pair-trade-screener

To identify cointegrated pairs for statistical arbitrage, you need to test stock price relationships using ADF testing and OLS regression. This Skill screens sectors to find pairs with long-term equilibrium relationships and generates market-neutral trade signals.

Calculating hedge ratios for a mean reversion strategy requires OLS regression to determine optimal position sizing for market-neutral exposure. This Skill automates that calculation while measuring AR(1) behavior to project how quickly spreads revert to equilibrium.

Yes, you can screen an entire market sector for pair trading opportunities by fetching historical price data via the Financial Modeling Prep API. The Skill processes sector stocks to detect cointegration and output actionable entry and exit signals.

Statistical methods used to test for cointegration in pair trading include the Augmented Dickey-Fuller (ADF) test for stationarity, Ordinary Least Squares (OLS) regression for hedge ratios, and AR(1) modeling to measure mean-reversion speed.

Yes, you need the Financial Modeling Prep API to fetch the historical price data required to run cointegration tests on stocks. The Skill uses this data to perform ADF testing, calculate hedge ratios, and generate trade signals.

A mean reversion pair trade screen may fail to find cointegrated stocks if the ADF test reveals no long-term equilibrium relationship between the assets, or if historical price data lacks sufficient variance to establish reliable statistical thresholds.