Adaptif Zero Lag EMA Trading Strategy

Penulis:ChaoZhang, Tanggal: 2023-09-13 14:22:55
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Strategi ini menggunakan indikator Adaptive Zero Lag EMA untuk penentuan tren dan sinyal perdagangan.

Logika Strategi:

  1. Hitung Adaptive Zero Lag EMA dengan algoritma adaptif kosinus dan I-Q.

  2. EMA adalah EMA normal, EC adalah EMA adaptif tanpa lag.

  3. Pergi panjang ketika EC melintasi EMA, dan pendek ketika melintasi di bawahnya.

  4. Menghitung kurva kesalahan dan menetapkan ambang untuk menyaring sinyal palsu.

  5. Gunakan titik tetap untuk stop loss dan mengambil keuntungan untuk pengendalian risiko.

Keuntungan:

  1. Adaptive EMA secara signifikan mengurangi keterlambatan indikator.

  2. Penyaringan ambang meningkatkan kualitas sinyal dan menghindari kebocoran palsu.

  3. Hentian dan target sederhana mudah diterapkan.

Risiko:

  1. Parameter EMA adaptif bisa menjadi tidak stabil.

  2. Stop/target tetap gagal beradaptasi dengan perubahan kondisi pasar.

  3. Tidak ada batasan ukuran kerugian, risiko kehilangan perdagangan besar.

Singkatnya, strategi ini menggunakan EMA adaptif untuk mengikuti tren, mengurangi lag sampai batas tertentu.


/*backtest
start: 2023-09-05 00:00:00
end: 2023-09-12 00:00:00
period: 2h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
strategy(title="Adaptive Zero Lag EMA v2 (w/ Backtest Date Range)", shorttitle="AZLEMA", overlay = true,  commission_type=strategy.commission.cash_per_contract, slippage = 5, pyramiding=1, calc_on_every_tick=true)

src = input(title="Source",  defval=close)
secType = input(title="Security Type", options=["Forex", "Metal Spot", "Cryptocurrency","Custom"], defval="Forex")
contracts = input(title="Custom # of Contracts", defval=1, step=1)
limit = input(title="Max Lots",  defval=100)
Period = input(title="Period",  defval = 20)
adaptive = input(title="Adaptive Method", options=["Off", "Cos IFM", "I-Q IFM", "Average"], defval="Cos IFM")
GainLimit = input(title="Gain Limit",  defval = 8)
Threshold = input(title="Threshold",  defval=0.05, step=0.01)
fixedSL = input(title="SL Points", defval=70)
fixedTP = input(title="TP Points", defval=10)
risk = input(title='Risk', defval=0.01, step=0.01)

// === INPUT BACKTEST RANGE ===
FromMonth = input(defval = 1, title = "From Month", minval = 1, maxval = 12)
FromDay   = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
FromYear  = input(defval = 2019, title = "From Year", minval = 2015)
ToMonth   = input(defval = 1, title = "To Month", minval = 1, maxval = 12)
ToDay     = input(defval = 1, title = "To Day", minval = 1, maxval = 31)
ToYear    = input(defval = 9999, title = "To Year", minval = 2015)

// === FUNCTION EXAMPLE ===
start     = timestamp(FromYear, FromMonth, FromDay, 00, 00)  // backtest start window
finish    = timestamp(ToYear, ToMonth, ToDay, 23, 59)        // backtest finish window
window()  => true

range = 50 //input(title="Max Period",  defval=60, minval=8, maxval=100)

PI = 3.14159265359
lenIQ = 0.0
lenC = 0.0

//##############################################################################
//I-Q IFM
//##############################################################################
if(adaptive=="I-Q IFM" or adaptive=="Average")
    imult = 0.635
    qmult = 0.338
    inphase = 0.0
    quadrature = 0.0
    re = 0.0
    im = 0.0
    deltaIQ = 0.0
    instIQ = 0.0
    V = 0.0
    
    P = src - src[7]
    inphase := 1.25*(P[4] - imult*P[2]) + imult*nz(inphase[3])
    quadrature := P[2] - qmult*P + qmult*nz(quadrature[2])
    re := 0.2*(inphase*inphase[1] + quadrature*quadrature[1]) + 0.8*nz(re[1])
    im := 0.2*(inphase*quadrature[1] - inphase[1]*quadrature) + 0.8*nz(im[1])
    if (re!= 0.0)
        deltaIQ := atan(im/re)
    for i=0 to range
        V := V + deltaIQ[i]
        if (V > 2*PI and instIQ == 0.0)
            instIQ := i
    if (instIQ == 0.0)
        instIQ := nz(instIQ[1])
    lenIQ := 0.25*instIQ + 0.75*nz(lenIQ[1])

//##############################################################################
//COSINE IFM
//##############################################################################
if(adaptive == "Cos IFM" or adaptive == "Average")
    s2 = 0.0
    s3 = 0.0
    deltaC = 0.0
    instC = 0.0
    v1 = 0.0
    v2 = 0.0
    v4 = 0.0
    
    v1 := src - src[7]
    s2 := 0.2*(v1[1] + v1)*(v1[1] + v1) + 0.8*nz(s2[1])
    s3 := 0.2*(v1[1] - v1)*(v1[1] - v1) + 0.8*nz(s3[1])
    if (s2 != 0)
        v2 := sqrt(s3/s2)
    if (s3 != 0)
        deltaC := 2*atan(v2)
    for i = 0 to range
        v4 := v4 + deltaC[i]
        if (v4 > 2*PI and instC == 0.0)
            instC := i - 1
    if (instC == 0.0)
        instC := instC[1]
    lenC := 0.25*instC + 0.75*nz(lenC[1])

if (adaptive == "Cos IFM")
    Period := round(lenC)
if (adaptive == "I-Q IFM")
    Period := round(lenIQ)
if (adaptive == "Average")
    Period := round((lenC + lenIQ)/2)

//##############################################################################
//ZERO LAG EXPONENTIAL MOVING AVERAGE
//##############################################################################
LeastError = 1000000.0
EC = 0.0
Gain = 0.0
EMA = 0.0
Error = 0.0
BestGain = 0.0

alpha =2/(Period + 1)
EMA := alpha*src + (1-alpha)*nz(EMA[1])

for i = -GainLimit to GainLimit
    Gain := i/10
    EC := alpha*(EMA + Gain*(src - nz(EC[1]))) + (1 - alpha)*nz(EC[1])
    Error := src - EC
    if(abs(Error)<LeastError)
        LeastError := abs(Error)
        BestGain := Gain

EC := alpha*(EMA + BestGain*(src - nz(EC[1]))) + (1-alpha)*nz(EC[1])

plot(EC, title="EC", color=orange, linewidth=2)
plot(EMA, title="EMA", color=red, linewidth=2)

//##############################################################################
//Trade Logic & Risk Management
//##############################################################################
buy = crossover(EC,EMA) and 100*LeastError/src > Threshold
sell = crossunder(EC,EMA) and 100*LeastError/src > Threshold

secScaler = secType == "Forex" ? 100000 : secType == "Metal Spot" ? 100 : secType == "Cryptocurrency" ? 10000 : secType == "Custom" ? contracts : 0
strategy.initial_capital = 50000
balance = strategy.initial_capital + strategy.netprofit
if (time>timestamp(2016, 1, 1 , 0, 0) and balance > 0)
    //LONG
    lots = ((risk * balance)/fixedSL)*secScaler
    lots := lots > limit * secScaler ? limit * secScaler : lots
    strategy.entry("BUY", strategy.long,  oca_name="BUY",  when=buy and window())
    strategy.exit("B.Exit", "BUY", qty_percent = 100, loss=fixedSL, trail_offset=15, trail_points=fixedTP)
    //SHORT
    strategy.entry("SELL", strategy.short,  oca_name="SELL",when=sell and window())
    strategy.exit("S.Exit", "SELL", qty_percent = 100, loss=fixedSL, trail_offset=15, trail_points=fixedTP)


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