Betas in the time of corona: a conditional CAPM approach using multivariate GARCH model for India

Abstract

Purpose

This paper empirically investigates the effect of the coronavirus pandemic (COVID-19) on the Indian financial market and firm betas, perhaps the first paper to do so. The results will be helpful for investors tracking betas during future the coronavirus waves.

Design/methodology/approach

A conditional capital asset pricing model (CAPM) and multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model is used to estimate time-varying daily betas of the 50 largest Indian stocks spread across 16 industries over five years (Nov 2017 to May 2021), including the two waves of COVID-19 in India.

Findings

The results show that the betas increased during the COVID wave-1 (2020) but not during COVID wave-2 (2021). Moreover, the increase is more pronounced for consumer goods, infrastructure, insurance and information technology, unlike energy (oil and gas, power and mining) industries. Further, there are positive abnormal residual returns during the COVID waves. The results will be helpful for investors tracking betas during future COVID-19 waves.

Originality/value

This is perhaps the first paper to study the firm betas in light of the COVID-19 pandemic.

Citation

Jain, S. (2022), "Betas in the time of corona: a conditional CAPM approach using multivariate GARCH model for India", Managerial Finance, Vol. 48 No. 2, pp. 243-257. https://doi.org/10.1108/MF-05-2021-0226