Strategi ini menggunakan indikator EMA yang beradaptasi dengan nol untuk menilai tren dan menghasilkan sinyal perdagangan. Indikator EMA ini dapat menyesuaikan parameter secara dinamis, secara efektif menghilangkan masalah lag.
Prinsip-prinsip Strategi:
Perhitungan indikator EMA beradaptasi nol-lagging, yang terdiri dari dua algoritma adaptasi sendiri, yaitu aritmatika rantai dan aritmatika I-Q.
EMA adalah indikator EMA normal, EC adalah EMA adaptasi nol-lagging.
Ketika EC di atas memakai EMA lebih banyak, EC di bawah memakai EMA kosong.
Menghitung kurva kesalahan, mengatur nilai ambang untuk memfilter sinyal palsu.
Tetapkan Stop Loss Fixed Stop Point untuk mengunci keuntungan dan mengendalikan risiko.
Keuntungan dari strategi ini:
Adaptasi EMA dapat secara efektif mengurangi keterlambatan indikator.
Filter threshold meningkatkan kualitas sinyal dan mencegah penembusan palsu.
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Bahaya dari strategi ini:
Adaptasi parameter EMA tidak stabil, ada kemungkinan kegagalan.
Stop loss yang tetap sulit untuk menyesuaikan dengan perubahan pasar.
Tidak ada batasan untuk jumlah kerugian, dan ada risiko lebih besar.
Kesimpulannya, strategi ini menggunakan indikator EMA adaptif untuk pelacakan tren, yang dapat mengurangi keterlambatan hingga batas tertentu, tetapi perlu memperhatikan stabilitas parameter dan dilengkapi dengan mekanisme stop loss yang dioptimalkan untuk mengendalikan risiko.
/*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)