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simonandClaude Opus 4.7 271a9343a5 Initial commit: cc-cursor 全链路量化研究平台

7 Sprints 全部完成:
  Sprint 0: 基础设施 (DataManager + MariaDB)
  Sprint 1: 因子引擎 (34因子/12分类)
  Sprint 2: VectorBT 回测 (5策略+截面)
  Sprint 3: Optuna 优化 (+Walk-Forward)
  Sprint 4: ML 模型 (LightGBM+CatBoost)
  Sprint 5: Qwen 情绪因子 (三源新闻+日期对齐)
  Sprint 6: Agent 系统 (4Agent+日报.md/.html)

生产加固 (15项): Tushare双源fallback, SSH自动恢复, pool_pre_ping,
  save_daily先删后插, load_dotenv绝对路径, 日报5d/20d修复,
  RiskAgent改上证指数, 昨日对比+数据截止, mac_report utf8mb4,
  CLAUDE-*.md 9条已知Bug, demo全参数化, djapi数据源归一化,
  indexDatas API修正

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

2026-06-07 15:59:05 +08:00

2.3 KiB

Raw Blame History

CLAUDE-backtest.md — 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。

2.3 KiB Raw Blame History Unescape Escape

CLAUDE-backtest.md — 回测引擎 + 参数优化

VectorBTEngine (finance/backtest/vectorbt/engine.py)

策略 (finance/backtest/strategies/)