Preparing Archive
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...
Architectural Overview
"This module is grounded in ai engineering patterns and exposes 1 core capabilities across 1 execution phases."
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.mdfor detailed patterns and examples.
Primary Stack
TypeScript
Tooling Surface
Guide only
Workspace Path
.agents/skills/backtesting-frameworks
Operational Ecosystem
The complete hardware and software toolchain required.
Module Topology
Antigravity Core
Principal Engineering Agent
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