Strategi perdagangan kuantitatif menggunakan beberapa indikator untuk mengidentifikasi titik pembalikan perdagangan
ChaoZhang
Ringkasan
Strategi ini menggunakan lima indikator utama EMA, VWAP, MACD, Bollinger Bands dan Schaff Trend Cycle untuk mengidentifikasi titik balik harga dalam kisaran tertentu, mengirim sinyal beli dan jual. Keuntungan dari strategi ini adalah bahwa portofolio dapat disesuaikan dengan indikator pasar yang berbeda, mengurangi probabilitas sinyal palsu, meningkatkan probabilitas keuntungan.
Prinsip Strategi
EMA rata-rata menilai arah tren besar, hanya membeli di arah tren
VWAP menilai bahwa dana yang mengalir ke lembaga hanya dibeli di tempat yang dibeli oleh lembaga.
MACD menilai tren garis pendek dan perubahan momentum, MACD garis menerobos garis sinyal dianggap sebagai sinyal beli/jual
Bollinger Bands menilai apakah ada oversold atau oversold, dengan harga yang melintasi rel bawah dianggap sebagai sinyal beli/jual
Schaff Trend Cycle menilai struktur perombakan jangka pendek yang berputar, melampaui batas tinggi dan rendah dianggap sebagai sinyal beli / jual
Instruksi beli/jual muncul saat 5 indikator besar berkoordinasi
Menetapkan Stop Loss dan Stop Loss, Optimalkan Manajemen Dana
Keunggulan Strategis
- Kombinasi multi-indikator mengurangi probabilitas sinyal palsu
Menggunakan kombinasi dari berbagai indikator seperti EMA, VWAP, MACD, BB dan STC, dapat saling diverifikasi, mengurangi sinyal palsu yang dihasilkan oleh satu indikator tunggal, sehingga meningkatkan keandalan sinyal.
- Indikator dapat disesuaikan
Memungkinkan untuk memilih apakah akan menggunakan satu indikator atau kombinasi indikator berdasarkan varietas dan kondisi pasar yang berbeda, sehingga strategi lebih tertarget dan adaptif.
- Pengelolaan dana yang optimal
Tetapkan stop loss dan stop loss untuk membatasi kerugian tunggal dan mengunci sebagian dari keuntungan untuk pengelolaan dana yang lebih baik.
- Strategi yang jelas
Dengan menggunakan indikator yang sederhana dan intuitif, dan dilengkapi dengan komentar kode yang terperinci, seluruh strategi menjadi jelas dan mudah dipahami dan dimodifikasi.
- Bermanfaat
Berbagai indikator yang digunakan secara luas, parameter yang diatur secara wajar, dapat langsung digunakan untuk perdagangan langsung, tidak perlu banyak pengoptimalan untuk mencapai efek yang baik.
Risiko Strategis
- Risiko terlambat mengidentifikasi perubahan indikator
Indikator seperti EMA, MACD dan lain-lain memiliki keterlambatan dalam mengidentifikasi perubahan harga, dan mungkin melewatkan saat terbaik untuk membeli.
- Risiko pengaturan parameter yang salah
Jika parameter indikator tidak diatur dengan benar, akan menghasilkan banyak sinyal palsu dan tidak dapat menjalankan strategi dengan baik.
- Risiko yang tidak terjamin
Kombinasi multi-indikator dapat meningkatkan tingkat kemenangan, tetapi tidak dapat memastikan bahwa setiap perdagangan menguntungkan. Perubahan lingkungan pasar dapat menyebabkan penurunan tingkat kemenangan.
- Stop Loss Menetapkan Risiko Terlalu Kecil
Jika stop loss terlalu kecil, maka stop loss dapat dilakukan pada saat harga normal berfluktuasi, menambah kerugian yang tidak perlu.
Arah optimasi strategi
- Menambahkan model pembelajaran mesin untuk menilai keandalan sinyal
Model dapat dilatih untuk menilai keandalan sinyal multi-indikator, memberi nilai pada sinyal, dan mengurangi sinyal palsu.
- Meningkatkan Indikator Kuantitatif untuk Identifikasi Tren
Menambahkan beberapa indikator kuantitatif seperti OBV, untuk mengidentifikasi tanda-tanda kenaikan harga, dan meningkatkan kepastian pembelian.
- Optimalkan strategi stop loss
Anda dapat mempelajari strategi stop loss atau lock-in yang lebih cocok untuk strategi ini, dan mengoptimalkan pengelolaan uang Anda.
- Optimasi parameter
Optimalkan parameter masing-masing indikator dengan pengulangan yang lebih sistematis untuk meningkatkan stabilitas keseluruhan strategi.
- Meningkatkan perdagangan robot
Menghubungkan API transaksi, melakukan pemesanan otomatis, sehingga strategi dapat benar-benar berjalan tanpa pengawasan manusia.
Meringkaskan
Strategi ini mengintegrasikan keunggulan berbagai indikator teknis, ide yang jelas, praktis, dan dapat digunakan sebagai referensi keputusan untuk perdagangan diskretionary, atau dapat digunakan langsung untuk perdagangan algoritmik. Namun, tetap perlu melakukan penyesuaian yang optimal untuk varietas dan lingkungan pasar tertentu, mengurangi risiko dan meningkatkan stabilitas, dan akhirnya dapat mempertahankan keuntungan yang stabil di pasar nyata.
/*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)