Pearson-Correlation Pairs Trading with Return-Divergence Ranking

Summary

The Pearson approach forms equity pairs by ranking stocks on the correlation of their monthly returns during a formation period. For each stock, it selects the most highly correlated peers and combines their returns into a benchmark portfolio, using either equal weights or weights proportional to correlation. A regression between a stock’s returns and its pairs-portfolio returns supplies a beta used to calculate risk-adjusted return divergence, with the risk-free rate included in the definition.

For each subsequent month, stocks are sorted by the prior month’s divergence. The highest-ranked fraction becomes the long side and the lowest-ranked fraction the short side; equal fractions produce a dollar-neutral selection by count. The peer portfolio is a sorting benchmark, while the individual stock itself enters the traded portfolio. The description explains formation and signal construction and notes that pairwise correlation computation can be intensive, motivating monthly data. It provides no performance figures here, and correlation-based relationships may change; the method’s results depend on formation choices, portfolio weights, and testing assumptions.

Key ideas

• The method selects each stock’s peers using correlations of monthly returns in a formation period.
• Peer returns are aggregated with equal weights or weights proportional to their correlations.
• Regression beta and the risk-free rate are used to measure a stock’s return divergence from its peer portfolio.
• Stocks are ranked by prior-month divergence to select long and short positions.
• The peer portfolio supplies a ranking benchmark, while only ranked individual stocks enter the constructed portfolio.
• Monthly data reduces computational demands, but the document provides no performance results.

Tags

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.