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add more trade stats

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This commit is contained in:
Sven Woldt 2023-11-02 02:16:23 +01:00 committed by c9s
parent e7a20db048
commit a484211aa5
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GPG Key ID: 7385E7E464CB0A54
6 changed files with 409 additions and 79 deletions
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28
pkg/backtest/report.go
View File

@ -79,7 +79,35 @@ type SessionSymbolReport struct {
InitialBalances types.BalanceMap `json:"initialBalances,omitempty"`
FinalBalances types.BalanceMap `json:"finalBalances,omitempty"`
Manifests Manifests `json:"manifests,omitempty"`
TradeCount fixedpoint.Value `json:"tradeCount,omitempty"`
RoundTurnCount fixedpoint.Value `json:"roundTurnCount,omitempty"`
TotalNetProfit fixedpoint.Value `json:"totalNetProfit,omitempty"`
AvgNetProfit fixedpoint.Value `json:"avgNetProfit,omitempty"`
GrossProfit fixedpoint.Value `json:"grossProfit,omitempty"`
GrossLoss fixedpoint.Value `json:"grossLoss,omitempty"`
PRR fixedpoint.Value `json:"prr,omitempty"`
PercentProfitable fixedpoint.Value `json:"percentProfitable,omitempty"`
MaxDrawdown fixedpoint.Value `json:"maxDrawdown,omitempty"`
AverageDrawdown fixedpoint.Value `json:"avgDrawdown,omitempty"`
MaxProfit fixedpoint.Value `json:"maxProfit,omitempty"`
MaxLoss fixedpoint.Value `json:"maxLoss,omitempty"`
AvgProfit fixedpoint.Value `json:"avgProfit,omitempty"`
AvgLoss fixedpoint.Value `json:"avgLoss,omitempty"`
TotalTimeInMarketSec int64 `json:"totalTimeInMarketSec,omitempty"`
AvgHoldSec int64 `json:"avgHoldSec,omitempty"`
WinningCount int `json:"winningCount,omitempty"`
LosingCount int `json:"losingCount,omitempty"`
MaxLossStreak int `json:"maxLossStreak,omitempty"`
Sharpe fixedpoint.Value `json:"sharpeRatio"`
AnnualHistoricVolatility fixedpoint.Value `json:"annualHistoricVolatility,omitempty"`
CAGR fixedpoint.Value `json:"cagr,omitempty"`
Calmar fixedpoint.Value `json:"calmar,omitempty"`
Sterling fixedpoint.Value `json:"sterling,omitempty"`
Burke fixedpoint.Value `json:"burke,omitempty"`
Kelly fixedpoint.Value `json:"kelly,omitempty"`
OptimalF fixedpoint.Value `json:"optimalF,omitempty"`
StatN fixedpoint.Value `json:"statN,omitempty"`
StdErr fixedpoint.Value `json:"statNStdErr,omitempty"`
Sortino fixedpoint.Value `json:"sortinoRatio"`
ProfitFactor fixedpoint.Value `json:"profitFactor"`
WinningRatio fixedpoint.Value `json:"winningRatio"`

90
pkg/cmd/backtest.go
View File

@ -12,12 +12,6 @@ import (
"github.com/fatih/color"
"github.com/google/uuid"
"github.com/c9s/bbgo/pkg/cmd/cmdutil"
"github.com/c9s/bbgo/pkg/core"
"github.com/c9s/bbgo/pkg/data/tsv"
"github.com/c9s/bbgo/pkg/util"
"github.com/pkg/errors"
log "github.com/sirupsen/logrus"
"github.com/spf13/cobra"
@ -26,10 +20,14 @@ import (
"github.com/c9s/bbgo/pkg/accounting/pnl"
"github.com/c9s/bbgo/pkg/backtest"
"github.com/c9s/bbgo/pkg/bbgo"
"github.com/c9s/bbgo/pkg/cmd/cmdutil"
"github.com/c9s/bbgo/pkg/core"
"github.com/c9s/bbgo/pkg/data/tsv"
"github.com/c9s/bbgo/pkg/exchange"
"github.com/c9s/bbgo/pkg/fixedpoint"
"github.com/c9s/bbgo/pkg/service"
"github.com/c9s/bbgo/pkg/types"
"github.com/c9s/bbgo/pkg/util"
)
func init() {
@ -542,6 +540,7 @@ var BacktestCmd = &cobra.Command{
for _, session := range environ.Sessions() {
for symbol, trades := range session.Trades {
if len(trades.Trades) == 0 {
log.Warnf("session has no %s trades", symbol)
continue
@ -552,7 +551,7 @@ var BacktestCmd = &cobra.Command{
winningRatio := tradeState.WinningRatio
intervalProfits := tradeState.IntervalProfits[types.Interval1d]
symbolReport, err := createSymbolReport(userConfig, session, symbol, trades.Copy(), intervalProfits, profitFactor, winningRatio)
symbolReport, err := createSymbolReport(userConfig, session, symbol, trades.Copy(), tradeStats)
if err != nil {
return err
}
@ -625,6 +624,8 @@ func createSymbolReport(
*backtest.SessionSymbolReport,
error,
) {
intervalProfit := tradeStats.IntervalProfits[types.Interval1d]
backtestExchange, ok := session.Exchange.(*backtest.Exchange)
if !ok {
return nil, fmt.Errorf("unexpected error, exchange instance is not a backtest exchange")
@ -634,6 +635,11 @@ func createSymbolReport(
if !ok {
return nil, fmt.Errorf("market not found: %s, %s", symbol, session.Exchange.Name())
}
tStart, tEnd := trades[0].Time, trades[len(trades)-1].Time
periodStart := tStart.Time()
periodEnd := tEnd.Time()
period := periodEnd.Sub(periodStart)
startPrice, ok := session.StartPrice(symbol)
if !ok {
@ -650,29 +656,81 @@ func createSymbolReport(
Market: market,
}
sharpeRatio := fixedpoint.NewFromFloat(intervalProfit.GetSharpe())
sortinoRatio := fixedpoint.NewFromFloat(intervalProfit.GetSortino())
report := calculator.Calculate(symbol, trades, lastPrice)
accountConfig := userConfig.Backtest.GetAccount(session.Exchange.Name().String())
initBalances := accountConfig.Balances.BalanceMap()
finalBalances := session.GetAccount().Balances()
maxProfit := n(intervalProfit.Profits.Max())
maxLoss := n(intervalProfit.Profits.Min())
drawdown := types.Drawdown(intervalProfit.Profits)
maxDrawdown := drawdown.Max()
avgDrawdown := drawdown.Average()
roundTurnCount := n(float64(tradeStats.NumOfProfitTrade + tradeStats.NumOfLossTrade))
roundTurnLength := n(float64(intervalProfit.Profits.Length()))
winningCount := n(float64(tradeStats.NumOfProfitTrade))
loosingCount := n(float64(tradeStats.NumOfLossTrade))
avgProfit := tradeStats.GrossProfit.Div(n(types.NNZ(float64(tradeStats.NumOfProfitTrade), 1)))
avgLoss := tradeStats.GrossLoss.Div(n(types.NNZ(float64(tradeStats.NumOfLossTrade), 1)))
winningPct := winningCount.Div(roundTurnCount)
// losingPct := fixedpoint.One.Sub(winningPct)
sharpeRatio := n(intervalProfit.GetSharpe())
sortinoRatio := n(intervalProfit.GetSortino())
annVolHis := n(types.AnnualHistoricVolatility(intervalProfit.Profits))
totalTimeInMarketSec, avgHoldSec := intervalProfit.GetTimeInMarket()
statn, stdErr := types.StatN(intervalProfit.Profits)
symbolReport := backtest.SessionSymbolReport{
Exchange: session.Exchange.Name(),
Symbol: symbol,
Market: market,
LastPrice: lastPrice,
StartPrice: startPrice,
PnL: report,
InitialBalances: initBalances,
FinalBalances: finalBalances,
// Manifests: manifests,
TradeCount: fixedpoint.NewFromInt(int64(len(trades))),
GrossLoss: tradeStats.GrossLoss,
GrossProfit: tradeStats.GrossProfit,
WinningCount: tradeStats.NumOfProfitTrade,
LosingCount: tradeStats.NumOfLossTrade,
RoundTurnCount: roundTurnCount,
WinningRatio: tradeStats.WinningRatio,
PercentProfitable: winningPct,
ProfitFactor: tradeStats.ProfitFactor,
MaxDrawdown: n(maxDrawdown),
AverageDrawdown: n(avgDrawdown),
MaxProfit: maxProfit,
MaxLoss: maxLoss,
MaxLossStreak: tradeStats.MaximumConsecutiveLosses,
TotalTimeInMarketSec: totalTimeInMarketSec,
AvgHoldSec: avgHoldSec,
AvgProfit: avgProfit,
AvgLoss: avgLoss,
AvgNetProfit: tradeStats.TotalNetProfit.Div(roundTurnLength),
TotalNetProfit: tradeStats.TotalNetProfit,
AnnualHistoricVolatility: annVolHis,
PnL: report,
PRR: types.PRR(tradeStats.GrossProfit, tradeStats.GrossLoss, winningCount, loosingCount),
Kelly: types.KellyCriterion(tradeStats.ProfitFactor, winningPct),
OptimalF: types.OptimalF(intervalProfit.Profits),
StatN: statn,
StdErr: stdErr,
Sharpe: sharpeRatio,
Sortino: sortinoRatio,
ProfitFactor: profitFactor,
WinningRatio: winningRatio,
}
cagr := types.NN(
types.CAGR(
symbolReport.InitialEquityValue().Float64(),
symbolReport.FinalEquityValue().Float64(),
int(period.Hours())/24,
), 0)
symbolReport.CAGR = n(cagr)
symbolReport.Calmar = n(types.CalmarRatio(cagr, maxDrawdown))
symbolReport.Sterling = n(types.SterlingRatio(cagr, avgDrawdown))
symbolReport.Burke = n(types.BurkeRatio(cagr, drawdown.AverageSquared()))
for _, s := range session.Subscriptions {
symbolReport.Subscriptions = append(symbolReport.Subscriptions, s)
}
@ -691,6 +749,10 @@ func createSymbolReport(
return &symbolReport, nil
}
func n(v float64) fixedpoint.Value {
return fixedpoint.NewFromFloat(v)
}
func verify(
userConfig *bbgo.Config, backtestService *service.BacktestService,
sourceExchanges map[types.ExchangeName]types.Exchange, startTime, endTime time.Time,

12
pkg/datatype/floats/slice.go
View File

@ -112,6 +112,18 @@ func (s Slice) Average() float64 {
return total / float64(len(s))
}
func (s Slice) AverageSquared() float64 {
if len(s) == 0 {
return 0.0
}
total := 0.0
for _, value := range s {
total += math.Pow(value, 2)
}
return total / float64(len(s))
}
func (s Slice) Diff() (values Slice) {
for i, v := range s {
if i == 0 {

151
pkg/types/trade_stat.go Normal file
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@ -0,0 +1,151 @@
package types
import (
"math"
"gonum.org/v1/gonum/stat"
"github.com/c9s/bbgo/pkg/datatype/floats"
"github.com/c9s/bbgo/pkg/fixedpoint"
)
const (
// DailyToAnnualFactor is the factor to scale daily observations to annual.
// Commonly defined as the number of public market trading days in a year.
DailyToAnnualFactor = 252 // todo does this apply to crypto at all?
)
// AnnualHistoricVolatility is the historic volatility of the equity curve as annualized std dev.
func AnnualHistoricVolatility(data Series) float64 {
var sd = Stdev(data, data.Length(), 1)
return sd * math.Sqrt(DailyToAnnualFactor)
}
// CAGR is the Compound Annual Growth Rate of the equity curve.
func CAGR(initial, final float64, days int) float64 {
var (
growthRate = (final - initial) / initial
x = 1 + growthRate
y = 365.0 / float64(days)
)
return math.Pow(x, y) - 1
}
// measures of risk-adjusted return based on drawdown risk
// calmar ratio - discounts expected excess return of a portfolio by the
// worst expected maximum draw down for that portfolio
// CR = E(re)/MD1 = (E(r) - rf) / MD1
func CalmarRatio(cagr, maxDrawdown float64) float64 {
return cagr / maxDrawdown
}
// Sterling ratio
// discounts the expected excess return of a portfolio by the average of the N worst
// expected maximum drawdowns for that portfolio
// CR = E(re) / (1/N)(sum MDi)
func SterlingRatio(cagr, avgDrawdown float64) float64 {
return cagr / avgDrawdown
}
// Burke Ratio
// similar to sterling, but less sensitive to outliers
// discounts the expected excess return of a portfolio by the square root of the average
// of the N worst expected maximum drawdowns for that portfolio
// BR = E(re) / ((1/N)(sum MD^2))^0.5 ---> smoothing, can take roots, logs etc
func BurkeRatio(cagr, avgDrawdownSquared float64) float64 {
return cagr / math.Sqrt(avgDrawdownSquared)
}
// KellyCriterion the famous method for trade sizing.
func KellyCriterion(profitFactor, winP fixedpoint.Value) fixedpoint.Value {
return profitFactor.Mul(winP).Sub(fixedpoint.One.Sub(winP)).Div(profitFactor)
}
// PRR (Pessimistic Return Ratio) is the profit factor with a penalty for a lower number of roundturns.
func PRR(profit, loss, winningN, losingN fixedpoint.Value) fixedpoint.Value {
var (
winF = 1 / math.Sqrt(1+winningN.Float64())
loseF = 1 / math.Sqrt(1+losingN.Float64())
)
return fixedpoint.NewFromFloat((1 - winF) / (1 + loseF) * (1 + profit.Float64()) / (1 + loss.Float64()))
}
// StatN returns the statistically significant number of samples required based on the distribution of a series.
// From: https://www.elitetrader.com/et/threads/minimum-number-of-roundturns-required-for-backtesting-results-to-be-trusted.356588/page-2
func StatN(xs floats.Slice) (sn, se fixedpoint.Value) {
var (
sd = Stdev(xs, xs.Length(), 1)
m = Mean(xs)
statn = math.Pow(4*(sd/m), 2)
stdErr = stat.StdErr(sd, float64(xs.Length()))
)
return fixedpoint.NewFromFloat(statn), fixedpoint.NewFromFloat(stdErr)
}
// OptimalF is a function that returns the 'OptimalF' for a series of trade returns as defined by Ralph Vince.
// It is a method for sizing positions to maximize geometric return whilst accounting for biggest trading loss.
// See: https://www.investopedia.com/terms/o/optimalf.asp
// Param roundturns is the series of profits (-ve amount for losses) for each trade
func OptimalF(roundturns floats.Slice) fixedpoint.Value {
var (
maxTWR, optimalF float64
maxLoss = roundturns.Min()
)
for i := 1.0; i <= 100.0; i++ {
twr := 1.0
f := i / 100
for j := range roundturns {
if roundturns[j] == 0 {
continue
}
hpr := 1 + f*(-roundturns[j]/maxLoss)
twr *= hpr
}
if twr > maxTWR {
maxTWR = twr
optimalF = f
}
}
return fixedpoint.NewFromFloat(optimalF)
}
// NN (Not Number) returns y if x is NaN or Inf.
func NN(x, y float64) float64 {
if math.IsNaN(x) || math.IsInf(x, 0) {
return y
}
return x
}
// NNZ (Not Number or Zero) returns y if x is NaN or Inf or Zero.
func NNZ(x, y float64) float64 {
if NN(x, y) == y || x == 0 {
return y
}
return x
}
// Compute the drawdown function associated to a portfolio equity curve,
// also called the portfolio underwater equity curve.
// Portfolio Optimization with Drawdown Constraints, Chekhlov et al., 2000
// http://papers.ssrn.com/sol3/papers.cfm?abstract_id=223323
func Drawdown(equityCurve floats.Slice) floats.Slice {
// Initialize highWaterMark
highWaterMark := math.Inf(-1)
// Create ddVector with the same length as equityCurve
ddVector := make([]float64, len(equityCurve))
// Loop over all the values to compute the drawdown vector
for i := 0; i < len(equityCurve); i++ {
if equityCurve[i] > highWaterMark {
highWaterMark = equityCurve[i]
}
ddVector[i] = (highWaterMark - equityCurve[i]) / highWaterMark
}
return ddVector
}

56
pkg/types/trade_stat_test.go Normal file
View File

@ -0,0 +1,56 @@
package types
import (
"testing"
"github.com/stretchr/testify/assert"
"github.com/c9s/bbgo/pkg/datatype/floats"
"github.com/c9s/bbgo/pkg/fixedpoint"
)
func TestCAGR(t *testing.T) {
giveInitial := 1000.0
giveFinal := 2500.0
giveDays := 190
want := 4.81
act := CAGR(giveInitial, giveFinal, giveDays)
assert.InDelta(t, want, act, 0.01)
}
func TestKellyCriterion(t *testing.T) {
var (
giveProfitFactor = fixedpoint.NewFromFloat(1.6)
giveWinP = fixedpoint.NewFromFloat(0.7)
want = 0.51
act = KellyCriterion(giveProfitFactor, giveWinP)
)
assert.InDelta(t, want, act.Float64(), 0.01)
}
func TestAnnualHistoricVolatility(t *testing.T) {
var (
give = floats.Slice{0.1, 0.2, -0.15, 0.1, 0.8, -0.3, 0.2}
want = 5.51
act = AnnualHistoricVolatility(give)
)
assert.InDelta(t, want, act, 0.01)
}
func TestOptimalF(t *testing.T) {
roundturns := floats.Slice{10, 20, 50, -10, 40, -40}
f := OptimalF(roundturns)
assert.EqualValues(t, 0.45, f)
}
func TestDrawdown(t *testing.T) {
roundturns := floats.Slice{100, 50, 100}
expected := []float64{.0, .5, .0}
drawdown := Drawdown(roundturns)
assert.EqualValues(t, 0.5, drawdown.Max())
assert.EqualValues(t, 0.16666666666666666, drawdown.Average())
assert.EqualValues(t, 0.08333333333333333, drawdown.AverageSquared())
for i, v := range expected {
assert.EqualValues(t, v, drawdown[i])
}
}

103
pkg/types/trade_stats.go
View File

@ -8,45 +8,16 @@ import (
"time"
log "github.com/sirupsen/logrus"
"gopkg.in/yaml.v3"
"github.com/c9s/bbgo/pkg/datatype/floats"
"github.com/c9s/bbgo/pkg/fixedpoint"
)
type IntervalProfitCollector struct {
Interval Interval `json:"interval"`
Profits *floats.Slice `json:"profits"`
Timestamp *floats.Slice `json:"timestamp"`
tmpTime time.Time `json:"tmpTime"`
}
func NewIntervalProfitCollector(i Interval, startTime time.Time) *IntervalProfitCollector {
return &IntervalProfitCollector{Interval: i, tmpTime: startTime, Profits: &floats.Slice{1.}, Timestamp: &floats.Slice{float64(startTime.Unix())}}
}
// Update the collector by every traded profit
func (s *IntervalProfitCollector) Update(profit *Profit) {
if s.tmpTime.IsZero() {
panic("No valid start time. Did you create IntervalProfitCollector instance using NewIntervalProfitCollector?")
} else {
duration := s.Interval.Duration()
if profit.TradedAt.Before(s.tmpTime.Add(duration)) {
(*s.Profits)[len(*s.Profits)-1] *= 1. + profit.NetProfitMargin.Float64()
} else {
for {
s.Profits.Update(1.)
s.tmpTime = s.tmpTime.Add(duration)
s.Timestamp.Update(float64(s.tmpTime.Unix()))
if profit.TradedAt.Before(s.tmpTime.Add(duration)) {
(*s.Profits)[len(*s.Profits)-1] *= 1. + profit.NetProfitMargin.Float64()
break
}
}
}
}
}
const (
ErrStartTimeNotValid = "No valid start time. Did you create IntervalProfitCollector instance using NewIntervalProfitCollector?"
ErrProfitArrEmpty = "profits array empty. Did you create IntervalProfitCollector instance using NewIntervalProfitCollector?"
)
type ProfitReport struct {
StartTime time.Time `json:"startTime"`
@ -62,6 +33,55 @@ func (s ProfitReport) String() string {
return string(b)
}
type IntervalProfitCollector struct {
Interval Interval `json:"interval"`
Profits floats.Slice `json:"profits"`
TimeInMarket []time.Duration `json:"timeInMarket"`
Timestamp floats.Slice `json:"timestamp"`
tmpTime time.Time `json:"tmpTime"`
}
func NewIntervalProfitCollector(i Interval, startTime time.Time) *IntervalProfitCollector {
return &IntervalProfitCollector{Interval: i, tmpTime: startTime, Profits: floats.Slice{1.}, Timestamp: floats.Slice{float64(startTime.Unix())}}
}
// Update the collector by every traded profit
func (s *IntervalProfitCollector) Update(profit *Profit) {
if s.tmpTime.IsZero() {
panic(ErrStartTimeNotValid)
} else {
s.TimeInMarket = append(s.TimeInMarket, profit.TradedAt.Sub(profit.PositionOpenedAt))
duration := s.Interval.Duration()
if profit.TradedAt.Before(s.tmpTime.Add(duration)) {
(s.Profits)[len(s.Profits)-1] *= 1. + profit.NetProfitMargin.Float64()
} else {
for {
s.Profits.Update(1.)
s.tmpTime = s.tmpTime.Add(duration)
s.Timestamp.Update(float64(s.tmpTime.Unix()))
if profit.TradedAt.Before(s.tmpTime.Add(duration)) {
(s.Profits)[len(s.Profits)-1] *= 1. + profit.NetProfitMargin.Float64()
break
}
}
}
}
}
// Determine average and total time spend in market
func (s *IntervalProfitCollector) GetTimeInMarket() (avgHoldSec, totalTimeInMarketSec int64) {
if s.Profits == nil {
return 0, 0
}
l := len(s.TimeInMarket)
for i := 0; i < l; i++ {
d := s.TimeInMarket[i]
totalTimeInMarketSec += int64(d / time.Millisecond)
}
avgHoldSec = totalTimeInMarketSec / int64(l)
return
}
// Get all none-profitable intervals
func (s *IntervalProfitCollector) GetNonProfitableIntervals() (result []ProfitReport) {
if s.Profits == nil {
@ -93,9 +113,9 @@ func (s *IntervalProfitCollector) GetProfitableIntervals() (result []ProfitRepor
// Get number of profitable traded intervals
func (s *IntervalProfitCollector) GetNumOfProfitableIntervals() (profit int) {
if s.Profits == nil {
panic("profits array empty. Did you create IntervalProfitCollector instance using NewIntervalProfitCollector?")
panic(ErrProfitArrEmpty)
}
for _, v := range *s.Profits {
for _, v := range s.Profits {
if v > 1. {
profit += 1
}
@ -107,9 +127,9 @@ func (s *IntervalProfitCollector) GetNumOfProfitableIntervals() (profit int) {
// (no trade within the interval or pnl = 0 will be also included here)
func (s *IntervalProfitCollector) GetNumOfNonProfitableIntervals() (nonprofit int) {
if s.Profits == nil {
panic("profits array empty. Did you create IntervalProfitCollector instance using NewIntervalProfitCollector?")
panic(ErrProfitArrEmpty)
}
for _, v := range *s.Profits {
for _, v := range s.Profits {
if v <= 1. {
nonprofit += 1
}
@ -121,10 +141,11 @@ func (s *IntervalProfitCollector) GetNumOfNonProfitableIntervals() (nonprofit in
// no smart sharpe ON for the calculated result
func (s *IntervalProfitCollector) GetSharpe() float64 {
if s.tmpTime.IsZero() {
panic("No valid start time. Did you create IntervalProfitCollector instance using NewIntervalProfitCollector?")
panic(ErrStartTimeNotValid)
}
if s.Profits == nil {
panic("profits array empty. Did you create IntervalProfitCollector instance using NewIntervalProfitCollector?")
panic(ErrStartTimeNotValid)
}
return Sharpe(Sub(s.Profits, 1.), s.Profits.Length(), true, false)
}
@ -133,10 +154,10 @@ func (s *IntervalProfitCollector) GetSharpe() float64 {
// No risk-free return rate and smart sortino OFF for the calculated result.
func (s *IntervalProfitCollector) GetSortino() float64 {
if s.tmpTime.IsZero() {
panic("No valid start time. Did you create IntervalProfitCollector instance using NewIntervalProfitCollector?")
panic(ErrStartTimeNotValid)
}
if s.Profits == nil {
panic("profits array empty. Did you create IntervalProfitCollector instance using NewIntervalProfitCollector?")
panic(ErrProfitArrEmpty)
}
return Sortino(Sub(s.Profits, 1.), 0., s.Profits.Length(), true, false)
}