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On the Exact Solution of the Multi-Period Portfolio Choice Problem for an Exponential Utility under Return Predictability

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  • Taras Bodnar
  • Nestor Parolya
  • Wolfgang Schmid

Abstract

In this paper we derive the exact solution of the multi-period portfolio choice problem for an exponential utility function under return predictability. It is assumed that the asset returns depend on predictable variables and that the joint random process of the asset returns and the predictable variables follow a vector autoregressive process. We prove that the optimal portfolio weights depend on the covariance matrices of the next two periods and the conditional mean vector of the next period. The case without predictable variables and the case of independent asset returns are partial cases of our solution. Furthermore, we provide an empirical study where the cumulative empirical distribution function of the investor's wealth is calculated using the exact solution. It is compared with the investment strategy obtained under the additional assumption that the asset returns are independently distributed.

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  • Taras Bodnar & Nestor Parolya & Wolfgang Schmid, 2012. "On the Exact Solution of the Multi-Period Portfolio Choice Problem for an Exponential Utility under Return Predictability," Papers 1207.1037, arXiv.org.
  • Handle: RePEc:arx:papers:1207.1037
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    Cited by:

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    2. Valeria V. Lakshina, 2019. "Do Portfolio Investors Need To Consider The Asymmetry Of Returns On The Russian Stock Market?," HSE Working papers WP BRP 75/FE/2019, National Research University Higher School of Economics.
    3. Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2018. "Estimation of the global minimum variance portfolio in high dimensions," European Journal of Operational Research, Elsevier, vol. 266(1), pages 371-390.
    4. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2021. "Short-Term Exuberance and Long-Term Stability: A Simultaneous Optimization of Stock Return Predictions for Short and Long Horizons," Mathematics, MDPI, vol. 9(6), pages 1-19, March.
    5. Bauder, David & Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2020. "Bayesian inference of the multi-period optimal portfolio for an exponential utility," Journal of Multivariate Analysis, Elsevier, vol. 175(C).
    6. Takuro Hidaka & Jun Sakamoto, 2021. "Predictability of market returns for the UK's former colonies, protectorates, and mandates," Discussion Papers in Economics and Business 21-08, Osaka University, Graduate School of Economics.
    7. Ariah Klages-Mundt & Dominik Harz & Lewis Gudgeon & Jun-You Liu & Andreea Minca, 2020. "Stablecoins 2.0: Economic Foundations and Risk-based Models," Papers 2006.12388, arXiv.org, revised Oct 2020.
    8. Escobar-Anel, Marcos & Gollart, Maximilian & Zagst, Rudi, 2022. "Closed-form portfolio optimization under GARCH models," Operations Research Perspectives, Elsevier, vol. 9(C).
    9. Lu, Jin-Ray & Hwang, Chih-Chiang & Liu, Min-Luan & Lin, Chien-Yi, 2016. "An incentive problem of risk balancing in portfolio choices," The Quarterly Review of Economics and Finance, Elsevier, vol. 61(C), pages 192-200.
    10. Ma, Guiyuan & Siu, Chi Chung & Zhu, Song-Ping, 2019. "Dynamic portfolio choice with return predictability and transaction costs," European Journal of Operational Research, Elsevier, vol. 278(3), pages 976-988.
    11. Ioannis Kyriakou & Parastoo Mousavi & Jens Perch Nielsen & Michael Scholz, 2020. "Short-Term Exuberance and long-term stability: A simultaneous optimization of stock return predictions for short and long horizons," Graz Economics Papers 2020-20, University of Graz, Department of Economics.
    12. Yong-Jun Liu & Wei-Guo Zhang, 2018. "Multiperiod Fuzzy Portfolio Selection Optimization Model Based on Possibility Theory," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 17(03), pages 941-968, May.
    13. Zhou, Zhongbao & Xiao, Helu & Yin, Jialing & Zeng, Ximei & Lin, Ling, 2016. "Pre-commitment vs. time-consistent strategies for the generalized multi-period portfolio optimization with stochastic cash flows," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 187-202.
    14. Taras Bodnar & Yarema Okhrin & Valdemar Vitlinskyy & Taras Zabolotskyy, 2018. "Determination and estimation of risk aversion coefficients," Computational Management Science, Springer, vol. 15(2), pages 297-317, June.
    15. Dmytro Ivasiuk, 2019. "An approximate solution for the power utility optimization under predictable returns," Papers 1911.06552, arXiv.org, revised Oct 2021.
    16. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wolfgang Schmid, 2023. "Multi-period power utility optimization under stock return predictability," Computational Management Science, Springer, vol. 20(1), pages 1-27, December.
    17. Taras Bodnar & Dmytro Ivasiuk & Nestor Parolya & Wofgang Schmid, 2018. "Mean-Variance Efficiency of Optimal Power and Logarithmic Utility Portfolios," Papers 1806.08005, arXiv.org, revised May 2019.

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