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107 lines
2.4 KiB
Go
107 lines
2.4 KiB
Go
package supertrend
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import (
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"time"
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"github.com/c9s/bbgo/pkg/datatype/floats"
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"github.com/c9s/bbgo/pkg/indicator"
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"github.com/c9s/bbgo/pkg/types"
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)
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// LinReg is Linear Regression baseline
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type LinReg struct {
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types.SeriesBase
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types.IntervalWindow
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// Values are the slopes of linear regression baseline
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Values floats.Slice
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klines types.KLineWindow
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EndTime time.Time
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}
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// Last slope of linear regression baseline
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func (lr *LinReg) Last() float64 {
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if lr.Values.Length() == 0 {
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return 0.0
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}
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return lr.Values.Last()
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}
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// Index returns the slope of specified index
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func (lr *LinReg) Index(i int) float64 {
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if i >= lr.Values.Length() {
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return 0.0
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}
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return lr.Values.Index(i)
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}
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// Length of the slope values
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func (lr *LinReg) Length() int {
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return lr.Values.Length()
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}
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var _ types.SeriesExtend = &LinReg{}
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// Update Linear Regression baseline slope
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func (lr *LinReg) Update(kline types.KLine) {
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lr.klines.Add(kline)
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lr.klines.Truncate(lr.Window)
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if len(lr.klines) < lr.Window {
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lr.Values.Push(0)
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return
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}
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var sumX, sumY, sumXSqr, sumXY float64 = 0, 0, 0, 0
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end := len(lr.klines) - 1 // The last kline
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for i := end; i >= end-lr.Window+1; i-- {
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val := lr.klines[i].GetClose().Float64()
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per := float64(end - i + 1)
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sumX += per
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sumY += val
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sumXSqr += per * per
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sumXY += val * per
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}
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length := float64(lr.Window)
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slope := (length*sumXY - sumX*sumY) / (length*sumXSqr - sumX*sumX)
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average := sumY / length
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endPrice := average - slope*sumX/length + slope
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startPrice := endPrice + slope*(length-1)
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lr.Values.Push((length - 1) / (endPrice - startPrice))
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log.Debugf("linear regression baseline slope: %f", lr.Last())
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}
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func (lr *LinReg) BindK(target indicator.KLineClosedEmitter, symbol string, interval types.Interval) {
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target.OnKLineClosed(types.KLineWith(symbol, interval, lr.PushK))
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}
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func (lr *LinReg) PushK(k types.KLine) {
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var zeroTime = time.Time{}
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if lr.EndTime != zeroTime && k.EndTime.Before(lr.EndTime) {
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return
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}
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lr.Update(k)
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lr.EndTime = k.EndTime.Time()
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}
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func (lr *LinReg) LoadK(allKLines []types.KLine) {
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for _, k := range allKLines {
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lr.PushK(k)
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}
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}
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// GetSignal get linear regression signal
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func (lr *LinReg) GetSignal() types.Direction {
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var lrSignal types.Direction = types.DirectionNone
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switch {
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case lr.Last() > 0:
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lrSignal = types.DirectionUp
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case lr.Last() < 0:
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lrSignal = types.DirectionDown
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}
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return lrSignal
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}
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