Please use this identifier to cite or link to this item: http://ir.lib.seu.ac.lk/handle/123456789/7350
Title: Stock market volatility and the COVID-19 pandemic in Sri Lanka
Authors: Mohamed Riyath, Mohamed Ismail
Dewasiri, Narayanage Jayantha
Mohamed Siraju, Mohamed Abdul Majeed
Grima, Simon
Mohamed Mustafa, Abdul Majeed
Keywords: Asymmetric Effect
COVID-19
CSE
EGARCH
Volatility
Sri Lanka
Market Return
Issue Date: 13-May-2024
Publisher: Emerald Publishing Limited
Citation: Riyath, M.I.M., Dewasiri, N.J., Siraju, M.A.M.M., Grima, S. and Mustafa, A.M.M. (2024), "Stock Market Volatility and the COVID-19 Pandemic in Sri Lanka", Singh, D., Sood, K., Kautish, S. and Grima, S. (Ed.) VUCA and Other Analytics in Business Resilience, Part A (Emerald Studies in Finance, Insurance, and Risk Management), Emerald Publishing Limited, Leeds, pp. 151-168.
Abstract: Purpose: This chapter examines the effect of COVID-19 on the stock market volatility (SMV) in the Colombo Stock Exchange (CSE), Sri Lanka. Need for the Study: The study is necessary to understand investor behaviour, market efficiency, and risk management strategies during a global crisis. Methodology: Utilising daily All Share Price Index (ASPI) data from 2 January 2018 to 31 August 2021, the data are divided into subsamples corresponding to the pre-pandemic period, the pandemic period, and distinct waves of the pandemic. The impact of the pandemic is investigated using the Mann–Whitney U test, the Kruskal–Wallis test, and the Exponential Generalised Autoregressive Conditional Heteroscedasticity (EGARCH) model. Findings: The pandemic considerably affected CSE – the Mann–Whitney U test produced different market returns during the pre-COVID and COVID eras. The Kruskal–Wallis test improved performance during COVID-19 but did not continue to do so across COVID-19 waves. The EGARCH model detected increased volatility and risk during the first wave, but the second and third waves outperformed the first. COVID-19 had a minimal overall effect on CSE market results. GARCH and Autoregressive Conditional Heteroskedasticity (ARCH) models identified long-term variance memory and volatility clustering. The News Impact Curve (NIC) showed that negative news had a more significant impact on market return volatility than positive news, even if the asymmetric term was not statistically significant. Practical Implications: This study offers significant insight into how Sri Lanka’s SMV is affected by COVID-19. The findings help create efficient mitigation strategies to mitigate the negative consequences of future events.
URI: https://doi.org/10.1108/978-1-83753-902-420241007
http://ir.lib.seu.ac.lk/handle/123456789/7350
ISBN: 978-1-83753-903-1
978-1-83753-902-4 (e-ISBN)
Appears in Collections:Research Articles

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