Pair Trade Screener

This is a statistical arbitrage screener that finds cointegrated stock pairs for market-neutral trading. It runs correlation analysis and Augmented Dickey-Fuller tests to identify pairs with mean-reverting spreads, then calculates z-scores to signal entry and exit points. The workflow is thorough: pulls two years of price data, filters by correlation thresholds (0.70+), validates cointegration (p < 0.05), and calculates half-life for mean-reversion speed. You'd use this if you're building pairs trades in specific sectors or want hedged positions that profit from relative moves rather than directional bets. The methodology is solid and well-documented, though you'll need clean data and patience since it's designed for systematic strategies, not quick scalps.

skills.sh installs: 3.6K
GitHub stars: 3.7K
last updated: Aug 21, 2026

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Install

$ npx -y skills add tradermonty/claude-trading-skills --skill pair-trade-screener --agent claude-code

Installs into .claude/skills of the current project.

Files

Pair Trade Screener

Overview

This skill identifies and analyzes statistical arbitrage opportunities through pair trading. Pair trading is a market-neutral strategy that profits from the relative price movements of two correlated securities, regardless of overall market direction. The skill uses rigorous statistical methods including correlation analysis and cointegration testing to find robust trading pairs.

Core Methodology:

Identify pairs of stocks with high correlation and similar sector/industry exposure
Test for cointegration (long-term statistical relationship)
Calculate spread z-scores to identify mean-reversion opportunities
Generate entry/exit signals based on statistical thresholds
Provide position sizing for market-neutral exposure

Key Advantages: