---
name: backtesting-frameworks-5d800b5f722d
description: 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 strategies, or building backtesting infrastructure.
---

# 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.


---
Source attribution: rmyndharis
Original project: https://github.com/rmyndharis/antigravity-skills/blob/364ea63c190fcf7cac035f7fa91f0406fa392584/skills/backtesting-frameworks/SKILL.md
License: MIT
License information: https://opensource.org/license/mit
Original upstream instructions; downloaded from Mega AI Hub.

## Upstream license notice

MIT License

Copyright (c) 2026 Yudhi Armyndharis

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.



# Mega AI Hub resource metadata

Creator / publisher: rmyndharis
Original project: https://github.com/rmyndharis/antigravity-skills/blob/364ea63c190fcf7cac035f7fa91f0406fa392584/skills/backtesting-frameworks/SKILL.md
Attribution basis: Source repository record

Fields of work: Data & Analytics, Development & Engineering, Finance & Accounting, Marketing, Product Management
Roles: Data Analyst, Financial Analyst, Growth Marketer, ML / AI Engineer, Product Manager
Specialties: API, Backend
Tools: Trading Platforms
Country applicability: Country not specified
Classification basis: Source catalog labels
Instruction SHA-256: 30a05933b82e43ebbb2f7b66cbccdd5153119d2d197db305b618e8977df922e2