signal-validation

What problem does it solve?

This skill provides a structured framework to validate trading signals using statistical methods before deployment, reducing the risk of live losses due to false signals.

Core Features & Use Cases

• Hypothesis testing: Apply p-values to assess signal profitability with defined thresholds.
• Confidence intervals: Use Wilson score intervals to quantify win-rate uncertainty.
• Go/No-Go criteria: Predefine development and production readiness criteria (p-value, sample size, EV) to guide decisions.
• Backtest & Walk-Forward: Evaluate signals across historical and out-of-sample data to detect overfitting.

Quick Start

Review the signal's data, run the validation routines to compute Wilson CI, binomial p-value, information coefficient, and conditional probability, then decide Go/No-Go based on predefined criteria.