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Multi-period portfolio optimization under probabilistic risk measure

Author

Listed:
  • Sun, Yufei
  • Aw, Grace
  • Teo, Kok Lay
  • Zhu, Yanjian
  • Wang, Xiangyu

Abstract

This paper develops a minimax model for a multi-period portfolio selection problem. An analytical solution is obtained and numerical simulations demonstrate the superiority of the multi-period model over its corresponding single period one, as well as over the market index.

Suggested Citation

  • Sun, Yufei & Aw, Grace & Teo, Kok Lay & Zhu, Yanjian & Wang, Xiangyu, 2016. "Multi-period portfolio optimization under probabilistic risk measure," Finance Research Letters, Elsevier, vol. 18(C), pages 60-66.
  • Handle: RePEc:eee:finlet:v:18:y:2016:i:c:p:60-66
    DOI: 10.1016/j.frl.2016.04.001
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    Cited by:

    1. Longsheng Cheng & Mahboubeh Shadabfar & Arash Sioofy Khoojine, 2023. "A State-of-the-Art Review of Probabilistic Portfolio Management for Future Stock Markets," Mathematics, MDPI, vol. 11(5), pages 1-34, February.
    2. Sanford, Anthony, 2022. "Optimized portfolio using a forward-looking expected tail loss," Finance Research Letters, Elsevier, vol. 46(PB).
    3. Bo Li & Yufei Sun & Kok Lay Teo, 2022. "An analytic solution for multi-period uncertain portfolio selection problem," Fuzzy Optimization and Decision Making, Springer, vol. 21(2), pages 319-333, June.
    4. Kamali, Rezvan & Mahmoodi, Safieh & Jahandideh, Mohammad-Taghi, 2019. "Optimization of multi-period portfolio model after fitting best distribution," Finance Research Letters, Elsevier, vol. 30(C), pages 44-50.

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    More about this item

    Keywords

    Portfolio optimization; Probability risk measure; Discrete-time optimal control; Dynamic programming;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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