311 lines
9.4 KiB
Go
311 lines
9.4 KiB
Go
package llmjob
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import (
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"fmt"
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"github.com/banbox/banbot/config"
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"github.com/banbox/banbot/core"
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"github.com/banbox/banbot/strat"
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ta "github.com/banbox/banta"
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"math"
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"sort"
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"sync"
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)
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/*
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需要多品种综合市场信息，品种数不可少于30
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此策略有综合市场信息并限制开单数量，回测和实盘开单预期不一致，但开单数量基本符合
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openMaxs中的前两个减少会降低收益
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待改进：
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zone1信号在22年有几次略大回撤
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*/
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// ZoneTradeState 用于存储每个交易区间的状态信息
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type ZoneTradeState struct {
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LastTimes [3]int64 // 3个买入信号的最后交易时间
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LastSellTime int64 // 最后卖出时间
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atrBase float64
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score float64
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upFlag float64
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volRate float64
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}
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func J3782(pol *config.RunPolicyConfig) *strat.TradeStrat {
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// 定义可调超参数
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maPeriod := pol.DefInt("maPeriod", 100, core.PNorm(20, 200))
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baseRetra := pol.Def("baseRetra", 0.08, core.PNorm(0.05, 0.2))
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retraRate := pol.Def("retraRate", 1.8, core.PNorm(1.5, 2.5))
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profitRate := pol.Def("profitRate", 0.03, core.PNorm(0.015, 0.06))
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tradeDelay := pol.Def("tradeDelay", 40, core.PNorm(10, 100))
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slRate := pol.Def("slRate", 63, core.PNorm(5, 35))
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openMaxs := [3]int{2, 8, 13} // 同一个bar最大同时允许开首单的数量
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holdMaxs := [3]int{25, 35, 50} // 最大同时持仓数
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buyWeis := [3]float64{1, 1.5, 3} // 不同信号开仓倍率
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maxJobTrades := [3]int{1, 3, 4} // 单个品种最大开仓数量
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// 计算各回撤比例
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retracement2 := baseRetra
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retracement3 := baseRetra * retraRate
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retracement4 := baseRetra * retraRate * 1.33
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lenAtr := 20
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baseAtrLen := int(math.Round(float64(lenAtr) * 4.3))
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rates := make([]float64, 0, 10)
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allOpens := 0
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openNums := [3]int{0, 0, 0} // 同一个bar开单数量
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holdNums := [3]int{0, 0, 0} // 总计持仓数量
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openUnits := 0.0
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var pairLock sync.Mutex
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addThres, firstRate := 1.0, 1.0
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avgAtrBase := 2.5
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maxAllowUnit := 3.0 // 这里默认为品种数
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rangeVolRate := 1.0 // 全局成交量倍率
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checkMaxPair := func(level int, openNum int) (int, float64) {
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if openNum >= maxJobTrades[level] {
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return -1, 0
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}
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costRate := buyWeis[level]
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pairLock.Lock()
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if openUnits < maxAllowUnit && openNums[level] < openMaxs[level] && holdNums[level] < holdMaxs[level] {
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openNums[level] += 1
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holdNums[level] += 1
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allOpens += 1
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openUnits += costRate
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} else {
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level = -1
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}
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pairLock.Unlock()
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return level, costRate
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}
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return &strat.TradeStrat{
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WarmupNum: maPeriod,
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BatchInfo: true,
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BatchInOut: true,
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RunTimeFrames: []string{"15m"},
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OnStartUp: func(s *strat.StratJob) {
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// 初始化状态信息
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s.More = &ZoneTradeState{
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LastTimes: [3]int64{},
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}
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},
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OnPairInfos: func(s *strat.StratJob) []*strat.PairSub {
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return []*strat.PairSub{
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{"_cur_", "4h", baseAtrLen * 2},
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}
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},
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OnBar: func(s *strat.StratJob) {
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e := s.Env
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state, _ := s.More.(*ZoneTradeState)
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// 计算MA100
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ma100 := ta.SMA(e.Close, maPeriod)
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ma100Val := ma100.Get(0)
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// 计算交易价格水平
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curRate := max(addThres, 1+state.score/10)
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itemRate := max(0.7, min(math.Sqrt(state.atrBase/avgAtrBase), 1.4))
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buyPrice2 := ma100Val * (1 - retracement2*curRate*itemRate*firstRate)
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buyPrice3 := ma100Val * (1 - retracement3*curRate*itemRate)
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buyPrice4 := ma100Val * (1 - retracement4*curRate*itemRate)
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sellPrice := ma100Val * (1 + profitRate)
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gapRange := (buyPrice2 - buyPrice4) / 2
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maVol := ta.EMA(e.Volume, lenAtr)
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volBase := ta.Lowest(ta.Highest(maVol, lenAtr), baseAtrLen).Get(0)
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state.volRate = maVol.Get(0) / volBase
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// 获取当前价格
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lowPrice := e.Low.Get(0)
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highPrice := e.High.Get(0)
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// 检查交易间隔条件
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currentBarTime := e.TimeStop
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lastEnt := max(state.LastTimes[0], state.LastTimes[1], state.LastTimes[2])
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canTrade := e.BarCount(lastEnt) >= 10
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canTrade2 := canTrade && e.BarCount(state.LastTimes[0]) >= tradeDelay
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canTrade3 := canTrade && e.BarCount(state.LastTimes[1]) >= tradeDelay
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canTrade4 := canTrade && e.BarCount(state.LastTimes[2]) >= tradeDelay
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canSell := e.BarCount(state.LastSellTime) >= tradeDelay
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// 获取当前总开仓数量，与原始策略的strategy.opentrades保持一致
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openTrades := len(s.LongOrders) + len(s.ShortOrders)
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buyIdx, costRate := -1, 0.0
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if lowPrice <= buyPrice4 && canTrade4 {
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buyIdx, costRate = checkMaxPair(2, openTrades)
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} else if lowPrice <= buyPrice3 && canTrade3 {
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buyIdx, costRate = checkMaxPair(1, openTrades)
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} else if lowPrice <= buyPrice2 && canTrade2 {
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buyIdx, costRate = checkMaxPair(0, openTrades)
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}
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if buyIdx >= 0 && costRate > 0 {
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callNum := allOpens
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//if buyIdx == 0 {
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// // 对信号1，累计开单较多时，下移入场价
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// pairLock.Lock()
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// callNum = max(callNum, int(math.Round(float64(holdNums[0])*0.5))-3)
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// pairLock.Unlock()
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//}
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// 同一个bar开单多次，从第三次开始，使用ln(num)下移入场价
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currRate := 1 + max(0, math.Log10(float64(callNum-2)))
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// 用倒抛物线映射成交量倍率，作为入场价距离调整系数
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volRate := 1 + max(0, 0.4-math.Pow(1.4*(rangeVolRate-1.5), 2))
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rangeRate := math.Pow(volRate*currRate, 0.3) - 1
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limitPrice := float64(0)
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if (rangeVolRate > 1.2 || callNum > 2) && rangeRate > 0.01 {
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limitPrice = e.Close.Get(0) - rangeRate*gapRange
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}
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tag := fmt.Sprintf("zone%d", buyIdx+1)
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s.OpenOrder(&strat.EnterReq{
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Tag: tag,
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CostRate: costRate,
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Limit: limitPrice,
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Log: true,
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StopBars: 3,
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})
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state.LastTimes[buyIdx] = currentBarTime
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}
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// 检查卖出条件
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if s.OrderNum > 0 {
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curPrice := e.Close.Get(0)
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slRange := slRate * itemRate * curPrice / 100
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avgPrice := s.PositionAvgPrice(core.OdDirtLong, "")
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if curPrice+slRange <= avgPrice {
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s.CloseOrders(&strat.ExitReq{
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Tag: "StopLoss",
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Log: true,
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})
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state.LastSellTime = currentBarTime
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} else {
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exitPrice := avgPrice*(1+profitRate)*0.4 + sellPrice*0.6
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if openTrades > 0 && highPrice >= exitPrice && canSell {
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s.CloseOrders(&strat.ExitReq{
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Tag: "SellAll",
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Log: true,
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})
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state.LastSellTime = currentBarTime
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}
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}
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}
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},
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OnInfoBar: func(s *strat.StratJob, e *ta.BarEnv, pair, tf string) {
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// 多指标综合计算大周期行情下跌分数
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score := float64(0)
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if ta.RSI(e.Close, 14).Get(0) < 30 {
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score += 1
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}
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roc := ta.ROC(e.Close, 20).Get(0)
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if roc < -20 {
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score += 2
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} else if roc < -10 {
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score += 1
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}
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plusDi, minusDi := ta.PluMinDI(e.High, e.Low, e.Close, 14)
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adx := ta.ADX(e.High, e.Low, e.Close, 14).Get(0)
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if minusDi.Get(0) > plusDi.Get(0) {
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if adx > 40 {
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score += 2
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} else if adx > 25 {
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score += 1
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}
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}
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atr := ta.ATR(e.High, e.Low, e.Close, lenAtr)
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atrBase := ta.Lowest(ta.Highest(atr, lenAtr), baseAtrLen).Get(0)
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rates = append(rates, atrBase/(e.Close.Get(0)*0.01))
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//openRate := 0.006 * closePrice / atrBase
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//if openRate < 1 {
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// openRate = math.Sqrt(openRate)
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//}
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//openRate = max(0.7, min(1.5, openRate))
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ma7 := ta.SMA(e.Close, 7).Get(0)
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ma20 := ta.SMA(e.Close, 20)
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ma20V := ma20.Get(0)
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ma99 := ta.SMA(e.Close, 99).Get(0)
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if ma99 > ma20V {
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score += 1
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}
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state, _ := s.More.(*ZoneTradeState)
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state.score = score
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state.upFlag = 0
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state.atrBase = atrBase / (e.Close.Get(0) * 0.01)
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if ma20V > ma99 && ma20V > ma20.Get(2) {
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state.upFlag = 1
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} else if ma7 < min(ma20V, ma99) {
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state.upFlag = -1
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}
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},
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OnBatchJobs: func(jobs []*strat.StratJob) {
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pairLock.Lock()
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openUnits = 0
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allOpens = 0
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openNums = [3]int{0, 0, 0}
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holdNums = [3]int{0, 0, 0}
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volRates := make([]float64, 0, len(jobs))
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for _, j := range jobs {
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for _, od := range j.LongOrders {
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if od.EnterTag == "zone1" {
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holdNums[0] += 1
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} else if od.EnterTag == "zone2" {
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holdNums[1] += 1
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} else if od.EnterTag == "zone3" {
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holdNums[2] += 1
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}
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}
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m, _ := j.More.(*ZoneTradeState)
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volRates = append(volRates, m.volRate)
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}
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pairLock.Unlock()
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sort.Float64s(volRates)
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rangeVolRate = max(1, math.Pow(volRates[len(volRates)/2]/2, 0.3))
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},
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OnBatchInfos: func(tf string, jobs map[string]*strat.JobEnv) {
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if len(jobs) < 3 {
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return
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}
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// 多品种综合计算整体市场下行激烈程度
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downNum, downHeavyNum := float64(0), float64(0)
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atrRates := make([]float64, 0, len(jobs))
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for _, j := range jobs {
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state, _ := j.Job.More.(*ZoneTradeState)
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if state.score >= 5 {
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downHeavyNum += 1
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}
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if state.score >= 3 {
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downNum += 1
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}
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atrRates = append(atrRates, state.atrBase)
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}
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jobNum := float64(len(jobs))
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downRate := downNum / jobNum
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downHeavyRate := downHeavyNum / jobNum
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sort.Float64s(atrRates)
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avgAtrBase = atrRates[len(jobs)/2]
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if downHeavyRate >= 0.8 {
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// 极端下跌
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addThres, firstRate = 1.6, 1.2
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maxAllowUnit = jobNum * 0.5
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} else if downRate >= 0.85 && downHeavyRate >= 0.6 {
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// 严重下跌
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addThres, firstRate = 1.45, 1.15
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maxAllowUnit = jobNum * 0.55
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} else if downRate >= 0.7 && downRate <= 0.85 {
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// 市场中度下跌
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addThres, firstRate = 1.3, 1.1
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maxAllowUnit = jobNum * 0.6
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} else if downRate >= 0.5 && downRate <= 0.7 {
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// 轻度下跌
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addThres, firstRate = 1.15, 1.05
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maxAllowUnit = jobNum * 0.7
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} else {
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// 轻度或未下跌
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maxAllowUnit = jobNum
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addThres, firstRate = 1, 1
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}
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},
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}
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}
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