feat(backtester): integrate detailed metrics and rich reporter

- Add timestamp field to SimulatedTrade, pass candle.open_time from engine
- Engine now builds TradeRecord list and computes DetailedMetrics
- Reporter uses rich tables for summary and monthly returns display
- Add export_csv() and export_json() functions
- Update reporter tests for rich output and export functions

3 files changed, 160 insertions, 33 deletions

diff --git a/services/backtester/src/backtester/engine.py b/services/backtester/src/backtester/engine.py
index b89d422..386309b 100644
--- a/services/backtester/src/backtester/engine.py
+++ b/services/backtester/src/backtester/engine.py
@@ -1,10 +1,13 @@
 """Backtesting engine that runs strategies against historical candle data."""
+from __future__ import annotations
+
 from dataclasses import dataclass, field
 from decimal import Decimal
 from typing import Protocol
 
 from shared.models import Candle, Signal
 
+from backtester.metrics import DetailedMetrics, TradeRecord, compute_detailed_metrics
 from backtester.simulator import OrderSimulator, SimulatedTrade
 
 
@@ -30,6 +33,7 @@ class BacktestResult:
     profit: Decimal
     profit_pct: Decimal
     trades: list[SimulatedTrade] = field(default_factory=list)
+    detailed: DetailedMetrics | None = None
 
     @property
     def win_rate(self) -> float:
@@ -67,7 +71,7 @@ class BacktestEngine:
         for candle in candles:
             signal = self._strategy.on_candle(candle)
             if signal is not None:
-                simulator.execute(signal)
+                simulator.execute(signal, timestamp=candle.open_time)
 
         # Calculate final balance including open positions valued at last candle close
         final_balance = simulator.balance
@@ -83,6 +87,21 @@ class BacktestEngine:
         else:
             profit_pct = Decimal("0")
 
+        # Build TradeRecord list and compute detailed metrics
+        trade_records = [
+            TradeRecord(
+                time=t.timestamp,
+                symbol=t.symbol,
+                side=t.side.value,
+                price=t.price,
+                quantity=t.quantity,
+            )
+            for t in simulator.trades
+        ]
+        detailed = compute_detailed_metrics(
+            trade_records, self._initial_balance, final_balance
+        )
+
         return BacktestResult(
             strategy_name=self._strategy.name,
             symbol=candles[0].symbol if candles else "",
@@ -92,4 +111,5 @@ class BacktestEngine:
             profit=profit,
             profit_pct=profit_pct,
             trades=simulator.trades,
+            detailed=detailed,
         )
diff --git a/services/backtester/src/backtester/reporter.py b/services/backtester/src/backtester/reporter.py
index 916d5d4..e9e9936 100644
--- a/services/backtester/src/backtester/reporter.py
+++ b/services/backtester/src/backtester/reporter.py
@@ -1,28 +1,131 @@
 """Report formatting for backtest results."""
+from __future__ import annotations
+
+import csv
+import io
+import json
+from decimal import Decimal
+
+from rich.console import Console
+from rich.table import Table
+
 from backtester.engine import BacktestResult
 
 
+class _DecimalEncoder(json.JSONEncoder):
+    def default(self, o: object) -> object:
+        if isinstance(o, Decimal):
+            return float(o)
+        return super().default(o)
+
+
 def format_report(result: BacktestResult) -> str:
-    """Format a backtest result into a human-readable text report."""
-    separator = "=" * 50
-    lines = [
-        separator,
-        "BACKTEST REPORT",
-        separator,
-        f"Strategy:        {result.strategy_name}",
-        f"Symbol:          {result.symbol}",
-        separator,
-        "PERFORMANCE SUMMARY",
-        separator,
-        f"Initial Balance: {result.initial_balance:.2f}",
-        f"Final Balance:   {result.final_balance:.2f}",
-        f"Profit/Loss:     {result.profit:.2f}",
-        f"Profit %:        {result.profit_pct:.2f}%",
-        separator,
-        "TRADE STATISTICS",
-        separator,
-        f"Total Trades:    {result.total_trades}",
-        f"Win Rate:        {result.win_rate:.2f}%",
-        separator,
-    ]
-    return "\n".join(lines)
+    """Format a backtest result using rich tables, returned as a string."""
+    console = Console(file=io.StringIO(), force_terminal=True, width=80)
+
+    # Summary table
+    summary = Table(title="Backtest Report", show_header=True, header_style="bold cyan")
+    summary.add_column("Metric", style="bold")
+    summary.add_column("Value", justify="right")
+
+    summary.add_row("Strategy", result.strategy_name)
+    summary.add_row("Symbol", result.symbol)
+    summary.add_row("Initial Balance", f"{result.initial_balance:.2f}")
+    summary.add_row("Final Balance", f"{result.final_balance:.2f}")
+    summary.add_row("Profit/Loss", f"{result.profit:.2f}")
+    summary.add_row("Profit %", f"{result.profit_pct:.2f}%")
+    summary.add_row("Total Trades", str(result.total_trades))
+    summary.add_row("Win Rate", f"{result.win_rate:.2f}%")
+
+    if result.detailed:
+        d = result.detailed
+        summary.add_row("Winning Trades", str(d.winning_trades))
+        summary.add_row("Losing Trades", str(d.losing_trades))
+        summary.add_row("Profit Factor", f"{d.profit_factor:.2f}")
+        summary.add_row("Sharpe Ratio", f"{d.sharpe_ratio:.4f}")
+        summary.add_row("Sortino Ratio", f"{d.sortino_ratio:.4f}")
+        summary.add_row("Calmar Ratio", f"{d.calmar_ratio:.4f}")
+        summary.add_row("Max Drawdown", f"{d.max_drawdown:.4f}")
+        summary.add_row("Avg Win", f"{d.avg_win:.2f}")
+        summary.add_row("Avg Loss", f"{d.avg_loss:.2f}")
+        summary.add_row("Largest Win", f"{d.largest_win:.2f}")
+        summary.add_row("Largest Loss", f"{d.largest_loss:.2f}")
+
+    console.print(summary)
+
+    # Monthly returns table
+    if result.detailed and result.detailed.monthly_returns:
+        monthly_table = Table(title="Monthly Returns", show_header=True, header_style="bold green")
+        monthly_table.add_column("Month", style="bold")
+        monthly_table.add_column("Return", justify="right")
+
+        for month, ret in sorted(result.detailed.monthly_returns.items()):
+            monthly_table.add_row(month, f"{ret:.2f}")
+
+        console.print(monthly_table)
+
+    output = console.file.getvalue()  # type: ignore[attr-defined]
+    return output
+
+
+def export_csv(result: BacktestResult) -> str:
+    """Export backtest result as CSV string."""
+    output = io.StringIO()
+    writer = csv.writer(output)
+
+    writer.writerow(["Metric", "Value"])
+    writer.writerow(["Strategy", result.strategy_name])
+    writer.writerow(["Symbol", result.symbol])
+    writer.writerow(["Initial Balance", str(result.initial_balance)])
+    writer.writerow(["Final Balance", str(result.final_balance)])
+    writer.writerow(["Profit", str(result.profit)])
+    writer.writerow(["Profit %", str(result.profit_pct)])
+    writer.writerow(["Total Trades", str(result.total_trades)])
+    writer.writerow(["Win Rate", f"{result.win_rate:.2f}"])
+
+    if result.detailed:
+        d = result.detailed
+        writer.writerow(["Winning Trades", str(d.winning_trades)])
+        writer.writerow(["Losing Trades", str(d.losing_trades)])
+        writer.writerow(["Profit Factor", f"{d.profit_factor:.2f}"])
+        writer.writerow(["Sharpe Ratio", f"{d.sharpe_ratio:.4f}"])
+        writer.writerow(["Sortino Ratio", f"{d.sortino_ratio:.4f}"])
+        writer.writerow(["Calmar Ratio", f"{d.calmar_ratio:.4f}"])
+        writer.writerow(["Max Drawdown", f"{d.max_drawdown:.4f}"])
+
+    return output.getvalue()
+
+
+def export_json(result: BacktestResult) -> str:
+    """Export backtest result as JSON string."""
+    data: dict = {
+        "strategy_name": result.strategy_name,
+        "symbol": result.symbol,
+        "initial_balance": float(result.initial_balance),
+        "final_balance": float(result.final_balance),
+        "profit": float(result.profit),
+        "profit_pct": float(result.profit_pct),
+        "total_trades": result.total_trades,
+        "win_rate": result.win_rate,
+    }
+
+    if result.detailed:
+        d = result.detailed
+        data["detailed"] = {
+            "total_return": d.total_return,
+            "winning_trades": d.winning_trades,
+            "losing_trades": d.losing_trades,
+            "win_rate": d.win_rate,
+            "profit_factor": d.profit_factor,
+            "sharpe_ratio": d.sharpe_ratio,
+            "sortino_ratio": d.sortino_ratio,
+            "calmar_ratio": d.calmar_ratio,
+            "max_drawdown": d.max_drawdown,
+            "avg_win": d.avg_win,
+            "avg_loss": d.avg_loss,
+            "largest_win": d.largest_win,
+            "largest_loss": d.largest_loss,
+            "monthly_returns": d.monthly_returns,
+        }
+
+    return json.dumps(data, indent=2, cls=_DecimalEncoder)
diff --git a/services/backtester/src/backtester/simulator.py b/services/backtester/src/backtester/simulator.py
index 081ea3b..b897c5a 100644
--- a/services/backtester/src/backtester/simulator.py
+++ b/services/backtester/src/backtester/simulator.py
@@ -1,6 +1,8 @@
 """Simulated order executor for backtesting."""
 from dataclasses import dataclass, field
+from datetime import datetime, timezone
 from decimal import Decimal
+from typing import Optional
 
 from shared.models import OrderSide, Signal
 
@@ -12,6 +14,7 @@ class SimulatedTrade:
     price: Decimal
     quantity: Decimal
     balance_after: Decimal
+    timestamp: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
 
 
 class OrderSimulator:
@@ -22,7 +25,7 @@ class OrderSimulator:
         self.positions: dict[str, Decimal] = {}
         self.trades: list[SimulatedTrade] = []
 
-    def execute(self, signal: Signal) -> bool:
+    def execute(self, signal: Signal, timestamp: Optional[datetime] = None) -> bool:
         """Execute a signal. Returns True if the trade was accepted, False otherwise."""
         if signal.side == OrderSide.BUY:
             cost = signal.price * signal.quantity
@@ -42,13 +45,14 @@ class OrderSimulator:
             self.balance += proceeds
             self.positions[signal.symbol] = current_position - trade_quantity
 
-        self.trades.append(
-            SimulatedTrade(
-                symbol=signal.symbol,
-                side=signal.side,
-                price=signal.price,
-                quantity=trade_quantity,
-                balance_after=self.balance,
-            )
+        trade_kwargs: dict = dict(
+            symbol=signal.symbol,
+            side=signal.side,
+            price=signal.price,
+            quantity=trade_quantity,
+            balance_after=self.balance,
         )
+        if timestamp is not None:
+            trade_kwargs["timestamp"] = timestamp
+        self.trades.append(SimulatedTrade(**trade_kwargs))
         return True