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Dynamic portfolio selection with mispricing and model ambiguity

Author

Listed:
  • Bo Yi
  • Frederi Viens
  • Baron Law
  • Zhongfei Li

Abstract

We investigate optimal portfolio selection problems with mispricing and model ambiguity under a financial market which contains a pair of mispriced stocks. We assume that the dynamics of the pair satisfies a “cointegrated system” advanced by Liu and Timmermann in a 2013 manuscript. The investor hopes to exploit the temporary mispricing by using a portfolio strategy under a utility function framework. Furthermore, she is ambiguity-averse and has a specific preference for model ambiguity robustness. The explicit solution for such a robust optimal strategy, and its value function, are derived. We analyze these robust strategies with mispricing in two cases: observed and unobserved mean-reverting stochastic risk premium. We show that the mispricing and model ambiguity have completely distinct impacts on the robust optimal portfolio selection, by comparing the utility losses. We also find that the ambiguity-averse investor who ignores the mispricing or the model ambiguity, suffers a substantially larger utility loss if the risk premium is unobserved, compared to when it is observed. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Bo Yi & Frederi Viens & Baron Law & Zhongfei Li, 2015. "Dynamic portfolio selection with mispricing and model ambiguity," Annals of Finance, Springer, vol. 11(1), pages 37-75, February.
    • Handle: RePEc:kap:annfin:v:11:y:2015:i:1:p:37-75
    DOI: 10.1007/s10436-014-0252-y
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    References listed on IDEAS

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    Cited by:

    1. Wang, Ning & Zhang, Yumo, 2023. "Robust optimal asset-liability management with mispricing and stochastic factor market dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 113(C), pages 251-273.
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    3. Gu, Ailing & Viens, Frederi G. & Yao, Haixiang, 2018. "Optimal robust reinsurance-investment strategies for insurers with mean reversion and mispricing," Insurance: Mathematics and Economics, Elsevier, vol. 80(C), pages 93-109.
    4. Luciano I. Castro & Marialaura Pesce & Nicholas C. Yannelis, 2020. "A new approach to the rational expectations equilibrium: existence, optimality and incentive compatibility," Annals of Finance, Springer, vol. 16(1), pages 1-61, March.
    5. Yumo Zhang, 2021. "Dynamic Optimal Mean-Variance Investment with Mispricing in the Family of 4/2 Stochastic Volatility Models," Mathematics, MDPI, vol. 9(18), pages 1-25, September.
    6. Wang, Ning & Siu, Tak Kuen, 2024. "Investment–consumption optimization with transaction cost and learning about return predictability," European Journal of Operational Research, Elsevier, vol. 318(3), pages 877-891.
    7. Cristina Sacala, 2016. "Portfolio Dynamics. A Macroeconomic Model," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 6(3), pages 170-176, July.
    8. Daniela Neykova & Marcos Escobar & Rudi Zagst, 2015. "Optimal investment in multidimensional Markov-modulated affine models," Annals of Finance, Springer, vol. 11(3), pages 503-530, November.
    9. Zeng, Yan & Li, Danping & Gu, Ailing, 2016. "Robust equilibrium reinsurance-investment strategy for a mean–variance insurer in a model with jumps," Insurance: Mathematics and Economics, Elsevier, vol. 66(C), pages 138-152.
    10. Cheng, Bingqian & Wang, Hao & Zhang, Lihong, 2024. "Robust investment for insurers with correlation ambiguity," The Quarterly Review of Economics and Finance, Elsevier, vol. 93(C), pages 247-257.
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    12. Hu, Duni & Wang, Hailong, 2019. "Reinsurance contract design when the insurer is ambiguity-averse," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 241-255.

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    More about this item

    Keywords

    Portfolio selection; Model ambiguity; Mispricing ; Stochastic risk premium; Robust control; Utility maximization; C61; G11; G17; G22;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies

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