Diese Strategie kombiniert den stochastischen Indikator zur Ermittlung von Überkauf- und Überverkaufsschwankungen und den MACD-Indikator zur Identifizierung von Trendumkehrungen, mit dem Ziel, durch Umkehrhandel niedrig zu kaufen und hoch zu verkaufen.
Verwenden Sie den stochastischen Indikator, um Überkauf- und Überverkaufszustände zu identifizieren.
Ein Kursumstieg über die Signallinie zeigt eine Umkehr des gleitenden Durchschnitts und impliziert eine Umkehr des Trends.
Lange oder kurze Positionen einnehmen, wenn die stochastische Umkehrung mit den MACD-Umkehrsignalen übereinstimmt.
Implementieren Sie einen Trailing Stop Loss. Nach dem Eintritt in einen Trend, wenn der Preis einen bestimmten Gewinnprozentsatz erreicht, wird der Trailing Stop ausgelöst.
Bestehende Positionen werden geschlossen und bei Erscheinen eines neuen Umkehrsignals wieder eingestellt.
Mehrfache Indikatorbestätigungen verbessern die Signalgenauigkeit
Stochastische Kennzeichnung von Überkauf-/Überverkaufszonen
Der MACD erfasst die Umkehrung des gleitenden Durchschnitts frühzeitig
Trailing-Stopp schließt sich den Gewinnen gut an
Ausreichende Daten aus dem Backtesting mit klaren Strategie-Signalen
Optimierbare Parameter für einfache Anpassungen
Schwierigkeiten bei der Optimierung mehrerer Indikatoren
Umkehrsignale können falsch beurteilt und validiert werden
Mehr Daten zur Prüfung und Optimierung von Trailing Stops erforderlich
Verzögerung des Stochastischen und des MACD
Häufige Handelsgeschäfte können zu höheren Kosten führen
Mehr Indikatoren hinzufügen, um ein robustes Handelssystem aufzubauen
Verschiedene Parameterperioden testen, um optimale Kombinationen zu finden
Entwickeln Sie anpassungsfähige Parameter, die in Echtzeit aktualisiert werden
Einrichtung von Aufnahmestoppverlusten zur Begrenzung des maximalen Aufnahmes
Einfügen der Lautstärke, um falsche Signale aus der Divergenz zu vermeiden
Berücksichtigen Sie die Auswirkungen der Handelskosten und legen Sie ein Mindestgewinnziel fest
Diese Strategie kombiniert die Stärken von Stochastic und MACD bei der Identifizierung günstiger Umkehrhandelspunkte. Der Trailing-Stop-Mechanismus sperrt auch effektiv Gewinne. Aber Umkehrhandel birgt immer noch inhärente Risiken, die von mehr Indikatoren validiert und weitere Parameteroptimierung benötigen. Mit stabilen Parametern und einem ordnungsgemäßen Kapitalmanagement kann diese Strategie zu einem hocheffizienten kurzfristigen Handelssystem werden.
/*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)