Please use this identifier to cite or link to this item:
https://www.um.edu.mt/library/oar/handle/123456789/140040| Title: | Stock market volatility and the COVID-19 pandemic in Sri Lanka |
| Other Titles: | VUCA and other analytics in business resilience, part A |
| Authors: | Riyath, Mohamed Ismail Mohamed Dewasiri, Narayanage Jayantha Siraju, Mohamed Abdul Majeed Mohamed Grima, Simon Mustafa, Abdul Majeed Mohamed |
| Keywords: | Stock exchanges -- Sri Lanka Stock price forecasting -- Sri Lanka COVID-19 Pandemic, 2020-2023 -- Economic aspects -- Sri Lanka Financial crises -- Sri Lanka Heteroscedasticity |
| Issue Date: | 2024 |
| Publisher: | Emerald Publishing Limited |
| Citation: | Riyath, M. I. M., Dewasiri, N. J., Siraju, M. A. M. M., Grima, S., & Mustafa, A. M. M. (2024). Stock market volatility and the COVID-19 pandemic in Sri Lanka. In D. Singh, K. Sood, S. Kautish, & S. Grima (Eds.), VUCA and other analytics in business resilience, part A (pp. 151–168). Leeds: Emerald Publishing. |
| 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 longterm 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://www.um.edu.mt/library/oar/handle/123456789/140040 |
| Appears in Collections: | Scholarly Works - FacEMAIns |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Stock market volatility and the COVID 19 pandemic in Sri Lanka 2024.pdf Restricted Access | 367.1 kB | Adobe PDF | View/Open Request a copy |
Items in OAR@UM are protected by copyright, with all rights reserved, unless otherwise indicated.
