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strategy-backtester

Backtest trading strategies with historical data and technical indicators.

50|17|Updated Mar 30, 2026
Search Tags:#performance#parameters#MVP#strategy#historical-data#risk#backtest
One-click install
npx skills add https://github.com/shaoxing-xie/openclaw-data-china-stock --skill strategy-backtester
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: strategy-backtester
Source: https://github.com/shaoxing-xie/openclaw-data-china-stock/tree/main/skills/strategy-backtester
Command: npx skills add https://github.com/shaoxing-xie/openclaw-data-china-stock --skill strategy-backtester

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Strategy evaluation often requires dedicated backtesting tools that are complex and hard to configure. This Skill provides a lightweight backtesting orchestration that uses historical market data and technical indicators to generate performance insights.

Core Features & Use Cases

  • Lightweight backtest orchestration that requires no external backtesting engine.
  • Outputs structured performance metrics (收益, risk, win rate) for strategy comparison.
  • Use Case: compare SMA crossover and RSI reversion strategies using predefined grids from config/strategy-backtester_config.yaml.

Quick Start

Provide a strategy descriptor and historical data to generate a backtest report with key metrics.

Frequently Asked Questions about strategy-backtester

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run a lightweight backtest for trading strategies without installing a complex engine?▼

You can perform lightweight backtesting by providing a strategy descriptor and historical data, which generates structured performance metrics without requiring an external backtesting engine.

What performance and risk metrics are included in a strategy backtest report?▼

A strategy backtest report includes structured performance metrics covering returns, risk metrics, and trade statistics, enabling direct comparison across multiple rule sets.

Can I compare different trading strategies using predefined parameter grids?▼

Yes, you can compare strategies like SMA crossover and RSI reversion by reading parameter grids from config/strategy-backtester_config.yaml to evaluate parameter sensitivity.

What do I need to provide to generate a backtest report with this tool?▼

You need to provide a strategy descriptor and historical market data to generate a backtest report containing strategy specifications, backtest windows, and performance insights.

Does strategy backtesting work for MVP constraints using built-in data tools?▼

Yes, this backtesting approach satisfies MVP constraints by using built-in data tools to process historical data and technical indicators without external dependencies.

Are there limitations to using lightweight backtesting for parameter optimization?▼

Lightweight backtesting focuses on MVP constraints and uses predefined parameter grids from a config file, meaning it lacks the advanced customization of dedicated external backtesting engines.

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