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Backtest A-share quant strategies with natural language and compare results fast.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "TickTest — A股量化回测" MCP server from askskill: Run: claude mcp add 'io-github-shakagold-ticktest-mcp' -- npx -y ticktest-mcp
Please backtest an A-share single moving average strategy: buy when the close crosses above the 20-day MA and sell when it crosses below. Return total return, max drawdown, and trade count.
A backtest summary with key performance and risk metrics for the single MA strategy.
Compare three dual moving average parameter sets in A-shares: 5/20, 10/30, and 20/60 days. Rank them by return and drawdown.
A comparison of multiple dual MA backtests to help select a better parameter combination.
Backtest a cross-timeframe strategy: use weekly moving averages for trend judgment and daily signals for execution, then provide the results.
Backtest results for the cross-timeframe strategy showing its historical performance in A-shares.
A data analyst or researcher can describe an A-share strategy in natural language and quickly get historical backtest results, reducing the need to write backtest code first. It is useful for validating an idea before deeper research.
When a user wants to compare single MA, dual MA, or different period settings, this tool helps run side-by-side backtests quickly. It is suitable for screening more promising strategy configurations.
Users can try cross-timeframe combinations or Turtle trading-related rules and examine their historical behavior in A-shares. It is suitable for exploring the feasibility of different trading logics.
No documentation provided
Check the source repo for usage and examples.
It is an A-share quantitative backtesting MCP server that lets an AI agent run backtests through natural language. The description explicitly mentions single MA, dual MA, arbitrary periods, cross-timeframe combinations, and Turtle trading-related backtests.
Based on the description, it emphasizes letting an AI agent backtest A-shares with natural language, so the core workflow does not require writing complex backtest logic first. For exact interfaces and usage details, see the source repository.
It is stated to support single moving average, dual moving average, arbitrary periods, cross-timeframe combinations, and Turtle trading. The provided materials do not confirm additional strategy types, so see the source repository for more.
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