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Portfolio optimization: A multi-period model with dynamic risk preference and minimum lots of transaction

Author

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  • Liu, Yiying
  • Zhou, Yongbin
  • Niu, Juanjuan

Abstract

Sufficient description of stock returns is essential to generate an efficient model of portfolio optimization. Security returns are considered to be random variables where there exist sufficient data of historical returns. Nonetheless, uncertain variables may be applied to increase the effectiveness of security returns. The following research entails an optimization objective problem focusing on minimum lots of transaction in uncertain environments of dynamic trading. Also, the changing risk preference of the investor over the horizon of investment has been factored in the model. An average- Value at Risk (VaR) framework has been used to maximize wealth creation using genetic algorithms.

Suggested Citation

  • Liu, Yiying & Zhou, Yongbin & Niu, Juanjuan, 2023. "Portfolio optimization: A multi-period model with dynamic risk preference and minimum lots of transaction," Finance Research Letters, Elsevier, vol. 55(PB).
    • Handle: RePEc:eee:finlet:v:55:y:2023:i:pb:s1544612323003367
    DOI: 10.1016/j.frl.2023.103964
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    References listed on IDEAS

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    1. W. Brent Lindquist & Svetlozar T. Rachev & Yuan Hu & Abootaleb Shirvani, 2022. "Dynamic Portfolio Optimization: Beyond MPT," Dynamic Modeling and Econometrics in Economics and Finance, in: Advanced REIT Portfolio Optimization, chapter 0, pages 93-112, Springer.
    2. Hiroshi Konno & Annista Wijayanayake, 2001. "Minimal Cost Index Tracking Under Nonlinear Transaction Costs And Minimal Transaction Unit Constraints," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 4(06), pages 939-957.
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