AI Agent Skill HUB

backtesting-frameworks

Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strateg...

6 stars
bynetbarros
View on GitHubInstallation ↓

Best use case

backtesting-frameworks is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strateg...

Teams using backtesting-frameworks should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/backtesting-frameworks/SKILL.md --create-dirs "https://raw.githubusercontent.com/netbarros/psique/main/.codex/skills/backtesting-frameworks/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/backtesting-frameworks/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How backtesting-frameworks Compares

Feature / Agentbacktesting-frameworksStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Build robust backtesting systems for trading strategies with proper handling of look-ahead bias, survivorship bias, and transaction costs. Use when developing trading algorithms, validating strateg...

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Backtesting Frameworks

Build robust, production-grade backtesting systems that avoid common pitfalls and produce reliable strategy performance estimates.

## Use this skill when

- Developing trading strategy backtests
- Building backtesting infrastructure
- Validating strategy performance and robustness
- Avoiding common backtesting biases
- Implementing walk-forward analysis

## Do not use this skill when

- You need live trading execution or investment advice
- Historical data quality is unknown or incomplete
- The task is only a quick performance summary

## Instructions

- Define hypothesis, universe, timeframe, and evaluation criteria.
- Build point-in-time data pipelines and realistic cost models.
- Implement event-driven simulation and execution logic.
- Use train/validation/test splits and walk-forward testing.
- If detailed examples are required, open `resources/implementation-playbook.md`.

## Safety

- Do not present backtests as guarantees of future performance.
- Avoid providing financial or investment advice.

## Resources

- `resources/implementation-playbook.md` for detailed patterns and examples.

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