The strategy is named “DayLight Hunter Quant Strategy with Two-way Position, Stochastic Signal and Random Stop loss/take profit”. The main idea is to generate trading signals with Stochastic indicator, filter the signals with SMA, implement two-way position opening, and set random stop loss and take profit points to lock in profits.
The strategy uses 5-day Stochastic Indicator %K and %D line crossovers to generate trading signals. When %K crosses over %D from below, a buy signal is generated. When %K crosses below %D from above, a sell signal is generated. To filter false signals, 50-day SMA lines are used - only when close price is below SMA low point, a buy signal is valid; only when close price is above SMA high point, a sell signal is valid.
Upon receiving a buy signal, the strategy will open long position with fixed quantity. Upon receiving a sell signal, if in one-way trading mode, it will close previous long position and open short position. If in hedging mode, it will simply open additional short position to hedge. For every trading unit, random stop loss and take profit points are set based on certain percentage of current price. This allows locking in profits and controlling risks.
The biggest advantage of this strategy is it uses Stochastic signals with SMA filter to achieve relatively low false signal rate in two-way trading. This provides more profit opportunities. In addition, the random stop loss/take profit mechanism allows taking profit in time after making profits, avoiding giving back all profits; and cutting losses in case of huge loss, to reduce loss. In summary, the strategy has larger profit margin and better risk control.
Main risks of this strategy include false signals of Stochastic indicator may lead to unnecessary losses; improper random stop loss/take profit points may be too aggressive, causing premature or late exit, impacting profitability; inability to cut loss in time in hedging trades can lead to amplification of losses.
To reduce risks, parameters of SMA filter can be optimized to filter out more false signals. Also consider combining other indicators to determine market trends to avoid trading against trends. Finally, reasonable stop loss range should be set, and independent stop loss points should be used for hedging units to control risk.
The strategies can be optimized in the following aspects:
Optimize parameters of Stochastic to find best parameter combination to reduce false signals.
Optimize or add other technical indicators to aid Stochastic in determining trends, e.g. MACD, KD etc.
Use machine learning models to study metrics like accuracy, win rate etc of Stochastic signals under different parameters, to find optimal parameter space.
Optimize the random stop loss/take profit algorithms to make them more intelligent and dynamic, e.g. incorporate concepts like moving stop loss, position sizing etc.
Add position sizing module, allowing dynamic position adjustments based on performance, market regimes etc.
The “DayLight Hunter Quant Strategy with Two-way Position, Stochastic Signal and Random Stop loss/take profit” combines Stochastic crossover signals, SMA filter principle, two-way trading and random stop loss/take profit method. It has advantages like relatively accurate signals, abundant two-way trading opportunities, flexible stop loss/profit taking, and risks within acceptable range. Further optimizations on parameter tuning, indicator combinations and risk control modules can help achieve more stable and better performance. It provides a very good reference case for quantitative trading practice.
/*backtest start: 2023-12-31 00:00:00 end: 2024-01-07 00:00:00 period: 15m basePeriod: 5m exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=5 var int slippage = 0 strategy("X48 - DayLight Hunter | Strategy | V.01.01", overlay=true, calc_on_order_fills = true, initial_capital = 50,default_qty_type = strategy.fixed, default_qty_value = 1, commission_type = strategy.commission.percent, commission_value = 0, currency = currency.USD, slippage = 0) var bool hedge_mode = false var int sto_buy = 0 var int sto_sell = 0 Trade_Mode = input.string(defval = "Hedge", title = "⚖️ Mode For Trade [Oneway / Hedge]", options = ["Oneway", "Hedge"], group = "Mode Trade", tooltip = "Oneway = Switching Position Type With Signal\nHedge Mode = Not Switching Position Type Unitl TP or SL") Risk_Mode = input.string(defval = "Low Risk", title = "⚖️ Risk Signal Mode [Low / Medium / High]", options = ["Low Risk", "Medium Risk", "High Risk"], group = "Mode Trade", tooltip = "[[Signal Form Stochastic]]\nLow Risk is >= 80 and <= 20\nMedium Risk is >= 70 and <= 30\nHigh Risk is >= 50 and <=50") if Trade_Mode == "Oneway" hedge_mode := false else hedge_mode := true if Risk_Mode == "Low Risk" sto_buy := 20 sto_sell := 80 else if Risk_Mode == "Medium Risk" sto_buy := 30 sto_sell := 70 else if Risk_Mode == "High Risk" sto_buy := 50 sto_sell := 50 periodK = input.int(15, title="%K Length", minval=1, group = "Stochastic Setting", inline = "Sto0") smoothK = input.int(3, title="%K Smoothing", minval=1, group = "Stochastic Setting", inline = "Sto0") periodD = input.int(3, title="%D Smoothing", minval=1, group = "Stochastic Setting", inline = "Sto0") SMA_Mode = input.bool(defval = true, title = "SMA High and Low Filter Mode", group = "SMA Filter Mode", tooltip = "Sell Signal With Open >= SMA High\nBuy Signal With Close <= SMA Low") SMA_High = input.int(defval = 50, title = "SMA High", group = "SMA Filter Mode", inline = "SMA1") SMA_Low = input.int(defval = 50, title = "SMA Low", group = "SMA Filter Mode", inline = "SMA1") k = ta.sma(ta.stoch(close, high, low, periodK), smoothK) d = ta.sma(k, periodD) high_line = ta.sma(high, SMA_High) low_line = ta.sma(low, SMA_Low) plot(SMA_Mode ? high_line : na, "H-Line", color = color.yellow, linewidth = 2) plot(SMA_Mode ? low_line : na, "L-Line", color = color.blue, linewidth = 2) entrybuyprice = strategy.position_avg_price var bool longcondition = na var bool shortcondition = na if SMA_Mode == true longcondition := ta.crossover(k,d) and d <= sto_buy and close < low_line and open < low_line// or ta.crossover(k, 20)// and close <= low_line shortcondition := ta.crossunder(k,d) and d >= sto_sell and close > high_line and open > high_line// or ta.crossunder(k, 80)// and close >= high_line else longcondition := ta.crossover(k,d) and d <= sto_buy shortcondition := ta.crossunder(k,d) and d >= sto_sell //longcondition_double = ta.crossover(d,20) and close < low_line// and strategy.position_size > 0 //shortcondition_double = ta.crossunder(d,80) and close > high_line// and strategy.position_size < 0 //=============== TAKE PROFIT and STOP LOSS by % ================= tpsl(percent) => strategy.position_avg_price * percent / 100 / syminfo.mintick GR4 = "=====🆘🆘🆘 TAKE PROFIT & STOP LOSS BY [%] 🆘🆘🆘=====" mode= input.bool(title="🆘 Take Profit & Stop Loss By Percent (%)", defval=true, group=GR4, tooltip = "Take Profit & Stop Loss by % Change\n0 = Disable") tp_l = tpsl(input.float(0, title='🆘 TP [LONG] % >> [Oneway Only]', group=GR4, tooltip = "0 = Disable")) tp_s = tpsl(input.float(0, title='🆘 TP [SHORT] % >> [Oneway Only]', group=GR4, tooltip = "0 = Disable")) sl = tpsl(input.float(0, title='🆘 Stop Loss %', group=GR4, tooltip = "0 = Disable")) tp_pnl = input.float(defval = 1, title = "🆘 TP by PNL $ eg. (0.1 = 0.1$)", group = GR4) spread_size = input.float(defval = 0.350, title = "🆘 Spread Point Size(Eg. 35 Point or 350 Point From Your Broker Digits)", tooltip = "Spread Point Form Your Broker \nEg. 1920.124 - 1920.135 or 1920.12 - 1920.13\nPlease Check From Your Broker", group = GR4) GR5 = "===💮💮💮 Hedge Mode 💮💮💮===" //hedge_mode = input.bool(defval = true, title = "⚖️ Hedge Mode", group = GR5) hedge_point = input.int(defval = 500, title = "💯 Hedge Point Range", group = GR5, tooltip = "After Entry Last Position And Current Price More Than Point Range Are Open New Hedge Position") hedge_gale = input.float(defval = 2.0, title = "✳️ Martingale For Hedge Multiply [default = 2]", tooltip = "Martingale For Multiply Hedge Order", group = GR5) hedge_point_size = hedge_point/100 calcStopLossPrice(OffsetPts) => if strategy.position_size > 0 strategy.position_avg_price - OffsetPts * syminfo.mintick else if strategy.position_size < 0 strategy.position_avg_price + OffsetPts * syminfo.mintick else na calcStopLossL_AlertPrice(OffsetPts) => strategy.position_avg_price - OffsetPts * syminfo.mintick calcStopLossS_AlertPrice(OffsetPts) => strategy.position_avg_price + OffsetPts * syminfo.mintick calcTakeProfitPrice(OffsetPts) => if strategy.position_size > 0 strategy.position_avg_price + OffsetPts * syminfo.mintick else if strategy.position_size < 0 strategy.position_avg_price - OffsetPts * syminfo.mintick else na calcTakeProfitL_AlertPrice(OffsetPts) => strategy.position_avg_price + OffsetPts * syminfo.mintick calcTakeProfitS_AlertPrice(OffsetPts) => strategy.position_avg_price - OffsetPts * syminfo.mintick var stoploss = 0. var stoploss_l = 0. var stoploss_s = 0. var takeprofit = 0. var takeprofit_l = 0. var takeprofit_s = 0. var takeprofit_ll = 0. var takeprofit_ss = 0. if mode == true if (strategy.position_size > 0) if sl > 0 stoploss := calcStopLossPrice(sl) stoploss_l := stoploss else if sl <= 0 stoploss := na if tp_l > 0 takeprofit := tp_l takeprofit_ll := close + ((close/100)*tp_l) //takeprofit_s := na else if tp_l <= 0 takeprofit := na if (strategy.position_size < 0) if sl > 0 stoploss := calcStopLossPrice(sl) stoploss_s := stoploss else if sl <= 0 stoploss := na if tp_s > 0 takeprofit := tp_s takeprofit_ss := close - ((close/100)*tp_s) //takeprofit_l := na else if tp_s <= 0 takeprofit := na else if strategy.position_size == 0 stoploss := na takeprofit := na //takeprofit_l := calcTakeProfitL_AlertPrice(tp_l) //takeprofit_s := calcTakeProfitS_AlertPrice(tp_s) //stoploss_l := calcStopLossL_AlertPrice(sl) //stoploss_s := calcStopLossS_AlertPrice(sl) //////////// INPUT BACKTEST RANGE //////////////////////////////////////////////////// var string BTR1 = '════════⌚⌚ INPUT BACKTEST TIME RANGE ⌚⌚════════' i_startTime = input(defval = timestamp("01 Jan 1945 00:00 +0000"), title = "Start", inline="timestart", group=BTR1, tooltip = 'Start Backtest YYYY/MM/DD') i_endTime = input(defval = timestamp("01 Jan 2074 23:59 +0000"), title = "End", inline="timeend", group=BTR1, tooltip = 'End Backtest YYYY/MM/DD') //////////////// Strategy Alert For X4815162342 BOT ////////////////////// Text_Alert_Future = '{{strategy.order.alert_message}}' copy_Fu = input( defval= Text_Alert_Future , title="Alert Message for BOT", inline = '00' ,group = '═ Bot Setting ═ \n >> If You Dont Use Bot Just Pass It' ,tooltip = 'Alert For X48-BOT > Copy and Paste To Alert Function') TimeFrame_input = input(defval= 'Input Your TimeFrame [1m, 15m, 1h, 4h, 1d ,1w]' , title="TimeFrame Text Alert", inline = '00' ,group = '═ Bot Setting ═ \n >> If You Dont Use Bot Just Pass It') string Alert_EntryL = '🪙 Asset : {{ticker}} \n💱 Status : {{strategy.market_position}}\n🕛 TimeFrame : '+str.tostring(TimeFrame_input)+'\n💸 Price : {{strategy.order.price}} $\n✅ TP : '+str.tostring(takeprofit_ll)+' $\n❌ SL : '+str.tostring(stoploss_l)+' $\n⏰ Time : {{timenow}}' string Alert_EntryS = '🪙 Asset : {{ticker}} \n💱 Status : {{strategy.market_position}}\n🕛 TimeFrame : '+str.tostring(TimeFrame_input)+'\n💸 Price : {{strategy.order.price}} $\n✅ TP : '+str.tostring(takeprofit_ss)+' $\n❌ SL : '+str.tostring(stoploss_s)+' $\n⏰ Time : {{timenow}}' string Alert_TPSL = '🪙 Asset : {{ticker}}\n🕛 TimeFrame : '+str.tostring(TimeFrame_input)+'\n💹 {{strategy.order.comment}}\n💸 Price : {{strategy.order.price}} $\n⏰ Time : {{timenow}}' if true if longcondition strategy.entry("Long", strategy.long, comment = "🌙", alert_message = Alert_EntryL) //if longcondition_double // //strategy.cancel_all() // strategy.entry("Long2", strategy.long, comment = "🌙🌙") // //strategy.exit("Exit",'Long', qty_percent = 100 , profit = takeprofit, stop = stoploss, comment_profit = "TP💚L", comment_loss = "SL💚L") if shortcondition strategy.entry("Short", strategy.short, comment = "👻", alert_message = Alert_EntryS) //strategy.exit("Exit",'Short', qty_percent = 100, profit = takeprofit, stop = stoploss, comment_profit = "TP❤️️S", comment_loss = "SL❤️️S") //if shortcondition_double // //strategy.cancel_all() // strategy.entry("Short2", strategy.short, comment = "👻👻") if strategy.position_size > 0 and strategy.opentrades >= 1 and hedge_mode == true entrypricel = strategy.opentrades.entry_price(strategy.opentrades - 1) callpointsize = entrypricel - close lastsize = strategy.position_size if callpointsize >= hedge_point_size and longcondition strategy.order("Long2", strategy.long, qty = lastsize * hedge_gale, comment = "🌙⌛", alert_message = Alert_EntryL) else if strategy.position_size < 0 and strategy.opentrades >= 1 and hedge_mode == true entryprices = strategy.opentrades.entry_price(strategy.opentrades - 1) callpointsize = (entryprices - close)* -1 lastsize = (strategy.position_size) * -1 if callpointsize >= hedge_point_size and shortcondition strategy.order("Short2", strategy.short, qty = lastsize * hedge_gale, comment = "👻⌛", alert_message = Alert_EntryS) last_price_l = (strategy.opentrades.entry_price(strategy.opentrades - 1) + (strategy.opentrades.entry_price(strategy.opentrades - 1)/100) * takeprofit) + spread_size last_price_s = (strategy.opentrades.entry_price(strategy.opentrades - 1) - (strategy.opentrades.entry_price(strategy.opentrades - 1)/100) * takeprofit) - spread_size current_price = request.security(syminfo.tickerid, "1", close) current_pricel = request.security(syminfo.tickerid, "1", close) + spread_size current_prices = request.security(syminfo.tickerid, "1", close) - spread_size //if mode == true if strategy.position_size > 0 and strategy.openprofit >= tp_pnl and mode == true and hedge_mode == true lastsize = strategy.position_size lastprofitorder = strategy.openprofit //if lastprofitorder >= 0.07 //strategy.close('Long', qty = lastsize, comment = "TP💚L", alert_message = Alert_TPSL, immediately = true) strategy.cancel_all() strategy.close_all(comment = "TP💚PNL", alert_message = Alert_TPSL, immediately = true) //strategy.close_all(comment = "TP💚LH", alert_message = Alert_TPSL) //strategy.exit("Exit",'Long2', qty_percent = 100, profit = last_price_l, stop = stoploss, comment_profit = "TP💚LH", comment_loss = "SL💚LH", alert_message = Alert_TPSL) //strategy.exit("Exit",'Long', qty_percent = 100, profit = last_price_l, stop = stoploss, comment_profit = "TP💚L", comment_loss = "SL💚L", alert_message = Alert_TPSL) else if strategy.position_size > 0 and strategy.openprofit < tp_pnl and mode == true and hedge_mode == true strategy.exit("Exit",'Long', qty_percent = 100, stop = stoploss, comment_loss = "SL💚%L", alert_message = Alert_TPSL) if strategy.position_size > 0 and mode == true and hedge_mode == false //strategy.close_all(comment = "TP💚LH", alert_message = Alert_TPSL, immediately = true) strategy.exit("Exit",'Long', qty_percent = 100, profit = takeprofit, stop = stoploss, comment_profit = "TP💚%L", comment_loss = "SL💚%L", alert_message = Alert_TPSL) //strategy.exit("Exit",'Long', qty_percent = 100, profit = takeprofit, stop = stoploss, comment_profit = "TP💚LL", comment_loss = "SL💚L", alert_message = Alert_TPSL) //else if strategy.position_size > 0 and strategy.opentrades > 1 // lastsize = strategy.position_size // lastprofitorder = strategy.openprofit // if lastprofitorder >= 0.07 // strategy.close_all(comment = "TP💚LL", alert_message = Alert_TPSL) if strategy.position_size < 0 and strategy.openprofit >= tp_pnl and mode == true and hedge_mode == true lastsize = (strategy.position_size) * -1 lastprofitorder = strategy.openprofit //if lastprofitorder >= 0.07 //strategy.close('Short', qty = lastsize, comment = "TP❤️️S", alert_message = Alert_TPSL, immediately = true) strategy.cancel_all() strategy.close_all(comment = "TP❤️️PNL", alert_message = Alert_TPSL, immediately = true) //strategy.close_all(comment = "TP❤️️SH", alert_message = Alert_TPSL) //strategy.exit("Exit",'Short2', qty_percent = 100, profit = last_price_s, stop = stoploss, comment_profit = "TP❤️️SH", comment_loss = "SL❤️️SH", alert_message = Alert_TPSL) //strategy.exit("Exit",'Short', qty_percent = 100, profit = last_price_s, stop = stoploss, comment_profit = "TP❤️️S", comment_loss = "SL❤️️S", alert_message = Alert_TPSL) else if strategy.position_size < 0 and strategy.openprofit < tp_pnl and mode == true and hedge_mode == true strategy.exit("Exit",'Short', qty_percent = 100, stop = stoploss, comment_loss = "SL❤️️%S", alert_message = Alert_TPSL) if strategy.position_size < 0 and mode == true and hedge_mode == false //strategy.close_all(comment = "TP❤️️SH", alert_message = Alert_TPSL, immediately = true) strategy.exit("Exit",'Short', qty_percent = 100, profit = takeprofit, stop = stoploss, comment_profit = "TP❤️️%S", comment_loss = "SL❤️️%S", alert_message = Alert_TPSL) //strategy.exit("Exit",'Short', qty_percent = 100, profit = takeprofit, stop = stoploss, comment_profit = "TP❤️️S", comment_loss = "SL❤️️S", alert_message = Alert_TPSL) //else if strategy.position_size < 0 and strategy.opentrades > 1 // lastsize = (strategy.position_size) * -1 // lastprofitorder = strategy.openprofit // if lastprofitorder >= 0.07 // strategy.close_all(comment = "TP❤️️SS", alert_message = Alert_TPSL) //===================== เรียกใช้ library ========================= import X4815162342/X48_LibaryStrategyStatus/2 as fuLi //แสดงผล Backtest show_Net = input.bool(true,'Monitor Profit&Loss', inline = 'Lnet', group = '= PNL MONITOR SETTING =') position_ = input.string('bottom_center','Position', options = ['top_right','middle_right','bottom_right','top_center','middle_center','bottom_center','middle_left','bottom_left'] , inline = 'Lnet') size_i = input.string('auto','size', options = ['auto','tiny','small','normal'] , inline = 'Lnet') color_Net = input.color(color.blue,"" , inline = 'Lnet') // fuLi.NetProfit_Show(show_Net , position_ , size_i, color_Net )