Covid-19 death risk estimation using VaR method

Abstract

PURPOSE: The purpose of this paper is to show that the Value at Risk (VaR) method can be used to estimate the death rate from Covid-19 infection.

DESIGN/METHODOLOGY/APPROACH: The VaR method allows for risk measurements and estimations of the highest expected loss on a portfolio at an assumed confidence level over a specified time horizon. The most important assumption affecting the calculation method is that price changes in financial markets follow a normal distribution.

FINDINGS: It appears that by appropriately re-defining the concepts of assets and portfolio rates of return, we can describe the volatility in the numbers of deaths caused by Covid-19. We also confirmed using the Shapiro-Wilk and Skewness and Kurtosis tests that the rates of return distribution for the death numbers follow a normal distribution.

PRACTICAL IMPLICATIONS: The VaR method allows to estimate the number of deaths based on current trends which can be utilised to better manage available resources in order to reduce casualties. We use the data regarding the number of deaths in the Visegrad Group (V4) countries as a case study to test the effectiveness and accuracy of the VaR method in a different, non-financial domain.

ORIGINALITY/VALUE: The theory we used in this paper is currently mainly applied to financial investments. We use this theory to describe social phenomenon which is the number of deaths, our approach has not been seen in the literature so far.