Files
nofx/store/position_query.go
T
tinkle-community cb31782be4 refactor: split large files and clean up project structure
- Rename experience/ to telemetry/ for clarity
- Split 15+ large Go files (800-2200 lines) into focused modules:
  kernel/engine.go, backtest/runner.go, market/data.go, store/position.go,
  api/handler_trader.go, trader/auto_trader_grid.go, and 9 exchange traders
- Split frontend monoliths: types.ts, api.ts, AITradersPage.tsx, BacktestPage.tsx
  into domain-specific modules with barrel re-exports
- Remove stale files: screenshots, .yml.old, pyproject.toml
- Remove unused scripts/ and cmd/ directories
- Remove broken/outdated test files (network-dependent, stale expectations)
2026-03-12 12:53:57 +08:00

407 lines
10 KiB
Go

package store
import (
"fmt"
"math"
"strings"
)
// TraderStats trading statistics metrics
type TraderStats struct {
TotalTrades int `json:"total_trades"`
WinTrades int `json:"win_trades"`
LossTrades int `json:"loss_trades"`
WinRate float64 `json:"win_rate"`
ProfitFactor float64 `json:"profit_factor"`
SharpeRatio float64 `json:"sharpe_ratio"`
TotalPnL float64 `json:"total_pnl"`
TotalFee float64 `json:"total_fee"`
AvgWin float64 `json:"avg_win"`
AvgLoss float64 `json:"avg_loss"`
MaxDrawdownPct float64 `json:"max_drawdown_pct"`
}
// GetPositionStats gets position statistics
func (s *PositionStore) GetPositionStats(traderID string) (map[string]interface{}, error) {
stats := make(map[string]interface{})
type result struct {
Total int
Wins int
TotalPnL float64
TotalFee float64
}
var r result
err := s.db.Model(&TraderPosition{}).
Select("COUNT(*) as total, SUM(CASE WHEN realized_pnl > 0 THEN 1 ELSE 0 END) as wins, COALESCE(SUM(realized_pnl), 0) as total_pnl, COALESCE(SUM(fee), 0) as total_fee").
Where("trader_id = ? AND status = ?", traderID, "CLOSED").
Scan(&r).Error
if err != nil {
return nil, err
}
stats["total_trades"] = r.Total
stats["win_trades"] = r.Wins
stats["total_pnl"] = r.TotalPnL
stats["total_fee"] = r.TotalFee
if r.Total > 0 {
stats["win_rate"] = float64(r.Wins) / float64(r.Total) * 100
} else {
stats["win_rate"] = 0.0
}
return stats, nil
}
// GetFullStats gets complete trading statistics
func (s *PositionStore) GetFullStats(traderID string) (*TraderStats, error) {
stats := &TraderStats{}
var count int64
if err := s.db.Model(&TraderPosition{}).Where("trader_id = ? AND status = ?", traderID, "CLOSED").Count(&count).Error; err != nil {
return nil, err
}
if count == 0 {
return stats, nil
}
var positions []TraderPosition
err := s.db.Where("trader_id = ? AND status = ?", traderID, "CLOSED").
Order("exit_time ASC").
Find(&positions).Error
if err != nil {
return nil, fmt.Errorf("failed to query position statistics: %w", err)
}
var pnls []float64
var totalWin, totalLoss float64
for _, pos := range positions {
stats.TotalTrades++
stats.TotalPnL += pos.RealizedPnL
stats.TotalFee += pos.Fee
pnls = append(pnls, pos.RealizedPnL)
if pos.RealizedPnL > 0 {
stats.WinTrades++
totalWin += pos.RealizedPnL
} else if pos.RealizedPnL < 0 {
stats.LossTrades++
totalLoss += -pos.RealizedPnL
}
}
if stats.TotalTrades > 0 {
stats.WinRate = float64(stats.WinTrades) / float64(stats.TotalTrades) * 100
}
if totalLoss > 0 {
stats.ProfitFactor = totalWin / totalLoss
}
if stats.WinTrades > 0 {
stats.AvgWin = totalWin / float64(stats.WinTrades)
}
if stats.LossTrades > 0 {
stats.AvgLoss = totalLoss / float64(stats.LossTrades)
}
if len(pnls) > 1 {
stats.SharpeRatio = calculateSharpeRatioFromPnls(pnls)
}
if len(pnls) > 0 {
stats.MaxDrawdownPct = calculateMaxDrawdownFromPnls(pnls)
}
return stats, nil
}
// RecentTrade recent trade record
type RecentTrade struct {
Symbol string `json:"symbol"`
Side string `json:"side"`
EntryPrice float64 `json:"entry_price"`
ExitPrice float64 `json:"exit_price"`
RealizedPnL float64 `json:"realized_pnl"`
PnLPct float64 `json:"pnl_pct"`
EntryTime int64 `json:"entry_time"`
ExitTime int64 `json:"exit_time"`
HoldDuration string `json:"hold_duration"`
}
// GetRecentTrades gets recent closed trades
func (s *PositionStore) GetRecentTrades(traderID string, limit int) ([]RecentTrade, error) {
var positions []TraderPosition
err := s.db.Where("trader_id = ? AND status = ?", traderID, "CLOSED").
Order("exit_time DESC").
Limit(limit).
Find(&positions).Error
if err != nil {
return nil, fmt.Errorf("failed to query recent trades: %w", err)
}
var trades []RecentTrade
for _, pos := range positions {
t := RecentTrade{
Symbol: pos.Symbol,
Side: strings.ToLower(pos.Side),
EntryPrice: pos.EntryPrice,
ExitPrice: pos.ExitPrice,
RealizedPnL: pos.RealizedPnL,
EntryTime: pos.EntryTime / 1000, // Convert ms to seconds for API compatibility
}
if pos.ExitTime > 0 {
t.ExitTime = pos.ExitTime / 1000 // Convert ms to seconds
durationMs := pos.ExitTime - pos.EntryTime
t.HoldDuration = formatDurationMs(durationMs)
}
if pos.EntryPrice > 0 {
if t.Side == "long" {
t.PnLPct = (pos.ExitPrice - pos.EntryPrice) / pos.EntryPrice * 100 * float64(pos.Leverage)
} else {
t.PnLPct = (pos.EntryPrice - pos.ExitPrice) / pos.EntryPrice * 100 * float64(pos.Leverage)
}
}
trades = append(trades, t)
}
return trades, nil
}
// calculateSharpeRatioFromPnls calculates Sharpe ratio
func calculateSharpeRatioFromPnls(pnls []float64) float64 {
if len(pnls) < 2 {
return 0
}
var sum float64
for _, pnl := range pnls {
sum += pnl
}
mean := sum / float64(len(pnls))
var variance float64
for _, pnl := range pnls {
variance += (pnl - mean) * (pnl - mean)
}
stdDev := math.Sqrt(variance / float64(len(pnls)-1))
if stdDev == 0 {
return 0
}
return mean / stdDev
}
// calculateMaxDrawdownFromPnls calculates maximum drawdown
func calculateMaxDrawdownFromPnls(pnls []float64) float64 {
if len(pnls) == 0 {
return 0
}
const startingEquity = 10000.0
equity := startingEquity
peak := startingEquity
var maxDD float64
for _, pnl := range pnls {
equity += pnl
if equity > peak {
peak = equity
}
if peak > 0 {
dd := (peak - equity) / peak * 100
if dd > maxDD {
maxDD = dd
}
}
}
return maxDD
}
// SymbolStats per-symbol trading statistics
type SymbolStats struct {
Symbol string `json:"symbol"`
TotalTrades int `json:"total_trades"`
WinTrades int `json:"win_trades"`
WinRate float64 `json:"win_rate"`
TotalPnL float64 `json:"total_pnl"`
AvgPnL float64 `json:"avg_pnl"`
AvgHoldMins float64 `json:"avg_hold_mins"`
}
// GetSymbolStats gets per-symbol trading statistics
func (s *PositionStore) GetSymbolStats(traderID string, limit int) ([]SymbolStats, error) {
var positions []TraderPosition
err := s.db.Where("trader_id = ? AND status = ?", traderID, "CLOSED").Find(&positions).Error
if err != nil {
return nil, fmt.Errorf("failed to query symbol stats: %w", err)
}
// Group by symbol
symbolMap := make(map[string]*SymbolStats)
symbolHoldMins := make(map[string][]float64)
for _, pos := range positions {
if _, ok := symbolMap[pos.Symbol]; !ok {
symbolMap[pos.Symbol] = &SymbolStats{Symbol: pos.Symbol}
symbolHoldMins[pos.Symbol] = []float64{}
}
s := symbolMap[pos.Symbol]
s.TotalTrades++
s.TotalPnL += pos.RealizedPnL
if pos.RealizedPnL > 0 {
s.WinTrades++
}
if pos.ExitTime > 0 {
holdMins := float64(pos.ExitTime-pos.EntryTime) / 60000.0 // ms to minutes
symbolHoldMins[pos.Symbol] = append(symbolHoldMins[pos.Symbol], holdMins)
}
}
var stats []SymbolStats
for symbol, s := range symbolMap {
if s.TotalTrades > 0 {
s.WinRate = float64(s.WinTrades) / float64(s.TotalTrades) * 100
s.AvgPnL = s.TotalPnL / float64(s.TotalTrades)
}
if len(symbolHoldMins[symbol]) > 0 {
var totalMins float64
for _, m := range symbolHoldMins[symbol] {
totalMins += m
}
s.AvgHoldMins = totalMins / float64(len(symbolHoldMins[symbol]))
}
stats = append(stats, *s)
}
// Sort by TotalPnL descending and limit
for i := 0; i < len(stats)-1; i++ {
for j := i + 1; j < len(stats); j++ {
if stats[j].TotalPnL > stats[i].TotalPnL {
stats[i], stats[j] = stats[j], stats[i]
}
}
}
if limit > 0 && len(stats) > limit {
stats = stats[:limit]
}
return stats, nil
}
// HoldingTimeStats holding duration analysis
type HoldingTimeStats struct {
Range string `json:"range"`
TradeCount int `json:"trade_count"`
WinRate float64 `json:"win_rate"`
AvgPnL float64 `json:"avg_pnl"`
}
// GetHoldingTimeStats analyzes performance by holding duration
func (s *PositionStore) GetHoldingTimeStats(traderID string) ([]HoldingTimeStats, error) {
var positions []TraderPosition
err := s.db.Where("trader_id = ? AND status = ? AND exit_time > 0", traderID, "CLOSED").Find(&positions).Error
if err != nil {
return nil, fmt.Errorf("failed to query holding time stats: %w", err)
}
rangeStats := map[string]*struct {
count int
wins int
totalPnL float64
}{
"<1h": {},
"1-4h": {},
"4-24h": {},
">24h": {},
}
for _, pos := range positions {
if pos.ExitTime == 0 {
continue
}
holdHours := float64(pos.ExitTime-pos.EntryTime) / 3600000.0 // ms to hours
var rangeKey string
switch {
case holdHours < 1:
rangeKey = "<1h"
case holdHours < 4:
rangeKey = "1-4h"
case holdHours < 24:
rangeKey = "4-24h"
default:
rangeKey = ">24h"
}
r := rangeStats[rangeKey]
r.count++
r.totalPnL += pos.RealizedPnL
if pos.RealizedPnL > 0 {
r.wins++
}
}
var stats []HoldingTimeStats
for _, rangeKey := range []string{"<1h", "1-4h", "4-24h", ">24h"} {
r := rangeStats[rangeKey]
if r.count > 0 {
stats = append(stats, HoldingTimeStats{
Range: rangeKey,
TradeCount: r.count,
WinRate: float64(r.wins) / float64(r.count) * 100,
AvgPnL: r.totalPnL / float64(r.count),
})
}
}
return stats, nil
}
// DirectionStats long/short performance comparison
type DirectionStats struct {
Side string `json:"side"`
TradeCount int `json:"trade_count"`
WinRate float64 `json:"win_rate"`
TotalPnL float64 `json:"total_pnl"`
AvgPnL float64 `json:"avg_pnl"`
}
// GetDirectionStats analyzes long vs short performance
func (s *PositionStore) GetDirectionStats(traderID string) ([]DirectionStats, error) {
var positions []TraderPosition
err := s.db.Where("trader_id = ? AND status = ?", traderID, "CLOSED").Find(&positions).Error
if err != nil {
return nil, fmt.Errorf("failed to query direction stats: %w", err)
}
sideStats := make(map[string]*DirectionStats)
for _, pos := range positions {
if _, ok := sideStats[pos.Side]; !ok {
sideStats[pos.Side] = &DirectionStats{Side: pos.Side}
}
s := sideStats[pos.Side]
s.TradeCount++
s.TotalPnL += pos.RealizedPnL
if pos.RealizedPnL > 0 {
s.WinRate++
}
}
var stats []DirectionStats
for _, s := range sideStats {
if s.TradeCount > 0 {
s.AvgPnL = s.TotalPnL / float64(s.TradeCount)
s.WinRate = s.WinRate / float64(s.TradeCount) * 100
}
stats = append(stats, *s)
}
return stats, nil
}