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Optimization of multi-period portfolio model after fitting best distribution

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  • Kamali, Rezvan
  • Mahmoodi, Safieh
  • Jahandideh, Mohammad-Taghi

Abstract

In this paper, we use a multi-periodic portfolio selection algorithm to maximum the investor wealth using probabilistic risk measure. We use ASX100 stock data from 2015 to 2017 with 36 periods, 100 stocks and 725 days. Then we examine and use T-student, stable and kernel distributions to improve and optimize the multi-period portfolio optimization model. Kolmogorov-Smirnov test indicates that these distributions fit the experimental data better in comparison with normal distribution. Furthermore, kernel density estimator is the best density function to fit returns.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:finlet:v:30:y:2019:i:c:p:44-50
    DOI: 10.1016/j.frl.2019.03.027
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    References listed on IDEAS

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    1. Righi, Marcelo Brutti & Borenstein, Denis, 2018. "A simulation comparison of risk measures for portfolio optimization," Finance Research Letters, Elsevier, vol. 24(C), pages 105-112.
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    3. 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.
    4. Liu, Yong-Jun & Zhang, Wei-Guo, 2015. "A multi-period fuzzy portfolio optimization model with minimum transaction lots," European Journal of Operational Research, Elsevier, vol. 242(3), pages 933-941.
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    Cited by:

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    2. Xi Zhang & Xu Wu & Linlin Zhang & Zhonglu Chen, 2022. "The Evaluation of Mean-Detrended Cross-Correlation Analysis Portfolio Strategy for Multiple risk Assets," Evaluation Review, , vol. 46(2), pages 138-164, April.

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