संसाधन लोड हो रहा है... लोड करना...
  1. वर्ग

लेखक:चाओझांग
टैगः

img

अवलोकन

रणनीति तर्क

लाभ विश्लेषण

जोखिम विश्लेषण

अनुकूलन दिशाएँ

इस रणनीति के लिए मुख्य अनुकूलन दिशाएं हैंः

  4. उच्च समय सीमाओं के विश्लेषण के आधार पर स्थिति आकार समायोजित करें। उच्च समय सीमाओं से प्रवृत्ति विश्लेषण के परिणामों के आधार पर प्रत्येक व्यापार के स्थिति आकार को गतिशील रूप से समायोजित करें।

सारांश

/*backtest
start: 2023-12-01 00:00:00
end: 2023-12-31 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
strategy("ES Stoch RSI Strategy [krypt]", overlay=true, calc_on_order_fills=true, calc_on_every_tick=true, initial_capital=10000, currency='USD')

//Backtest Range
FromMonth = input(defval = 06, title = "From Month", minval = 1)
FromDay   = input(defval = 1, title = "From Day", minval = 1)
FromYear  = input(defval = 2018, title = "From Year", minval = 2014)
ToMonth   = input(defval = 7, title = "To Month", minval = 1)
ToDay     = input(defval = 30, title = "To Day", minval = 1)
ToYear    = input(defval = 2018, title = "To Year", minval = 2014)

PI = 3.14159265359

drop1st(src) =>
    x = na
    x := na(src[1]) ? na : src

xlowest(src, len) =>
    x = src
    for i = 1 to len - 1
        v = src[i]
        if (na(v))
            break
        x := min(x, v)
    x

xhighest(src, len) =>
    x = src
    for i = 1 to len - 1
        v = src[i]
        if (na(v))
            break
        x := max(x, v)
    x

xstoch(c, h, l, len) =>
    xlow = xlowest(l, len)
    xhigh = xhighest(h, len) 
    100 * (c - xlow) / (xhigh - xlow)

Stochastic(c, h, l, length) =>
    rawsig = xstoch(c, h, l, length)
    min(max(rawsig, 0.0), 100.0)

xrma(src, len) =>
    sum = na
    sum := (src + (len - 1) * nz(sum[1], src)) / len

xrsi(src, len) =>
    msig = nz(change(src, 1), 0.0)
    up = xrma(max(msig, 0.0), len)
    dn = xrma(max(-msig, 0.0), len)
    rs = up / dn
    100.0 - 100.0 / (1.0 + rs)

EhlersSuperSmoother(src, lower) =>
	a1 = exp(-PI * sqrt(2) / lower)
	coeff2 = 2 * a1 * cos(sqrt(2) * PI / lower)
	coeff3 = -pow(a1, 2)
	coeff1 = (1 - coeff2 - coeff3) / 2
	filt = na
	filt := nz(coeff1 * (src + nz(src[1], src)) + coeff2 * filt[1] + coeff3 * filt[2], src)

smoothK = input(7, minval=1, title="K")
smoothD = input(2, minval=1, title="D")
lengthRSI = input(10, minval=1, title="RSI Length")
lengthStoch = input(3, minval=1, title="Stochastic Length")
showsignals = input(true, title="Buy/Sell Signals")
src = input(close,  title="Source")

ob = 80
os = 20
midpoint = 50

price = log(drop1st(src))
rsi1 = xrsi(price, lengthRSI)
rawsig = Stochastic(rsi1, rsi1, rsi1, lengthStoch)
sig = EhlersSuperSmoother(rawsig, smoothK)
ma = sma(sig, smoothD)

plot(sig, color=#0094ff, title="K", transp=0)
plot(ma, color=#ff6a00, title="D", transp=0)
lineOB = hline(ob, title="Upper Band", color=#c0c0c0)
lineOS = hline(os, title="Lower Band", color=#c0c0c0)
fill(lineOB, lineOS, color=purple, title="Background")

// Buy/Sell Signals

// use curvature information to filter out some false positives
mm1 = change(change(ma, 1), 1)
mm2 = change(change(ma, 2), 2)
ms1 = change(change(sig, 1), 1)
ms2 = change(change(sig, 2), 2)

sellsignals = showsignals and (mm1 + ms1 < 0 and mm2 + ms2 < 0) and crossunder(sig, ma) and sig[1] > ob
buysignals = showsignals and (mm1 + ms1 > 0 and mm2 + ms2 > 0) and crossover(sig, ma) and sig[1] < os

ploff = 4
plot(buysignals ? sig[1] - ploff : na, style=circles, color=#008fff, linewidth=3, title="Buy Signal", transp=0)
plot(sellsignals ? sig[1] + ploff : na, style=circles, color=#ff0000, linewidth=3, title="Sell Signal", transp=0)

longCondition = buysignals
if (longCondition)
    strategy.entry("L", strategy.long, comment="Long", when=(buysignals))

shortCondition = sellsignals
if (shortCondition)
    strategy.entry("S", strategy.short, comment="Short", when=(sellsignals))
अधिक

2019 FMZ - सभी अधिकार सुरक्षित