109 lines
2.9 KiB
Go
109 lines
2.9 KiB
Go
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package indicator
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import (
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"math"
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"git.qtrade.icu/lychiyu/bbgo/pkg/datatype/floats"
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"git.qtrade.icu/lychiyu/bbgo/pkg/types"
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)
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// Refer: Variable Index Dynamic Average
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// Refer URL: https://metatrader5.com/en/terminal/help/indicators/trend_indicators/vida
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// The Variable Index Dynamic Average (VIDYA) is a technical analysis indicator that is used to smooth price data and reduce the lag
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// associated with traditional moving averages. It is calculated by taking the weighted moving average of the input data, with the
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// weighting factors determined using a variable index that is based on the standard deviation of the data and the specified length of
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// the moving average. This resulting average is then plotted on the price chart as a line, which can be used to make predictions about
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// future price movements. The VIDYA is typically more responsive to changes in the underlying data than a simple moving average, but may
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// be less reliable in trending markets.
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//go:generate callbackgen -type VIDYA
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type VIDYA struct {
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types.SeriesBase
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types.IntervalWindow
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Values floats.Slice
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input floats.Slice
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updateCallbacks []func(value float64)
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}
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func (inc *VIDYA) Update(value float64) {
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if inc.Values.Length() == 0 {
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inc.SeriesBase.Series = inc
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inc.Values.Push(value)
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inc.input.Push(value)
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return
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}
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inc.input.Push(value)
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if len(inc.input) > MaxNumOfEWMA {
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inc.input = inc.input[MaxNumOfEWMATruncateSize-1:]
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}
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/*upsum := 0.
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downsum := 0.
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for i := 0; i < inc.Window; i++ {
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if len(inc.input) <= i+1 {
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break
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}
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diff := inc.input.Index(i) - inc.input.Index(i+1)
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if diff > 0 {
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upsum += diff
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} else {
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downsum += -diff
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}
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}
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if upsum == 0 && downsum == 0 {
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return
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}
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CMO := math.Abs((upsum - downsum) / (upsum + downsum))*/
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change := types.Change(&inc.input)
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CMO := math.Abs(types.Sum(change, inc.Window) / types.Sum(types.Abs(change), inc.Window))
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alpha := 2. / float64(inc.Window+1)
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inc.Values.Push(value*alpha*CMO + inc.Values.Last(0)*(1.-alpha*CMO))
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if inc.Values.Length() > MaxNumOfEWMA {
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inc.Values = inc.Values[MaxNumOfEWMATruncateSize-1:]
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}
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}
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func (inc *VIDYA) Last(i int) float64 {
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return inc.Values.Last(i)
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}
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func (inc *VIDYA) Index(i int) float64 {
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return inc.Last(i)
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}
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func (inc *VIDYA) Length() int {
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return inc.Values.Length()
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}
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var _ types.SeriesExtend = &VIDYA{}
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func (inc *VIDYA) PushK(k types.KLine) {
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inc.Update(k.Close.Float64())
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}
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func (inc *VIDYA) CalculateAndUpdate(allKLines []types.KLine) {
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if inc.input.Length() == 0 {
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for _, k := range allKLines {
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inc.PushK(k)
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inc.EmitUpdate(inc.Last(0))
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}
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} else {
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k := allKLines[len(allKLines)-1]
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inc.PushK(k)
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inc.EmitUpdate(inc.Last(0))
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}
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}
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func (inc *VIDYA) handleKLineWindowUpdate(interval types.Interval, window types.KLineWindow) {
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if inc.Interval != interval {
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return
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}
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inc.CalculateAndUpdate(window)
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}
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func (inc *VIDYA) Bind(updater KLineWindowUpdater) {
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updater.OnKLineWindowUpdate(inc.handleKLineWindowUpdate)
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}
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