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feature/dynamicSpread: dynamicSpread as a common package
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Andy Cheng
parent
7de9975336
commit
df05cf65d2
275
pkg/dynamicmetric/dynamic_spread.go
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275
pkg/dynamicmetric/dynamic_spread.go
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package dynamicmetric
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import (
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"github.com/pkg/errors"
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log "github.com/sirupsen/logrus"
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"math"
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"github.com/c9s/bbgo/pkg/bbgo"
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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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type DynamicSpread struct {
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// AmpSpread calculates spreads based on kline amplitude
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AmpSpread *DynamicSpreadAmp `json:"amplitude"`
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// WeightedBollWidthRatioSpread calculates spreads based on two Bollinger Bands
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WeightedBollWidthRatioSpread *DynamicSpreadBollWidthRatio `json:"weightedBollWidth"`
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// deprecated
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Enabled *bool `json:"enabled"`
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// deprecated
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types.IntervalWindow
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// deprecated. AskSpreadScale is used to define the ask spread range with the given percentage.
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AskSpreadScale *bbgo.PercentageScale `json:"askSpreadScale"`
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// deprecated. BidSpreadScale is used to define the bid spread range with the given percentage.
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BidSpreadScale *bbgo.PercentageScale `json:"bidSpreadScale"`
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}
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// Initialize dynamic spread
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func (ds *DynamicSpread) Initialize(symbol string, session *bbgo.ExchangeSession) {
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switch {
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case ds.AmpSpread != nil:
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ds.AmpSpread.initialize(symbol, session)
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case ds.WeightedBollWidthRatioSpread != nil:
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ds.WeightedBollWidthRatioSpread.initialize(symbol, session)
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case ds.Enabled != nil && *ds.Enabled:
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// backward compatibility
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ds.AmpSpread = &DynamicSpreadAmp{
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IntervalWindow: ds.IntervalWindow,
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AskSpreadScale: ds.AskSpreadScale,
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BidSpreadScale: ds.BidSpreadScale,
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}
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ds.AmpSpread.initialize(symbol, session)
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}
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}
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func (ds *DynamicSpread) IsEnabled() bool {
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return ds.AmpSpread != nil || ds.WeightedBollWidthRatioSpread != nil
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}
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// GetAskSpread returns current ask spread
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func (ds *DynamicSpread) GetAskSpread() (askSpread float64, err error) {
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switch {
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case ds.AmpSpread != nil:
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return ds.AmpSpread.getAskSpread()
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case ds.WeightedBollWidthRatioSpread != nil:
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return ds.WeightedBollWidthRatioSpread.getAskSpread()
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default:
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return 0, errors.New("dynamic spread is not enabled")
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}
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}
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// GetBidSpread returns current dynamic bid spread
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func (ds *DynamicSpread) GetBidSpread() (bidSpread float64, err error) {
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switch {
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case ds.AmpSpread != nil:
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return ds.AmpSpread.getBidSpread()
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case ds.WeightedBollWidthRatioSpread != nil:
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return ds.WeightedBollWidthRatioSpread.getBidSpread()
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default:
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return 0, errors.New("dynamic spread is not enabled")
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}
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}
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// DynamicSpreadAmp uses kline amplitude to calculate spreads
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type DynamicSpreadAmp struct {
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types.IntervalWindow
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// AskSpreadScale is used to define the ask spread range with the given percentage.
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AskSpreadScale *bbgo.PercentageScale `json:"askSpreadScale"`
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// BidSpreadScale is used to define the bid spread range with the given percentage.
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BidSpreadScale *bbgo.PercentageScale `json:"bidSpreadScale"`
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dynamicAskSpread *indicator.SMA
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dynamicBidSpread *indicator.SMA
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}
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// initialize amplitude dynamic spread and preload SMAs
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func (ds *DynamicSpreadAmp) initialize(symbol string, session *bbgo.ExchangeSession) {
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ds.dynamicBidSpread = &indicator.SMA{IntervalWindow: types.IntervalWindow{Interval: ds.Interval, Window: ds.Window}}
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ds.dynamicAskSpread = &indicator.SMA{IntervalWindow: types.IntervalWindow{Interval: ds.Interval, Window: ds.Window}}
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// Subscribe kline
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session.Subscribe(types.KLineChannel, symbol, types.SubscribeOptions{
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Interval: ds.Interval,
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})
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// Update on kline closed
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session.MarketDataStream.OnKLineClosed(types.KLineWith(symbol, ds.Interval, func(kline types.KLine) {
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ds.update(kline)
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}))
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// Preload
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kLineStore, _ := session.MarketDataStore(symbol)
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if klines, ok := kLineStore.KLinesOfInterval(ds.Interval); ok {
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for i := 0; i < len(*klines); i++ {
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ds.update((*klines)[i])
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}
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}
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}
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// update amplitude dynamic spread with kline
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func (ds *DynamicSpreadAmp) update(kline types.KLine) {
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// ampl is the amplitude of kline
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ampl := (kline.GetHigh().Float64() - kline.GetLow().Float64()) / kline.GetOpen().Float64()
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switch kline.Direction() {
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case types.DirectionUp:
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ds.dynamicAskSpread.Update(ampl)
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ds.dynamicBidSpread.Update(0)
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case types.DirectionDown:
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ds.dynamicBidSpread.Update(ampl)
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ds.dynamicAskSpread.Update(0)
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default:
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ds.dynamicAskSpread.Update(0)
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ds.dynamicBidSpread.Update(0)
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}
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}
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func (ds *DynamicSpreadAmp) getAskSpread() (askSpread float64, err error) {
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if ds.AskSpreadScale != nil && ds.dynamicAskSpread.Length() >= ds.Window {
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askSpread, err = ds.AskSpreadScale.Scale(ds.dynamicAskSpread.Last())
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if err != nil {
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log.WithError(err).Errorf("can not calculate dynamicAskSpread")
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return 0, err
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}
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return askSpread, nil
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}
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return 0, errors.New("incomplete dynamic spread settings or not enough data yet")
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}
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func (ds *DynamicSpreadAmp) getBidSpread() (bidSpread float64, err error) {
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if ds.BidSpreadScale != nil && ds.dynamicBidSpread.Length() >= ds.Window {
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bidSpread, err = ds.BidSpreadScale.Scale(ds.dynamicBidSpread.Last())
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if err != nil {
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log.WithError(err).Errorf("can not calculate dynamicBidSpread")
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return 0, err
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}
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return bidSpread, nil
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}
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return 0, errors.New("incomplete dynamic spread settings or not enough data yet")
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}
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// BollingerSetting is for Bollinger Band settings
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type BollingerSetting struct {
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types.IntervalWindow
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BandWidth float64 `json:"bandWidth"`
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}
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type DynamicSpreadBollWidthRatio struct {
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// AskSpreadScale is used to define the ask spread range with the given percentage.
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AskSpreadScale *bbgo.PercentageScale `json:"askSpreadScale"`
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// BidSpreadScale is used to define the bid spread range with the given percentage.
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BidSpreadScale *bbgo.PercentageScale `json:"bidSpreadScale"`
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// Sensitivity factor of the weighting function: 1 / (1 + exp(-(x - mid) * sensitivity / width))
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// A positive number. The greater factor, the sharper weighting function. Default set to 1.0 .
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Sensitivity float64 `json:"sensitivity"`
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DefaultBollinger *BollingerSetting `json:"defaultBollinger"`
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NeutralBollinger *BollingerSetting `json:"neutralBollinger"`
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StandardIndicatorSet *bbgo.StandardIndicatorSet
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neutralBoll *indicator.BOLL
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defaultBoll *indicator.BOLL
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}
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func (ds *DynamicSpreadBollWidthRatio) initialize(symbol string, session *bbgo.ExchangeSession) {
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ds.neutralBoll = ds.StandardIndicatorSet.BOLL(ds.NeutralBollinger.IntervalWindow, ds.NeutralBollinger.BandWidth)
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ds.defaultBoll = ds.StandardIndicatorSet.BOLL(ds.DefaultBollinger.IntervalWindow, ds.DefaultBollinger.BandWidth)
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// Subscribe kline
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session.Subscribe(types.KLineChannel, symbol, types.SubscribeOptions{
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Interval: ds.NeutralBollinger.Interval,
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})
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session.Subscribe(types.KLineChannel, symbol, types.SubscribeOptions{
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Interval: ds.DefaultBollinger.Interval,
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})
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if ds.Sensitivity <= 0. {
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ds.Sensitivity = 1.
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}
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}
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func (ds *DynamicSpreadBollWidthRatio) getAskSpread() (askSpread float64, err error) {
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askSpread, err = ds.AskSpreadScale.Scale(ds.getWeightedBBWidthRatio(true))
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if err != nil {
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log.WithError(err).Errorf("can not calculate dynamicAskSpread")
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return 0, err
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}
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return askSpread, nil
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}
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func (ds *DynamicSpreadBollWidthRatio) getBidSpread() (bidSpread float64, err error) {
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bidSpread, err = ds.BidSpreadScale.Scale(ds.getWeightedBBWidthRatio(false))
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if err != nil {
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log.WithError(err).Errorf("can not calculate dynamicAskSpread")
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return 0, err
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}
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return bidSpread, nil
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}
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func (ds *DynamicSpreadBollWidthRatio) getWeightedBBWidthRatio(positiveSigmoid bool) float64 {
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// Weight the width of Boll bands with sigmoid function and calculate the ratio after integral.
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//
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// Given the default band: moving average default_BB_mid, band from default_BB_lower to default_BB_upper.
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// And the neutral band: from neutral_BB_lower to neutral_BB_upper.
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// And a sensitivity factor alpha, which is a positive constant.
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//
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// width of default BB w = default_BB_upper - default_BB_lower
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//
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// 1 x - default_BB_mid
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// sigmoid weighting function f(y) = ------------- where y = --------------------
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// 1 + exp(-y) w / alpha
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// Set the sigmoid weighting function:
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// - To ask spread, the weighting density function d_weight(x) is sigmoid((x - default_BB_mid) / (w / alpha))
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// - To bid spread, the weighting density function d_weight(x) is sigmoid((default_BB_mid - x) / (w / alpha))
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// - The higher sensitivity factor alpha, the sharper weighting function.
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//
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// Then calculate the weighted band width ratio by taking integral of d_weight(x) from neutral_BB_lower to neutral_BB_upper:
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// infinite integral of ask spread sigmoid weighting density function F(x) = (w / alpha) * ln(exp(x / (w / alpha)) + exp(default_BB_mid / (w / alpha)))
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// infinite integral of bid spread sigmoid weighting density function F(x) = x - (w / alpha) * ln(exp(x / (w / alpha)) + exp(default_BB_mid / (w / alpha)))
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// Note that we've rescaled the sigmoid function to fit default BB,
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// the weighted default BB width is always calculated by integral(f of x from default_BB_lower to default_BB_upper)
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// F(neutral_BB_upper) - F(neutral_BB_lower)
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// weighted ratio = -------------------------------------------
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// F(default_BB_upper) - F(default_BB_lower)
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// - The wider neutral band get greater ratio
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// - To ask spread, the higher neutral band get greater ratio
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// - To bid spread, the lower neutral band get greater ratio
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defaultMid := ds.defaultBoll.SMA.Last()
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defaultUpper := ds.defaultBoll.UpBand.Last()
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defaultLower := ds.defaultBoll.DownBand.Last()
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defaultWidth := defaultUpper - defaultLower
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neutralUpper := ds.neutralBoll.UpBand.Last()
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neutralLower := ds.neutralBoll.DownBand.Last()
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factor := defaultWidth / ds.Sensitivity
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var weightedUpper, weightedLower, weightedDivUpper, weightedDivLower float64
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if positiveSigmoid {
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weightedUpper = factor * math.Log(math.Exp(neutralUpper/factor)+math.Exp(defaultMid/factor))
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weightedLower = factor * math.Log(math.Exp(neutralLower/factor)+math.Exp(defaultMid/factor))
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weightedDivUpper = factor * math.Log(math.Exp(defaultUpper/factor)+math.Exp(defaultMid/factor))
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weightedDivLower = factor * math.Log(math.Exp(defaultLower/factor)+math.Exp(defaultMid/factor))
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} else {
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weightedUpper = neutralUpper - factor*math.Log(math.Exp(neutralUpper/factor)+math.Exp(defaultMid/factor))
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weightedLower = neutralLower - factor*math.Log(math.Exp(neutralLower/factor)+math.Exp(defaultMid/factor))
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weightedDivUpper = defaultUpper - factor*math.Log(math.Exp(defaultUpper/factor)+math.Exp(defaultMid/factor))
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weightedDivLower = defaultLower - factor*math.Log(math.Exp(defaultLower/factor)+math.Exp(defaultMid/factor))
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}
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return (weightedUpper - weightedLower) / (weightedDivUpper - weightedDivLower)
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}
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