Does Markowitz’s Mean–Variance Model Matter During Turmoil Periods? Lessons from the COVID Crisis - Mounir, Amine (Indian Journal of Finance, 2024)
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.