A survey of statistical arbitrage pairs trading strategies with non-machine learning methods, 2016-2023

Yufei Sun ()
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Yufei Sun: Faculty of Economic Sciences, University of Warsaw

No 2025-19, Working Papers from Faculty of Economic Sciences, University of Warsaw

Abstract: This review examines the growing literature on pairs trading frameworks, which involve relative value arbitrage strategies between two or more securities. Existing research is categorized into five main categories: distance methods use nonparametric distance measures to identify pairs trading opportunities; cointegration methods rely on formal cointegration tests to reveal stationary time series of spreads; time series methods focus on finding optimal trading rules for mean-reverting spreads; stochastic control methods aim to determine the optimal portfolio holdings in pairs trading relative to other available securities; and the "Other Methods" category encompasses other relevant pairs trading frameworks, albeit with a more limited supporting literature. Through a comprehensive review of over 100 papers published between 2016 and 2023, the survey identifies the key strengths and weaknesses of each approach, providing insights relevant for future research and practical implementation.

Keywords: statistical arbitrage; pairs trading; distance method; cointegration method; time series method; stochastic control method; mean-reversion (search for similar items in EconPapers)
JEL-codes: C32 C58 C63 G11 G14 (search for similar items in EconPapers)
Pages: 100 pages
Date: 2025
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