY The MACD indicator must cross below the histogram. If it crosses when the price is below the EMA, only short positions are traded. Above the EMA - long. EXIT The Lowest Low (long) / highest high (short) serves as the stop loss. The TP is formed on the basis of a factor. (SL multiplied by factor 2.1 = TP). The red lines are used to illustrate the SL. Above for short positions below for long positions. The results of the strategy are without commissions and levers. If you have any questions or feedback, please let me know in the comments. If you need more information about the strategy and want to know exactly how to apply it, check out my profile. I wish you good luck with the strategy!
Stratégie Pine Script®
par TradingStrategyCheck
11