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Mixed-asset portfolio allocation under mean-reverting asset returns

Author

Listed:
  • Charles-Olivier Amédée-Manesme

    () (Laval University)

  • Fabrice Barthélémy

    () (University of Versailles Saint-Quentin-en-Yvelines)

  • Philippe Bertrand

    () (Aix-Marseille Graduate School of Management - IAE, CERGAM and AMSE
    KEDGE BS)

  • Jean-Luc Prigent

    () (University of Cergy-Pontoise)

Abstract

Standard results about portfolio optimization suggest that the allocation to real estate in a mixed-asset portfolio should be around 15–20%. However, the institutional investors share in real estate is significantly smaller, around 7–9%. Many researches have addressed this point even if as of today no consensus has emerged. In this paper, we built-up an allocation model that can explain the empirical observed weights. For this purpose, we account for the term structure of all standard financial assets and also of real estate asset class (expected returns, volatilities and correlations depending on the time to maturity). We propose a dynamic portfolio optimization model that allows analyzing portfolio weights with respect to the whole term structure modelling, due to its tractability and its good fit when being adequately calibrated. In this framework, we provide explicit and operational solutions to the dynamic mixed-asset portfolio allocation (cash, real estate, stock and bond). The results show that accounting for investment horizon and mean-reverting dynamics allows to better examine how portfolio allocations depend on both risk aversion and investment horizon.

Suggested Citation

  • Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Philippe Bertrand & Jean-Luc Prigent, 2019. "Mixed-asset portfolio allocation under mean-reverting asset returns," Annals of Operations Research, Springer, vol. 281(1), pages 65-98, October.
  • Handle: RePEc:spr:annopr:v:281:y:2019:i:1:d:10.1007_s10479-018-2761-y
    DOI: 10.1007/s10479-018-2761-y
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