2022-12-16 03:51:52 +00:00
package dynamicrisk
2022-10-21 08:15:55 +00:00
import (
"github.com/pkg/errors"
log "github.com/sirupsen/logrus"
"math"
"github.com/c9s/bbgo/pkg/bbgo"
"github.com/c9s/bbgo/pkg/indicator"
"github.com/c9s/bbgo/pkg/types"
)
type DynamicSpread struct {
// AmpSpread calculates spreads based on kline amplitude
2022-12-15 09:12:04 +00:00
AmpSpread * DynamicAmpSpread ` json:"amplitude" `
2022-10-21 08:15:55 +00:00
// WeightedBollWidthRatioSpread calculates spreads based on two Bollinger Bands
WeightedBollWidthRatioSpread * DynamicSpreadBollWidthRatio ` json:"weightedBollWidth" `
}
// Initialize dynamic spread
func ( ds * DynamicSpread ) Initialize ( symbol string , session * bbgo . ExchangeSession ) {
switch {
case ds . AmpSpread != nil :
ds . AmpSpread . initialize ( symbol , session )
case ds . WeightedBollWidthRatioSpread != nil :
ds . WeightedBollWidthRatioSpread . initialize ( symbol , session )
}
}
func ( ds * DynamicSpread ) IsEnabled ( ) bool {
return ds . AmpSpread != nil || ds . WeightedBollWidthRatioSpread != nil
}
// GetAskSpread returns current ask spread
func ( ds * DynamicSpread ) GetAskSpread ( ) ( askSpread float64 , err error ) {
switch {
case ds . AmpSpread != nil :
return ds . AmpSpread . getAskSpread ( )
case ds . WeightedBollWidthRatioSpread != nil :
return ds . WeightedBollWidthRatioSpread . getAskSpread ( )
default :
return 0 , errors . New ( "dynamic spread is not enabled" )
}
}
// GetBidSpread returns current dynamic bid spread
func ( ds * DynamicSpread ) GetBidSpread ( ) ( bidSpread float64 , err error ) {
switch {
case ds . AmpSpread != nil :
return ds . AmpSpread . getBidSpread ( )
case ds . WeightedBollWidthRatioSpread != nil :
return ds . WeightedBollWidthRatioSpread . getBidSpread ( )
default :
return 0 , errors . New ( "dynamic spread is not enabled" )
}
}
// DynamicSpreadAmp uses kline amplitude to calculate spreads
2022-12-15 09:12:04 +00:00
type DynamicAmpSpread struct {
2022-10-21 08:15:55 +00:00
types . IntervalWindow
// AskSpreadScale is used to define the ask spread range with the given percentage.
AskSpreadScale * bbgo . PercentageScale ` json:"askSpreadScale" `
// BidSpreadScale is used to define the bid spread range with the given percentage.
BidSpreadScale * bbgo . PercentageScale ` json:"bidSpreadScale" `
dynamicAskSpread * indicator . SMA
dynamicBidSpread * indicator . SMA
}
// initialize amplitude dynamic spread and preload SMAs
2022-12-15 09:12:04 +00:00
func ( ds * DynamicAmpSpread ) initialize ( symbol string , session * bbgo . ExchangeSession ) {
2022-10-21 08:15:55 +00:00
ds . dynamicBidSpread = & indicator . SMA { IntervalWindow : types . IntervalWindow { Interval : ds . Interval , Window : ds . Window } }
ds . dynamicAskSpread = & indicator . SMA { IntervalWindow : types . IntervalWindow { Interval : ds . Interval , Window : ds . Window } }
// Subscribe kline
session . Subscribe ( types . KLineChannel , symbol , types . SubscribeOptions {
Interval : ds . Interval ,
} )
// Update on kline closed
session . MarketDataStream . OnKLineClosed ( types . KLineWith ( symbol , ds . Interval , func ( kline types . KLine ) {
ds . update ( kline )
} ) )
// Preload
kLineStore , _ := session . MarketDataStore ( symbol )
if klines , ok := kLineStore . KLinesOfInterval ( ds . Interval ) ; ok {
for i := 0 ; i < len ( * klines ) ; i ++ {
ds . update ( ( * klines ) [ i ] )
}
}
}
// update amplitude dynamic spread with kline
2022-12-15 09:12:04 +00:00
func ( ds * DynamicAmpSpread ) update ( kline types . KLine ) {
2022-10-21 08:15:55 +00:00
// ampl is the amplitude of kline
ampl := ( kline . GetHigh ( ) . Float64 ( ) - kline . GetLow ( ) . Float64 ( ) ) / kline . GetOpen ( ) . Float64 ( )
switch kline . Direction ( ) {
case types . DirectionUp :
ds . dynamicAskSpread . Update ( ampl )
ds . dynamicBidSpread . Update ( 0 )
case types . DirectionDown :
ds . dynamicBidSpread . Update ( ampl )
ds . dynamicAskSpread . Update ( 0 )
default :
ds . dynamicAskSpread . Update ( 0 )
ds . dynamicBidSpread . Update ( 0 )
}
}
2022-12-15 09:12:04 +00:00
func ( ds * DynamicAmpSpread ) getAskSpread ( ) ( askSpread float64 , err error ) {
2022-10-21 08:15:55 +00:00
if ds . AskSpreadScale != nil && ds . dynamicAskSpread . Length ( ) >= ds . Window {
askSpread , err = ds . AskSpreadScale . Scale ( ds . dynamicAskSpread . Last ( ) )
if err != nil {
log . WithError ( err ) . Errorf ( "can not calculate dynamicAskSpread" )
return 0 , err
}
return askSpread , nil
}
return 0 , errors . New ( "incomplete dynamic spread settings or not enough data yet" )
}
2022-12-15 09:12:04 +00:00
func ( ds * DynamicAmpSpread ) getBidSpread ( ) ( bidSpread float64 , err error ) {
2022-10-21 08:15:55 +00:00
if ds . BidSpreadScale != nil && ds . dynamicBidSpread . Length ( ) >= ds . Window {
bidSpread , err = ds . BidSpreadScale . Scale ( ds . dynamicBidSpread . Last ( ) )
if err != nil {
log . WithError ( err ) . Errorf ( "can not calculate dynamicBidSpread" )
return 0 , err
}
return bidSpread , nil
}
return 0 , errors . New ( "incomplete dynamic spread settings or not enough data yet" )
}
type DynamicSpreadBollWidthRatio struct {
// AskSpreadScale is used to define the ask spread range with the given percentage.
AskSpreadScale * bbgo . PercentageScale ` json:"askSpreadScale" `
// BidSpreadScale is used to define the bid spread range with the given percentage.
BidSpreadScale * bbgo . PercentageScale ` json:"bidSpreadScale" `
// Sensitivity factor of the weighting function: 1 / (1 + exp(-(x - mid) * sensitivity / width))
// A positive number. The greater factor, the sharper weighting function. Default set to 1.0 .
Sensitivity float64 ` json:"sensitivity" `
2022-11-23 08:53:08 +00:00
DefaultBollinger types . IntervalWindowBandWidth ` json:"defaultBollinger" `
NeutralBollinger types . IntervalWindowBandWidth ` json:"neutralBollinger" `
2022-10-21 08:15:55 +00:00
neutralBoll * indicator . BOLL
defaultBoll * indicator . BOLL
}
func ( ds * DynamicSpreadBollWidthRatio ) initialize ( symbol string , session * bbgo . ExchangeSession ) {
2022-11-23 04:28:38 +00:00
ds . neutralBoll = session . StandardIndicatorSet ( symbol ) . BOLL ( ds . NeutralBollinger . IntervalWindow , ds . NeutralBollinger . BandWidth )
ds . defaultBoll = session . StandardIndicatorSet ( symbol ) . BOLL ( ds . DefaultBollinger . IntervalWindow , ds . DefaultBollinger . BandWidth )
2022-10-21 08:15:55 +00:00
// Subscribe kline
session . Subscribe ( types . KLineChannel , symbol , types . SubscribeOptions {
Interval : ds . NeutralBollinger . Interval ,
} )
session . Subscribe ( types . KLineChannel , symbol , types . SubscribeOptions {
Interval : ds . DefaultBollinger . Interval ,
} )
if ds . Sensitivity <= 0. {
ds . Sensitivity = 1.
}
}
func ( ds * DynamicSpreadBollWidthRatio ) getAskSpread ( ) ( askSpread float64 , err error ) {
askSpread , err = ds . AskSpreadScale . Scale ( ds . getWeightedBBWidthRatio ( true ) )
if err != nil {
log . WithError ( err ) . Errorf ( "can not calculate dynamicAskSpread" )
return 0 , err
}
return askSpread , nil
}
func ( ds * DynamicSpreadBollWidthRatio ) getBidSpread ( ) ( bidSpread float64 , err error ) {
bidSpread , err = ds . BidSpreadScale . Scale ( ds . getWeightedBBWidthRatio ( false ) )
if err != nil {
log . WithError ( err ) . Errorf ( "can not calculate dynamicAskSpread" )
return 0 , err
}
return bidSpread , nil
}
func ( ds * DynamicSpreadBollWidthRatio ) getWeightedBBWidthRatio ( positiveSigmoid bool ) float64 {
// Weight the width of Boll bands with sigmoid function and calculate the ratio after integral.
//
// Given the default band: moving average default_BB_mid, band from default_BB_lower to default_BB_upper.
// And the neutral band: from neutral_BB_lower to neutral_BB_upper.
// And a sensitivity factor alpha, which is a positive constant.
//
// width of default BB w = default_BB_upper - default_BB_lower
//
// 1 x - default_BB_mid
// sigmoid weighting function f(y) = ------------- where y = --------------------
// 1 + exp(-y) w / alpha
// Set the sigmoid weighting function:
// - To ask spread, the weighting density function d_weight(x) is sigmoid((x - default_BB_mid) / (w / alpha))
// - To bid spread, the weighting density function d_weight(x) is sigmoid((default_BB_mid - x) / (w / alpha))
// - The higher sensitivity factor alpha, the sharper weighting function.
//
2022-11-23 08:53:08 +00:00
// Then calculate the weighted bandwidth ratio by taking integral of d_weight(x) from neutral_BB_lower to neutral_BB_upper:
2022-10-21 08:15:55 +00:00
// infinite integral of ask spread sigmoid weighting density function F(x) = (w / alpha) * ln(exp(x / (w / alpha)) + exp(default_BB_mid / (w / alpha)))
// 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)))
// Note that we've rescaled the sigmoid function to fit default BB,
// the weighted default BB width is always calculated by integral(f of x from default_BB_lower to default_BB_upper)
// F(neutral_BB_upper) - F(neutral_BB_lower)
// weighted ratio = -------------------------------------------
// F(default_BB_upper) - F(default_BB_lower)
// - The wider neutral band get greater ratio
// - To ask spread, the higher neutral band get greater ratio
// - To bid spread, the lower neutral band get greater ratio
defaultMid := ds . defaultBoll . SMA . Last ( )
defaultUpper := ds . defaultBoll . UpBand . Last ( )
defaultLower := ds . defaultBoll . DownBand . Last ( )
defaultWidth := defaultUpper - defaultLower
neutralUpper := ds . neutralBoll . UpBand . Last ( )
neutralLower := ds . neutralBoll . DownBand . Last ( )
factor := defaultWidth / ds . Sensitivity
var weightedUpper , weightedLower , weightedDivUpper , weightedDivLower float64
if positiveSigmoid {
weightedUpper = factor * math . Log ( math . Exp ( neutralUpper / factor ) + math . Exp ( defaultMid / factor ) )
weightedLower = factor * math . Log ( math . Exp ( neutralLower / factor ) + math . Exp ( defaultMid / factor ) )
weightedDivUpper = factor * math . Log ( math . Exp ( defaultUpper / factor ) + math . Exp ( defaultMid / factor ) )
weightedDivLower = factor * math . Log ( math . Exp ( defaultLower / factor ) + math . Exp ( defaultMid / factor ) )
} else {
weightedUpper = neutralUpper - factor * math . Log ( math . Exp ( neutralUpper / factor ) + math . Exp ( defaultMid / factor ) )
weightedLower = neutralLower - factor * math . Log ( math . Exp ( neutralLower / factor ) + math . Exp ( defaultMid / factor ) )
weightedDivUpper = defaultUpper - factor * math . Log ( math . Exp ( defaultUpper / factor ) + math . Exp ( defaultMid / factor ) )
weightedDivLower = defaultLower - factor * math . Log ( math . Exp ( defaultLower / factor ) + math . Exp ( defaultMid / factor ) )
}
return ( weightedUpper - weightedLower ) / ( weightedDivUpper - weightedDivLower )
}