Multi-Faktor Adaptive Momentum-Tracking-Strategie

Schriftsteller:ChaoZhang, Datum: 2023-12-12 12:02:13
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Übersicht

Die Multi-Faktor-adaptive Momentum-Tracking-Strategie realisiert den automatisierten Handel mit hochvolatilen Vermögenswerten wie Kryptowährungen, indem sie Markttrends und wichtige Unterstützungs-/Widerstandsniveaus durch die Integration mehrerer technischer Indikatoren identifiziert.

Strategieprinzip

Der Kern der Multi-Faktor-Adaptive Momentum-Tracking-Strategie liegt in der Integration mehrerer technischer Indikatoren.

  1. RSI, um überkaufte/überverkaufte Bedingungen zu beurteilen. Verschiedene Parameter können verwendet werden, um normale RSI-Signale oder die optimierten Connors-RSI-Signale zu identifizieren, um festzustellen, ob Umkehrmöglichkeiten bestehen.

  2. Kauf- und Verkaufssignale werden erzeugt, wenn die MACD-Linie über oder unter der Signallinie kreuzt.

  3. Stochastische zu Spot-Überkauf-/Überverkaufszonen.

  4. Berechnet die prozentuale Veränderung des höchsten Preises, des niedrigsten Preises, des Schlusskurses usw. über einen bestimmten Zeitraum, um festzustellen, ob ein echter Ausbruch stattgefunden hat.

  5. Ein Anstieg der schnellen EMA über der langsamen EMA gibt Aufwärtssignale, während ein Abwärtsstieg Bärensignale gibt.

Die Strategie wählt, ob man lang oder kurz geht, basierend auf den Marktbedingungen, und setzt Stop-Loss und Take-Profit, nachdem man Positionen eingegeben hat, um Risiken effektiv zu kontrollieren.

Analyse der Vorteile

Zu den Vorteilen dieser Strategie gehören:

  1. Im Vergleich zu einzelnen Indikatoren ermöglicht die Kombination mehrerer Indikatoren eine gegenseitige Überprüfung und zuverlässigere Ergebnisse und spart unnötige Handelskosten.

  2. Die Strategie legt strenge Anforderungen an Kauf-/Verkaufssignale fest und erfordert mehrere gleichzeitige Signale, um Lärm zu filtern und schlechte Trades zu vermeiden.

  3. Adaptive Parameter reduzieren manuelle Störungen. Die eingebaute Fähigkeit, Indikatorparameter dynamisch zu berechnen, vermeidet die Subjektivität der manuellen Parameterwahl und macht die Parameter wissenschaftlicher und objektiver.

  4. Die Strategie berechnet und zeichnet kontinuierlich die Stop-Loss-/Take-Profit-Niveaus nach dem Eröffnen von Positionen, wodurch der Verlust pro Handel effektiv begrenzt und Margin-Calls verhindert werden.

Risikoanalyse

Zu den Risiken, die verhindert werden müssen, gehören:

  1. Wahrscheinlichkeit falscher Signale von Indikatoren. Obwohl der Mehrfach-Verifizierungsprozess fehlerhafte Signale stark reduziert, bleibt eine gewisse Wahrscheinlichkeit bestehen. Dies kann zu unnötigen Verlusten führen.

  2. Bei extremen Marktbedingungen können die Preise leicht von den ursprünglich festgelegten Stop-Losses durchdringen, was zu überdurchschnittlichen Verlusten führt.

  3. Überoptimierung durch Parameter-Tuning. Obwohl dynamische Parameter die Subjektivität reduzieren, können sie auch zu einer Überanpassung und Verlust der Verallgemeinerbarkeit führen.

Lösungen:

  1. Steigern Sie die Strenge der Signalfilterung, um fehlerhafte Signale zu reduzieren.
  2. Verwenden Sie abgestufte Einträge, um überdimensionierte Verluste bei einem einzigen Stopp zu vermeiden.
  3. Verbessern Sie die Probenprüfung, um die Parameterstabilität streng zu bewerten.

Optimierungsrichtlinien

Diese Strategie kann weiter optimiert werden, indem

  1. Erhöhung der Beurteilungsfaktoren: Kombination von Signalen aus mehreren Indikatoren verschiedener Art, z. B. Volatilität, Volumen usw., um das Urteilsvermögen zu verbessern.

  2. Optimierung von Stop-Loss-Algorithmen. Einführung fortschrittlicher Stop-Loss-Algorithmen wie Trailing Stop-Loss, Volatility Stop-Loss usw., um die Wahrscheinlichkeit, dass ein Stop-Loss getroffen wird, weiter zu reduzieren.

  3. Einführung von Modellen des maschinellen Lernens. Modellierung historischer Daten unter Verwendung von RNN, LSTM usw. zur Unterstützung bei Kauf-/Verkaufsentscheidungen.

  4. Strategievereinigung: Mehrfache Teilstrategien annehmen und Ensemble-Methoden zur Integration für eine robustere Gesamtleistung verwenden.

Schlussfolgerung

Die Multi-Faktor-Adaptive Momentum-Tracking-Strategie integriert mehrere technische Indikatoren, um Handelschancen zu identifizieren. Im Vergleich zu einzelnen Indikatoren verfügt diese Strategie über genauere Urteile, gepaart mit integrierter Parameteranpassung und Stop-Loss-Mechanismen zur Risikokontrolle. Zu den nächsten Schritten gehören die Einführung von mehr Hilfsurteilsfaktoren, fortschrittlichen Stop-Loss-Algorithmen, maschinellem Lernen usw., um die Strategieleistung weiter zu verbessern.


/*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")




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