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Development of an efficient cluster-based portfolio optimization model under realistic market conditions

Author

Listed:
  • Mahdi Massahi

    (Amirkabir University of Technology)

  • Masoud Mahootchi

    (Amirkabir University of Technology)

  • Alireza Arshadi Khamseh

    (Kharazmi University)

Abstract

Modern portfolio theory introduced by Markowitz in 1952 is the most popular portfolio optimization framework established based on the trade-off between risk and return as an operation research model. The main shortcoming of applying Markowitz portfolio optimization in practice is that the obtained optimal weights are really sensitive to the embedded uncertainty in return series of stocks. In this paper, it is demonstrated how using a new methodology of time series clustering as a remedy can lead to a more robust and accurate portfolio in terms of the gap between mean variance efficient frontier obtained from the optimization model and the one observed in reality. In this regard, two similarity measures, the autocorrelation coefficients and the weighted dynamic time warping, are used in an innovative way to construct the desired portfolio optimization model. Moreover, the effectiveness of proposed approach is investigated in two different market conditions: semi-realistic and full-realistic. In the first one, it is assumed that the forecasted and realized stocks mean returns are the same; however, these returns are not necessarily equal in the second market conditions. Finally, a database of stock prices from the literature is utilized to show the robustness and accuracy of the proposed approach in empirical results in comparison with applied similarity measures in previous researches.

Suggested Citation

  • Mahdi Massahi & Masoud Mahootchi & Alireza Arshadi Khamseh, 2020. "Development of an efficient cluster-based portfolio optimization model under realistic market conditions," Empirical Economics, Springer, vol. 59(5), pages 2423-2442, November.
    • Handle: RePEc:spr:empeco:v:59:y:2020:i:5:d:10.1007_s00181-019-01802-5
    DOI: 10.1007/s00181-019-01802-5
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    References listed on IDEAS

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    2. Hidetoshi Ito & Akane Murakami & Nixon Dutta & Yukari Shirota & Basabi Chakraborty, 2021. "Clustering of ETF Data for Portfolio Selection during Early Period of Corona Virus Outbreak," Gakushuin Economic Papers, Gakushuin University, Faculty of Economics, vol. 58(1), pages 99-114.
    3. Dejan Živkov & Suzana Balaban & Marijana Joksimović, 2022. "Making a Markowitz portfolio with agricultural commodity futures," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(6), pages 219-229.

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    More about this item

    Keywords

    Portfolio optimization; Realized efficient frontier; Time series clustering; Weighted dynamic time warping; Autocorrelation coefficient; Realistic market condition;
    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
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis

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