ソルティノレシオの追加､その他リファクタリング

cmd/main.go

@@ -6,6 +6,7 @@ import (
 	"net/http"
 	"time"
 	chart "v1/pkg/charts"
+	data "v1/pkg/data/utils"
 	// "v1/pkg/analytics/metrics"
 	// "v1/pkg/db/models"
 	// p "v1/pkg/management/position"
@@ -147,32 +148,32 @@ func main() {
 	// query.GetCloseData("BTCUSDT", "4h")
 
 	//DBにデータを追加するための関数
-	// var assets_names []string = []string{"RUNEUSDT", "BTCUSDT", "AAVEUSDT", "ORDIUSDT", "SANUSDT", "LTCUSDT", "OKBUSDT", "ASTRUSDT", "MNTUSDT", "FTMUSDT", "SNXUSDT", "DYDXUSDT", "BONKUSDT", "LUNAUSDT", "MAGICUSDT", "XLMUSDT", "DOGEUSDT", "TRSUSDT", "LINKUSDT", "TONUSDT", "ISPUSDT", "BONKUSDT", "GMXUSDT", "INJUSDT", "ETHUSDT", "SOLUSDT", "AVAXUSDT", "MATICUSDT", "ATOMUSDT", "UNIUSDT", "ARBUSDT", "OPUSDT", "PEPEUSDT", "SEIUSDT", "SUIUSDT", "TIAUSDT", "WLDUSDT", "XRPUSDT", "NEARUSDT", "DOTUSDT", "APTUSDT", "XMRUSDT", "LDOUSDT", "FILUSDT", "KASUSDT", "STXUSDT", "RNDRUSDT", "GRTUSDT"}
-
-	// var durations []string = []string{"1m", "3m", "5m", "15m", "30m", "1h", "2h", "4h", "6h", "8h", "12h"}
-	// paths := data.GetRelativePaths()
-
-	// groupedPaths := data.GroupAssetNamePaths(paths)
-
-	// asset_data, err := data.LoadOHLCV(groupedPaths, assets_names, durations)
-	// if err != nil {
-	// 	log.Fatalf("Error loading OHLCV data: %v", err)
-	// }
-
-	// // // data.SaveAssetDatasCSV(asset_data)
-
-	// // DBに接続する関数を呼び出し
-	// db, err := data.ConnectDB("./db/kline.db")
-	// if err != nil {
-	// 	log.Fatal(err)
-	// }
-	// // DBをクローズするのを遅延実行
-	// defer db.Close()
-	// // データをDBに保存する関数を呼び出し
-	// err = data.SaveAssetDatasDB(db, asset_data)
-	// if err != nil {
-	// 	log.Fatal(err)
-	// }
+	var assets_names []string = []string{"RUNEUSDT", "BTCUSDT", "AAVEUSDT", "ORDIUSDT", "SANUSDT", "LTCUSDT", "OKBUSDT", "ASTRUSDT", "MNTUSDT", "FTMUSDT", "SNXUSDT", "DYDXUSDT", "BONKUSDT", "LUNAUSDT", "MAGICUSDT", "XLMUSDT", "DOGEUSDT", "TRSUSDT", "LINKUSDT", "TONUSDT", "ISPUSDT", "BONKUSDT", "GMXUSDT", "INJUSDT", "ETHUSDT", "SOLUSDT", "AVAXUSDT", "MATICUSDT", "ATOMUSDT", "UNIUSDT", "ARBUSDT", "OPUSDT", "PEPEUSDT", "SEIUSDT", "SUIUSDT", "TIAUSDT", "WLDUSDT", "XRPUSDT", "NEARUSDT", "DOTUSDT", "APTUSDT", "XMRUSDT", "LDOUSDT", "FILUSDT", "KASUSDT", "STXUSDT", "RNDRUSDT", "GRTUSDT"}
+
+	var durations []string = []string{"1m", "3m", "5m", "15m", "30m", "1h", "2h", "4h", "6h", "8h", "12h"}
+	paths := data.GetRelativePaths()
+
+	groupedPaths := data.GroupAssetNamePaths(paths)
+
+	asset_data, err := data.LoadOHLCV(groupedPaths, assets_names, durations)
+	if err != nil {
+		log.Fatalf("Error loading OHLCV data: %v", err)
+	}
+
+	// // data.SaveAssetDatasCSV(asset_data)
+
+	// DBに接続する関数を呼び出し
+	db, err := data.ConnectDB("./db/kline.db")
+	if err != nil {
+		log.Fatal(err)
+	}
+	// DBをクローズするのを遅延実行
+	defer db.Close()
+	// データをDBに保存する関数を呼び出し
+	err = data.SaveAssetDatasDB(db, asset_data)
+	if err != nil {
+		log.Fatal(err)
+	}
 	//ここまで
 
 	// for key, paths := range groupedPaths {

config.yml

@@ -2,7 +2,7 @@
 
 
 #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"
-start: "2021-04"
-end: "2022-011"
+assetName: "BTCUSDT"
+duration: "5m"
+start: "20220101"
+end: "20220109"

main.go

@@ -10,10 +10,20 @@ func main() {
 
 	start := time.Now()
 
-	strategey.RunEmaOptimize()
-	// strategey.RunBacktestDonchainChoppy()
-	// strategey.RunBacktestSuperTrend()
+	// strategey.RunEmaOptimize()
+	// strategey.RunSTOptimize()
+	// strategey.RunDonchainOptimize()
 
+	// strategey.DonchainBacktest()
+	// strategey.SuperTrendBacktest()
+	// strategey.EmaBacktest()
+	// strategey.RunBacktestST()
+	// strategey.RunRsi2Optimize()
+
+	strategey.RunBacktestMacd()
+
+	// strategey.RunBacktestMacd()
+	// strategey.EmaBacktest()
 	// assetName := "TIAUSDT"
 	// duration := "4h"
 

pkg/analytics/calc_total_trade.go

@@ -196,3 +196,55 @@ func AverageLosingHoldingBars(s *execute.SignalEvents) float64 {
 	}
 	return float64(totalBars) / float64(losingTrades)
 }
+
+func MaxWinCount(s *execute.SignalEvents) int {
+	if s == nil {
+		return 0
+	}
+	var maxWinStreak, winStreak int
+	var buyPrice float64
+
+	for _, signal := range s.Signals {
+		if signal.Side == "BUY" {
+			buyPrice = signal.Price
+		} else if signal.Side == "SELL" && buyPrice != 0 {
+			if signal.Price > buyPrice {
+				winStreak++
+				if winStreak > maxWinStreak {
+					maxWinStreak = winStreak
+				}
+			} else {
+				winStreak = 0
+			}
+			buyPrice = 0 // Reset buy price after a sell
+		}
+	}
+
+	return maxWinStreak
+}
+
+func MaxLoseCount(s *execute.SignalEvents) int {
+	if s == nil {
+		return 0
+	}
+	var maxLoseStreak, loseStreak int
+	var buyPrice float64
+
+	for _, signal := range s.Signals {
+		if signal.Side == "BUY" {
+			buyPrice = signal.Price
+		} else if signal.Side == "SELL" && buyPrice != 0 {
+			if signal.Price < buyPrice {
+				loseStreak++
+				if loseStreak > maxLoseStreak {
+					maxLoseStreak = loseStreak
+				}
+			} else {
+				loseStreak = 0
+			}
+			buyPrice = 0 // Reset buy price after a sell
+		}
+	}
+
+	return maxLoseStreak
+}

pkg/analytics/sharp_ratio.go

@@ -63,3 +63,38 @@ func SharpeRatio(s *execute.SignalEvents, riskFreeRate float64) float64 {
 
 	return sharpeRatio
 }
+
+func downsideDeviation(data []float64, target float64) float64 {
+	var sqDiffSum float64
+	for _, value := range data {
+		diff := math.Min(value-target, 0) // Only consider negative deviations
+		sqDiffSum += diff * diff
+	}
+	variance := sqDiffSum / float64(len(data))
+	return math.Sqrt(variance)
+}
+
+// Modified function to calculate the Sortino Ratio
+func SortinoRatio(s *execute.SignalEvents, riskFreeRate float64) float64 {
+
+	if s == nil {
+		return 0.0
+	}
+	// Calculate the returns
+	returns := calculateReturns(s)
+
+	// Calculate the excess returns
+	excessReturns := make([]float64, len(returns))
+	for i, ret := range returns {
+		excessReturns[i] = ret - riskFreeRate
+	}
+
+	// Calculate the mean and downside deviation of the excess returns
+	meanExcessReturn := mean(excessReturns)
+	downsideDeviationExcessReturn := downsideDeviation(excessReturns, 0)
+
+	// Calculate the Sortino Ratio
+	sortinoRatio := meanExcessReturn / downsideDeviationExcessReturn
+
+	return sortinoRatio
+}

pkg/charts/candle_chart.go

@@ -406,7 +406,7 @@ func klineWithChoppy() *charts.Kline {
 		lowdata[i] = k.data[2]
 		closedata[i] = k.data[1]
 	}
-	index := risk.ChoppySlice(closedata, highdata, lowdata)
+	index := risk.ChoppySlice(70, closedata, highdata, lowdata)
 	choppyEma13 := risk.ChoppyEma(index, 13)
 
 	choppyIndex := make([]opts.LineData, len(index))

pkg/management/risk/market_index.go

@@ -22,27 +22,27 @@ func ChoppyMarketIndex(close []float64, high []float64, low []float64) float64 {
 	return index
 }
 
-func ChoppySlice(close []float64, high []float64, low []float64) []float64 {
+func ChoppySlice(d int, close []float64, high []float64, low []float64) []float64 {
 
-	if len(close) < 30 || len(high) < 30 || len(low) < 30 {
+	if len(close) < d || len(high) < d || len(low) < d {
 		return nil
 	}
 
 	var choppySlice []float64
 
 	for i := 1; i < len(close); i++ {
 
-		if i < 30 {
+		if i < d {
 			continue
 		}
 
 		// iが30以上のときだけChoppyIndexの計算を行う
 
 		// 現在の終値と30日前の終値の差の絶対値を計算する
-		direction := math.Abs(close[i] - close[i-30])
+		direction := math.Abs(close[i] - close[i-d])
 
 		// 過去30日間の最高値と最安値の差を計算する
-		volatility := Max(high[len(high)-30:]) - Min(low[len(low)-30:])
+		volatility := Max(high[len(high)-d:]) - Min(low[len(low)-d:])
 
 		// 市場の方向性とボラティリティのバランスを計算する
 		choppySlice = append(choppySlice, direction/volatility*100.0)

pkg/strategey/bb.go

@@ -2,21 +2,15 @@ package strategey
 
 import (
 	"fmt"
-	"log"
 	"runtime"
 	"sync"
 	"v1/pkg/analytics"
-	"v1/pkg/config"
 	"v1/pkg/execute"
 	"v1/pkg/trader"
 
 	"github.com/markcheno/go-talib"
 )
 
-func getStrageyNameBb() string {
-	return "BB"
-}
-
 func (df *DataFrameCandle) BbStrategy(n int, k float64, account *trader.Account) *execute.SignalEvents {
 
 	var StrategyName = "BB"
@@ -57,9 +51,9 @@ func (df *DataFrameCandle) OptimizeBbGoroutin() (performance float64, bestN int,
 	bestN = 20
 	bestK = 2.0
 
-	a := trader.NewAccount(1000)
+	// a := trader.NewAccount(1000)
 
-	marketDefault, _ := BuyAndHoldingStrategy(a)
+	// marketDefault, _ := BuyAndHoldingStrategy(a)
 	var mu sync.Mutex
 	var wg sync.WaitGroup
 
@@ -80,9 +74,9 @@ func (df *DataFrameCandle) OptimizeBbGoroutin() (performance float64, bestN int,
 					return
 				}
 
-				if analytics.NetProfit(signalEvents) < marketDefault {
-					return
-				}
+				// if analytics.NetProfit(signalEvents) < marketDefault {
+				// 	return
+				// }
 
 				// if analytics.WinRate(signalEvents) < 0.50 {
 				// 	return
@@ -114,23 +108,7 @@ func (df *DataFrameCandle) OptimizeBbGoroutin() (performance float64, bestN int,
 }
 func RunBacktestBb() {
 
-	var err error
-
-	// account := trader.NewAccount(1000)
-	btcfg, err := config.Yaml()
-	if err != nil {
-		log.Fatalf("error: %v", err)
-	}
-
-	fmt.Println(btcfg.AssetName)
-
-	assetName := btcfg.AssetName
-	duration := btcfg.Dration
-	// limit := btcfg.Limit
-
-	account := trader.NewAccount(1000)
-
-	df, _ := GetCandleData(assetName, duration)
+	df, account, _ := RadyBacktest()
 
 	performance, bestN, bestK := df.OptimizeBbGoroutin()
 

pkg/strategey/donchain.go

@@ -15,7 +15,7 @@ import (
 // 	return "DBO"
 // }
 
-func (df *DataFrameCandleCsv) DonchainStrategy(period int, account *trader.Account) *execute.SignalEvents {
+func (df *DataFrameCandle) DonchainStrategy(period int, account *trader.Account) *execute.SignalEvents {
 	var StrategyName = "DBO"
 
 	lenCandles := len(df.Candles)
@@ -63,7 +63,7 @@ func (df *DataFrameCandleCsv) DonchainStrategy(period int, account *trader.Accou
 	return signalEvents
 
 }
-func (df *DataFrameCandleCsv) OptimizeDonchainGoroutin() (performance float64, bestPeriod int) {
+func (df *DataFrameCandle) OptimizeDonchainGoroutin() (performance float64, bestPeriod int) {
 
 	bestPeriod = 40
 	var mu sync.Mutex