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Modelling Stock Market Volatility During the COVID-19 Pandemic: Evidence from BRICS Countries

Author

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  • Karunanithy Banumathy

    (Pondicherry University Community College, India)

Abstract

The objective of the research paper is to identify the stock market volatility patterns of BRICS countries during the outbreak of the COVID-19 pandemic. The study is based on time series data, which consist of the daily closing prices of the BRICS countries’ indices for a two-year (pandemic) period from 1 January 2020 to 31 December 2021. Both symmetric and asymmetric models of Generalized Autoregressive Conditional Heteroscedasticity (GARCH) have been employed in the study to investigate whether volatility changed over the pandemic period. The results of the GARCH-M (1,1) model evidenced the presence of a positive and insignificant risk premium. Based on the empirical work carried out using the market indices of BRICS countries, it was found from the EGARCH (1,1) and TGARCH (1,1) models that there exists a leverage effect in the countries, namely Brazil, Russia, India, China, and South Africa. Since stock prices during the pandemic period triggered the entire financial market, investors, fund managers, and portfolio managers should be more aware of uncertainty and adjust their investments accordingly.

Suggested Citation

  • Karunanithy Banumathy, 2023. "Modelling Stock Market Volatility During the COVID-19 Pandemic: Evidence from BRICS Countries," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 21(3 (Fall)), pages 253-268.
    • Handle: RePEc:mgt:youmgt:v:21:y:2023:i:3:p:253-268
    DOI: 10.26493/1854-6935.21.253-268
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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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