Runs MLR-based predictive analysis on GitHub data for repository insights.
npx skills add https://github.com/KeynesZZZ/Common --skill a-stock-backtest
Please help me install this Agent Skill. Skill: a-stock-backtest Source: https://github.com/KeynesZZZ/Common/tree/main/.trae/skills/a-stock-backtest Command: npx skills add https://github.com/KeynesZZZ/Common --skill a-stock-backtest
This tool provides an end-to-end backtesting workflow for A-share strategies by converting local 60-minute bar data into daily bars, storing results in SQLite, and enabling full-market testing, parameter configuration, visualization, and strategy comparison.
Run a default backtest with your local 60-minute A-share data and review the output.
High-intent search queries and answers about installing and using this skill.
To backtest A-share strategies, this tool automatically converts locally stored 60-minute bar data into daily bars and runs full-market testing across user-defined historical periods.
Yes, full-market A-share backtesting supports configurable parameters including holding periods, risk controls, costs, and flexible stock pools to evaluate strategy performance.
60-minute data aggregation works by converting local intraday bars into daily bars, then efficiently storing the transformed results in an SQLite database for backtesting.
The best way to compare multiple A-share strategies is by running side-by-side tests that generate visualizations and reports for performance, drawdown, and parameter optimization.
Yes, you need locally stored 60-minute A-share bar data available beforehand, as the backtest workflow relies on converting this local data into daily bars for analysis.
wudyeRetrieve minute OHLCV data and compute VWAP, TWAP, and volume metrics.
xingwudaoEvaluate open-xquant backtest metrics and audit findings to determine strategy viability.
monarchjunoDesign and evaluate quantitative investment signals from hypothesis through validation.
GGwujunFetch A-share OHLCV and intraday data via the Mootdx TCP protocol.
