backtest-expert

Run v4 production-grade backtests and analyze trading strategy results.

Updated Mar 15, 2026

Search Tags:#production #metrics #data-analysis #risk-management #backtesting #trading #walk-forward

Ready to run

npx skills add https://github.com/PasinduUpendra/Binance-Futures-Trading --skill backtest-expert-pasinduupendra

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: backtest-expert
Source: https://github.com/PasinduUpendra/Binance-Futures-Trading/tree/main/.github/skills/backtest-expert
Command: npx skills add https://github.com/PasinduUpendra/Binance-Futures-Trading --skill backtest-expert-pasinduupendra

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Backtesting workflows for Claude Quant enable efficient validation of trading strategies, comparison of backtest versions, and interpretation of key metrics in production-like environments.

Core Features & Use Cases

Production-grade backtests using v4 architecture and real production classes (AdaptiveStrategy, PositionSizer, LeverageManager, VolatilityModel, CircuitBreaker, FeeCalculator, IndicatorEngine).
Walk-forward validation, strategy versioning, and interpretation of Sharpe, PF, win rate, and drawdown across multiple data sets.
Data from user_data and integration with indicator, risk, and execution components to ensure fidelity and reproducibility.

Quick Start

Run the v4 production-backed backtest to validate your strategy's performance.

Frequently Asked Questions about backtest-expert

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

FAQPage Schema

How do I run a walk-forward validation on my trading strategy?▼

Walk-forward validation tests strategy robustness by optimizing parameters on historical segments and evaluating forward periods. This Skill automates the process using v4 production classes and historical data to ensure reproducible results.

What is production-grade backtesting and how does it differ from basic simulations?▼

Production-grade backtesting simulates trades using real risk, indicator, and execution modules rather than simplified assumptions. This Skill applies v4 architecture with production classes to validate strategies accurately.

Can I compare multiple backtest versions to see which strategy performs better?▼

Yes, you can compare backtest versions by running them against identical historical datasets and analyzing metrics. This Skill interprets Sharpe, profit factor, win rate, and drawdown across multiple data sets to highlight differences.

Do I need specific data formats or folder structures for backtesting trading strategies?▼

You need historical data stored in the user_data directory and integration with production indicator, risk, and execution components. This Skill requires v4 production-grade components to ensure fidelity and reproducibility.

What's the best way to validate trading strategy changes before deployment?▼

Validating strategy changes requires running backtests against production-grade data and comparing key metrics. This Skill streamlines the process by applying real risk and execution modules to ensure changes perform under realistic conditions.