Does Markowitz’s Mean–Variance Model Matter During Turmoil Periods? Lessons from the COVID Crisis

Authors

  •   Amine Mounir Associate Professor, ESCA Ecole de Management, 67-3 Avenue de l’Aéropostale Casablanca Finance City (CFC) 20250 Casablanca - 20070

DOI:

https://doi.org/10.17010/ijf/2024/v18i1/171339

Keywords:

asset allocation

, data envelopment analysis, shortage function, COVID-19

JEL Classification Codes

, C67, G11, G15

Paper Submission Date

, October 25, 2022, Paper sent back for Revision, August 25, 2023, Paper Acceptance Date, November 16, Paper Published Online, January 15, 2024

Abstract

Purpose : This paper examined the effects of higher-order moments on the performance of optimal portfolios during the crisis period of the COVID-19 pandemic.

Design/Methodology/Approach : This paper employed the nonparametric model of data envelopment analysis (DEA) to assess performance using the shortage function as the measure of performance. Three higher-order moment parameters were included in the model: skewness and kurtosis.

Findings : The results showed that in contrast to the traditional mean–variance selection model, the measures of skewness and kurtosis did not lead to better performance during the COVID-19 pandemic despite the substantial departure from normalcy in asset returns. Additionally, the results showed that the sector rankings aligned with investor expectations regarding the economic activity sectors in high demand or less demand during the pandemic period in the American, French, and Moroccan markets.

Practical Implications : The study’s conclusions suggested that, rather than considering higher-order moments, investors and portfolio managers would find it advantageous to concentrate their investing strategy on return and risk considerations during an unexpected market crisis. It didn’t seem that taking skewness and kurtosis measurements into account enhanced portfolio performance.

Originality/Value : This study filled a knowledge vacuum in the literature about portfolio selection and generating asset returns, particularly during market crashes. It offered insightful information about the relationship between the higher-order moment allocation method and other factors.

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Published

2024-01-01

How to Cite

Mounir, A. (2024). Does Markowitz’s Mean–Variance Model Matter During Turmoil Periods? Lessons from the COVID Crisis. Indian Journal of Finance, 18(1), 29–41. https://doi.org/10.17010/ijf/2024/v18i1/171339

Issue

Volume 18, issue 1, January 2024

Section

Articles
Crossref
Scopus
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Europe PMC

References

Aloui, D., Goutte, S., Guesmi, K., & Hchaichi, R. (2020). COVID-19's impact on crude oil and natural gas S&P GS indexes. Available at SSRN. https://doi.org/10.2139/ssrn.3587740

Briec, W., & Kerstens, K. (2010). Portfolio selection in multidimensional general and partial moment space. Journal of Economic Dynamics and Control, 34(4), 636–656. https://doi.org/10.1016/j.jedc.2009.11.001

Campbell, J. Y., Lo, A. W., & MacKinlay, A. C. (1997). The econometrics of financial markets. Dans Princeton University Press eBooks. https://doi.org/10.1515/9781400830213

Conlon, T., Corbet, S., & McGee, R. (2020). Are cryptocurrencies a safe haven for equity markets? An international perspective from the COVID-19 pandemic. Research in International Business and Finance, 54, 101248. https://doi.org/10.1016/j.ribaf.2020.101248

Delis, M. D., Savva, C. S., & Theodossiou, P. (2020). The impact of the Coronavirus crisis on the market price of risk. Available at SSRN. https://doi.org/10.2139/ssrn.3618827

Dey, K., & Brown, A. (2021). Indian stock market's response in five - phases to the COVID-19 pandemic. Indian Journal of Research in Capital Markets, 8(1–2), 26–45. https://doi.org/10.17010/10.17010/ijrcm/2021/v8i1-2/160230

Filipe, J. A. (2020). Epidemics and pandemics: Covid-19 and the ''Drop of Honey Effect''. International Journal of Economics and Business Administration, 8(2), 240–249. https://doi.org/10.35808/ijeba/456

Goodell, J. W., & Huynh, T. L. D. (2020). Did Congress trade ahead? Considering the reaction of US industries to COVID-19. Finance Research Letters, 36, 101578. https://doi.org/10.1016/j.frl.2020.101578

Hung, C.-H., D., Azad, A. S, & Fang, V. (2014). Determinants of stock returns: Factors or systematic co-moments? Crisis versus non-crisis periods. Journal of International Financial Markets, Institutions and Money, 31, 14–29. https://doi.org/10.1016/j.intfin.2014.03.005

Jhaveri, C. A., Sood, G., & Shah, R. (2021). Efficiency assessment of Indian textile units using data envelopment and regression analysis. Indian Journal of Finance, 15(5–7), 9–25. https://doi.org/10.17010/ijf/2021/v15i5-7/164490

Kaur Makkar, M., Ghayas, A., & Gupta, N. (2023). Performance of conventional and sustainable index in pre and during the COVID-19 pandemic : A comparative analysis. Indian Journal of Finance, 17(5), 39–52. https://doi.org/10.17010/ijf/2023/v17i5/172736

Kerstens, K., Mounir, A., & Van de Woestyne, I. (2011a). Geometric representation of the mean–variance–skewness portfolio frontier based upon the shortage function. European Journal of Operational Research, 210(1), 81–94. https://doi.org/10.1016/j.ejor.2010.09.014

Kerstens, K., Mounir, A., & Van de Woestyne, I. (2011b). Non-parametric frontier estimates of mutual fund performance using C- and L-moments: Some specification tests. Journal of Banking & Finance, 35(5), 1190–1201. https://doi.org/10.1016/j.jbankfin.2010.09.030

Kraus, A., & Litzenberger, R. H. (1976). Skewness preference and the valuation of risk assets. The Journal of Finance, 31(4), 1085–1100. https://doi.org/10.2307/2326275

Mandelbrot, B. (1963). The variation of certain speculative prices. The Journal of Business, 36(4), 394–419. https://doi.org/10.1086/294632

Mangala Minutha, V., & Jagannathan, U. K. (2022). A study on the impact of COVID - 19 on alternative investment funds in India. Indian Journal of Research in Capital Markets, 9(2–3), 42–53. https://doi.org/10.17010/ijrcm/2022/v9i2-3/172551

Markowitz, H. (1952). Portfolio selection. The Journal of Finance, 7(1), 77–91. https://doi.org/10.1111/j.1540-6261.1952.tb01525.x

Mohania, S., & Mainrai, G. (2020). The COVID-19 pandemic and its impact on the banking industry – A case of National Bank Ltd. Indian Journal of Finance, 14(8–9), 80–89. https://doi.org/10.17010/ijf/2020/v14i8-9/154950

Mounir, A. (2021). Prudence and temperance in portfolio selection with shariah-compliant investments. International Journal of Islamic and Middle Eastern Finance and Management, 14(4), 753–766. https://doi.org/10.1108/imefm-07-2019-0292

Naveen, S., & Mallikarjunappa, T. (2021). Performance of mutual funds amidst COVID 19 - A study on selected equity diversified categories in India. Indian Journal of Research in Capital Markets, 8(4), 8–22. https://doi.org/10.17010/ijrcm/2021/v8i4/168583

Nekhili, R., & Bouri, E. (2023). Higher-order moments and co-moments' contribution to spillover analysis and portfolio risk management. Energy Economics, 119, 106596. https://doi.org/10.1016/j.eneco.2023.106596

Soni, T. K. (2023). ESG score and mutual fund performance : Empirical evidence from India. Indian Journal of Finance, 17(3), 37–49. https://doi.org/10.17010/ijf/2023/v17i3/172671

Syed, A. A., Tripathi, R., & Deewan, J. (2021). Investigating the impact of the first and second waves of the COVID-19 pandemic on the Indian stock and commodity markets : An ARDL analysis of gold, oil, and stock market prices. Indian Journal of Finance, 15(12), 8–21. https://doi.org/10.17010/ijf/2021/v15i12/167306