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Pair Trade Screener

Pair Trade Screener

by Veeramanikandanr48 · v1.0.0

Research
ClawHub
7.8
/ 10
1 evaluations
1.9k Downloads

Overview

Identifies, tests, and ranks statistically robust pair-trading opportunities (market-neutral, mean-reversion/stat-arb) using correlation, cointegration, spread/z-score analysis, and rule-based entry/exit guidance.

Key Advantages

1.End-to-end statistical arbitrage workflow: universe definition, data fetch, correlation, cointegration, spread/z-score, signal generation, and reporting.
2.Uses established statistical methods (Pearson correlation, ADF cointegration tests, half-life estimation) rather than heuristic screening.
3.Clear, rule-based trading logic for entries, exits, stop-loss, and position sizing geared toward market-neutral exposure.
4.Flexible universe selection: by sector, industry, or explicit ticker lists, with sensible liquidity and market-cap filters.
5.Good documentation of methodology, including references, parameter thresholds, and integration suggestions with other analytical/backtest skills.

Use Cases

  • Screen a sector (e.g., Technology, Financials) for cointegrated stock pairs offering mean-reversion opportunities.
  • Analyze a specific stock pair (e.g., AAPL/MSFT, JPM/BAC) for suitability as a pair trade, including z-score and half-life.
  • Construct or maintain a market-neutral sub-portfolio based on multiple pair trades ranked by statistical strength.
  • Generate pair-trading ideas within a focused industry such as regional banks or utilities.
  • Pre-screen candidate pairs to feed into a separate backtesting or portfolio construction pipeline.

Evaluation Scores

7.8
/ 10
Reliability
7.0
Functionality
8.8
Usability
8.7
Safety
6.5
Performance
7.5
Compatibility
8.0

Based on 1 evaluation · Latest: 3/19/2026

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Evaluation History (1)

7.8/103/19/2026
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OS: win32-x64LLM: stepfun/step-3.5-flash
**Quick judgment** Well-designed, statistically grounded tool for pair-trade screening and analysis. It offers a full pipeline from universe definition to actionable entry/exit suggestions, suitable for users who understand quantitative trading concepts and can supply an FMP API key. **Key strengths** - Robust methodology: correlation + cointegration + z-score + half-life, with clear quality criteria. - Practical trading rules: conservative/aggressive thresholds, stop-loss logic, and market-neutral sizing. - Strong documentation with concrete workflows, CLI options, and output formats. **Main risks / limitations** - Financial risk: Outputs can be mistaken for personalized investment advice; real-world performance depends on execution quality, regime shifts, and transaction costs. - Data dependency: Relies on FMP API (availability, rate limits, and correctness), plus correct API-key configuration. - Model/structural risk: Cointegration relationships can break after corporate events or regime changes; the skill outlines red flags, but users must still apply judgment. **Recommended scenarios** - Quantitative or semi-quantitative users seeking market-neutral, mean-reversion opportunities within liquid equity universes. - Traders or researchers who want a systematic way to generate and rank pair-trading candidates before more detailed backtesting. - Portfolio builders who need a repeatable process to maintain a small book of diversified pair trades alongside other strategies.

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