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Time consistent behavioral portfolio policy for dynamic mean–variance formulation

Author

Listed:
  • Xiangyu Cui

    (Shanghai University of Finance and Economics)

  • Xun Li

    (The Hong Kong Polytechnic University)

  • Duan Li

    (The Chinese University of Hong Kong)

  • Yun Shi

    (Shanghai University)

Abstract

When one considers an optimal portfolio policy under a mean-risk formulation, it is essential to correctly model investors’ risk aversion which may be time variant or even state dependent. In this paper, we propose a behavioral risk aversion model, in which risk aversion is a piecewise linear function of the current excess wealth level with a reference point at the discounted investment target (either surplus or shortage), to reflect a behavioral pattern with both house money and break-even effects. Due to the time inconsistency of the resulting multi-period mean–variance model with adaptive risk aversion, we investigate the time consistent behavioral portfolio policy by solving a nested mean–variance game formulation. We derive a semi-analytical time consistent behavioral portfolio policy which takes a piecewise linear feedback form of the current excess wealth level with respect to the discounted investment target. Finally, we extend the above results to time consistent behavioral portfolio selection for dynamic mean–variance formulation with a cone constraint.

Suggested Citation

  • Xiangyu Cui & Xun Li & Duan Li & Yun Shi, 2017. "Time consistent behavioral portfolio policy for dynamic mean–variance formulation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(12), pages 1647-1660, December.
  • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:12:d:10.1057_s41274-017-0179-6
    DOI: 10.1057/s41274-017-0179-6
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    1. Napp, C., 2003. "The Dalang-Morton-Willinger theorem under cone constraints," Journal of Mathematical Economics, Elsevier, vol. 39(1-2), pages 111-126, February.
    2. Ying Hu & Hanqing Jin & Xun Yu Zhou, 2012. "Time-Inconsistent Stochastic Linear--Quadratic Control," Post-Print hal-00691816, HAL.
    3. A. Jobert & L. C. G. Rogers, 2008. "Valuations And Dynamic Convex Risk Measures," Mathematical Finance, Wiley Blackwell, vol. 18(1), pages 1-22, January.
    4. Cui, Xiangyu & Gao, Jianjun & Li, Xun & Li, Duan, 2014. "Optimal multi-period mean–variance policy under no-shorting constraint," European Journal of Operational Research, Elsevier, vol. 234(2), pages 459-468.
    5. Suleyman Basak & Georgy Chabakauri, 2010. "Dynamic Mean-Variance Asset Allocation," The Review of Financial Studies, Society for Financial Studies, vol. 23(8), pages 2970-3016, August.
    6. Kang Boda & Jerzy Filar, 2006. "Time Consistent Dynamic Risk Measures," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 63(1), pages 169-186, February.
    7. Richard H. Thaler & Eric J. Johnson, 1990. "Gambling with the House Money and Trying to Break Even: The Effects of Prior Outcomes on Risky Choice," Management Science, INFORMS, vol. 36(6), pages 643-660, June.
    8. Martin Weber & Heiko Zuchel, 2005. "How Do Prior Outcomes Affect Risk Attitude? Comparing Escalation of Commitment and the House-Money Effect," Decision Analysis, INFORMS, vol. 2(1), pages 30-43, March.
    9. R. Horst & N. V. Thoai, 1999. "DC Programming: Overview," Journal of Optimization Theory and Applications, Springer, vol. 103(1), pages 1-43, October.
    10. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    11. Wang, J. & Forsyth, P.A., 2011. "Continuous time mean variance asset allocation: A time-consistent strategy," European Journal of Operational Research, Elsevier, vol. 209(2), pages 184-201, March.
    12. Duan Li & Wan‐Lung Ng, 2000. "Optimal Dynamic Portfolio Selection: Multiperiod Mean‐Variance Formulation," Mathematical Finance, Wiley Blackwell, vol. 10(3), pages 387-406, July.
    13. Rosazza Gianin, Emanuela, 2006. "Risk measures via g-expectations," Insurance: Mathematics and Economics, Elsevier, vol. 39(1), pages 19-34, August.
    14. Yun Shi & Xiangyu Cui & Jing Yao & Duan Li, 2015. "Dynamic Trading with Reference Point Adaptation and Loss Aversion," Operations Research, INFORMS, vol. 63(4), pages 789-806, August.
    15. Cuoco, Domenico, 1997. "Optimal Consumption and Equilibrium Prices with Portfolio Constraints and Stochastic Income," Journal of Economic Theory, Elsevier, vol. 72(1), pages 33-73, January.
    16. Philippe Artzner & Freddy Delbaen & Jean-Marc Eber & David Heath & Hyejin Ku, 2007. "Coherent multiperiod risk adjusted values and Bellman’s principle," Annals of Operations Research, Springer, vol. 152(1), pages 5-22, July.
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    Cited by:

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    2. Liyuan Wang & Zhiping Chen, 2019. "Stochastic Game Theoretic Formulation for a Multi-Period DC Pension Plan with State-Dependent Risk Aversion," Mathematics, MDPI, vol. 7(1), pages 1-16, January.
    3. Xiangyu Cui & Yun Shi & Lu Xu, 2017. "Alleviating time inconsistent behaviors via a competition scheme," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(5), pages 357-372, August.
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    5. Dong-Mei Zhu & Jia-Wen Gu & Feng-Hui Yu & Tak-Kuen Siu & Wai-Ki Ching, 2021. "Optimal pairs trading with dynamic mean-variance objective," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(1), pages 145-168, August.

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