from __future__ import annotations from datetime import date, timedelta import polars as pl from app.backtest.engine import BacktestEngine, MatcherConfig def _panel(symbols: list[str], days: int = 4, price: float = 10.0, overrides: dict[tuple[str, int], dict] | None = None) -> pl.DataFrame: overrides = overrides or {} start = date(2024, 1, 1) rows = [] for sym in symbols: for i in range(days): patch = overrides.get((sym, i), {}) rows.append({ "symbol": sym, "name": sym, "date": start + timedelta(days=i), "open": patch.get("open", price), "high": patch.get("high", price), "low": patch.get("low", price), "close": patch.get("close", price), "volume": patch.get("volume", 100_000), "score": patch.get("score", {"A": 4, "B": 3, "C": 2, "D": 1}.get(sym, 0)), "signal_limit_up": patch.get("signal_limit_up", False), "signal_limit_down": patch.get("signal_limit_down", False), }) return pl.DataFrame(rows).sort(["symbol", "date"]) def _mask(panel: pl.DataFrame, marks: set[tuple[str, int]]) -> pl.Series: values = [] base = date(2024, 1, 1) for row in panel.select(["symbol", "date"]).iter_rows(named=True): day = (row["date"] - base).days values.append((row["symbol"], day) in marks) return pl.Series(values, dtype=pl.Boolean) def _engine() -> BacktestEngine: return BacktestEngine(repo=None) # simulate_portfolio 不访问 repo def test_max_exposure_sets_target_position_and_caps_count(): panel = _panel(["A", "B", "C", "D"], days=3) entries = _mask(panel, {("A", 0), ("B", 0), ("C", 0), ("D", 0)}) exits = _mask(panel, set()) result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig( matching="open_t+1", fees_pct=0, slippage_bps=0, max_positions=3, max_exposure_pct=0.6, initial_capital=100_000, ), ) assert len(result.trades) == 3 assert {t.symbol for t in result.trades} == {"A", "B", "C"} assert all(abs(t.position_pct - 0.2) < 0.001 for t in result.trades) assert result.stats["max_exposure"] <= 0.61 def test_one_price_limit_up_blocks_buy(): panel = _panel( ["A"], days=3, overrides={ ("A", 1): {"open": 11, "high": 11, "low": 11, "close": 11, "signal_limit_up": True}, }, ) entries = _mask(panel, {("A", 0)}) exits = _mask(panel, set()) result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig(matching="open_t+1", fees_pct=0, slippage_bps=0, max_positions=1, initial_capital=100_000), ) assert result.trades == [] assert result.stats["execution"]["buy_limit_up"] == 1 def test_failed_open_exit_keeps_slot_and_blocks_replacement_buy(): panel = _panel( ["A", "B", "C", "D"], days=4, overrides={ ("A", 2): {"open": 9, "high": 9, "low": 9, "close": 9, "signal_limit_down": True}, }, ) entries = _mask(panel, { ("A", 0), ("B", 0), ("C", 0), ("D", 1), }) exits = _mask(panel, {("A", 1)}) result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig( matching="open_t+1", fees_pct=0, slippage_bps=0, max_positions=3, max_exposure_pct=0.6, initial_capital=100_000, ), ) assert "D" not in {t.symbol for t in result.trades} assert result.stats["execution"]["sell_limit_down"] == 1 assert result.stats["execution"]["pending_exit"] == 1 assert result.stats["execution"]["buy_no_slot"] >= 1 a_trade = next(t for t in result.trades if t.symbol == "A") assert a_trade.blocked_exit_days == 1 assert a_trade.exit_reason == "signal" def test_trailing_stop_uses_high_water_mark(): panel = _panel( ["A"], days=5, overrides={ ("A", 2): {"open": 10, "high": 12, "low": 11.8, "close": 12}, ("A", 3): {"open": 12, "high": 12, "low": 11.3, "close": 11.3}, }, ) entries = _mask(panel, {("A", 0)}) exits = _mask(panel, set()) result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig( matching="open_t+1", fees_pct=0, slippage_bps=0, max_positions=1, initial_capital=100_000, trailing_stop_pct=0.05, ), ) assert len(result.trades) == 1 trade = result.trades[0] assert trade.exit_reason == "trailing_stop" assert trade.exit_price == 11.4 def test_trailing_take_profit_requires_activation(): panel = _panel( ["A"], days=5, overrides={ ("A", 2): {"open": 10, "high": 10.8, "low": 10.4, "close": 10.8}, ("A", 3): {"open": 10.8, "high": 10.8, "low": 10.4, "close": 10.4}, }, ) entries = _mask(panel, {("A", 0)}) exits = _mask(panel, set()) result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig( matching="open_t+1", fees_pct=0, slippage_bps=0, max_positions=1, initial_capital=100_000, trailing_take_profit_activate_pct=0.10, trailing_take_profit_drawdown_pct=0.03, ), ) assert result.trades[0].exit_reason == "end" def test_trailing_take_profit_exits_after_activation(): panel = _panel( ["A"], days=5, overrides={ ("A", 2): {"open": 10, "high": 12, "low": 11.8, "close": 12}, ("A", 3): {"open": 12, "high": 12, "low": 11.5, "close": 11.5}, }, ) entries = _mask(panel, {("A", 0)}) exits = _mask(panel, set()) result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig( matching="open_t+1", fees_pct=0, slippage_bps=0, max_positions=1, initial_capital=100_000, trailing_take_profit_activate_pct=0.10, trailing_take_profit_drawdown_pct=0.03, ), ) assert len(result.trades) == 1 trade = result.trades[0] assert trade.exit_reason == "trailing_take_profit" assert trade.exit_price == 11.7 def test_score_filter_uses_signal_day_score_range(): panel = _panel( ["A", "B", "C"], days=3, overrides={ ("A", 0): {"score": 70}, ("B", 0): {"score": 80}, ("C", 0): {"score": 90}, ("A", 1): {"score": 100}, ("B", 1): {"score": 1}, ("C", 1): {"score": 1}, }, ) entries = _mask(panel, {("A", 0), ("B", 0), ("C", 0)}) exits = _mask(panel, set()) result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig( matching="open_t+1", fees_pct=0, slippage_bps=0, max_positions=3, initial_capital=100_000, score_min=71, score_max=85, ), ) assert {t.symbol for t in result.trades} == {"B"} assert result.trades[0].entry_score == 80 assert result.stats["execution"]["buy_score_filter"] == 2 def test_independent_candidates_allow_overlapping_same_symbol_trades(): panel = _panel( ["A"], days=5, overrides={ ("A", 0): {"close": 10}, ("A", 1): {"close": 11}, ("A", 2): {"close": 12}, ("A", 3): {"close": 13}, ("A", 4): {"close": 14}, }, ) entries = _mask(panel, {("A", 0), ("A", 1)}) exits = _mask(panel, set()) result = _engine().simulate_independent_candidates( panel, entries, exits, MatcherConfig(matching="close_t", fees_pct=0, slippage_bps=0, max_hold_days=2), ) assert result.stats["full_kind"] == "candidate_execution" assert result.stats["n_candidates"] == 2 assert len(result.trades) == 2 assert [t.entry_date for t in result.trades] == ["2024-01-01", "2024-01-02"] assert [t.exit_date for t in result.trades] == ["2024-01-03", "2024-01-04"] assert all(t.exit_reason == "max_hold" for t in result.trades) def test_independent_candidates_apply_stop_loss(): panel = _panel( ["A"], days=4, overrides={ ("A", 0): {"close": 10, "low": 10}, ("A", 1): {"open": 10, "high": 10, "low": 8.9, "close": 9}, }, ) entries = _mask(panel, {("A", 0)}) exits = _mask(panel, set()) result = _engine().simulate_independent_candidates( panel, entries, exits, MatcherConfig(matching="close_t", fees_pct=0, slippage_bps=0, stop_loss_pct=0.1), ) assert len(result.trades) == 1 assert result.trades[0].exit_reason == "stop_loss" assert result.trades[0].exit_price == 9.0 def test_signal_exit_takes_priority_over_max_hold(): """同一日既有卖点信号又到期 → 应按 signal 平仓 (卖点优先于 max_hold 兜底)。""" panel = _panel( ["A"], days=4, overrides={ # day1 次日开盘买入 (open_t+1), 价 10 ("A", 1): {"open": 10, "high": 10, "low": 10, "close": 10}, # day2 持有 (hold_days 计到 1) ("A", 2): {"open": 11, "high": 11, "low": 11, "close": 11}, # day3: 既到期 (hold_days=2 >= max_hold_days=2) 又有卖点信号 → signal 优先 ("A", 3): {"open": 12, "high": 12, "low": 12, "close": 12}, }, ) entries = _mask(panel, {("A", 0)}) # day0 收盘确认 → day1 开盘买 exits = _mask(panel, {("A", 2)}) # day2 收盘确认卖点 → day3 开盘卖 result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig( matching="open_t+1", fees_pct=0, slippage_bps=0, max_positions=1, max_hold_days=2, initial_capital=100_000, ), ) assert len(result.trades) == 1 trade = result.trades[0] assert trade.exit_reason == "signal" assert trade.exit_price == 12.0 # 卖点用 day3 开盘 (exit_fill 跟随 matching=open_t+1) def test_stop_loss_triggers_even_when_expired_in_open_mode(): """open_t+1 模式下仓位到期且当日破止损 → 应按 stop_loss 平仓 (风控优先于 max_hold)。""" panel = _panel( ["A"], days=4, overrides={ ("A", 1): {"open": 10, "high": 10, "low": 10, "close": 10}, # day3 开盘跳空跌破止损 (-10%): open=8.9 < 9.0 止损线, low=8.5 ("A", 3): {"open": 8.9, "high": 8.9, "low": 8.5, "close": 8.7}, }, ) entries = _mask(panel, {("A", 0)}) exits = _mask(panel, set()) result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig( matching="open_t+1", fees_pct=0, slippage_bps=0, max_positions=1, max_hold_days=2, stop_loss_pct=0.1, initial_capital=100_000, ), ) assert len(result.trades) == 1 trade = result.trades[0] assert trade.exit_reason == "stop_loss" # 风控盘中触发: 开盘价 8.9 <= 止损线 9.0 → 按开盘价 8.9 成交 assert trade.exit_price == 8.9 def test_default_fill_is_buy_open_sell_close(): """拆分口径: 建仓=次日开盘, 清仓=收盘。entry_price 用次日 open, exit_price 用收盘价。""" panel = _panel( ["A"], days=4, overrides={ # day1: 次日开盘买入, 开盘 10 ("A", 1): {"open": 10, "high": 10.5, "low": 9.5, "close": 10.2}, # day2: 到期 (max_hold_days=1), 收盘卖 ("A", 2): {"open": 11, "high": 11, "low": 10, "close": 10.8}, }, ) entries = _mask(panel, {("A", 0)}) # day0 收盘确认 exits = _mask(panel, set()) result = _engine().simulate_portfolio( panel, entries, exits, MatcherConfig( entry_fill="open_t+1", exit_fill="close_t", fees_pct=0, slippage_bps=0, max_positions=1, max_hold_days=1, initial_capital=100_000, ), ) assert len(result.trades) == 1 trade = result.trades[0] assert trade.entry_price == 10.0 # 次日开盘 assert trade.exit_price == 10.8 # 到期日收盘 assert trade.exit_reason == "max_hold"