Display stats on returns

backtesting.go

@@ -12,6 +12,7 @@ import (
 	"github.com/go-echarts/go-echarts/v2/components"
 	"github.com/go-echarts/go-echarts/v2/opts"
 	"golang.org/x/exp/rand"
+	"golang.org/x/exp/slices"
 )
 
 var (
@@ -23,6 +24,7 @@ var (
 func Backtest(trader *Trader) {
 	switch broker := trader.Broker.(type) {
 	case *TestBroker:
+		rand.Seed(uint64(time.Now().UnixNano()))
 		trader.Init() // Initialize the trader and strategy.
 		start := time.Now()
 		for !trader.EOF {
@@ -30,20 +32,81 @@ func Backtest(trader *Trader) {
 			broker.Advance() // Give the trader access to the next candlestick.
 		}
 		log.Println("Backtest complete. Opening report...")
+		stats := trader.Stats()
 
 		page := components.NewPage()
 
-		// Create a new line chart based on account equity and add it to the page.
-		chart := charts.NewLine()
-		chart.SetGlobalOptions(charts.WithTitleOpts(opts.Title{
-			Title:    fmt.Sprintf("Backtest (%s)", time.Now().Format(time.DateTime)),
-			Subtitle: fmt.Sprintf("%s %s %T  (took %.2f seconds)", trader.Symbol, trader.Frequency, trader.Strategy, time.Since(start).Seconds()),
+		// Create a new line balChart based on account equity and add it to the page.
+		balChart := charts.NewLine()
+		balChart.SetGlobalOptions(charts.WithTitleOpts(opts.Title{
+			Title:    "Balance",
+			Subtitle: fmt.Sprintf("%s %s %T  (took %.2f seconds) %s", trader.Symbol, trader.Frequency, trader.Strategy, time.Since(start).Seconds(), time.Now().Format(time.DateTime)),
 		}))
-		chart.SetXAxis(seriesStringArray(trader.Stats().Dates())).
-			AddSeries("Equity", lineDataFromSeries(trader.Stats().Series("Equity"))).
-			AddSeries("Drawdown", lineDataFromSeries(trader.Stats().Series("Drawdown")))
+		balChart.SetXAxis(seriesStringArray(stats.Dated.Dates())).
+			AddSeries("Equity", lineDataFromSeries(stats.Dated.Series("Equity"))).
+			AddSeries("Drawdown", lineDataFromSeries(stats.Dated.Series("Drawdown")))
 
-		page.AddCharts(chart)
+		// Sort Returns by value.
+		// Plot returns as a bar chart.
+		returnsSeries := stats.Dated.Series("Returns")
+		returns := make([]float64, 0, returnsSeries.Len())
+		// returns := stats.Dated.Series("Returns").Values()
+		// Remove nil values.
+		for i := 0; i < returnsSeries.Len(); i++ {
+			r := returnsSeries.Value(i)
+			if r != nil {
+				returns = append(returns, r.(float64))
+			}
+		}
+		// Sort the returns.
+		slices.Sort(returns)
+		// Create the X axis labels for the returns chart based on length of the returns slice.
+		returnsLabels := make([]int, len(returns))
+		for i := range returns {
+			returnsLabels[i] = i + 1
+		}
+		returnsBars := make([]opts.BarData, len(returns))
+		for i, r := range returns {
+			returnsBars[i] = opts.BarData{Value: r}
+			if r < 0 {
+				log.Println("Negative return:", r, "at index", i)
+			}
+		}
+		var avg float64
+		for _, r := range returns {
+			avg += r
+		}
+		avg /= float64(len(returns))
+		returnsAverage := make([]opts.LineData, len(returns))
+		for i := range returnsAverage {
+			returnsAverage[i] = opts.LineData{Value: avg}
+		}
+
+		returnsChart := charts.NewBar()
+		returnsChart.SetGlobalOptions(charts.WithTitleOpts(opts.Title{
+			Title:    "Returns",
+			Subtitle: fmt.Sprintf("Average: $%.2f", avg),
+		}))
+		returnsChart.SetXAxis(returnsLabels).
+			AddSeries("Returns", returnsBars)
+
+		returnsChartAvg := charts.NewLine()
+		returnsChartAvg.SetGlobalOptions(charts.WithTitleOpts(opts.Title{
+			Title: "Average Returns",
+		}))
+		returnsChartAvg.SetXAxis(returnsLabels).
+			AddSeries("Average", returnsAverage, func(s *charts.SingleSeries) {
+				s.LineStyle = &opts.LineStyle{
+					Width: 2,
+				}
+			})
+		returnsChart.Overlap(returnsChartAvg)
+
+		// TODO: Use Radar to display performance metrics.
+
+		// Add all the charts in the desired order.
+		page.PageTitle = "Backtest Report"
+		page.AddCharts(balChart, returnsChart)
 
 		// Draw the page to a file.
 		f, err := os.Create("backtest.html")
@@ -62,7 +125,21 @@ func Backtest(trader *Trader) {
 	}
 }
 
+func barDataFromSeries(s Series) []opts.BarData {
+	if s == nil || s.Len() == 0 {
+		return []opts.BarData{}
+	}
+	data := make([]opts.BarData, s.Len())
+	for i := 0; i < s.Len(); i++ {
+		data[i] = opts.BarData{Value: s.Value(i)}
+	}
+	return data
+}
+
 func lineDataFromSeries(s Series) []opts.LineData {
+	if s == nil || s.Len() == 0 {
+		return []opts.LineData{}
+	}
 	data := make([]opts.LineData, s.Len())
 	for i := 0; i < s.Len(); i++ {
 		data[i] = opts.LineData{Value: s.Value(i)}
@@ -280,6 +357,7 @@ func (p *TestPosition) Close() error {
 	p.closed = true
 	p.closePrice = p.broker.Data.Close(p.broker.CandleIndex()) - p.broker.Spread // Get the last close price.
 	p.broker.Cash += p.Value()                                                   // Return the value of the position to the broker.
+	p.broker.SignalEmit("PositionClosed", p)
 	return nil
 }
 

broker.go

@@ -52,7 +52,11 @@ type Position interface {
 	Value() float64      // Value returns the value of the position at the current price.
 }
 
+// Broker is an interface that defines the methods that a broker must implement to report symbol data and place orders, etc. All Broker implementations must also implement the Signaler interface and emit the following functions when necessary:
+//
+//   - PositionClosed(Position) - Emitted after a position is closed either manually or automatically.
 type Broker interface {
+	Signaler
 	// Candles returns a dataframe of candles for the given symbol, frequency, and count by querying the broker.
 	Candles(symbol string, frequency string, count int) (*DataFrame, error)
 	MarketOrder(symbol string, units float64, stopLoss, takeProfit float64) (Order, error)

cmd/sma_crossover.go

@@ -15,18 +15,13 @@ func (s *SMAStrategy) Next(t *auto.Trader) {
 	sma1 := t.Data().Closes().Rolling(s.period1).Mean()
 	sma2 := t.Data().Closes().Rolling(s.period2).Mean()
 	// If the shorter SMA crosses above the longer SMA, buy.
-	if crossover(sma1, sma2) {
+	if auto.Crossover(sma1, sma2) {
 		t.Buy(1000)
-	} else if crossover(sma2, sma1) {
+	} else if auto.Crossover(sma2, sma1) {
 		t.Sell(1000)
 	}
 }
 
-// crossover returns true if s1 crosses above s2 at the latest float.
-func crossover(s1, s2 auto.Series) bool {
-	return s1.Float(-1) > s2.Float(-1) && s1.Float(-2) <= s2.Float(-2)
-}
-
 func main() {
 	data, err := auto.EURUSD()
 	if err != nil {

data.go

@@ -35,6 +35,7 @@ type Series interface {
 
 	// Writing data.
 	SetName(name string) Series
+	SetValue(i int, val interface{}) Series
 	Push(val interface{}) Series
 
 	// Statistical functions.
@@ -321,6 +322,13 @@ func (s *DataSeries) Push(value interface{}) Series {
 	return s
 }
 
+func (s *DataSeries) SetValue(i int, val interface{}) Series {
+	if s.data != nil {
+		s.data.Update(EasyIndex(i, s.Len()), val)
+	}
+	return s
+}
+
 func (s *DataSeries) Value(i int) interface{} {
 	if s.data == nil {
 		return nil
@@ -335,10 +343,11 @@ func (s *DataSeries) ValueRange(start, end int) []interface{} {
 		return nil
 	}
 	start = EasyIndex(start, s.Len())
+	if end < 0 {
+		end = s.Len() - 1
+	}
 	if start < 0 || start >= s.Len() || end >= s.Len() || start > end {
 		return nil
-	} else if end < 0 {
-		end = s.Len() - 1
 	}
 
 	items := make([]interface{}, end-start+1)

trader.go

@@ -12,6 +12,12 @@ import (
 	"github.com/rocketlaunchr/dataframe-go"
 )
 
+// Performance (financial) reporting and statistics.
+type TraderStats struct {
+	Dated             *DataFrame
+	returnsThisCandle float64
+}
+
 // Trader acts as the primary interface to the broker and strategy. To the strategy, it provides all the information
 // about the current state of the market and the portfolio. To the broker, it provides the orders to be executed and
 // requests for the current state of the portfolio.
@@ -26,14 +32,14 @@ type Trader struct {
 
 	data  *DataFrame
 	sched *gocron.Scheduler
-	stats *DataFrame // Performance (financial) reporting and statistics.
+	stats *TraderStats
 }
 
 func (t *Trader) Data() *DataFrame {
 	return t.data
 }
 
-func (t *Trader) Stats() *DataFrame {
+func (t *Trader) Stats() *TraderStats {
 	return t.stats
 }
 
@@ -79,11 +85,16 @@ func (t *Trader) Run() {
 
 func (t *Trader) Init() {
 	t.Strategy.Init(t)
-	t.stats = NewDataFrame(
+	t.stats.Dated = NewDataFrame(
 		NewDataSeries(dataframe.NewSeriesTime("Date", nil)),
 		NewDataSeries(dataframe.NewSeriesFloat64("Equity", nil)),
 		NewDataSeries(dataframe.NewSeriesFloat64("Drawdown", nil)),
+		NewDataSeries(dataframe.NewSeriesFloat64("Returns", nil)),
 	)
+	t.Broker.SignalConnect("PositionClosed", func(args ...interface{}) {
+		position := args[0].(Position)
+		t.stats.returnsThisCandle += position.PL()
+	})
 }
 
 // Tick updates the current state of the market and runs the strategy.
@@ -93,19 +104,27 @@ func (t *Trader) Tick() {
 	t.Strategy.Next(t) // Run the strategy.
 
 	// Update the stats.
-	t.stats.PushValues(map[string]interface{}{
+	t.stats.Dated.PushValues(map[string]interface{}{
 		"Date":   t.data.Date(-1),
 		"Equity": t.Broker.NAV(),
 		"Drawdown": func() float64 {
 			var bal float64
-			if t.stats.Len() > 0 {
-				bal = t.stats.Float("Equity", 0) // Take starting balance
+			if t.stats.Dated.Len() > 0 {
+				bal = t.stats.Dated.Float("Equity", 0) // Take starting balance
 			} else {
-				bal = t.Broker.NAV()
+				bal = t.Broker.NAV() // Take current balance for first value
 			}
 			return Max(bal-t.Broker.NAV(), 0)
 		}(),
+		"Returns": func() interface{} {
+			if t.stats.returnsThisCandle != 0 {
+				return t.stats.returnsThisCandle
+			} else {
+				return nil
+			}
+		}(),
 	})
+	t.stats.returnsThisCandle = 0
 }
 
 func (t *Trader) fetchData() {
@@ -165,6 +184,6 @@ func NewTrader(config TraderConfig) *Trader {
 		Frequency:     config.Frequency,
 		CandlesToKeep: config.CandlesToKeep,
 		Log:           logger,
-		stats:         NewDataFrame(),
+		stats:         &TraderStats{},
 	}
 }

utils.go

@@ -9,6 +9,11 @@ import (
 
 const floatComparisonTolerance = float64(1e-6)
 
+// Crossover returns true if the latest a value crosses above the latest b value, but only if it just happened. For example, if a series is [1, 2, 3, 4, 5] and b series is [1, 2, 3, 4, 3], then Crossover(a, b) returns false because the latest a value is 5 and the latest b value is 3. However, if a series is [1, 2, 3, 4, 5] and b series is [1, 2, 3, 4, 6], then Crossover(a, b) returns true because the latest a value is 5 and the latest b value is 6
+func Crossover(a, b Series) bool {
+	return a.Float(-1) > b.Float(-1) && a.Float(-2) <= b.Float(-2)
+}
+
 // EasyIndex returns an index to the `n` -length object that allows for negative indexing. For example, EasyIndex(-1, 5) returns 4. This is similar to Python's negative indexing. The return value may be less than zero if (-i) > n.
 func EasyIndex(i, n int) int {
 	if i < 0 {