Strategi dagangan kuantitatif menggunakan pelbagai penunjuk untuk mengenal pasti titik pembalikan dagangan
ChaoZhang
Gambaran keseluruhan
Strategi ini menggunakan lima indikator utama EMA, VWAP, MACD, Bollinger Bands dan Schaff Trend Cycle untuk mengenal pasti titik balik harga dalam julat tertentu, dan menghantar isyarat membeli dan menjual. Keuntungan strategi ini adalah bahawa anda boleh menyesuaikan pakej indikator mengikut pasaran yang berbeza, mengurangkan kebarangkalian isyarat palsu, dan meningkatkan kebarangkalian keuntungan.
Prinsip Strategi
EMA rata-rata menilai arah trend besar, hanya membeli di arah trend
VWAP menilai aliran dana institusi, hanya membeli ke arah pembelian institusi
MACD menilai trend garis pendek dan perubahan momentum, garis MACD mematahkan garis isyarat sebagai isyarat beli / jual
Bollinger Bands menilai sama ada terlampau atau terjual, harga melintasi laluan bawah dianggap sebagai isyarat beli / jual
Schaff Trend Cycle menilai bahawa struktur penumpuan jangka pendek, melebihi nilai terhad yang tinggi atau rendah dianggap sebagai isyarat beli / jual
Apabila lima indikator yang besar memberi isyarat yang sama, ia akan memberi arahan beli/jual.
Tetapkan titik hentian dan penangguhan, optimumkan pengurusan wang
Kelebihan Strategik
- Kombinasi pelbagai indikator mengurangkan kemungkinan isyarat palsu
Menggunakan gabungan pelbagai petunjuk seperti EMA, VWAP, MACD, BB dan STC, ia boleh disahkan antara satu sama lain, mengurangkan isyarat palsu yang dihasilkan oleh satu petunjuk tunggal, dan dengan itu meningkatkan kebolehpercayaan isyarat.
- Penunjuk boleh disesuaikan
Mengizinkan pilihan sama ada untuk menggunakan salah satu indikator, kombinasi indikator boleh dibuat mengikut pelbagai jenis dan keadaan pasaran, menjadikan strategi lebih disasarkan dan disesuaikan.
- Pengurusan wang yang lebih baik
Tetapkan titik berhenti dan titik berhenti, anda boleh mengehadkan kerugian tunggal, dan mengunci sebahagian keuntungan, untuk pengurusan wang yang lebih baik.
- Strategi yang jelas
Menggunakan petunjuk yang mudah difahami, dan dilengkapi dengan kod terperinci, keseluruhan strategi mudah difahami dan diubah suai.
- Berguna
Pelbagai penunjuk digunakan secara meluas, parameter yang ditetapkan adalah munasabah, boleh digunakan secara langsung untuk perdagangan cakera, dan tidak memerlukan pengoptimuman yang besar untuk mencapai kesan yang baik.
Risiko Strategik
- Risiko untuk mengenal pasti perubahan dalam penunjuk
EMA, MACD dan lain-lain mungkin terlewat dalam mengesan perubahan harga dan mungkin terlepas masa pembelian terbaik.
- Risiko parameter yang tidak betul
Jika parameter penunjuk tidak ditetapkan dengan betul, banyak isyarat palsu akan dihasilkan dan tidak dapat menjalankan strategi dengan betul.
- Risiko yang tidak dijamin
Kombinasi pelbagai indikator dapat meningkatkan kadar kemenangan, tetapi tidak dapat memastikan setiap perdagangan mendapat keuntungan. Perubahan keadaan pasaran boleh menyebabkan penurunan kadar kemenangan.
- Stop loss menetapkan risiko yang terlalu kecil
Jika titik penangguhan ditetapkan terlalu kecil, ia mungkin dihentikan semasa harga turun naik secara normal, meningkatkan kerugian yang tidak perlu.
Arah pengoptimuman strategi
- Menambah model pembelajaran mesin untuk menilai kebolehpercayaan isyarat
Model boleh dilatih untuk menilai kebolehpercayaan isyarat pelbagai petunjuk, memberi penilaian kepada isyarat, dan mengurangkan isyarat palsu.
- Meningkatkan penunjuk kuantitatif untuk mengenal pasti trend
Menambah beberapa penunjuk kuantitatif seperti OBV, untuk mengenal pasti tanda-tanda kenaikan harga dan meningkatkan kepastian tempat pembelian.
- Mengoptimumkan strategi hentian kerugian
Anda boleh mengkaji strategi stop loss atau kunci keuntungan bergerak yang lebih sesuai dengan strategi ini, dan mengoptimumkan pengurusan wang.
- Optimumkan parameter
Mengoptimumkan parameter bagi setiap indikator dengan pengulangan yang lebih sistematik, meningkatkan ketahanan keseluruhan strategi.
- Peningkatan perdagangan robot
Menghubungkan API transaksi, melaksanakan pesanan automatik, membolehkan strategi beroperasi secara benar-benar tanpa pengawal.
ringkaskan
Strategi ini menggabungkan kelebihan pelbagai petunjuk teknikal, idea yang jelas, praktikal, boleh digunakan sebagai rujukan keputusan perdagangan diskretionari, atau boleh digunakan secara langsung untuk perdagangan algoritma. Tetapi masih perlu melakukan penyesuaian optimum untuk varieti dan persekitaran pasaran tertentu, mengurangkan risiko dan meningkatkan kestabilan, dan akhirnya dapat mengekalkan keuntungan yang stabil di pasaran 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)