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Optimal Portfolios under Time-Varying Investment Opportunities, Parameter Uncertainty, and Ambiguity Aversion

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  • Dangl, Thomas
  • Weissensteiner, Alex

Abstract

We study the implications of predictability on the optimal asset allocation of ambiguity-averse long-term investors and analyze the term structure of the multivariate risk–return trade-off considering parameter uncertainty. We calibrate the model to real returns of U.S. stocks, long-term bonds, cash, real estate, and gold using the term spread and the dividend–price ratio as additional predictive variables, and we show that over long horizons, the optimal asset allocation is significantly influenced by the covariance structure induced by estimation errors. The ambiguity-averse long-term investor optimally tilts his or her portfolio toward a seemingly inefficient portfolio, which shows maximum robustness against estimation errors.

Suggested Citation

  • Dangl, Thomas & Weissensteiner, Alex, 2020. "Optimal Portfolios under Time-Varying Investment Opportunities, Parameter Uncertainty, and Ambiguity Aversion," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(4), pages 1163-1198, June.
    • Handle: RePEc:cup:jfinqa:v:55:y:2020:i:4:p:1163-1198_4
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    Cited by:

    1. Mykola Babiak & Jozef Barunik, 2020. "Deep Learning, Predictability, and Optimal Portfolio Returns," Papers 2009.03394, arXiv.org, revised Jul 2021.
    2. Wang, Jiarui & Liu, Shancun & Yang, Haijun, 2022. "Institutional investor’ proportions and inactive trading," International Review of Financial Analysis, Elsevier, vol. 82(C).
    3. Andrea Rigamonti & Alex Weissensteiner, 2020. "Asset allocation under predictability and parameter uncertainty using LASSO," Computational Management Science, Springer, vol. 17(2), pages 179-201, June.
    4. Julian Holzermann, 2023. "Optimal Investment with Stochastic Interest Rates and Ambiguity," Papers 2306.13343, arXiv.org, revised Oct 2023.

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