Please use this identifier to cite or link to this item: http://ir.lib.seu.ac.lk/handle/123456789/7350
Full metadata record
DC FieldValueLanguage
dc.contributor.authorMohamed Riyath, Mohamed Ismail-
dc.contributor.authorDewasiri, Narayanage Jayantha-
dc.contributor.authorMohamed Siraju, Mohamed Abdul Majeed-
dc.contributor.authorGrima, Simon-
dc.contributor.authorMohamed Mustafa, Abdul Majeed-
dc.date.accessioned2025-03-26T08:26:42Z-
dc.date.available2025-03-26T08:26:42Z-
dc.date.issued2024-05-13-
dc.identifier.citationRiyath, 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.en_US
dc.identifier.isbn978-1-83753-903-1-
dc.identifier.isbn978-1-83753-902-4 (e-ISBN)-
dc.identifier.urihttps://doi.org/10.1108/978-1-83753-902-420241007-
dc.identifier.urihttp://ir.lib.seu.ac.lk/handle/123456789/7350-
dc.description.abstractPurpose: 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.en_US
dc.language.isoen_USen_US
dc.publisherEmerald Publishing Limiteden_US
dc.subjectAsymmetric Effecten_US
dc.subjectCOVID-19en_US
dc.subjectCSEen_US
dc.subjectEGARCHen_US
dc.subjectVolatilityen_US
dc.subjectSri Lankaen_US
dc.subjectMarket Returnen_US
dc.titleStock market volatility and the COVID-19 pandemic in Sri Lankaen_US
dc.typeArticleen_US
Appears in Collections:Research Articles

Files in This Item:
File Description SizeFormat 
Stock Market Volatility and the COVID-19.pdf33.02 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.