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qka

A-share quantitative backtesting, indicators, and strategy analysis

Generates A-share quantitative trading strategies, backtests, and stock screening code using the QKA framework. Loads market data from baostock, akshare, or QMT and precomputes over 60 technical indicators automatically. Simulates realistic trading with commissions, stamp tax, and slippage, then reports returns, Sharpe ratio, and drawdown. Eliminates manual data cleaning and spreadsheet calculations so strategies can be tested in minutes.
npx skills add zsrl/qka --all -g -y

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Pure Emerald Level Indicators

Frequently Asked Questions

FAQPage Schema
How to install QKA?โ–ผ

Run `npx skills add zsrl/qka --all -g -y` in your terminal to install the skill globally for your coding assistant.

What is QKA used for?โ–ผ

QKA is a Python framework for backtesting quantitative trading strategies on Chinese A-share stocks, with built-in data loading, indicators, position sizing, and performance metrics.

How do I backtest a trading strategy with QKA?โ–ผ

Define a Strategy class with an on_bar method, load data with qka.Data, then call Backtest.run() with your starting cash and date range to get returns, Sharpe ratio, and drawdown metrics.

Which data sources does QKA support?โ–ผ

QKA supports baostock by default, plus akshare and QMT, and can precompute all 60+ indicators from the ta library automatically.

Does QKA work with Claude Code and Cursor?โ–ผ

Yes. Once installed, the skill loads the full QKA API reference so your coding assistant can generate correct strategy and backtest code from plain-English requests.

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