Strategi ini menggabungkan indikator stokastik untuk menentukan titik pembalikan overbought dan oversold dan indikator MACD untuk mengidentifikasi pembalikan tren, yang bertujuan untuk membeli rendah dan menjual tinggi melalui perdagangan pembalikan.
Menggunakan indikator stokastik untuk mengidentifikasi kondisi overbought dan oversold. pembacaan di bawah 20 menunjukkan tingkat oversold sementara di atas 80 menunjukkan zona overbought, membentuk sinyal pembalikan.
Pergi panjang pada MACD golden crosses dan pergi pendek pada MACD death crosses.
Mengambil posisi panjang atau pendek ketika pembalikan stokastik sejajar dengan sinyal pembalikan MACD.
Implementasikan stop loss trailing. Setelah memasuki tren, ketika harga mencapai persentase keuntungan tertentu, stop trailing dipicu.
Posisi yang ada ditutup dan stop loss diatur kembali ketika sinyal pembalikan baru muncul.
Konfirmasi beberapa indikator meningkatkan akurasi sinyal
Stochastic secara efektif mengidentifikasi zona overbought/oversold
MACD menangkap pembalikan rata-rata bergerak lebih awal
Trailing stop mengunci keuntungan dengan baik
Data backtesting yang cukup dengan sinyal strategi yang jelas
Parameter yang dapat dioptimalkan untuk penyesuaian mudah
Kesulitan dalam mengoptimalkan beberapa indikator
Sinyal pembalikan dapat salah dinilai dan perlu divalidasi
Lebih banyak data yang dibutuhkan untuk menguji dan mengoptimalkan trailing stop
Sifat keterlambatan dari stochastic dan MACD
Perdagangan yang sering dapat menyebabkan biaya yang lebih tinggi
Tambahkan lebih banyak indikator untuk membangun sistem perdagangan yang kuat
Uji periode parameter yang berbeda untuk menemukan kombinasi optimal
Mengembangkan parameter adaptif yang diperbarui secara real-time
Tentukan stop loss penarikan untuk membatasi penarikan maksimum
Masukkan volume untuk menghindari sinyal palsu dari perbedaan
Pertimbangkan dampak biaya perdagangan dan tetapkan target keuntungan minimum
Strategi ini menggabungkan kekuatan stochastic dan MACD dalam mengidentifikasi titik perdagangan pembalikan yang menguntungkan. Mekanisme trailing stop juga secara efektif mengunci keuntungan. Tetapi perdagangan pembalikan masih membawa risiko yang melekat yang membutuhkan validasi dari lebih banyak indikator dan optimasi parameter lebih lanjut. Dengan parameter yang stabil dan manajemen modal yang tepat, strategi ini dapat menjadi sistem perdagangan jangka pendek yang sangat efisien.
/*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)