As principais direcções de otimização para esta estratégia são:
Ajustar o tamanho da posição com base na análise de prazos mais longos Ajustar dinamicamente o tamanho da posição de cada negociação com base nos resultados da análise de tendências de prazos mais longos.
/*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))