Cette stratégie combine l'indicateur stochastique pour déterminer les points d'inversion de surachat et de survente et l'indicateur MACD pour identifier les inversions de tendance, visant à acheter à bas prix et à vendre à haut prix par le biais d'un trading d'inversion.
Utilisez l'indicateur stochastique pour identifier les conditions de surachat et de survente. Des lectures inférieures à 20 indiquent des niveaux de survente tandis qu'au-dessus de 80 suggèrent des zones de surachat, formant des signaux d'inversion.
Une fois que le MACD est passé au-dessus de la ligne de signal, il indique un renversement de la moyenne mobile et implique un renversement de tendance.
Prendre des positions longues ou courtes lorsque l'inversion stochastique s'aligne sur les signaux d'inversion MACD.
Implémenter un stop-loss de suivi. Après avoir pénétré dans une tendance, lorsque le prix atteint un certain pourcentage de profit, un stop de suivi est déclenché. Le niveau de stop suit ensuite le canal de prix ascendant.
Les positions existantes sont fermées et le stop-loss réinitialisé lorsqu'un nouveau signal d'inversion apparaît.
La confirmation de plusieurs indicateurs améliore la précision du signal
Le stochastique identifie efficacement les zones de surachat/survente
Le MACD capte un renversement précoce de la moyenne mobile
Les profits sont bien bloqués
Des données suffisantes de backtesting avec des signaux stratégiques clairs
Paramètres optimisés pour des réglages faciles
Difficulté à optimiser plusieurs indicateurs
Les signaux d'inversion peuvent être mal jugés et doivent être validés
Plus de données nécessaires pour tester et optimiser les arrêts de trail
Nature retardée du stochastique et du MACD
Les échanges fréquents peuvent entraîner des coûts plus élevés
Ajouter plus d'indicateurs pour construire un système de négociation robuste
Testez différentes périodes de paramètres pour trouver des combinaisons optimales
Développer des paramètres adaptatifs mis à jour en temps réel
Définir le stop-loss pour le prélèvement afin de limiter le prélèvement maximal
Incorporer le volume pour éviter les faux signaux de divergence
Considérer l'impact des coûts de négociation et fixer un objectif de profit minimum
Cette stratégie combine les atouts du stochastique et du MACD dans l'identification de points de trading de renversement favorables. Le mécanisme de trailing stop bloque également efficacement les profits. Mais le trading de renversement comporte toujours des risques inhérents qui nécessitent la validation de plus d'indicateurs et une optimisation des paramètres. Avec des paramètres stables et une bonne gestion du capital, cette stratégie peut devenir un système de trading à court terme très efficace.
/*backtest start: 2022-09-14 00:00:00 end: 2023-06-24 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=4 //////////////////////////////////////////////////////////// // @CoinDigger // // Credits for the base strategy go to HPotter // // I've just added a trail stop, basic leverage simulation and stop loss // //////////////////////////////////////////////////////////// // Copyright by HPotter v1.0 28/01/2021 // This is combo strategies for get a cumulative signal. // // First strategy // This System was created from the Book "How I Tripled My Money In The // Futures Market" by Ulf Jensen, Page 183. This is reverse type of strategies. // The strategy buys at market, if close price is higher than the previous close // during 2 days and the meaning of 9-days Stochastic Slow Oscillator is lower than 50. // The strategy sells at market, if close price is lower than the previous close price // during 2 days and the meaning of 9-days Stochastic Fast Oscillator is higher than 50. // // Second strategy // MACD – Moving Average Convergence Divergence. The MACD is calculated // by subtracting a 26-day moving average of a security's price from a // 12-day moving average of its price. The result is an indicator that // oscillates above and below zero. When the MACD is above zero, it means // the 12-day moving average is higher than the 26-day moving average. // This is bullish as it shows that current expectations (i.e., the 12-day // moving average) are more bullish than previous expectations (i.e., the // 26-day average). This implies a bullish, or upward, shift in the supply/demand // lines. When the MACD falls below zero, it means that the 12-day moving average // is less than the 26-day moving average, implying a bearish shift in the // supply/demand lines. // A 9-day moving average of the MACD (not of the security's price) is usually // plotted on top of the MACD indicator. This line is referred to as the "signal" // line. The signal line anticipates the convergence of the two moving averages // (i.e., the movement of the MACD toward the zero line). // Let's consider the rational behind this technique. The MACD is the difference // between two moving averages of price. When the shorter-term moving average rises // above the longer-term moving average (i.e., the MACD rises above zero), it means // that investor expectations are becoming more bullish (i.e., there has been an // upward shift in the supply/demand lines). By plotting a 9-day moving average of // the MACD, we can see the changing of expectations (i.e., the shifting of the // supply/demand lines) as they occur. // // WARNING: // - For purpose educate only // - This script to change bars colors. //////////////////////////////////////////////////////////// Reversal123(Length, KSmoothing, DLength, Level) => vFast = sma(stoch(close, high, low, Length), KSmoothing) vSlow = sma(vFast, DLength) pos = 0.0 pos := iff(close[2] < close[1] and close > close[1] and vFast < vSlow and vFast > Level, 1, iff(close[2] > close[1] and close < close[1] and vFast > vSlow and vFast < Level, -1, nz(pos[1], 0))) pos MACD(fastLength,slowLength,signalLength) => pos = 0.0 fastMA = ema(close, fastLength) slowMA = ema(close, slowLength) macd = fastMA - slowMA signal = sma(macd, signalLength) pos:= iff(signal < macd , 1, iff(signal > macd, -1, nz(pos[1], 0))) pos strategy(title="Combo Backtest 123 Reversal & MACD Crossover with Trail and Stop", shorttitle="ComboReversal123MACDWithStop", overlay = false, precision=8,default_qty_type=strategy.percent_of_equity, default_qty_value=100, initial_capital=100, currency="USD", commission_type=strategy.commission.percent, commission_value=0.075) leverage=input(2,"leverage",step=1) percentOfEquity=input(100,"percentOfEquity",step=1) sl_trigger = input(10, title='Stop Trail Trigger %', type=input.float)/100 sl_trail = input(5, title='Stop Trail %', type=input.float)/100 sl_inp = input(10, title='Stop Loss %', type=input.float)/100 Length = input(100, minval=1) KSmoothing = input(1, minval=1) DLength = input(2, minval=1) Level = input(1, minval=1) //------------------------- fastLength = input(10, minval=1) slowLength = input(19,minval=1) signalLength=input(24,minval=1) xSeria = input(title="Source", type=input.source, defval=close) reverse = input(false, title="Trade reverse") //////////////////////////////////////////////////////////////////////////////// // BACKTESTING RANGE // From Date Inputs fromDay = input(defval = 1, title = "From Day", minval = 1, maxval = 31) fromMonth = input(defval = 1, title = "From Month", minval = 1, maxval = 12) fromYear = input(defval = 2015, title = "From Year", minval = 1970) // To Date Inputs toDay = input(defval = 1, title = "To Day", minval = 1, maxval = 31) toMonth = input(defval = 1, title = "To Month", minval = 1, maxval = 12) toYear = input(defval = 2999, title = "To Year", minval = 1970) // Calculate start/end date and time condition startDate = timestamp(fromYear, fromMonth, fromDay, 00, 00) finishDate = timestamp(toYear, toMonth, toDay, 00, 00) time_cond = time >= startDate and time <= finishDate //////////////////////////////////////////////////////////////////////////////// ////////////////////// STOP LOSS CALCULATIONS ////////////////////////////// /////////////////////////////////////////////////// cond() => barssince(strategy.position_size[1] == 0 and (strategy.position_size > 0 or strategy.position_size < 0)) > 0 lastStopLong = 0.0 lastStopLong := lastStopLong[1] != strategy.position_avg_price - (strategy.position_avg_price * (sl_inp)) and lastStopLong[1] != 0.0 ? lastStopLong[1] : strategy.position_size > 0 ? (cond() and close > strategy.position_avg_price + (strategy.position_avg_price * (sl_trigger)) ? strategy.position_avg_price + (strategy.position_avg_price * (sl_trail)) : strategy.position_avg_price - (strategy.position_avg_price * (sl_inp))) : 0 lastStopShort = 0.0 lastStopShort := lastStopShort[1] != strategy.position_avg_price + (strategy.position_avg_price * (sl_inp)) and lastStopShort[1] != 9999999999.0 ? lastStopShort[1] : strategy.position_size < 0 ? (cond() and close < strategy.position_avg_price - (strategy.position_avg_price * (sl_trigger)) ? strategy.position_avg_price - (strategy.position_avg_price * (sl_trail)) : strategy.position_avg_price + (strategy.position_avg_price * (sl_inp))) : 9999999999.0 longStopPrice = 0.0 longStopPrice2 = 0.0 longStopPrice3 = 0.0 shortStopPrice = 0.0 longStopPrice := if strategy.position_size > 0 originalStop = strategy.position_avg_price - (strategy.position_avg_price * (sl_inp)) trigger = strategy.position_avg_price + (strategy.position_avg_price * (sl_trigger)) trail = strategy.position_avg_price + (strategy.position_avg_price * (sl_trail)) stopValue = high > trigger ? trail : 0 max(stopValue, originalStop, longStopPrice[1]) else 0 longStopPrice2 := if strategy.position_size > 0 originalStop = strategy.position_avg_price - (strategy.position_avg_price * (sl_inp)) trigger = strategy.position_avg_price + (strategy.position_avg_price * (sl_trigger*2)) trail = strategy.position_avg_price + (strategy.position_avg_price * (sl_trail*2)) stopValue = high > trigger ? trail : 0 max(stopValue, originalStop, longStopPrice2[1]) else 0 longStopPrice3 := if strategy.position_size > 0 originalStop = strategy.position_avg_price - (strategy.position_avg_price * (sl_inp)) trigger = strategy.position_avg_price + (strategy.position_avg_price * (sl_trigger*4)) trail = strategy.position_avg_price + (strategy.position_avg_price * (sl_trail*3)) stopValue = high > trigger ? trail : 0 max(stopValue, originalStop, longStopPrice3[1]) else 0 shortStopPrice := if strategy.position_size < 0 originalStop = strategy.position_avg_price + (strategy.position_avg_price * (sl_inp)) trigger = strategy.position_avg_price - (strategy.position_avg_price * (sl_trigger)) trail = strategy.position_avg_price - (strategy.position_avg_price * (sl_trail)) stopValue = low < trigger ? trail : 999999 min(stopValue, originalStop, shortStopPrice[1]) else 999999 /////////////////////////////////////////////////// /////////////////////////////////////////////////// posReversal123 = Reversal123(Length, KSmoothing, DLength, Level) posMACD = MACD(fastLength,slowLength, signalLength) pos = iff(posReversal123 == 1 and posMACD == 1 , 1, iff(posReversal123 == -1 and posMACD == -1, -1, 0)) possig = pos quantity = max(0.000001,min(((strategy.equity*(percentOfEquity/100))*leverage/open),100000000)) if (possig == 1 and time_cond) strategy.entry("Long", strategy.long, qty=quantity) if (possig == -1 and time_cond) strategy.entry("Short", strategy.short, qty=quantity) if (strategy.position_size > 0 and possig == -1 and time_cond) strategy.close_all() if (strategy.position_size < 0 and possig == 1 and time_cond) strategy.close_all() if ((strategy.position_size < 0 or strategy.position_size > 0) and possig == 0) strategy.close_all() //EXIT TRADE @ TSL if strategy.position_size > 0 strategy.exit(id="Long", stop=longStopPrice) if strategy.position_size < 0 strategy.exit(id="Short", stop=shortStopPrice)