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Strategi multi-indikator untuk mengidentifikasi titik perubahan perdagangan dalam Quant Trading

Penulis:ChaoZhang, Tanggal: 2023-11-02 14:09:34
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Gambaran umum

Strategi ini mengintegrasikan 5 indikator utama termasuk EMA, VWAP, MACD, Bollinger Bands dan Siklus Tren Schaff untuk mengidentifikasi titik infleksi di mana harga berbalik dalam kisaran tertentu, dan menghasilkan sinyal beli dan jual. Keuntungan dari strategi ini adalah fleksibilitas untuk menggabungkan indikator yang berbeda berdasarkan kondisi pasar yang bervariasi untuk mengurangi sinyal palsu dan meningkatkan profitabilitas. Namun, ada juga risiko identifikasi sinyal yang tertinggal dan penyesuaian parameter yang tidak tepat. Secara keseluruhan, strategi ini memiliki aliran logika yang jelas dan nilai praktis yang kuat.

Logika Strategi

  1. EMA menilai arah tren secara keseluruhan, hanya membeli dengan tren

  2. VWAP menilai aliran uang institusional, hanya membeli ketika institusi membeli

  3. MACD menilai tren jangka pendek dan perubahan momentum, garis MACD crossover sinyal garis adalah sinyal beli / jual

  4. Bollinger Bands menilai kondisi overbought dan oversold, harga keluar dari band menunjukkan sinyal beli/jual

  5. Schaff Trend Cycle menilai struktur jangka pendek yang terikat pada kisaran, melebihi ambang tinggi/rendah menunjukkan sinyal beli/jual

  6. Kirim pesanan beli/jual ketika semua 5 indikator setuju pada sinyal

  7. Atur stop loss dan ambil keuntungan untuk mengoptimalkan manajemen modal

Keuntungan

  1. Menurunkan sinyal palsu dengan kombinasi multi-indikator

Menggunakan kombinasi indikator seperti EMA, VWAP, MACD, BB, dan STC memungkinkan validasi silang untuk menghilangkan sinyal palsu dari setiap indikator individu, meningkatkan keandalan.

  1. Indikator yang dapat disesuaikan

Kemampuan untuk mengaktifkan/menonaktifkan indikator memungkinkan untuk menggabungkan indikator ideal untuk produk dan lingkungan pasar yang berbeda, meningkatkan kemampuan beradaptasi.

  1. Manajemen modal yang dioptimalkan

Stop loss dan take profit memungkinkan membatasi kerugian perdagangan tunggal dan mengunci keuntungan, memungkinkan manajemen modal yang lebih baik.

  1. Logika strategi yang jelas

Indikator intuitif sederhana yang digunakan dengan komentar kode rinci membuat logika strategi keseluruhan mudah dipahami dan dimodifikasi.

  1. Kepraktisan yang kuat

Indikator yang banyak digunakan dengan penyesuaian yang wajar memungkinkan perdagangan langsung dengan hasil yang layak segera tanpa optimasi ekstensif.

Risiko

  1. Risiko identifikasi sinyal keterlambatan

EMA, MACD dll memiliki keterlambatan dalam mengidentifikasi perubahan harga, yang dapat menyebabkan hilangnya waktu masuk terbaik.

  1. Risiko penyesuaian parameter yang tidak benar

Parameter indikator yang buruk akan menghasilkan sinyal palsu yang berlebihan dan strategi putus.

  1. Tidak ada jaminan tingkat kemenangan

Kombinasi multi-indikator meningkatkan tetapi tidak menjamin tingkat kemenangan.

  1. Stop loss diatur terlalu ketat

Jika stop loss terlalu ketat, fluktuasi harga normal dapat dihentikan menyebabkan kerugian yang tidak perlu.

Peluang Peningkatan

  1. Tambahkan model ML untuk penilaian keandalan sinyal

Train model untuk skor multi-indikator sinyal pada keandalan, menyaring sinyal palsu.

  1. Tambahkan indikator momentum untuk identifikasi akumulasi

Tambahkan indikator kuantitatif seperti OBV untuk mengidentifikasi akumulasi harga, meningkatkan kepastian titik beli.

  1. Optimalkan logika stop loss dan take profit

Penelitian yang lebih cocok trailing stop atau mengambil keuntungan logika untuk strategi ini untuk lebih mengoptimalkan manajemen modal.

  1. Optimasi parameter

Melakukan pengujian backtest yang lebih sistematis untuk menemukan parameter optimal untuk setiap indikator, meningkatkan ketahanan.

  1. Tambahkan perdagangan otomatis

Sambungkan ke API perdagangan untuk memungkinkan eksekusi pesanan otomatis, memungkinkan eksekusi strategi hands-off sepenuhnya otomatis.

Kesimpulan

Strategi ini menggabungkan kekuatan dari beberapa indikator teknis dengan aliran logika yang jelas dan nilai praktis yang kuat. Ini dapat berfungsi sebagai dukungan keputusan perdagangan discretionary atau perdagangan algoritmik langsung. Tetapi optimasi dan penyesuaian berdasarkan lingkungan produk dan pasar tertentu diperlukan untuk mengurangi risiko dan meningkatkan stabilitas sebelum perdagangan langsung yang menguntungkan secara konsisten.


/*backtest
start: 2023-10-02 00:00:00
end: 2023-11-01 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © MakeMoneyCoESTB2020

//*********************Notes for continued work***************
//3) add a Table of contents to each section of code
//4) add candle stick pattern considerations to chart
//5) add an input value for DTE range to backtest
//7) add abilit to turn on/off MACD plot
//9)
//************************************************************


//Hello my fellow investors
//After hours of reading, backtesting, and YouTube video watching
//I discovered that 200EMA, VWAP, BB, MACD, and STC 
//produce the most consistent results for investment planning.
//This strategy allows you to pick between the aforementioned indicators or layer them together.
//It works on the pricipal of:
//1) Always follow the market trend - buy/sell above/below 200EMA
//2) Follow corporate investing trends - buy/sell above/below VWAP
//3) Apply MACD check - buy--> MACD line above signal line 
// and corssover below histogram \\ sell --> MACD line below signal line 
// and crossover above histogram.
//4) Check volitility with price against BB limits upper/Sell or lower/buy
//5) When STC crosses about 10 buy and when it drops below 90 sell
//6) Exit position when stop loss is triggered or profit target is hit.  BB also provides a parameter to exit positions.

//This code is the product of many hours of hard work on the part of the greater tradingview community.  The credit goes to everyone in the community who has put code out there for the greater good.

//Happy Hunting!



//Title
// strategy("WOMBO COMBO: 100/200EMA & VWAP & MACD", shorttitle="WOMBO COMBO", default_qty_type=strategy.percent_of_equity, default_qty_value=1.5, initial_capital=10000,slippage=2, currency=currency.USD, overlay=true)

//define calculations price source
price = input(title="Price Source", defval=close)


//***************************
//Calculate 20/50/100/200EMA 
EMAlength = input(title="EMA_Length", defval=200)
EMA=ema(price, EMAlength)
//plot EMA
ColorEMA=EMAlength==200?color.blue:EMAlength==100?color.aqua:EMAlength==50?color.orange:color.red
plot(EMA, title = "EMA", color = ColorEMA)


//*****************************
//calculate VWAP
ColorVWAP = (price > vwap) ? color.lime : color.maroon
plot(vwap, title = "VWAP", color=ColorVWAP, linewidth=2)


//*****************************
//calculate MACD
//define variables for speed
fast = 12, slow = 26
//define parameters to calculate MACD
fastMA = ema(price, fast)
slowMA = ema(price, slow)
//define MACD line
macd = fastMA - slowMA
//define SIGNAL line
signal = sma(macd, 9)
//plot MACD line
//plot(macd, title = "MACD",  color=color.orange)
//plot signal line
//plot(signal, title = "Signal", color=color.purple)
//plot histogram
//define histogram colors
//col_grow_above = color.green
//col_grow_below = color.red
//col_fall_above = color.lime
//col_fall_below = color.maroon
//define histogram value
//hist = macd - signal
//plot histogram
//plot(hist, title="Histogram", style=plot.style_columns, color=(hist>=0 ? (hist[1] < hist ? col_grow_above : col_fall_above) : (hist[1] < hist ? col_grow_below : col_fall_below) ), transp=0 )


//***************************************
//Calculate Bollinger Bands
//Define BB input variables
//lengthBB = input(20, minval=1)
//multBB = input(2.0, minval=0.001, maxval=50)
lengthBB = 20
multBB = 2
//define BB average
basisBB = sma(price, lengthBB)
//define BB standar deviation
devBB = multBB * stdev(price, lengthBB)
//define BB upper and lower limits
upperBB = basisBB + devBB
lowerBB = basisBB - devBB
//Plot BB graph
ShowBB = input(title="Show BB", defval="Y", type=input.string, options=["Y", "N"])
transP = (ShowBB=="Y") ? 0 : 100
plot (upperBB, title = "BB Upper Band", color = color.aqua, transp=transP)
plot (basisBB, title = "BB Average", color = color.red, transp=transP)
plot (lowerBB, title = "BB Lower Band", color = color.aqua, transp=transP)


//*************************************************
//Calculate STC
//fastLength = input(title="MACD Fast Length", type=input.integer, defval=12)
//slowLength = input(title="MACD Slow Length", type=input.integer, defval=26)
fastLength = 23
slowLength = 50
cycleLength = input(title="Cycle Length", type=input.integer, defval=10)
//d1Length = input(title="1st %D Length", type=input.integer, defval=3)
//d2Length = input(title="2nd %D Length", type=input.integer, defval=3)
d1Length = 3
d2Length = 3
srcSTC = close

macdSTC = ema(srcSTC, fastLength) - ema(srcSTC, slowLength)
k = nz(fixnan(stoch(macdSTC, macdSTC, macdSTC, cycleLength)))
d = ema(k, d1Length)
kd = nz(fixnan(stoch(d, d, d, cycleLength)))
stc = ema(kd, d2Length)
stc := 	stc > 100 ? 100 : stc < 0 ? 0 : stc
upperSTC = input(title="Upper STC limit", defval=90)
lowerSTC = input( title="Lower STC limit", defval=10)

ma1length=35
ma1 = ema(close,ma1length)
ma2 = ema(close,EMAlength)

//STCbuy = crossover(stc, lowerSTC) and ma1>ma2 and close>ma1
//STCsell = crossunder(stc, upperSTC) and ma1<ma2 and close<ma1
STCbuy = crossover(stc, lowerSTC) 
STCsell = crossunder(stc, upperSTC) 




//*************************************************
//Candle stick patterns
//DojiSize = input(0.05, minval=0.01, title="Doji size")
//data=(abs(open - close) <= (high - low) * DojiSize)
//plotchar(data, title="Doji", text='Doji', color=color.white)

data2=(close[2] > open[2] and min(open[1], close[1]) > close[2] and open < min(open[1], close[1]) and close < open )
//plotshape(data2, title= "Evening Star", color=color.red, style=shape.arrowdown, text="Evening\nStar")

data3=(close[2] < open[2] and max(open[1], close[1]) < close[2] and open > max(open[1], close[1]) and close > open )
//plotshape(data3,  title= "Morning Star", location=location.belowbar, color=color.lime, style=shape.arrowup, text="Morning\nStar")

data4=(open[1] < close[1] and open > close[1] and high - max(open, close) >= abs(open - close) * 3 and min(close, open) - low <= abs(open - close))
//plotshape(data4, title= "Shooting Star", color=color.red, style=shape.arrowdown, text="Shooting\nStar")

data5=(((high - low)>3*(open -close)) and  ((close - low)/(.001 + high - low) > 0.6) and ((open - low)/(.001 + high - low) > 0.6))
//plotshape(data5, title= "Hammer", location=location.belowbar, color=color.white, style=shape.diamond, text="H")

data5b=(((high - low)>3*(open -close)) and  ((high - close)/(.001 + high - low) > 0.6) and ((high - open)/(.001 + high - low) > 0.6))
//plotshape(data5b, title= "Inverted Hammer", location=location.belowbar, color=color.white, style=shape.diamond, text="IH")

data6=(close[1] > open[1] and open > close and open <= close[1] and open[1] <= close and open - close < close[1] - open[1] )
//plotshape(data6, title= "Bearish Harami",  color=color.red, style=shape.arrowdown, text="Bearish\nHarami")

data7=(open[1] > close[1] and close > open and close <= open[1] and close[1] <= open and close - open < open[1] - close[1] )
//plotshape(data7,  title= "Bullish Harami", location=location.belowbar, color=color.lime, style=shape.arrowup, text="Bullish\nHarami")

data8=(close[1] > open[1] and open > close and open >= close[1] and open[1] >= close and open - close > close[1] - open[1] )
//plotshape(data8,  title= "Bearish Engulfing", color=color.red, style=shape.arrowdown, text="Bearish\nEngulfing")

data9=(open[1] > close[1] and close > open and close >= open[1] and close[1] >= open and close - open > open[1] - close[1] )
//plotshape(data9, title= "Bullish Engulfing", location=location.belowbar, color=color.lime, style=shape.arrowup, text="Bullish\nEngulfling")

upper = highest(10)[1]
data10=(close[1] < open[1] and  open < low[1] and close > close[1] + ((open[1] - close[1])/2) and close < open[1])
//plotshape(data10, title= "Piercing Line", location=location.belowbar, color=color.lime, style=shape.arrowup, text="Piercing\nLine")

lower = lowest(10)[1]
data11=(low == open and  open < lower and open < close and close > ((high[1] - low[1]) / 2) + low[1])
//plotshape(data11, title= "Bullish Belt", location=location.belowbar, color=color.lime, style=shape.arrowup, text="Bullish\nBelt")

data12=(open[1]>close[1] and open>=open[1] and close>open)
//plotshape(data12, title= "Bullish Kicker", location=location.belowbar, color=color.lime, style=shape.arrowup, text="Bullish\nKicker")

data13=(open[1]<close[1] and open<=open[1] and close<=open)
//plotshape(data13, title= "Bearish Kicker", color=color.red, style=shape.arrowdown, text="Bearish\nKicker")

data14=(((high-low>4*(open-close))and((close-low)/(.001+high-low)>=0.75)and((open-low)/(.001+high-low)>=0.75)) and high[1] < open and high[2] < open)
//plotshape(data14,  title= "Hanging Man", color=color.red, style=shape.arrowdown, text="Hanging\nMan")

data15=((close[1]>open[1])and(((close[1]+open[1])/2)>close)and(open>close)and(open>close[1])and(close>open[1])and((open-close)/(.001+(high-low))>0.6))
//plotshape(data15, title= "Dark Cloud Cover", color=color.red, style=shape.arrowdown, text="Dark\nCloudCover")




//**********Long & Short Entry Calculations***********************************
//Define countback variable
countback=input(minval=0, maxval=5, title="Price CountBack", defval=0)
//User input for what evaluations to run: EMA, VWAP, MACD, BB
EMA_Y_N=input(defval = "N", title="Run EMA", type=input.string, options=["Y", "N"])
VWAP_Y_N=input(defval = "N", title="Run VWAP", type=input.string, options=["Y", "N"])
MACD_Y_N=input(defval = "N", title="Run MACD", type=input.string, options=["Y", "N"])
BB_Y_N=input(defval = "N", title="Run BB", type=input.string, options=["Y", "N"])
STC_Y_N=input(defval = "Y", title="Run STC", type=input.string, options=["Y", "N"])
//long entry condition
dataHCLB=(iff(STC_Y_N=="Y", STCbuy, true) and iff(EMA_Y_N=="Y", price[countback]>EMA, true) and iff(VWAP_Y_N=="Y", price[countback]>vwap, true) and iff(MACD_Y_N=="Y", crossunder(signal[countback], macd[countback]), true) and iff(MACD_Y_N=="Y", macd[countback]<0, true) and iff(BB_Y_N=="Y", crossunder(price[countback], lowerBB), true))
plotshape(dataHCLB, title= "HC-LB", color=color.lime, style=shape.circle, text="HC-LB")
strategy.entry("HC-Long", strategy.long, comment="HC-Long", when = dataHCLB)
//short entry condition
dataHCSB=(iff(STC_Y_N=="Y", STCsell, true) and iff(EMA_Y_N=="Y", price[countback]<EMA, true) and iff(VWAP_Y_N=="Y", price[countback]<vwap, true) and iff(MACD_Y_N=="Y", crossunder(macd[countback], signal[countback]), true) and iff(MACD_Y_N=="Y", signal[countback]>0, true) and iff(BB_Y_N=="Y", crossover(price[countback], upperBB), true))
plotshape(dataHCSB, title= "HC-SB", color=color.fuchsia, style=shape.circle, text="HC-SB")
strategy.entry("HC-Short", strategy.short, comment="HC-Short", when=dataHCSB)




//******************Exit Conditions******************************
// Profit and Loss Exit Calculations
// User Options to Change Inputs (%)
stopPer = input(5, title='Stop Loss %', type=input.float) / 100
takePer = input(10, title='Take Profit %', type=input.float) / 100

// Determine where you've entered and in what direction
longStop = strategy.position_avg_price * (1 - stopPer)
shortStop = strategy.position_avg_price * (1 + stopPer)
shortTake = strategy.position_avg_price * (1 - takePer)
longTake = strategy.position_avg_price * (1 + takePer)

//exit position conditions and orders
if strategy.position_size > 0 or crossunder(price[countback], upperBB)
    strategy.exit(id="Close Long", stop=longStop, limit=longTake)
if strategy.position_size < 0 or crossover(price[countback], lowerBB)
    strategy.exit(id="Close Short", stop=shortStop, limit=shortTake)

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