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Adaptive universal portfolios

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  • Patrick O'Sullivan
  • David Edelman

Abstract

In this article, we consider Cover's universal portfolio and the problem of multi-period investment in a nonparametric setting. We show that Cover's universal portfolio is equivalent to a Bayes estimator of the optimal growth portfolio. However, as noted by Cover, it can take a long time for the universal portfolio to produce significant growth. Therefore, we propose the adaptive universal portfolio, which retains much of the qualitative nature of Cover's universal portfolio while enhancing early performance. An empirical study is carried out over a range of exchange traded funds over a 5 year period, which exhibits the enhanced early performance generated by the adaptive universal portfolio.

Suggested Citation

  • Patrick O'Sullivan & David Edelman, 2015. "Adaptive universal portfolios," The European Journal of Finance, Taylor & Francis Journals, vol. 21(4), pages 337-351, March.
    • Handle: RePEc:taf:eurjfi:v:21:y:2015:i:4:p:337-351
    DOI: 10.1080/1351847X.2013.788534
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    Cited by:

    1. Xingyu Yang & Jin’an He & Hong Lin & Yong Zhang, 2020. "Boosting Exponential Gradient Strategy for Online Portfolio Selection: An Aggregating Experts’ Advice Method," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 231-251, January.
    2. Esther Mohr & Robert Dochow, 2017. "Risk management strategies for finding universal portfolios," Annals of Operations Research, Springer, vol. 256(1), pages 129-147, September.
    3. Yong Zhang & Hong Lin & Lina Zheng & Xingyu Yang, 2022. "Adaptive online portfolio strategy based on exponential gradient updates," Journal of Combinatorial Optimization, Springer, vol. 43(3), pages 672-696, April.

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