dfキャンドルの取得期間の選択機能を追加

config.yml

@@ -1,9 +1,8 @@
 
 
 
-
-assetName: "LINKUSDT"
-
+#バックテストの基本設定 startとendの月は必ず二桁になるように｡
+assetName: "SOLUSDT"
 duration: "15m"
-
-limit: 17000
+start: "2021-04"
+end: "2022-011"

main.go

@@ -10,12 +10,9 @@ func main() {
 
 	start := time.Now()
 
-	strategey.RunBacktestEma()
-	strategey.RunBacktestEmaChoppy()
-	strategey.RunBacktestDonchain()
-	strategey.RunBacktestDonchainChoppy()
-	strategey.RunBacktestST()
-	strategey.RunBacktestSuperTrend()
+	strategey.RunEmaOptimize()
+	// strategey.RunBacktestDonchainChoppy()
+	// strategey.RunBacktestSuperTrend()
 
 	// assetName := "TIAUSDT"
 	// duration := "4h"

pkg/config/yaml.go

@@ -11,7 +11,8 @@ var data = "config.yml"
 type Config struct {
 	AssetName string `yaml:"assetName"`
 	Dration   string `yaml:"duration"`
-	Limit     int    `yaml:"limit"`
+	Start     string `yaml:"start"`
+	End       string `yaml:"end"`
 }
 
 func Yaml() (Config, error) {

pkg/strategey/donchain.go

@@ -15,7 +15,7 @@ import (
 // 	return "DBO"
 // }
 
-func (df *DataFrameCandle) DonchainStrategy(period int, account *trader.Account) *execute.SignalEvents {
+func (df *DataFrameCandleCsv) DonchainStrategy(period int, account *trader.Account) *execute.SignalEvents {
 	var StrategyName = "DBO"
 
 	lenCandles := len(df.Candles)
@@ -63,7 +63,7 @@ func (df *DataFrameCandle) DonchainStrategy(period int, account *trader.Account)
 	return signalEvents
 
 }
-func (df *DataFrameCandle) OptimizeDonchainGoroutin() (performance float64, bestPeriod int) {
+func (df *DataFrameCandleCsv) OptimizeDonchainGoroutin() (performance float64, bestPeriod int) {
 
 	bestPeriod = 40
 	var mu sync.Mutex
@@ -128,15 +128,14 @@ func RunBacktestDonchain() {
 
 	fmt.Println("--------------------------------------------")
 
-	// strategyName := getStrageyNameDonchain()
 	assetName := btcfg.AssetName
 	duration := btcfg.Dration
-
-	// limit := btcfg.Limit
+	start := btcfg.Start
+	end := btcfg.End
 
 	account := trader.NewAccount(1000)
 
-	df, _ := GetCandleData(assetName, duration)
+	df, _ := GetCsvDataFrame(assetName, duration, start, end)
 
 	performancePayOffRatio, bestPayOffRatioPeriod := df.OptimizeDonchainGoroutin()
 

pkg/strategey/donchain_choppy.go

@@ -2,10 +2,8 @@ package strategey
 
 import (
 	"fmt"
-	"log"
 	"sync"
 	"v1/pkg/analytics"
-	"v1/pkg/config"
 	"v1/pkg/execute"
 	"v1/pkg/indicator/indicators"
 	"v1/pkg/management/risk"
@@ -16,7 +14,7 @@ import (
 // 	return "DBO"
 // }
 
-func (df *DataFrameCandle) DonchainChoppyStrategy(period int, choppy int, account *trader.Account) *execute.SignalEvents {
+func (df *DataFrameCandleCsv) DonchainChoppyStrategy(period int, choppy int, account *trader.Account) *execute.SignalEvents {
 	var StrategyName = "DBO_CHOPPY"
 
 	lenCandles := len(df.Candles)
@@ -68,7 +66,7 @@ func (df *DataFrameCandle) DonchainChoppyStrategy(period int, choppy int, accoun
 
 }
 
-func (df *DataFrameCandle) OptimizeDonchainChoppyGoroutin() (performance float64, bestPeriod int, bestChoppy int) {
+func (df *DataFrameCandleCsv) OptimizeDonchainChoppyGoroutin() (performance float64, bestPeriod int, bestChoppy int) {
 
 	bestPeriod = 40
 	bestChoppy = 13
@@ -81,7 +79,7 @@ func (df *DataFrameCandle) OptimizeDonchainChoppyGoroutin() (performance float64
 	limit := 1000
 	slots := make(chan struct{}, limit)
 
-	for period := 10; period < 250; period += 3 {
+	for period := 5; period < 100; period += 1 {
 		for choppy := 5; choppy < 18; choppy += 1 {
 			wg.Add(1)
 			slots <- struct{}{}
@@ -135,27 +133,9 @@ func (df *DataFrameCandle) OptimizeDonchainChoppyGoroutin() (performance float64
 	return performance, bestPeriod, bestChoppy
 }
 
-func RunBacktestDonchainChoppy() {
+func RunDonchainOptimize() {
 
-	var err error
-
-	// account := trader.NewAccount(1000)
-	btcfg, err := config.Yaml()
-	if err != nil {
-		log.Fatalf("error: %v", err)
-	}
-
-	fmt.Println("--------------------------------------------")
-
-	// strategyName := getStrageyNameDonchain()
-	assetName := btcfg.AssetName
-	duration := btcfg.Dration
-
-	// limit := btcfg.Limit
-
-	account := trader.NewAccount(1000)
-
-	df, _ := GetCandleData(assetName, duration)
+	df, account, _ := RadyBacktest()
 
 	p, bestPeriod, bestChoppy := df.OptimizeDonchainChoppyGoroutin()
 
@@ -167,3 +147,11 @@ func RunBacktestDonchainChoppy() {
 	}
 
 }
+
+func DonchainBacktest() {
+
+	df, account, _ := RadyBacktest()
+
+	df.Signal = df.DonchainChoppyStrategy(40, 13, account)
+	Result(df.Signal)
+}

pkg/strategey/ema.go

@@ -13,7 +13,7 @@ import (
 	"github.com/markcheno/go-talib"
 )
 
-func (df *DataFrameCandle) EmaStrategy(period1, period2 int, account *trader.Account) *execute.SignalEvents {
+func (df *DataFrameCandleCsv) EmaStrategy(period1, period2 int, account *trader.Account) *execute.SignalEvents {
 
 	var StrategyName = "EMA"
 	lenCandles := len(df.Candles)
@@ -61,7 +61,7 @@ func (df *DataFrameCandle) EmaStrategy(period1, period2 int, account *trader.Acc
 	return signalEvents
 }
 
-func (df *DataFrameCandle) OptimizeEma() (performance float64, bestPeriod1 int, bestPeriod2 int) {
+func (df *DataFrameCandleCsv) OptimizeEma() (performance float64, bestPeriod1 int, bestPeriod2 int) {
 	runtime.GOMAXPROCS(10)
 	bestPeriod1 = 5
 	bestPeriod2 = 21
@@ -173,11 +173,12 @@ func RunBacktestEma() {
 
 	assetName := btcfg.AssetName
 	duration := btcfg.Dration
-	// limit := btcfg.Limit
+	start := btcfg.Start
+	end := btcfg.End
 
 	account := trader.NewAccount(1000)
 
-	df, _ := GetCandleData(assetName, duration)
+	df, _ := GetCsvDataFrame(assetName, duration, start, end)
 
 	performance, bestPeriod1, bestPeriod2 := df.OptimizeEma()
 

pkg/strategey/ema_choppy.go

@@ -2,19 +2,17 @@ package strategey
 
 import (
 	"fmt"
-	"log"
 	"runtime"
 	"sync"
 	"v1/pkg/analytics"
-	"v1/pkg/config"
 	"v1/pkg/execute"
 	"v1/pkg/management/risk"
 	"v1/pkg/trader"
 
 	"github.com/markcheno/go-talib"
 )
 
-func (df *DataFrameCandle) EmaChoppyStrategy(period1, period2 int, choppy int, account *trader.Account) *execute.SignalEvents {
+func (df *DataFrameCandleCsv) EmaChoppyStrategy(period1, period2 int, choppy int, account *trader.Account) *execute.SignalEvents {
 
 	var StrategyName = "EMA_CHOPPY"
 	lenCandles := len(df.Candles)
@@ -66,7 +64,7 @@ func (df *DataFrameCandle) EmaChoppyStrategy(period1, period2 int, choppy int, a
 	return signalEvents
 }
 
-func (df *DataFrameCandle) OptimizeEmaChoppy() (performance float64, bestPeriod1 int, bestPeriod2 int, bestChoppy int) {
+func (df *DataFrameCandleCsv) OptimizeEmaChoppy() (performance float64, bestPeriod1 int, bestPeriod2 int, bestChoppy int) {
 	runtime.GOMAXPROCS(10)
 	bestPeriod1 = 5
 	bestPeriod2 = 21
@@ -81,8 +79,8 @@ func (df *DataFrameCandle) OptimizeEmaChoppy() (performance float64, bestPeriod1
 	var mu sync.Mutex
 	var wg sync.WaitGroup
 
-	for period1 := 3; period1 < 92; period1 += 3 {
-		for period2 := 5; period2 < 260; period2 += 3 {
+	for period1 := 1; period1 < 34; period1 += 2 {
+		for period2 := 5; period2 < 250; period2 += 3 {
 			for choppy := 5; choppy < 18; choppy += 1 {
 
 				wg.Add(1)
@@ -144,25 +142,9 @@ func (df *DataFrameCandle) OptimizeEmaChoppy() (performance float64, bestPeriod1
 	return performance, bestPeriod1, bestPeriod2, bestChoppy
 }
 
-func RunBacktestEmaChoppy() {
+func RunEmaOptimize() {
 
-	var err error
-
-	// account := trader.NewAccount(1000)
-	btcfg, err := config.Yaml()
-	if err != nil {
-		log.Fatalf("error: %v", err)
-	}
-
-	fmt.Println("--------------------------------------------")
-
-	assetName := btcfg.AssetName
-	duration := btcfg.Dration
-	// limit := btcfg.Limit
-
-	account := trader.NewAccount(1000)
-
-	df, _ := GetCandleData(assetName, duration)
+	df, account, _ := RadyBacktest()
 
 	performance, bestPeriod1, bestPeriod2, bestChoppy := df.OptimizeEmaChoppy()
 
@@ -174,3 +156,12 @@ func RunBacktestEmaChoppy() {
 	}
 
 }
+
+func EmaBacktest() {
+
+	df, account, _ := RadyBacktest()
+
+	df.Signal = df.EmaChoppyStrategy(5, 21, 12, account)
+	Result(df.Signal)
+
+}

pkg/strategey/strategy.go

@@ -10,6 +10,7 @@ import (
 	"strings"
 	"time"
 	"v1/pkg/analytics"
+	"v1/pkg/config"
 	"v1/pkg/data"
 	dbquery "v1/pkg/data/query"
 	"v1/pkg/execute"
@@ -321,6 +322,29 @@ func (df *DataFrameCandleCsv) Hlc3() []float64 {
 	return s
 }
 
+func RadyBacktest() (*DataFrameCandleCsv, *trader.Account, error) {
+
+	var err error
+
+	btcfg, err := config.Yaml()
+	if err != nil {
+		return &DataFrameCandleCsv{}, &trader.Account{}, nil
+	}
+	account := trader.NewAccount(1000)
+
+	assetName := btcfg.AssetName
+	duration := btcfg.Dration
+	start := btcfg.Start
+	end := btcfg.End
+
+	df, err := GetCsvDataFrame(assetName, duration, start, end)
+	if err != nil {
+		return &DataFrameCandleCsv{}, &trader.Account{}, err
+	}
+
+	return df, account, nil
+}
+
 func Result(s *execute.SignalEvents) {
 
 	if s == nil || len(s.Signals) == 0 {
@@ -345,7 +369,7 @@ func Result(s *execute.SignalEvents) {
 
 	fmt.Println("🌟", name, "🌟")
 	fmt.Println("初期残高", initialBalance)
-	fmt.Println("最終残高", l, lr)
+	fmt.Println("最終残高", l, "USD", lr, "倍")
 
 	fmt.Println("勝率", analytics.WinRate(s)*100, "%")
 	fmt.Println("総利益", analytics.Profit(s))
@@ -374,4 +398,6 @@ func Result(s *execute.SignalEvents) {
 	// fmt.Println("バルサラの破産確率", analytics.BalsaraAxum(s))
 
 	// fmt.Println(s)
+
+	fmt.Println("--------------------------------------------")
 }

pkg/strategey/supertorend_choppy.go

@@ -2,18 +2,16 @@ package strategey
 
 import (
 	"fmt"
-	"log"
 	"runtime"
 	"sync"
 	"v1/pkg/analytics"
-	"v1/pkg/config"
 	"v1/pkg/execute"
 	"v1/pkg/indicator/indicators"
 	"v1/pkg/management/risk"
 	"v1/pkg/trader"
 )
 
-func (df *DataFrameCandle) SuperTrendChoppyStrategy(atrPeriod int, factor float64, choppy int, account *trader.Account) *execute.SignalEvents {
+func (df *DataFrameCandleCsv) SuperTrendChoppyStrategy(atrPeriod int, factor float64, choppy int, account *trader.Account) *execute.SignalEvents {
 
 	var StrategyName = "SUPERTREND_CHOPPY"
 	// var err error
@@ -81,7 +79,7 @@ func (df *DataFrameCandle) SuperTrendChoppyStrategy(atrPeriod int, factor float6
 	return signalEvents
 }
 
-func (df *DataFrameCandle) OptimizeSuperTrend() (performance float64, bestAtrPeriod int, bestFactor float64, bestChoppy int) {
+func (df *DataFrameCandleCsv) OptimizeSuperTrend() (performance float64, bestAtrPeriod int, bestFactor float64, bestChoppy int) {
 	runtime.GOMAXPROCS(10)
 	bestAtrPeriod = 21
 	bestFactor = 3.0
@@ -161,25 +159,7 @@ func (df *DataFrameCandle) OptimizeSuperTrend() (performance float64, bestAtrPer
 
 func RunBacktestSuperTrend() {
 
-	var err error
-
-	// account := trader.NewAccount(1000)
-	btcfg, err := config.Yaml()
-	if err != nil {
-		log.Fatalf("error: %v", err)
-	}
-
-	fmt.Println("--------------------------------------------")
-
-	// strategyName := getStrageyNameDonchain()
-	assetName := btcfg.AssetName
-	duration := btcfg.Dration
-
-	// limit := btcfg.Limit
-
-	account := trader.NewAccount(1000)
-
-	df, _ := GetCandleData(assetName, duration)
+	df, account, _ := RadyBacktest()
 
 	performance, bestAtrPeriod, bestFactor, bestChoppy := df.OptimizeSuperTrend()
 
@@ -191,3 +171,12 @@ func RunBacktestSuperTrend() {
 	}
 
 }
+
+func SuperTrendBacktest() {
+
+	df, account, _ := RadyBacktest()
+
+	df.Signal = df.SuperTrendChoppyStrategy(21, 3.0, 13, account)
+	Result(df.Signal)
+
+}