La
La stratégie commence par calculer le canal de Vegas, qui est dérivé de la moyenne mobile simple (SMA) et de l'écart type (STD) des prix de clôture sur une longueur de fenêtre spécifiée. Ce canal aide à mesurer la volatilité du marché et constitue la base pour ajuster l'indicateur de SuperTrend. Ensuite, la plage moyenne vraie (ATR) et le multiplicateur ajusté sont utilisés pour déterminer les seuils supérieur et inférieur de la SuperTrend.
L'avantage principal de la stratégie de trading quantitative de SuperTrend ajustée à la volatilité du canal de Double Vegas réside dans sa capacité à ajuster dynamiquement l'indicateur de SuperTrend pour s'adapter aux conditions changeantes du marché. En incorporant la largeur du canal de Vegas, la stratégie peut mieux réagir à la volatilité du marché, améliorant la précision de l'identification des tendances.
Bien que la stratégie vise à améliorer la précision de l'identification des tendances, il y a encore quelques risques impliqués. Premièrement, la stratégie peut générer de faux signaux de trading pendant les périodes de volatilité extrêmement élevée ou la direction du marché peu claire. Deuxièmement, un trading trop fréquent peut entraîner des coûts de transaction élevés, affectant la performance globale de la stratégie. Pour atténuer ces risques, les traders peuvent envisager d'optimiser les paramètres de la stratégie, tels que l'ajustement des périodes ATR, des longueurs de fenêtre du canal Vegas et des multiplicateurs de SuperTrend pour répondre aux conditions spécifiques du marché.
La stratégie de trading quantitative de la SuperTrend ajustée à la volatilité du canal de Double Vegas peut être optimisée de plusieurs façons. Une direction d'optimisation potentielle consiste à incorporer des indicateurs techniques supplémentaires, tels que l'indice de force relative (RSI) ou la divergence de convergence moyenne mobile (MACD), pour améliorer la fiabilité de la confirmation de la tendance. Une autre direction d'optimisation consiste à introduire des mécanismes adaptatifs qui ajustent dynamiquement les paramètres de la stratégie en fonction des conditions du marché. Cela peut être réalisé à l'aide d'algorithmes d'apprentissage automatique ou d'approches basées sur des règles. En outre, l'optimisation des périodes de détention et des niveaux de prise de profit / stop-loss peut également améliorer la performance globale de la stratégie.
En résumé, la
/*backtest start: 2024-05-01 00:00:00 end: 2024-05-31 23:59:59 period: 3h basePeriod: 15m exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ // This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/ // © PresentTrading // The "Double Vegas SuperTrend Enhanced" strategy uses two SuperTrend indicators with different ATR and Vegas Channel settings // to identify market trends and generate trades. Trades are executed only when both SuperTrends align in the same direction. // The strategy includes configurable take-profit and stop-loss levels, and plots the SuperTrend levels on the chart. //@version=5 strategy("Double Vegas SuperTrend Enhanced - Strategy [presentTrading]", shorttitle="Double Vegas SuperTrend Enhanced - Strategy [presentTrading]", overlay=true, overlay = false, precision=3, commission_value= 0.1, commission_type=strategy.commission.percent, slippage= 1, currency=currency.USD, default_qty_type = strategy.percent_of_equity, default_qty_value = 10, initial_capital= 10000) // Input settings allow the user to customize the strategy's parameters. tradeDirectionChoice = input.string(title="Trade Direction", defval="Both", options=["Long", "Short", "Both"]) // Option to select the trading direction // Settings for the first Vegas SuperTrend atrPeriod1 = input(10, "ATR Period for SuperTrend 1") // Length of the ATR for volatility measurement vegasWindow1 = input(100, "Vegas Window Length 1") // Length of the moving average for the Vegas Channel superTrendMultiplier1 = input(5, "SuperTrend Multiplier Base 1") // Base multiplier for the SuperTrend calculation volatilityAdjustment1 = input.float(5, "Volatility Adjustment Factor 1") // Factor to adjust the SuperTrend sensitivity to the Vegas Channel width // Settings for the second Vegas SuperTrend atrPeriod2 = input(5, "ATR Period for SuperTrend 2") // Length of the ATR for volatility measurement vegasWindow2 = input(200, "Vegas Window Length 2") // Length of the moving average for the Vegas Channel superTrendMultiplier2 = input(7, "SuperTrend Multiplier Base 2") // Base multiplier for the SuperTrend calculation volatilityAdjustment2 = input.float(7, "Volatility Adjustment Factor 2") // Factor to adjust the SuperTrend sensitivity to the Vegas Channel width // Settings for Hold Days and TPSL Conditions useHoldDays = input.bool(true, title="Use Hold Days") holdDays = input.int(5, title="Hold Days", minval=1, maxval=60, step=1) TPSLCondition = input.string("None", "TPSL Condition", options=["TP", "SL", "Both", "None"]) takeProfitPerc = input(30.0, title="Take Profit (%)") stopLossPerc = input(20.0, title="Stop Loss (%)") // Calculate the first Vegas Channel using a simple moving average and standard deviation. vegasMovingAverage1 = ta.sma(close, vegasWindow1) vegasChannelStdDev1 = ta.stdev(close, vegasWindow1) vegasChannelUpper1 = vegasMovingAverage1 + vegasChannelStdDev1 vegasChannelLower1 = vegasMovingAverage1 - vegasChannelStdDev1 // Adjust the first SuperTrend multiplier based on the width of the Vegas Channel. channelVolatilityWidth1 = vegasChannelUpper1 - vegasChannelLower1 adjustedMultiplier1 = superTrendMultiplier1 + volatilityAdjustment1 * (channelVolatilityWidth1 / vegasMovingAverage1) // Calculate the first SuperTrend indicator values. averageTrueRange1 = ta.atr(atrPeriod1) superTrendUpper1 = hlc3 - (adjustedMultiplier1 * averageTrueRange1) superTrendLower1 = hlc3 + (adjustedMultiplier1 * averageTrueRange1) var float superTrendPrevUpper1 = na var float superTrendPrevLower1 = na var int marketTrend1 = 1 // Update SuperTrend values and determine the current trend direction for the first SuperTrend. superTrendPrevUpper1 := nz(superTrendPrevUpper1[1], superTrendUpper1) superTrendPrevLower1 := nz(superTrendPrevLower1[1], superTrendLower1) marketTrend1 := close > superTrendPrevLower1 ? 1 : close < superTrendPrevUpper1 ? -1 : nz(marketTrend1[1], 1) superTrendUpper1 := marketTrend1 == 1 ? math.max(superTrendUpper1, superTrendPrevUpper1) : superTrendUpper1 superTrendLower1 := marketTrend1 == -1 ? math.min(superTrendLower1, superTrendPrevLower1) : superTrendLower1 superTrendPrevUpper1 := superTrendUpper1 superTrendPrevLower1 := superTrendLower1 // Calculate the second Vegas Channel using a simple moving average and standard deviation. vegasMovingAverage2 = ta.sma(close, vegasWindow2) vegasChannelStdDev2 = ta.stdev(close, vegasWindow2) vegasChannelUpper2 = vegasMovingAverage2 + vegasChannelStdDev2 vegasChannelLower2 = vegasMovingAverage2 - vegasChannelStdDev2 // Adjust the second SuperTrend multiplier based on the width of the Vegas Channel. channelVolatilityWidth2 = vegasChannelUpper2 - vegasChannelLower2 adjustedMultiplier2 = superTrendMultiplier2 + volatilityAdjustment2 * (channelVolatilityWidth2 / vegasMovingAverage2) // Calculate the second SuperTrend indicator values. averageTrueRange2 = ta.atr(atrPeriod2) superTrendUpper2 = hlc3 - (adjustedMultiplier2 * averageTrueRange2) superTrendLower2 = hlc3 + (adjustedMultiplier2 * averageTrueRange2) var float superTrendPrevUpper2 = na var float superTrendPrevLower2 = na var int marketTrend2 = 1 // Update SuperTrend values and determine the current trend direction for the second SuperTrend. superTrendPrevUpper2 := nz(superTrendPrevUpper2[1], superTrendUpper2) superTrendPrevLower2 := nz(superTrendPrevLower2[1], superTrendLower2) marketTrend2 := close > superTrendPrevLower2 ? 1 : close < superTrendPrevUpper2 ? -1 : nz(marketTrend2[1], 1) superTrendUpper2 := marketTrend2 == 1 ? math.max(superTrendUpper2, superTrendPrevUpper2) : superTrendUpper2 superTrendLower2 := marketTrend2 == -1 ? math.min(superTrendLower2, superTrendPrevLower2) : superTrendLower2 superTrendPrevUpper2 := superTrendUpper2 superTrendPrevLower2 := superTrendLower2 // Enhanced Visualization // Plot the SuperTrend and Vegas Channel for visual analysis for both lengths. plot(marketTrend1 == 1 ? superTrendUpper1 : na, "SuperTrend Upper 1", color=color.green, linewidth=2) plot(marketTrend1 == -1 ? superTrendLower1 : na, "SuperTrend Lower 1", color=color.red, linewidth=2) plot(marketTrend2 == 1 ? superTrendUpper2 : na, "SuperTrend Upper 2", color=color.rgb(31, 119, 130), linewidth=2) plot(marketTrend2 == -1 ? superTrendLower2 : na, "SuperTrend Lower 2", color=color.rgb(120, 42, 26), linewidth=2) // Detect trend direction changes and plot entry/exit signals for both lengths. trendShiftToBullish1 = marketTrend1 == 1 and marketTrend1[1] == -1 trendShiftToBearish1 = marketTrend1 == -1 and marketTrend1[1] == 1 trendShiftToBullish2 = marketTrend2 == 1 and marketTrend2[1] == -1 trendShiftToBearish2 = marketTrend2 == -1 and marketTrend2[1] == 1 // Define conditions for entering long or short positions, and execute trades based on these conditions for both lengths. enterLongCondition1 = marketTrend1 == 1 enterShortCondition1 = marketTrend1 == -1 enterLongCondition2 = marketTrend2 == 1 enterShortCondition2 = marketTrend2 == -1 // Entry conditions: Both conditions must be met for a trade to be executed. enterLongCondition = enterLongCondition1 and enterLongCondition2 and not na(superTrendPrevUpper1[1]) and not na(superTrendPrevUpper2[1]) enterShortCondition = enterShortCondition1 and enterShortCondition2 and not na(superTrendPrevLower1[1]) and not na(superTrendPrevLower2[1]) // Variables to track entry times var float longEntryTime = na var float shortEntryTime = na // Variables to track whether we have recently exited a trade to prevent re-entry in the same trend var bool recentlyExitedLong = false var bool recentlyExitedShort = false // Check trade direction choice before executing trade entries. if (enterLongCondition and (tradeDirectionChoice == "Long" or tradeDirectionChoice == "Both")) if (strategy.position_size < 0) strategy.close("Short Position") strategy.entry("Long Position", strategy.long) longEntryTime := time recentlyExitedLong := false recentlyExitedShort := false if (enterShortCondition and (tradeDirectionChoice == "Short" or tradeDirectionChoice == "Both")) if (strategy.position_size > 0) strategy.close("Long Position") strategy.entry("Short Position", strategy.short) shortEntryTime := time recentlyExitedShort := false recentlyExitedLong := false // Exit conditions: Either condition being met will trigger an exit. exitLongCondition = marketTrend1 == -1 or marketTrend2 == -1 exitShortCondition = marketTrend1 == 1 or marketTrend2 == 1 // Close positions based on exit conditions or hold days. if (useHoldDays and not na(longEntryTime) and (time >= longEntryTime + holdDays * 86400000) and strategy.position_size > 0) strategy.close("Long Position") longEntryTime := na recentlyExitedLong := true if (useHoldDays and not na(shortEntryTime) and (time >= shortEntryTime + holdDays * 86400000) and strategy.position_size < 0) strategy.close("Short Position") shortEntryTime := na recentlyExitedShort := true if (not useHoldDays and exitLongCondition and strategy.position_size > 0) strategy.close("Long Position") longEntryTime := na recentlyExitedLong := true if (not useHoldDays and exitShortCondition and strategy.position_size < 0) strategy.close("Short Position") shortEntryTime := na recentlyExitedShort := true // Reset recently exited flags on trend change to allow re-entry on a new trend if (trendShiftToBullish1 or trendShiftToBullish2) recentlyExitedLong := false if (trendShiftToBearish1 or trendShiftToBearish2) recentlyExitedShort := false // Conditional Profit and Loss Management if (TPSLCondition == "TP" or TPSLCondition == "Both") // Apply take profit conditions strategy.exit("TakeProfit_Long", "Long Position", limit=close * (1 + takeProfitPerc / 100)) strategy.exit("TakeProfit_Short", "Short Position", limit=close * (1 - takeProfitPerc / 100)) if (TPSLCondition == "SL" or TPSLCondition == "Both") // Apply stop loss conditions strategy.exit("StopLoss_Long", "Long Position", stop=close * (1 - stopLossPerc / 100)) strategy.exit("StopLoss_Short", "Short Position", stop=close * (1 + stopLossPerc / 100)) // Ensure that new entry signals can override the hold days condition if (enterLongCondition and (tradeDirectionChoice == "Long" or tradeDirectionChoice == "Both")) if (strategy.position_size < 0) strategy.close("Short Position") strategy.entry("Long Position", strategy.long) longEntryTime := time recentlyExitedLong := false recentlyExitedShort := false if (enterShortCondition and (tradeDirectionChoice == "Short" or tradeDirectionChoice == "Both")) if (strategy.position_size > 0) strategy.close("Long Position") strategy.entry("Short Position", strategy.short) shortEntryTime := time recentlyExitedShort := false recentlyExitedLong := false