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配对交易策略，通过协整检验寻找长期均衡关系并基于价差均值回归生成交易信号。适用于量化金融教学与统计套利概念演示；基于简化协整模型，不适用于实盘交易。
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| name | pairs-trading |
| description | 配对交易策略，通过协整检验寻找长期均衡关系并基于价差均值回归生成交易信号。适用于量化金融教学与统计套利概念演示；基于简化协整模型，不适用于实盘交易。 |
| version | 1.0.0 |
| author | wangyi |
配对交易策略：通过协整检验寻找具有长期均衡关系的两只股票，基于价差的均值回归特性生成交易信号。
📌 说明：本工具基于简化模型实现，仅使用 Python 标准库。结果仅供学习参考，不构成投资建议或交易依据。
calc_mean(data)计算列表的算术平均值。 必填: data
calc_variance(data, ddof=1)计算列表的方差。 必填: data
calc_std(data, ddof=1)计算列表的标准差。 必填: data
calc_covariance(data_a, data_b)计算两个等长列表的协方差。 必填: data_a, data_b
calc_hedge_ratio(prices_a, prices_b)通过最小二乘法计算对冲比率 β。 必填: prices_a, prices_b
calc_spread(prices_a, prices_b, hedge_ratio)计算价差序列。 必填: prices_a, prices_b, hedge_ratio
simplified_adf_test(spread)简化版 ADF（Augmented Dickey-Fuller）检验。 必填: spread
rolling_zscore(spread, window=20)计算滚动 Z-score。 必填: spread
generate_signals(z_scores, entry_threshold=2.0, exit_threshold=0.5)生成配对交易信号。 必填: z_scores
calc_stats(signals, spread)计算策略统计信息。 必填: signals, spread
run_pairs_trading(prices_a, prices_b, window=20, entry_threshold=2.0, exit_threshold=0.5)运行完整的配对交易策略。 必填: prices_a, prices_b
python scripts/main.py \
--prices-a <prices_a> \
--prices-b <prices_b> \
--window <window> \
--entry-threshold <entry_threshold> \
--exit-threshold <exit_threshold>