feat(backtest): add PortfolioTracker with equity curve and drawdown

- Pre-allocate numpy arrays for performance (cash, position, avg_price)
- apply_trades() processes buys/sells with commission and slippage
- equity_curve returns DataFrame with drawdown calculation
- positions returns DataFrame with market value and unrealized PnL
- 12 unit tests covering all scenarios

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

tests/unit/test_backtest_portfolio.py

@@ -0,0 +1,289 @@
+"""回测引擎持仓追踪器单元测试。"""
+
+from __future__ import annotations
+
+import pandas as pd
+
+from easy_tdx.backtest.portfolio import PortfolioTracker
+from easy_tdx.backtest.types import Trade
+
+
+def _make_df(n: int = 10) -> pd.DataFrame:
+    """创建测试用 DataFrame。
+
+    Args:
+        n: bar 数量
+
+    Returns:
+        包含 close 和 datetime 列的 DataFrame
+    """
+    close = [100.0] * 5 + [110.0] * 5
+    close = close[:n]
+    datetime = list(range(20240101, 20240101 + n))
+
+    return pd.DataFrame({"close": close, "datetime": datetime})
+
+
+def test_initial_state() -> None:
+    """测试初始状态。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df, initial_cash=100000)
+
+    assert tracker.initial_cash == 100000
+
+
+def test_buy_then_sell() -> None:
+    """测试买入再卖出。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df, initial_cash=100000)
+
+    # bar 0 买入 100 股 @100，手续费 5
+    buy_trade = Trade(
+        datetime=20240101,
+        direction="BUY",
+        size=100,
+        price=100.0,
+        commission=5.0,
+        slippage=0.0,
+    )
+
+    # bar 5 卖出 100 股 @110，手续费 11
+    sell_trade = Trade(
+        datetime=20240106,
+        direction="SELL",
+        size=100,
+        price=110.0,
+        commission=11.0,
+        slippage=0.0,
+    )
+
+    tracker.apply_trades([buy_trade, sell_trade])
+
+    equity = tracker.equity_curve
+    final_cash = equity["cash"].iloc[-1]
+
+    # 最终现金 = 100000 - 10000 - 5 + 11000 - 11 = 100984
+    expected = 100984.0
+    assert abs(final_cash - expected) < 1.0, f"Expected {expected}, got {final_cash}"
+
+
+def test_drawdown_calculation() -> None:
+    """测试回撤计算（无交易时回撤全为 0）。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df, initial_cash=100000)
+
+    tracker.apply_trades([])
+
+    equity = tracker.equity_curve
+
+    # 无交易时，总资产应保持不变，回撤为 0
+    assert (equity["drawdown"] == 0).all()
+    assert (equity["drawdown_pct"] == 0).all()
+
+
+def test_equity_curve_columns() -> None:
+    """测试资金曲线列名。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df)
+
+    tracker.apply_trades([])
+    equity = tracker.equity_curve
+
+    expected_cols = {"datetime", "cash", "position_value", "total", "drawdown", "drawdown_pct"}
+    assert set(equity.columns) == expected_cols
+
+
+def test_position_tracking() -> None:
+    """测试持仓追踪。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df)
+
+    # bar 0 买入 100 股
+    buy_trade = Trade(
+        datetime=20240101,
+        direction="BUY",
+        size=100,
+        price=100.0,
+        commission=5.0,
+        slippage=0.0,
+    )
+
+    tracker.apply_trades([buy_trade])
+    positions = tracker.positions
+
+    # 买入后持仓应为 100，并持续到最后
+    assert positions["size"].iloc[0] == 100
+    assert positions["size"].iloc[-1] == 100
+    assert (positions["size"].iloc[1:] == 100).all()
+
+
+def test_avg_price_update() -> None:
+    """测试均价更新。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df)
+
+    # bar 0 买入 100 股 @100
+    buy1 = Trade(
+        datetime=20240101,
+        direction="BUY",
+        size=100,
+        price=100.0,
+        commission=0.0,
+        slippage=0.0,
+    )
+
+    # bar 1 再买入 50 股 @110
+    buy2 = Trade(
+        datetime=20240102,
+        direction="BUY",
+        size=50,
+        price=110.0,
+        commission=0.0,
+        slippage=0.0,
+    )
+
+    tracker.apply_trades([buy1, buy2])
+    positions = tracker.positions
+
+    # 均价 = (100*100 + 50*110) / 150 = 103.33
+    expected_avg = (100 * 100 + 50 * 110) / 150
+    assert abs(positions["avg_price"].iloc[1] - expected_avg) < 0.01
+
+
+def test_sell_clears_position() -> None:
+    """测试卖出清空持仓。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df)
+
+    buy = Trade(
+        datetime=20240101,
+        direction="BUY",
+        size=100,
+        price=100.0,
+        commission=0.0,
+        slippage=0.0,
+    )
+
+    sell = Trade(
+        datetime=20240102,
+        direction="SELL",
+        size=100,
+        price=110.0,
+        commission=0.0,
+        slippage=0.0,
+    )
+
+    tracker.apply_trades([buy, sell])
+    positions = tracker.positions
+
+    # 卖出后持仓应为 0
+    assert positions["size"].iloc[0] == 100
+    assert positions["size"].iloc[1] == 0
+    assert positions["avg_price"].iloc[1] == 0
+
+
+def test_position_market_value() -> None:
+    """测试持仓市值计算。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df)
+
+    buy = Trade(
+        datetime=20240101,
+        direction="BUY",
+        size=100,
+        price=100.0,
+        commission=0.0,
+        slippage=0.0,
+    )
+
+    tracker.apply_trades([buy])
+    positions = tracker.positions
+
+    # 前 5 个 bar 价格 100，后 5 个 bar 价格 110
+    assert positions["market_value"].iloc[0] == 100 * 100
+    assert positions["market_value"].iloc[5] == 100 * 110
+
+
+def test_unrealized_pnl() -> None:
+    """测试未实现盈亏计算。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df)
+
+    buy = Trade(
+        datetime=20240101,
+        direction="BUY",
+        size=100,
+        price=100.0,
+        commission=0.0,
+        slippage=0.0,
+    )
+
+    tracker.apply_trades([buy])
+    positions = tracker.positions
+
+    # 前 5 个 bar 价格 100，盈亏为 0
+    assert positions["unrealized_pnl"].iloc[0] == 0
+
+    # 后 5 个 bar 价格 110，盈亏为 (110-100)*100 = 1000
+    assert positions["unrealized_pnl"].iloc[5] == 1000
+
+
+def test_rejected_trade_ignored() -> None:
+    """测试被拒绝的交易不产生影响。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df, initial_cash=100000)
+
+    rejected_buy = Trade(
+        datetime=20240101,
+        direction="BUY",
+        size=100,
+        price=100.0,
+        commission=0.0,
+        slippage=0.0,
+        rejected=True,
+    )
+
+    tracker.apply_trades([rejected_buy])
+    equity = tracker.equity_curve
+
+    # 现金应保持不变
+    assert (equity["cash"] == 100000).all()
+    assert (tracker.positions["size"] == 0).all()
+
+
+def test_commission_and_slippage() -> None:
+    """测试手续费和滑点扣减。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df, initial_cash=10000)
+
+    buy = Trade(
+        datetime=20240101,
+        direction="BUY",
+        size=100,
+        price=100.0,
+        commission=10.0,
+        slippage=5.0,
+    )
+
+    tracker.apply_trades([buy])
+    equity = tracker.equity_curve
+
+    # 现金 = 10000 - 100*100 - 10 - 5 = -15
+    expected_cash = 10000 - 10000 - 10 - 5
+    assert equity["cash"].iloc[0] == expected_cash
+
+
+def test_empty_trades() -> None:
+    """测试空交易列表不崩溃。"""
+    df = _make_df(10)
+    tracker = PortfolioTracker(df)
+
+    tracker.apply_trades([])
+
+    equity = tracker.equity_curve
+    positions = tracker.positions
+
+    # 所有 bar 现金应等于初始现金
+    assert (equity["cash"] == 100000).all()
+    # 所有 bar 持仓应为 0
+    assert (positions["size"] == 0).all()