feat: phase 1 — data downloader, backtrader runner, SMA strategy

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

backtest/config.py

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+from dataclasses import dataclass, field
+from datetime import date
+
+
+@dataclass
+class BacktestConfig:
+    symbols: list[str] = field(default_factory=lambda: ["sh600000"])
+    start_date: str = "2023-01-01"
+    end_date: str = "2024-12-31"
+    initial_cash: float = 1_000_000.0
+    commission: float = 0.0003  # 0.03% for Chinese A-shares
+    stamp_duty: float = 0.001   # 0.1% stamp duty on sells only (handled in strategy)
+    adjust: str = "qfq"

backtest/feed.py

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+"""Convert pandas DataFrames to backtrader data feeds."""
+import backtrader as bt
+import pandas as pd
+
+
+def df_to_bt_feed(df: pd.DataFrame) -> bt.feeds.PandasData:
+    """Convert a standardized OHLCV DataFrame to a backtrader PandasData feed."""
+    df = df.copy()
+    df["date"] = pd.to_datetime(df["date"])
+    df = df.set_index("date")
+    df = df[["open", "high", "low", "close", "volume"]]
+    return bt.feeds.PandasData(dataname=df)

backtest/runner.py

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+"""BacktestRunner: orchestrates data loading, cerebro setup, and execution."""
+import logging
+import backtrader as bt
+from typing import Optional
+
+from backtest.config import BacktestConfig
+from backtest.feed import df_to_bt_feed
+from data.downloader import download_daily
+
+logger = logging.getLogger(__name__)
+
+
+class BacktestRunner:
+    """Run backtrader backtests with Chinese equity data."""
+
+    def __init__(self, config: BacktestConfig):
+        self.config = config
+        self.cerebro = bt.Cerebro()
+        self._results: Optional[list] = None
+
+    def add_data(self, symbol: str) -> None:
+        """Download data for a symbol and add to cerebro as a feed."""
+        df = download_daily(
+            symbol=symbol,
+            start=self.config.start_date,
+            end=self.config.end_date,
+            adjust=self.config.adjust,
+        )
+        feed = df_to_bt_feed(df)
+        self.cerebro.adddata(feed, name=symbol)
+        logger.info(f"Added {symbol}: {len(df)} bars")
+
+    def add_strategy(self, strategy_cls, **kwargs) -> None:
+        """Add a strategy class to cerebro."""
+        self.cerebro.addstrategy(strategy_cls, **kwargs)
+
+    def setup(self, strategy_cls, strategy_kwargs: Optional[dict] = None) -> None:
+        """Full setup: load data for all symbols, configure cerebro, add strategy."""
+        # Load data for all symbols
+        for sym in self.config.symbols:
+            self.add_data(sym)
+
+        # Configure cerebro
+        self.cerebro.broker.setcash(self.config.initial_cash)
+        self.cerebro.broker.setcommission(commission=self.config.commission)
+
+        # Add analyzers
+        self.cerebro.addanalyzer(bt.analyzers.SharpeRatio, _name="sharpe", riskfreerate=0.02)
+        self.cerebro.addanalyzer(bt.analyzers.DrawDown, _name="drawdown")
+        self.cerebro.addanalyzer(bt.analyzers.Returns, _name="returns")
+        self.cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name="trades")
+
+        # Add strategy
+        strategy_kwargs = strategy_kwargs or {}
+        self.cerebro.addstrategy(strategy_cls, **strategy_kwargs)
+
+    def run(self, strategy_cls, strategy_kwargs: Optional[dict] = None) -> list:
+        """Setup and run the backtest. Returns cerebro run results."""
+        self.setup(strategy_cls, strategy_kwargs)
+        start_val = self.cerebro.broker.getvalue()
+        logger.info(f"Starting portfolio value: {start_val:,.2f}")
+        self._results = self.cerebro.run()
+        end_val = self.cerebro.broker.getvalue()
+        logger.info(f"Ending portfolio value: {end_val:,.2f}")
+        return self._results
+
+    def get_results(self) -> Optional[list]:
+        return self._results