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Scaled and stable mean-variance-EVaR portfolio selection strategy with proportional transaction costs

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  • Ebenezer Fiifi Emire Atta Mills
  • Bo Yu
  • Jie Yu

Abstract

This paper studies a portfolio optimization problem with variance and Entropic Value-at-Risk (EVaR) as risk measures. As the variance measures the deviation around the expected return, the introduction of EVaR in the mean-variance framework helps to control the downside risk of portfolio returns. This study utilized the squared l2-norm to alleviate estimation risk problems arising from the mean estimate of random returns. To adequately represent the variance-EVaR risk measure of the resulting portfolio, this study pursues rescaling by the capital accessible after payment of transaction costs. The results of this paper extend the classical Markowitz model to the case of proportional transaction costs and enhance the efficiency of portfolio selection by alleviating estimation risk and controlling the downside risk of portfolio returns. The model seeks to meet the requirements of regulators and fund managers as it represents a balance between short tails and variance. The practical implications of the findings of this study are that the model when applied, will increase the amount of capital for investment, lower transaction cost and minimize risk associated with the deviation around the expected return at the expense of a small additional risk in short tails.

Suggested Citation

  • Ebenezer Fiifi Emire Atta Mills & Bo Yu & Jie Yu, 2017. "Scaled and stable mean-variance-EVaR portfolio selection strategy with proportional transaction costs," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 18(4), pages 561-584, July.
    • Handle: RePEc:taf:jbemgt:v:18:y:2017:i:4:p:561-584
    DOI: 10.3846/16111699.2017.1342272
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    References listed on IDEAS

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    1. John Lintner, 1965. "Security Prices, Risk, And Maximal Gains From Diversification," Journal of Finance, American Finance Association, vol. 20(4), pages 587-615, December.
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    Cited by:

    1. Chuan-Hsiang Han & Kun Wang, 2022. "Stressed portfolio optimization with semiparametric method," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-34, December.

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