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Partial cointegration is a weakening of cointegration that allows for the ‘cointegrating’ residual to contain a random walk and a mean-reverting component. We derive its representation in state space, provide a maximum likelihood-based estimation routine, and a suitable likelihood ratio test. Then, we explore the use of partial cointegration as a means for identifying promising pairs and for generating buy and sell signals. Specifically, we benchmark partial cointegration against several classical pairs trading variants from 1990 until 2015, on a survivor bias free data-set of the S&P 500 constituents. We find annualized returns of more than 12% after transaction costs. These results can only partially be explained by common sources of systematic risk and are well superior to classical distance-based or cointegration-based pairs trading variants on our data-set.

Acknowledgements

We are grateful to Thomas Fischer, Michael Grottke, Nicolas Huck, Ingo Klein, Jerzy Pawlowski, Jonas Rende, Johannes Stübinger, and two anonymous referees for many helpful discussions and suggestions on this topic.

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