Simon
6acf938caf
- 删除 11 个残留文件: continuation.md, init_plan.md, reasonix.toml, djapi/continuation.md, djapi/.serena/, djapi/.claude/, djapi/.mcp.json, .claude/skills/, docs/usage.html, docs/db_schema.md, docs/report_db_design.md - 7 个 CLAUDE-*.md 移入 docs/ 并重命名去 CLAUDE- 前缀 - 新增 4 个文档: architecture.md, development.md, api.md, deployment.md - 重写 usage.md, README.md - 修复所有过时引用和交叉链接
2.3 KiB
2.3 KiB
回测引擎 + 参数优化
VectorBTEngine (finance/backtest/vectorbt/engine.py)
只做多，10万/万三。
from backtest.vectorbt.engine import VectorBTEngine
engine_bt = VectorBTEngine(initial_capital=100_000, commission=0.0003)
report = engine_bt.run(strategy, price_df, factor_df)
# → BacktestReport
report = engine_bt.run_cross_section(strategy, price_univ, factor_univ)
信号流：1=buy, 0=sell, -1=hold → _signals_to_entries → vbt.Portfolio.from_signals（direction="longonly"）。
策略 (finance/backtest/strategies/)
| 策略 | 参数 | 逻辑 |
|---|---|---|
SMACrossStrategy |
fast=5, slow=20 | 金叉买/死叉卖 |
RSIMeanRevertStrategy |
oversold=30, overbought=70 | 超卖买/超买卖 |
MomentumBreakoutStrategy |
lookback=20, exit=10 | 新高买/跌破卖 |
FactorCrossStrategy |
factor_column, buy/sell_threshold | 阈值交叉（通用） |
FactorRotationStrategy |
factor_name, top_n=5 | 排序选股 |
自定义策略
继承 backtest/base.py:BaseStrategy，实现 generate_signals(factor_df) → pd.Series。
信号工具 (backtest/signal.py)
factor_to_threshold_signal(series, buy, sell, direction)
cross_signal(fast, slow) # 金叉/死叉
factor_to_quantile_signal(...) # 分位数信号
BacktestReport (backtest/report.py)
字段：total_return, cagr, max_drawdown, sharpe_ratio, calmar_ratio, annual_volatility, win_rate, profit_factor, total_trades, avg_hold_days, best/worst_trade_pct, equity_curve, drawdown_curve, monthly_returns, trades_df, stats_dict。summary() 一行摘要。
OptunaEngine (finance/optimizer/engine.py)
from optimizer.engine import OptunaEngine
from optimizer.space import rsi_revert_space
opt = OptunaEngine(bt_engine)
result = opt.optimize(StrategyClass, space, price_df, factor_df, metric="sharpe", n_trials=200)
# → OptimizationResult(best_params, best_value, best_report, trial_df, param_importance)
wf = opt.optimize_walk_forward(StrategyClass, space, price_df, factor_df,
train_window=756, test_window=252)
预置空间：sma_cross_space, rsi_revert_space, momentum_breakout_space, factor_cross_space（optimizer/space.py）。
目标指标：sharpe/cagr/calmar/total_return/return_over_dd。