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重组目录结构：将策略文件移至 quant 子目录

- 创建 quant/ 子目录存放所有策略相关文件
- 保留根目录配置文件（AGENTS.md, SOUL.md等）
- quant/ 目录包含：
  * 策略脚本（cyb50_*.py）
  * 数据文件（cyb50_*.csv）
  * 回测图表（train_*.png, val_*.png）
  * 文档（回测验证报告.md, 策略方案详解.md）
openclaw 3 mesi fa
parent
d00c6ed377
commit
7913a894e5
44 ha cambiato i file con 0 aggiunte e 0 eliminazioni
Visualizzazione separata Mostra Diff Stats
  1. 0 0
      quant/cyb50_all_strategies_real_data.py
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      quant/cyb50_baostock.csv
  3. 0 0
      quant/cyb50_data.csv
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      quant/cyb50_high_perf.py
  5. 0 0
      quant/cyb50_historical.py
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      quant/cyb50_historical_data.csv
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      quant/cyb50_multifactor.py
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      quant/cyb50_real_backtest.py
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      quant/cyb50_realistic.py
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      quant/cyb50_realistic_data.csv
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      quant/cyb50_simple.py
  12. 0 0
      quant/cyb50_strategy.py
  13. 0 0
      quant/cyb50_trend.py
  14. 0 0
      quant/cyb50_ultimate.py
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      quant/train_RSI策略.png
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      quant/train_high_perf.png
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      quant/train_historical.png
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      quant/train_multifactor.png
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      quant/train_real_data.png
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      quant/train_trend.png
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      quant/train_ultimate.png
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      quant/train_动量策略.png
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      quant/train_双均线策略.png
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      quant/train_多因子策略.png
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      quant/train_趋势跟踪策略.png
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      quant/val_RSI策略.png
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      quant/val_high_perf.png
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      quant/val_stable.png
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      quant/val_动量策略.png
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      quant/val_多因子策略.png
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      quant/回测验证报告.md
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      quant/策略方案详解.md

cyb50_all_strategies_real_data.py → quant/cyb50_all_strategies_real_data.py
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cyb50_baostock.csv → quant/cyb50_baostock.csv
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cyb50_data.csv → quant/cyb50_data.csv
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cyb50_high_perf.py → quant/cyb50_high_perf.py
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cyb50_historical.py → quant/cyb50_historical.py
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cyb50_historical_data.csv → quant/cyb50_historical_data.csv
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cyb50_multifactor.py → quant/cyb50_multifactor.py
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cyb50_real_backtest.py → quant/cyb50_real_backtest.py
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cyb50_realistic.py → quant/cyb50_realistic.py
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cyb50_realistic_data.csv → quant/cyb50_realistic_data.csv
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cyb50_simple.py → quant/cyb50_simple.py
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cyb50_strategy.py → quant/cyb50_strategy.py
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cyb50_trend.py → quant/cyb50_trend.py
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cyb50_ultimate.py → quant/cyb50_ultimate.py
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train_RSI策略.png → quant/train_RSI策略.png
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train_high_perf.png → quant/train_high_perf.png
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train_historical.png → quant/train_historical.png
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train_multifactor.png → quant/train_multifactor.png
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train_real_data.png → quant/train_real_data.png
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train_realistic.png → quant/train_realistic.png
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train_results.png → quant/train_results.png
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train_stable.png → quant/train_stable.png
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train_trend.png → quant/train_trend.png
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train_ultimate.png → quant/train_ultimate.png
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train_动量策略.png → quant/train_动量策略.png
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train_双均线策略.png → quant/train_双均线策略.png
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train_多因子策略.png → quant/train_多因子策略.png
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train_趋势跟踪策略.png → quant/train_趋势跟踪策略.png
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val_RSI策略.png → quant/val_RSI策略.png
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val_high_perf.png → quant/val_high_perf.png
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val_historical.png → quant/val_historical.png
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val_multifactor.png → quant/val_multifactor.png
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val_real_data.png → quant/val_real_data.png
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val_realistic.png → quant/val_realistic.png
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val_results.png → quant/val_results.png
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val_stable.png → quant/val_stable.png
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val_trend.png → quant/val_trend.png
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val_ultimate.png → quant/val_ultimate.png
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val_动量策略.png → quant/val_动量策略.png
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val_双均线策略.png → quant/val_双均线策略.png
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val_多因子策略.png → quant/val_多因子策略.png
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val_趋势跟踪策略.png → quant/val_趋势跟踪策略.png
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回测验证报告.md → quant/回测验证报告.md
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策略方案详解.md → quant/策略方案详解.md
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