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Strategi Pengesanan Momentum Adaptif Berbilang Faktor

Penulis:ChaoZhang, Tarikh: 2023-12-12 12:02:13
Tag:

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Ringkasan

Strategi pengesanan momentum adaptif pelbagai faktor mewujudkan perdagangan automatik aset yang sangat tidak menentu seperti mata wang kripto dengan mengenal pasti trend pasaran dan tahap sokongan / rintangan utama melalui penggabungan beberapa penunjuk teknikal. Strategi ini menggabungkan penunjuk seperti RSI, MACD, Stochastic untuk menentukan masa masuk dan keluar, sementara juga menggabungkan perubahan peratusan harga untuk membolehkan pengenalan corak yang lebih tepat.

Prinsip Strategi

Inti strategi penjejakan momentum adaptif pelbagai faktor terletak pada integrasi pelbagai penunjuk teknikal.

  1. RSI untuk menilai keadaan overbought / oversold. Parameter yang berbeza boleh digunakan untuk mengenal pasti isyarat RSI biasa atau isyarat RSI Connors yang disesuaikan untuk menentukan sama ada peluang pembalikan wujud.

  2. Sinyal beli dan jual dihasilkan apabila garis MACD melintasi di atas atau di bawah garis isyarat.

  3. Stokastik untuk spot zon overbought / oversold. kombinasi salib emas dan salib kematian garis K dan D menunjukkan sama ada pembalikan mungkin berlaku.

  4. Perubahan peratusan harga untuk memeriksa sama ada pecah adalah sebenar. Mengira perubahan peratusan harga tertinggi, harga terendah, harga tutup dan lain-lain dalam tempoh tertentu untuk menentukan sama ada pecah sebenar telah berlaku.

  5. EMA untuk menilai trend keseluruhan. Upcrossing EMA cepat di atas EMA perlahan memberikan isyarat menaik manakala downcrossing memberi isyarat menurun.

Strategi ini memilih untuk pergi lama atau pendek berdasarkan keadaan pasaran, dan menetapkan stop loss dan mengambil keuntungan selepas memasuki kedudukan untuk mengawal risiko dengan berkesan. Keluar apabila isyarat pembalikan berlaku. Seluruh proses keputusan mengintegrasikan penilaian dari pelbagai faktor untuk mencapai hasil yang lebih tepat.

Analisis Kelebihan

Kelebihan strategi ini termasuk:

  1. Banyak faktor mendorong penilaian yang lebih baik. berbanding dengan satu penunjuk, menggabungkan beberapa penunjuk membolehkan pengesahan bersama dan keputusan yang lebih boleh dipercayai, menjimatkan kos perdagangan yang tidak perlu.

  2. Syarat yang ketat mengelakkan perdagangan buruk. Strategi menetapkan keperluan yang ketat untuk isyarat beli / jual, yang memerlukan beberapa isyarat serentak untuk menapis bunyi bising dan mengelakkan perdagangan buruk.

  3. Parameter penyesuaian mengurangkan gangguan manual. Keupayaan terbina dalam untuk mengira parameter penunjuk secara dinamik mengelakkan subjektiviti pemilihan parameter manual, menjadikan parameter lebih saintifik dan objektif.

  4. Strategi secara berterusan mengira dan merangka tahap stop loss / take profit selepas membuka kedudukan, secara berkesan membatasi kerugian setiap perdagangan dan mencegah panggilan margin.

Analisis Risiko

Risiko yang perlu dicegah termasuk:

  1. Kemungkinan isyarat yang salah dari penunjuk. Walaupun proses pengesahan berganda sangat mengurangkan isyarat yang salah, beberapa kebarangkalian masih ada. Ini boleh menyebabkan kerugian yang tidak perlu.

  2. Risiko kerugian berhenti menembusi. Dalam keadaan pasaran yang melampau, harga boleh terjun tebing dan menembusi kerugian berhenti yang ditetapkan pada asalnya dengan mudah, yang membawa kepada kerugian di atas purata.

  3. Walaupun parameter dinamik mengurangkan subjektiviti, mereka juga boleh menyebabkan terlalu sesuai dan kehilangan generalisasi.

Penyelesaian:

  1. Meningkatkan ketegasan penapisan isyarat untuk mengurangkan isyarat yang salah.
  2. Mengambil masuk bertahap untuk mengelakkan kehilangan berhenti tunggal yang terlalu besar.
  3. Meningkatkan ujian sampel untuk menilai kestabilan parameter dengan ketat.

Arahan pengoptimuman

Strategi ini boleh dioptimumkan lagi melalui:

  1. Meningkatkan faktor penilaian: Gabungkan isyarat dari lebih banyak penunjuk jenis yang berbeza, contohnya turun naik, jumlah, dan lain-lain untuk membantu penilaian.

  2. Mengoptimumkan algoritma stop loss. Memperkenalkan algoritma stop loss yang lebih maju seperti trailing stop loss, volatility stop loss dan lain-lain untuk mengurangkan lagi kebarangkalian stop loss.

  3. Memperkenalkan model pembelajaran mesin. Model data sejarah menggunakan RNN, LSTM dan lain-lain untuk membantu keputusan beli / jual.

  4. Menggabungkan strategi: Mengambil beberapa sub-strategi dan menggunakan kaedah ensemble untuk mengintegrasikan prestasi keseluruhan yang lebih kukuh.

Kesimpulan

Strategi penjejakan momentum adaptif pelbagai faktor mengintegrasikan beberapa penunjuk teknikal untuk mengenal pasti peluang perdagangan. Berbanding dengan penunjuk tunggal, strategi ini mempunyai penilaian yang lebih tepat, ditambah dengan penyesuaian parameter terbina dalam dan mekanisme stop loss untuk mengawal risiko. Langkah seterusnya termasuk memperkenalkan lebih banyak faktor penilaian tambahan, algoritma stop loss lanjutan, pembelajaran mesin dll untuk meningkatkan prestasi strategi.


/*backtest
start: 2023-12-04 00:00:00
end: 2023-12-11 00:00:00
period: 3m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
//@version=4

// ██████╗██████╗ ███████╗ █████╗ ████████╗███████╗██████╗     ██████╗ ██╗   ██╗    
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//╚══════╝ ╚═════╝ ╚══════╝ ╚═════╝    ╚═╝   ╚═╝ ╚═════╝ ╚═╝  ╚═══╝╚══════╝ ╚═╝ ╚════╝    ╚═╝   ╚════╝ 

strategy(shorttitle='Ain1 No Label',title='All in One Strategy no RSI Label', overlay=true, scale=scale.left, initial_capital = 1000, process_orders_on_close=true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, commission_type=strategy.commission.percent, commission_value=0.18, calc_on_every_tick=true)

kcolor = color.new(#0094FF, 60)
dcolor = color.new(#FF6A00, 60)



// -----------------  Strategy Inputs -------------------------------------------------------------
//Backtest dates with auto finish date of today
start = input(defval = timestamp("01 April 2021 00:00 -0500"), title = "Start Time", type = input.time)
finish = input(defval = timestamp("31 December 2021 00:00 -0600"), title = "End Time", type = input.time)
window()  => true       // create function "within window of time"


// Strategy Selection - Long, Short, or Both
stratinfo = input(true, "Long/Short for Mixed Market, Long for Bull, Short for Bear")
strat = input(title="Trade Types", defval="Long/Short", options=["Long Only", "Long/Short", "Short Only"])
strat_val = strat == "Long Only" ? 1 : strat == "Long/Short" ? 0 : -1

// Risk Management Inputs
sl= input(10.0, "Stop Loss %", minval = 0, maxval = 100, step = 0.01)
stoploss = sl/100
tp = input(20.0, "Target Profit %", minval = 0, maxval = 100, step = 0.01)
TargetProfit = tp/100


useXRSI = input(false, "Use RSI crossing back, select only one strategy")
useCRSI = input(false, "Use Tweaked Connors RSI, select only one")
RSIInfo = input(true, "These are the RSI Strategy Inputs, RSI Length applies to MACD, set OB and OS to 45 for using Stoch and EMA strategies.")
length = input(14, "RSI Length", minval=1)
overbought= input(62, "Overbought")
oversold= input(35, "Oversold")
cl1 = input(3, "Connor's MA Length 1", minval=1, step=1)
cl2 = input(20, "Connor's MA Lenght 2", minval=1, step=1)
cl3 = input(50, "Connor's MA Lenght 3", minval=1, step=1)

// MACD and EMA Inputs
useMACD = input(false, "Use MACD Only, select only one strategy")
useEMA  = input(false, "Use EMA Only, select only one strategy (EMA uses Stochastic inputs too)")
MACDInfo=input(true, "These are the MACD strategy variables")
fastLength = input(5, minval=1, title="EMA Fast Length")
slowLength = input(10, minval=1, title="EMA Slow Length")
ob_min = input(52, "Overbought Lookback Minimum Value", minval=0, maxval=200)
ob_lb = input(25, "Overbought Lookback Bars", minval=0, maxval=100)
os_min = input(50, "Oversold Lookback Minimum Value", minval=0, maxval=200)
os_lb = input(35, "Oversold Lookback Bars", minval=0, maxval=100)
source = input(title="Source", type=input.source, defval=close)
RSI = rsi(source, length)


// Price Movement Inputs
PriceInfo = input(true, "Price Change Percentage Cross Check Inputs for all Strategies, added logic to avoid early sell")
lkbk = input(5,"Max Lookback Period")

// EMA and SMA Background Inputs
useStoch    = input(false, "Use Stochastic Strategy, choose only one")
StochInfo   = input(true, "Stochastic Strategy Inputs")
smoothK     = input(3, "K", minval=1)
smoothD     = input(3, "D", minval=1)
k_mode      = input("SMA", "K Mode", options=["SMA", "EMA", "WMA"])
high_source = input(high,"High Source")
low_source= input(low,"Low Source")
HTF = input("","Curernt or Higher time frame only", type=input.resolution)

// Selections to show or hide the overlays
showZones = input(true, title="Show Bullish/Bearish Zones")
showStoch = input(true, title="Show Stochastic Overlays")
showRSIBS = input(true, title="Show RSI Buy Sell Zones")
showMACD = input(true, title="Show MACD")
color_bars=input(true, "Color Bars")



// ------------------ Dynamic RSI Calculation ----------------------------------------

AvgHigh(src,cnt,val) =>
    total = 0.0
    count = 0
    for i = 0 to cnt
        if src[i] > val
            count := count + 1
            total := total + src[i]
    round(total / count)
    
RSI_high = AvgHigh(RSI, ob_lb, ob_min)

AvgLow(src,cnt,val) =>
    total = 0.0
    count = 0
    for i = 0 to cnt
        if src[i] < val
            count := count + 1
            total := total + src[i]
    round(total / count)

RSI_low = AvgLow(RSI, os_lb, os_min)




// ------------------ Price Percentage Change Calculation -----------------------------------------
perc_change(lkbk) =>
    overall_change = ((close[0] - open[lkbk]) / open[lkbk]) * 100
    highest_high = 0.0
    lowest_low = 0.0
    for i = lkbk to 0
        highest_high := i == lkbk ? high : high[i] > high[(i + 1)] ? high[i] : highest_high[1]
        lowest_low := i == lkbk ? low : low[i] < low[(i + 1)] ? low[i] : lowest_low[1]
    
    start_to_high = ((highest_high - open[lkbk]) / open[lkbk]) * 100
    start_to_low = ((lowest_low - open[lkbk]) / open[lkbk]) * 100
    previous_to_high = ((highest_high - open[1])/open[1])*100
    previous_to_low = ((lowest_low-open[1])/open[1])*100
    previous_bar = ((close[1]-open[1])/open[1])*100
    
    [overall_change, start_to_high, start_to_low, previous_to_high, previous_to_low, previous_bar]
    
// Call the function    
[overall, to_high, to_low, last_high, last_low, last_bar] = perc_change(lkbk)

// Plot the function
//plot(overall*50, color=color.white, title='Overall Percentage Change', linewidth=3)
//plot(to_high*50, color=color.green,title='Percentage Change from Start to High', linewidth=2)
//plot(to_low*50, color=color.red, title='Percentage Change from Start to Low', linewidth=2)
//plot(last_high*100, color=color.teal, title="Previous to High", linewidth=2)
//plot(last_low*100, color=color.maroon, title="Previous to Close", linewidth=2)
//plot(last_bar*100, color=color.orange, title="Previous Bar", linewidth=2)
//hline(0, title='Center Line', color=color.orange, linewidth=2)

true_dip = overall < 0 and to_high > 0 and to_low < 0 and last_high > 0 and last_low < 0 and last_bar < 0
true_peak = overall > 0 and to_high > 0 and to_low > 0 and last_high > 0 and last_low < 0 and last_bar > 0

alertcondition(true_dip, title='True Dip', message='Dip')
alertcondition(true_peak, title='True Peak', message='Peak')

// ------------------ Background Colors based on EMA Indicators -----------------------------------
// Uses standard lengths of 9 and 21, if you want control delete the constant definition and uncomment the inputs
haClose(gap) => (open[gap] + high[gap] + low[gap] + close[gap]) / 4
rsi_ema = rsi(haClose(0), length)
v2 = ema(rsi_ema, length)                                                
v3 = 2 * v2 - ema(v2, length)  
emaA = ema(rsi_ema, fastLength)                                     
emaFast = 2 * emaA - ema(emaA, fastLength)
emaB = ema(rsi_ema, slowLength)                                     
emaSlow = 2 * emaB - ema(emaB, slowLength) 

//plot(rsi_ema, color=color.white, title='RSI EMA', linewidth=3)
//plot(v2, color=color.green,title='v2', linewidth=2)
//plot(v3, color=color.red, title='v3', linewidth=2)
//plot(emaFast, color=color.teal, title="EMA Fast", linewidth=2)
//plot(emaSlow, color=color.maroon, title="EMA Slow", linewidth=2)

EMABuy = crossunder(emaFast, v2) and window()
EMASell = crossover(emaFast, emaSlow) and window()


alertcondition(EMABuy, title='EMA Buy', message='EMA Buy Condition')
alertcondition(EMASell, title='EMA Sell', message='EMA Sell Condition')



// bullish signal rule: 
bullishRule =emaFast > emaSlow
// bearish signal rule: 
bearishRule =emaFast < emaSlow

// current trading State
ruleState = 0
ruleState := bullishRule ? 1 : bearishRule ? -1 : nz(ruleState[1])
ruleColor = ruleState==1 ? color.new(color.blue, 90) : ruleState == -1 ? color.new(color.red, 90) : ruleState == 0 ? color.new(color.gray, 90) : na
bgcolor(showZones ? ruleColor : na, title="Bullish/Bearish Zones")


// ------------------  Stochastic Indicator Overlay -----------------------------------------------

// Calculation
// Use highest highs and lowest lows
h_high = highest(high_source ,lkbk)
l_low = lowest(low_source ,lkbk)

stoch = stoch(RSI, RSI_high, RSI_low, length)
k =
 k_mode=="EMA" ? ema(stoch, smoothK) :
 k_mode=="WMA" ? wma(stoch, smoothK) :
 sma(stoch, smoothK)
d = sma(k, smoothD)
k_c = change(k)
d_c = change(d)
kd = k - d

// Plot
signalColor = k>oversold and d<overbought and k>d and k_c>0 and d_c>0 ? kcolor : 
 k<overbought and d>oversold and k<d and k_c<0 and d_c<0 ? dcolor : na
kp = plot(showStoch ? k : na, "K", color=kcolor)
dp = plot(showStoch ? d : na, "D", color=dcolor)
fill(kp, dp, color = signalColor, title="K-D")
signalUp = showStoch ? not na(signalColor) and kd>0 : na
signalDown = showStoch ? not na(signalColor) and kd<0 : na
//plot(signalUp ? kd : na, "Signal Up", color=kcolor, transp=90, style=plot.style_columns)
//plot(signalDown ? (kd+100) : na , "Signal Down", color=dcolor, transp=90, style=plot.style_columns, histbase=100)

//StochBuy = crossover(k, d) and kd>0 and to_low<0 and window()
//StochSell = crossunder(k,d) and kd<0 and to_high>0 and window()

StochBuy = crossover(k, d) and window()
StochSell = crossunder(k, d) and window()

alertcondition(StochBuy, title='Stoch Buy', message='K Crossing D')
alertcondition(StochSell, title='Stoch Sell', message='D Crossing K')


// -------------- Add Price Movement -------------------------
// Calculations
h1 = vwma(high, length)
l1 = vwma(low, length)
hp = h_high[1]
lp = l_low[1]

// Plot
var plot_color=#353535
var sig = 0
if (h1 >hp)
    sig:=1
    plot_color:=color.lime
else if (l1 <lp)
    sig:=-1
    plot_color:=color.maroon
//plot(1,title = "Price Movement Bars", style=plot.style_columns,color=plot_color)
//plot(sig,title="Signal 1 or -1",display=display.none)



// --------------------------------------- RSI Plot ----------------------------------------------
// Plot Oversold and Overbought Lines
over = hline(oversold, title="Oversold", color=color.green)
under = hline(overbought, title="Overbought", color=color.red)
fillcolor = color.new(#9915FF, 90)
fill(over, under, fillcolor, title="Band Background")


// Show RSI and EMA crosses with arrows and RSI Color (tweaked Connors RSI)
// Improves strategy setting ease by showing where EMA 5 crosses EMA 10 from above to confirm overbought conditions or trend reversals
// This shows where you should enter shorts or exit longs

// Tweaked Connors RSI Calculation
connor_ob = overbought
connor_os = oversold
ma1 = sma(close,cl1)
ma2 = sma(close, cl2)
ma3 = sma(close, cl3)

// Buy Sell Zones using tweaked Connors RSI (RSI values of 80 and 20 for Crypto as well as ma3, ma20, and ma50 are the tweaks)
RSI_SELL = ma1 > ma2 and open > ma3 and RSI >= connor_ob and true_peak and window()
RSI_BUY = ma2 < ma3 and ma3 > close and RSI <= connor_os and true_dip and window()

alertcondition(RSI_BUY, title='Connors Buy', message='Connors RSI Buy')
alertcondition(RSI_SELL, title='Connors Sell', message='Connors RSI Sell')

// Color Definition
col = useCRSI ? (close > ma2 and close < ma3 and RSI <= connor_os ? color.lime : close < ma2 and close > ma3 and RSI <= connor_ob ? color.red : color.yellow ) : color.yellow

// Plot colored RSI Line
plot(RSI, title="RSI", linewidth=3, color=col)


//------------------- MACD Strategy -------------------------------------------------
[macdLine, signalLine, _] = macd(close, fastLength, slowLength, length)

bartrendcolor = macdLine > signalLine and k > 50 and RSI > 50 ? color.teal : macdLine < signalLine and k < 50 and RSI < 50 ? color.maroon : macdLine < signalLine ? color.yellow : color.gray
barcolor(color = color_bars ? bartrendcolor : na)


MACDBuy = macdLine>signalLine and RSI<RSI_low and overall<0 and window()
MACDSell = macdLine<signalLine and RSI>RSI_high and overall>0 and window()

//plotshape(showMACD ? MACDBuy: na, title = "MACD Buy", style = shape.arrowup, text = "MACD Buy", color=color.green, textcolor=color.green, size=size.small)
//plotshape(showMACD ? MACDSell: na, title = "MACD Sell", style = shape.arrowdown, text = "MACD Sell", color=color.red, textcolor=color.red, size=size.small)
MACColor = MACDBuy ? color.new(color.teal, 50) : MACDSell ? color.new(color.maroon, 50) : na
bgcolor(showMACD ? MACColor : na, title ="MACD Signals")


// -------------------------------- Entry and Exit Logic ------------------------------------


// Entry Logic
XRSI_OB = crossunder(RSI, overbought) and overall<0 and window()
RSI_OB = RSI>overbought and true_peak and window()
XRSI_OS = crossover(RSI, oversold) and overall>0 and window()
RSI_OS = RSI<oversold and true_dip and window()

alertcondition(XRSI_OB, title='Reverse RSI Sell', message='RSI Crossing back under OB')
alertcondition(XRSI_OS, title='Reverse RSI Buy', message='RSI Crossing back over OS')

alertcondition(RSI_OS, title='RSI Buy', message='RSI Crossover OS')
alertcondition(RSI_SELL, title='RSI Sell', message='RSI Crossunder OB')


// Strategy Entry and Exit with built in Risk Management
GoLong = strategy.position_size==0 and strat_val > -1 and rsi_ema > RSI and k < d ? (useXRSI ? XRSI_OS : useMACD ? MACDBuy : useCRSI ? RSI_BUY : useStoch ? StochBuy : RSI_OS) : false

GoShort = strategy.position_size==0 and strat_val < 1 and rsi_ema < RSI and d < k ? (useXRSI ? XRSI_OB : useMACD ? MACDSell : useCRSI ? RSI_SELL : useStoch ? StochSell : RSI_OB) : false

if (GoLong)
    strategy.entry("LONG", strategy.long)

if (GoShort) 
    strategy.entry("SHORT", strategy.short)


longStopPrice  = strategy.position_avg_price * (1 - stoploss)
longTakePrice  = strategy.position_avg_price * (1 + TargetProfit)
shortStopPrice = strategy.position_avg_price * (1 + stoploss)
shortTakePrice = strategy.position_avg_price * (1 - TargetProfit)

//plot(series=(strategy.position_size > 0) ? longTakePrice : na, color=color.green, style=plot.style_circles, linewidth=3, title="Long Take Profit")
//plot(series=(strategy.position_size < 0) ? shortTakePrice : na, color=color.green, style=plot.style_circles, linewidth=3, title="Short Take Profit")
//plot(series=(strategy.position_size > 0) ? longStopPrice : na, color=color.red, style=plot.style_cross, linewidth=2, title="Long Stop Loss")
//plot(series=(strategy.position_size < 0) ? shortStopPrice : na, color=color.red, style=plot.style_cross, linewidth=2, title="Short Stop Loss")

if (strategy.position_size > 0)
    strategy.exit(id="Exit Long", from_entry = "LONG", stop = longStopPrice, limit = longTakePrice)
    
if (strategy.position_size < 0)
    strategy.exit(id="Exit Short", from_entry = "SHORT", stop = shortStopPrice, limit = shortTakePrice)


CloseLong = strat_val > -1 and strategy.position_size > 0 and rsi_ema > RSI and d > k ? (useXRSI ? XRSI_OB : useMACD ? MACDSell : useCRSI ? RSI_SELL : RSI_OB) : false

if(CloseLong)
    strategy.close("LONG")
        
CloseShort = strat_val < 1 and strategy.position_size < 0 and rsi_ema < RSI and k > d ? (useXRSI ? XRSI_OS : useMACD ? MACDBuy : useCRSI ? RSI_BUY : RSI_OS) : false

if(CloseShort)
    strategy.close("SHORT")




Lebih lanjut