init
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159
arb/common.go
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159
arb/common.go
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package arb
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import (
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"github.com/banbox/banbot/exg"
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"github.com/banbox/banbot/orm"
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"github.com/banbox/banbot/strat"
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"github.com/banbox/banexg"
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"github.com/banbox/banexg/errs"
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"github.com/banbox/banstagy/com"
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"gonum.org/v1/gonum/floats"
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"math"
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"slices"
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"sort"
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)
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func init() {
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strat.AddStratGroup("arb", map[string]strat.FuncMakeStrat{
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"stat": MeanRegressStat,
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})
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}
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type spikeTuple struct {
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A *orm.ExSymbol
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B *orm.ExSymbol
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Score float64 // 分数，越高越好
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BigSlope float64 // 大趋势平均斜率
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PftRate float64 // (hh-ll)/minChg平均倍率
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RawXBig int // 价格比率与大周期均线交叉次数
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LastDiff float64 // 最新fast与大趋势偏移，是PftRate倍数，越小越好
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}
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/*
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发现两个品种价格比率套利机会。
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通过此函数发现的机会实际上是交易量很小，价格变动百分比较大的小品种的波动。如XEM，最小变动0.6%，不如直接交易这个品种
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要求：EMA1333较稳定，(hh-ll)/maxChg较大，ratio和大均线交叉次数较多
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建议：pftRate>0.4，rawXBig>200，score>0.3
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*/
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func findSpikeTuples(endMS int64, tf string, barNum, hlWindow, itemMax int) ([]*spikeTuple, *errs.Error) {
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// 获取所有标的的K线
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exgId := exg.Default.Info().ID
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exsMap := orm.GetExSymbols(exgId, banexg.MarketLinear)
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exsList, barList, _, err := getExsBars(exg.Default, exsMap, tf, 0, endMS, barNum)
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if err != nil {
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return nil, err
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}
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// 计算周期内关键指标
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minChg := 0.0005 * 4 * 4 // 变动至少是两次开平仓手续费的4倍
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bigSlopeDist := 120 // 计算大周期斜率的距离
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items := make([]*spikeTuple, 0, len(exsList)*2)
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halfWindow := hlWindow / 2
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if hlWindow%2 > 0 {
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halfWindow += 1
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}
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for i := 0; i < len(exsList); i++ {
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barsA := barList[i]
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for j := i + 1; j < len(exsList); j++ {
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barsB := barList[j]
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barsRes := getAlignBars(barsA, barsB)
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a, b := barsRes[0], barsRes[1]
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if len(a) < barNum/2 {
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continue
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}
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var ma = com.NewEMA(0.08)
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//var maSlow = common.NewEMA(0.03)
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var maBig = com.NewEMA(0.0015)
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var rawXBig = com.NewCrossLog()
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//var rawXfa = common.NewCrossLog()
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//var vmax, vmin = float64(0), float64(0)
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var raw = make([]float64, 0, len(a))
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var bbRates = make([]float64, 0, len(a)/3)
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var spikeNum = 0
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var maBigs = make([]float64, 0, len(a))
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var bigSlopes = make([]float64, 0, 100)
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for m := 0; m < len(a); m++ {
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ratio := a[m].Close / b[m].Close
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raw = append(raw, ratio)
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maVal := ma.Update(ratio)
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maBigV := maBig.Update(ratio)
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if math.IsNaN(maBigV) {
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continue
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}
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maBigs = append(maBigs, maBigV)
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if len(maBigs)%bigSlopeDist == 0 && len(maBigs) > 0 {
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// 采样大周期斜率
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bigSlopes = append(bigSlopes, math.Abs(maBigV/maBigs[len(maBigs)-bigSlopeDist]-1))
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}
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if m%halfWindow == 0 && len(raw) > hlWindow {
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// 计算hh-ll的盈利空间
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near5 := raw[len(raw)-hlWindow:]
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bbRates = append(bbRates, (slices.Max(near5)-slices.Min(near5))/maVal/minChg)
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}
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// 计算raw与big均线交叉次数
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if ratio != maBigV {
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rawXBig.Update(ratio - maBigV)
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fxs := rawXBig.Get()
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if fxs == 1 {
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// 只记录上穿，避免交叉太多
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spikeNum += 1
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}
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}
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// 计算比率在均线附近振幅可盈利的次数
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//rawXfa.Update(ratio - maVal)
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//rxf := rawXfa.Get()
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//if rxf == 1 || rxf == -1 {
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// pft := (vmax-vmin)/maVal > minChg
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// if pft {
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// spikeNum += 1
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// }
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// vmin = maVal
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// vmax = maVal
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//}
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//if ratio > maVal {
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// vmax = max(vmax, ratio)
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//} else {
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// vmin = min(vmin, ratio)
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//}
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}
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// 平均大周期斜率
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avgSlope := floats.Sum(bigSlopes) * 50 / float64(len(bigSlopes))
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slopeRate := math.Pow(1-min(1, avgSlope), 1.5)
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// 平均盈利空间
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sort.Slice(bbRates, func(i, j int) bool {
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return bbRates[i] < bbRates[j]
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})
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bbRates = bbRates[:len(bbRates)/2]
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avgPftRate := floats.Sum(bbRates) / float64(len(bbRates))
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// 与大周期交叉的分数，交叉少于200权重降低
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hitScore := math.Log(float64(spikeNum)/200 + 1)
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val := hitScore * avgPftRate * slopeRate
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// 计算fast与大周期偏移
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lastDiff := math.Abs(ma.Val/maBig.Val-1) / minChg / avgPftRate
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items = append(items, &spikeTuple{
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A: exsList[i],
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B: exsList[j],
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Score: val,
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BigSlope: avgSlope,
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PftRate: avgPftRate,
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RawXBig: spikeNum,
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LastDiff: lastDiff,
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})
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}
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}
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sort.Slice(items, func(i, j int) bool {
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return items[i].Score > items[j].Score
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})
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tops := items[:min(1000, int(float64(len(items))*0.1))]
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res := make([]*spikeTuple, 0, len(tops)/2)
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hits := make(map[string]int)
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for _, t := range tops {
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numA, _ := hits[t.A.Symbol]
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numB, _ := hits[t.B.Symbol]
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if max(numA, numB) < itemMax {
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hits[t.A.Symbol] = numA + 1
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hits[t.B.Symbol] = numB + 1
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res = append(res, t)
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}
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}
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return res, nil
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}
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