sig-pub/internal/trading/backtest/account.go

package backtest

import (
	"fmt"
	"math"
	"sig-pub/pkg/trade"
	"sig-pub/pkg/types"
	"sig-pub/pkg/types/decimals"
	"sig-pub/pkg/utils/conver"
	"sig-pub/pkg/utils/lang"
	"sort"
	"time"
)

type BacktestAccount struct {
	trade.ITradeAccount
	cash        float64
	initialCash float64
	positions   map[int64]*trade.Position
	trades      map[int64]*Trade
	closeTrades map[int64]*Trade
	simulator   *TradeSimulator

	profit        float64
	winningTrades int
	losingTrades  int
	fee           float64
	maxDrawdown   [4]float64 // 最大回撤
}

func NewBacktestAccount(cash float64, simulator *TradeSimulator) *BacktestAccount {
	return &BacktestAccount{
		// keep initial cash for return calculations
		initialCash: cash,
		cash:        cash,
		positions:   make(map[int64]*trade.Position),
		trades:      make(map[int64]*Trade),
		closeTrades: make(map[int64]*Trade),
		simulator:   simulator,
		maxDrawdown: [4]float64{cash, cash, cash, cash},
	}
}

// initialCash stores the starting capital for return calculations
// (placed here to avoid changing exported API)
func (a *BacktestAccount) InitialCash() float64 { return a.initialCash }

// SharpeRatio computes an annualized Sharpe ratio based on closed trades.
// rfAnnual is the annual risk-free rate expressed as a decimal (e.g. 0.01 for 1%).
// Method:
// - For each closed trade, we compute a period return = trade.Pnl / initialCash.
// - Period lengths are derived from successive trade close timestamps (ms).
// - Excess returns = periodReturn - rfAnnual * periodYears.
// - Sharpe = mean(excess) / stddev(excess) * sqrt(periodsPerYear)
// This provides a reasonable approximation when equity snapshots are not available.
func (a *BacktestAccount) SharpeRatio(rfAnnual float64) float64 {
	if a.initialCash <= 0 {
		return 0
	}
	n := len(a.closeTrades)
	if n < 2 {
		return 0
	}

	trades := make([]*Trade, 0, n)
	for _, t := range a.closeTrades {
		trades = append(trades, t)
	}
	sort.Slice(trades, func(i, j int) bool { return trades[i].CloseTime < trades[j].CloseTime })

	// returns per closed trade (relative to initial capital)
	returns := make([]float64, 0, n)
	// periods in seconds between closes; length will be n-1 initially
	periodsSec := make([]float64, 0, n-1)
	for i, t := range trades {
		returns = append(returns, t.Pnl/a.initialCash)
		if i > 0 {
			// CloseTs is in milliseconds in this codebase
			dtSec := float64(t.CloseTime-trades[i-1].CloseTime) / 1000.0
			if dtSec <= 0 {
				dtSec = 1.0
			}
			periodsSec = append(periodsSec, dtSec)
		}
	}
	if len(periodsSec) == 0 {
		return 0
	}
	// average period (seconds) used to approximate period length for the first return
	sumDt := 0.0
	for _, d := range periodsSec {
		sumDt += d
	}
	avgDt := sumDt / float64(len(periodsSec))

	// Build final periods slice aligned with returns length
	periods := make([]float64, 0, n)
	periods = append(periods, avgDt)
	periods = append(periods, periodsSec...)

	const secsYear = 365.0 * 24.0 * 3600.0
	excess := make([]float64, len(returns))
	for i := range returns {
		years := periods[i] / secsYear
		excess[i] = returns[i] - rfAnnual*years
	}

	meanEx := mean(excess)
	sd := stddev(excess)
	if sd == 0 {
		return 0
	}
	// approximate number of periods per year
	periodsPerYear := secsYear / avgDt
	return meanEx / sd * math.Sqrt(periodsPerYear)
}

func mean(x []float64) float64 {
	if len(x) == 0 {
		return 0
	}
	s := 0.0
	for _, v := range x {
		s += v
	}
	return s / float64(len(x))
}

func stddev(x []float64) float64 {
	if len(x) <= 1 {
		return 0
	}
	m := mean(x)
	s := 0.0
	for _, v := range x {
		d := v - m
		s += d * d
	}
	// population or sample? use sample (n-1)
	return math.Sqrt(s / float64(len(x)-1))
}

// CurrentEquity 根据当前价格对仓位进行 mark-to-market，返回账户净值
func (a *BacktestAccount) CurrentEquity(price float64) float64 {
	equity := a.cash
	for _, p := range a.positions {
		switch p.Side {
		case types.SideLong:
			// equity += (price - p.EntryPx) * p.Qty
			equity += price * p.Qty
		case types.SideShort:
			// equity += (p.EntryPx - price) * p.Qty
			equity += (p.EntryPx - price + p.EntryPx) * p.Qty
		}
	}
	return equity
}

// CurrentExposure 返回当前仓位的名义总敞口（绝对值）
func (a *BacktestAccount) CurrentExposure() float64 {
	var sum float64
	for _, p := range a.positions {
		sum += (p.Qty * p.EntryPx)
	}
	return sum
}

// CanOpen 判断在给定价格下是否可以开仓（基于 MaxPosPct 和 MaxExposurePct）
// func (a *BacktestAccount) CanOpen(side types.Side, qty, price float64) bool {
// 	if qty <= 0 || price <= 0 {
// 		return false
// 	}
// 	equity := a.CurrentEquity(price)
// 	if equity <= 0 {
// 		return false
// 	}
// 	notional := math.Abs(qty * price)
// 	// 单仓位限制
// 	if a.MaxPosPct > 0 {
// 		if notional > a.MaxPosPct*equity {
// 			return false
// 		}
// 	}
// 	// 总敞口限制
// 	if a.MaxExposurePct > 0 {
// 		if a.CurrentExposure(price)+notional > a.MaxExposurePct*equity {
// 			return false
// 		}
// 	}
// 	return true
// }

// 获取未平仓交易单
func (a *BacktestAccount) OpenPositions() map[int64]*trade.Position {
	return a.positions
}

// 获取未平仓交易单数
func (a *BacktestAccount) CountOpenPositions() int {
	return len(a.positions)
}

// 订单下单
func (a *BacktestAccount) TradeOrder(ta trade.TradeArg) (ok bool, cause trade.Cause, err error) {
	order, ok := a.simulator.ExecuteMarket(ta.Side, ta.Qty, ta.Price, ta.Time)
	if !ok {
		return
	}

	// apply cash/position, short side also need earnest money
	cost := order.Price*order.Qty + order.Fee
	if cost > a.cash {
		ok = false
		return
	}
	a.cash -= cost
	// open/add position
	pos := &trade.Position{TradeId: order.Id, Side: order.Side, Qty: order.Qty, EntryPx: order.Price, EntryTs: order.Time, PeakPx: order.Price, Fee: order.Fee}
	a.positions[order.Id] = pos
	a.trades[order.Id] = order
	ok = true
	return
}

// 将仓位进行平仓
func (a *BacktestAccount) ClosePosition(pos *trade.Position, kline types.Kline, cause trade.Cause) (err error) {
	closeSide := lang.Ternary(pos.Side == types.SideLong, types.SideShort, types.SideLong)

	closePrice := decimals.MustToFloat64(kline.Close)
	t, ok := a.simulator.ExecuteMarket(closeSide, pos.Qty, closePrice, kline.Ts)
	if !ok {
		err = fmt.Errorf("close position error: %#v", pos)
		return
	}
	t.CloseCause = cause

	// apply cash change
	// calc profit
	var receive, profit float64
	if pos.Side == types.SideLong {
		profit = t.Qty*(t.Price-pos.EntryPx) - t.Fee - pos.Fee
		receive = t.Price*pos.Qty - t.Fee
	} else {
		profit = (pos.EntryPx - t.Price) * t.Qty
		receive = pos.EntryPx*pos.Qty + profit - t.Fee
		profit = profit - t.Fee - pos.Fee
	}
	a.cash += receive
	a.profit += profit

	if profit > 0 {
		a.winningTrades++
	} else {
		a.losingTrades++
	}
	a.fee += t.Fee

	// remove position
	delete(a.positions, pos.TradeId)
	a.closeTrades[t.Id] = t

	if trade, ok := a.trades[pos.TradeId]; ok {
		trade.ClosePrice = closePrice
		trade.CloseFee = t.Fee
		trade.CloseTime = kline.Ts
		trade.CloseCause = cause
		trade.Pnl = profit
		trade.HoldTime = conver.TimeDurationFormat(time.Duration(trade.CloseTime-trade.Time)*time.Millisecond, ".")
		trade.PeakPx = pos.PeakPx
	}

	// 记录最大回撤 [high, low, high, low]
	currentEquity := a.CurrentEquity(closePrice)
	if currentEquity < a.maxDrawdown[1] {
		a.maxDrawdown[1] = currentEquity
	}
	if currentEquity > a.maxDrawdown[0] {
		if a.maxDrawdown[0]-a.maxDrawdown[1] > a.maxDrawdown[2]-a.maxDrawdown[3] {
			a.maxDrawdown[2], a.maxDrawdown[3] = a.maxDrawdown[0], a.maxDrawdown[1]
		}
		a.maxDrawdown[0] = currentEquity
		a.maxDrawdown[1] = currentEquity
	}
	return
}