緩和する方法は,より高い周波数データと 会社の基本面に関するリアルタイムフィードバックを組み込むこと. または検証と最適化のためにより主観的な取引信号で補完することです.
戦略をさらに改善するいくつかの方法があります.
/*backtest start: 2023-01-12 00:00:00 end: 2024-01-18 00:00:00 period: 1d basePeriod: 1h exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ // This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/ // © FrancoPassuello //@version=5 strategy("Heiken Ashi ADM", overlay=true) haClose = (open + high + low + close) / 4 // prevHaOpen = line.new(na, na, na, na, width = 1) haOpen = (open[1] + close[1]) / 2 // line.set_xy1(prevHaOpen, bar_index[1], nz(haOpen[1])) // line.set_xy2(prevHaOpen, bar_index, haClose[1]) [monopen, _1monopen, _2monopen, _3monopen, _4monopen, _5monopen, _6monopen] = request.security(syminfo.tickerid, "M", [haOpen, haOpen[1], haOpen[2], haOpen[3], haOpen[4], haOpen[5], haOpen[6]] , barmerge.gaps_off, barmerge.lookahead_on) [monclose, _1monclose, _3monclose, _6monclose] = request.security(syminfo.tickerid, "M", [haClose, haClose[1], haClose[3], haClose[6]] , barmerge.gaps_off, barmerge.lookahead_on) [dayclose1, _21dayclose, _63dayclose, _126dayclose, dayclose] = request.security(syminfo.tickerid, "1D", [haClose[1], haClose[21], haClose[63], haClose[126], haClose], barmerge.gaps_off, barmerge.lookahead_on) [dayopen1, _21dayopen, _63dayopen, _126dayopen] = request.security(syminfo.tickerid, "1D", [haOpen[1], haOpen[21], haOpen[63], haOpen[126]], barmerge.gaps_off, barmerge.lookahead_on) get_rate_of_return(price1, price2) => return_ = (price1/price2 -1)*100 return_ m0 = get_rate_of_return(monclose, monopen) m1 = get_rate_of_return(_1monclose, _1monopen) m2 = get_rate_of_return(monclose, _2monopen) m3 = get_rate_of_return(_1monclose, _3monopen) m4 = get_rate_of_return(monclose, _4monopen) m5 = get_rate_of_return(monclose, _5monopen) m6 = get_rate_of_return(_1monclose, _6monopen) MS = (m1 + m3 + m6)/100 CS = (m0 + m2 + m5)/100 d1 = get_rate_of_return(dayclose1, _21dayopen) d2 = get_rate_of_return(dayclose1, _63dayopen) d3 = get_rate_of_return(dayclose1, _126dayopen) DS = (d1 + d2 + d3)/100 //Last (DAILY) lastd_s_avg1 = DS/3 lastd_Approximate1 = dayclose1*(1-lastd_s_avg1) last_approx1_d21 = lastd_Approximate1 / _21dayopen-1 last_approx1_d63 = lastd_Approximate1 / _63dayopen-1 last_approx1_d126 = lastd_Approximate1 / _126dayopen-1 lastd_s_avg2 = (last_approx1_d21 + last_approx1_d63 + last_approx1_d126) / 3 lastd_approximate2 = (dayclose1)*(1-(lastd_s_avg1 + lastd_s_avg2)) lastd_price = lastd_approximate2 //plot(lastd_price,color = color.rgb(255, 255, 255, 14), title = "Last momentum threshold") //Last last_s_avg1 = MS/3 last_Approximate1 = _1monclose*(1-last_s_avg1) last_approx1_m1 = last_Approximate1 / _1monopen-1 last_approx1_m3 = last_Approximate1 / _3monopen-1 last_approx1_m6 = last_Approximate1 / _6monopen-1 last_s_avg2 = (last_approx1_m1 + last_approx1_m3 + last_approx1_m6) / 3 last_approximate2 = (_1monclose)*(1-(last_s_avg1 + last_s_avg2)) last_price = last_approximate2 Scoring_price = _1monclose*(1-CS) plot(last_price,color = color.rgb(255, 255, 255, 14), title = "Last momentum threshold") //plot(Scoring_price,color = color.rgb(234, 0, 255, 14), title = "Last momentum threshold") //Long based on month close and being the first trade of the month. var int lastClosedMonth = -1 limit_longCondition = _1monclose > last_approximate2 and (lastClosedMonth == -1 or month(time) != lastClosedMonth) // Long based on day close and being the first trade of the month. limit_Dlongcondition = dayclose1 > lastd_approximate2 and (lastClosedMonth == -1 or month(time) != lastClosedMonth) // Close trade based on day close DCloseLongCondition = dayclose1<lastd_approximate2 //Old standard Trading rules longCondition = _1monclose > Scoring_price MCloseLongCondition = _1monclose<Scoring_price shortCondition = CS < 0 if (longCondition) strategy.entry("Long", strategy.long) if (strategy.position_size > 0 and MCloseLongCondition) strategy.close("Long") lastClosedMonth := month(time)