{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T23:18:41Z","timestamp":1775863121448,"version":"3.50.1"},"reference-count":41,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T00:00:00Z","timestamp":1697500800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JRFM"],"abstract":"<jats:p>This study examines the impact of volatility on the returns of nine National Stock Exchange (NSE) indices before, during, and after the COVID-19 pandemic. The study employed generalized autoregressive conditional heteroskedasticity (GARCH) modelling to analyse investor risk and the impact of volatility on returns. The study makes several contributions to the existing literature. First, it uses advanced volatility forecasting models, such as ARCH and GARCH, to improve volatility estimates and anticipate future volatility. Second, it enhances the analysis of index return volatility. The study found that the COVID-19 period outperformed the pre-COVID-19 and overall periods. Since the Nifty Realty Index is the most volatile, Nifty Bank, Metal, and Information Technology (IT) investors reaped greater returns during COVID-19 than before. The study provides a comprehensive review of the volatility and risk of nine NSE indices. Volatility forecasting techniques can help investors to understand index volatility and mitigate risk while navigating these dynamic indices.<\/jats:p>","DOI":"10.3390\/jrfm16100447","type":"journal-article","created":{"date-parts":[[2023,10,17]],"date-time":"2023-10-17T08:10:19Z","timestamp":1697530219000},"page":"447","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["COVID-19 Pandemic and Indices Volatility: Evidence from GARCH Models"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3497-2468","authenticated-orcid":false,"given":"Rajesh","family":"Mamilla","sequence":"first","affiliation":[{"name":"VIT Business School, Vellore Institute of Technology, Vellore 632014, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2064-1927","authenticated-orcid":false,"given":"Chinnadurai","family":"Kathiravan","sequence":"additional","affiliation":[{"name":"VIT Business School, Vellore Institute of Technology, Vellore 632014, India"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6808-1327","authenticated-orcid":false,"given":"Aidin","family":"Salamzadeh","sequence":"additional","affiliation":[{"name":"College of Management, University of Tehran, Tehran 141556311, Iran"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0806-1911","authenticated-orcid":false,"given":"L\u00e9o-Paul","family":"Dana","sequence":"additional","affiliation":[{"name":"ICD Business School, 75010 Paris, France"},{"name":"LUT School of Business and Management, Lappeenranta University of Technology, 53850 Lappeenranta, Finland"}]},{"given":"Mohamed","family":"Elheddad","sequence":"additional","affiliation":[{"name":"Teesside University International Business School, Teesside University, Middlesbrough TS1 3BX, UK"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"687","DOI":"10.1108\/SEF-10-2021-0457","article-title":"COVID-19 and the ASEAN stock market: A wavelet analysis of conventional and Islamic equity indices","volume":"40","author":"Ali","year":"2023","journal-title":"Studies in Economics and Finance"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"87","DOI":"10.9790\/487X-09687103","article-title":"Stock Market Seasonality\u2014Time-Varying Volatility in The Emerging Indian Stock Market","volume":"9","author":"Arumugam","year":"2013","journal-title":"IOSR Journal of Business and Management (IOSR-JBM)"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"340","DOI":"10.4236\/jssm.2022.153020","article-title":"Impact of Capital Market Performance on Economic Growth in Developing Nations: A Qualitative Approach","volume":"15","author":"Bello","year":"2022","journal-title":"Journal of Service Science and Management"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1023\/A:1008295500105","article-title":"The event study methodology since 1969","volume":"11","author":"Binder","year":"1998","journal-title":"Review of quantitative Finance and Accounting"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/0304-4076(86)90063-1","article-title":"Generalized autoregressive conditional heteroskedasticity","volume":"31","author":"Bollerslev","year":"1986","journal-title":"Journal of Econometrics"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Chaudhary, Rashmi, Bakhshi, Priti, and Gupta, Hemendra (2020). 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