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Optimal Convergence Trading with Unobservable Pricing Errors

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  • Suhan Altay
  • Katia Colaneri
  • Zehra Eksi

Abstract

We study a dynamic portfolio optimization problem related to convergence trading, which is an investment strategy that exploits temporary mispricing by simultaneously buying relatively underpriced assets and selling short relatively overpriced ones with the expectation that their prices converge in the future. We build on the model of Liu and Timmermann (2013) and extend it by incorporating unobservable Markov-modulated pricing errors into the price dynamics of two co-integrated assets. We characterize the optimal portfolio strategies in full and partial information settings both under the assumption of unrestricted and beta-neutral strategies. By using the innovations approach, we provide the filtering equation that is essential for solving the optimization problem under partial information. Finally, in order to illustrate the model capabilities, we provide an example with a two-state Markov chain.

Suggested Citation

  • Suhan Altay & Katia Colaneri & Zehra Eksi, 2019. "Optimal Convergence Trading with Unobservable Pricing Errors," Papers 1910.01438, arXiv.org, revised Oct 2019.
    • Handle: RePEc:arx:papers:1910.01438
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    References listed on IDEAS

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    2. Lei, Yaoting & Xu, Jing, 2015. "Costly arbitrage through pairs trading," Journal of Economic Dynamics and Control, Elsevier, vol. 56(C), pages 1-19.
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    4. Suhan Altay & Katia Colaneri & Zehra Eksi, 2017. "Pairs Trading under Drift Uncertainty and Risk Penalization," Papers 1704.06697, arXiv.org, revised Sep 2018.
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    Cited by:

    1. Katia Colaneri & Stefano Herzel & Marco Nicolosi, 2021. "The value of knowing the market price of risk," Annals of Operations Research, Springer, vol. 299(1), pages 101-131, April.

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