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  • 标题:Volatility modelling of asset classes: An empirical study during different phases of Covid-19
  • 本地全文:下载
  • 作者:Hemendra Gupta ; Rashmi Chaudhary ; Kajal Srivastava
  • 期刊名称:Academy of Accounting and Financial Studies Journal
  • 印刷版ISSN:1096-3685
  • 出版年度:2022
  • 卷号:26
  • 期号:2
  • 页码:1-19
  • 语种:English
  • 出版社:The DreamCatchers Group, LLC
  • 摘要:The objective of this paper is to examine the performance of return and volatility of various asset classes which include equity, gold, debt, oil, currency, cryptocurrency and money market during different phases of COVID-19 in India. The study has been conducted using daily returns of these assets from 1st January, 2019 to 20th May, 2021. Volatility during the first and second COVID-19 waves in India, across assets, have been compared using different models such as GARCH, TARCH, EGARCH, and GARCH-M model. The results indicate contrasting behaviour of assets during different phases of COVID-19. It was observed that during the first COVID-19 wave, excluding Gold and Currency, all other assets showed negative returns. Furthermore, there was high volatility during this period. A sharp reversal in performance was observed after the downturn of the first COVID-19 wave. This reversal continued during the second, and more lethal, COVID-19 wave in India. During the second wave, volatility across assets was much less, thereby indicating the resilience of the asset performance due to COVID-19. The results also point towards an asymmetric impact of volatility in many asset classes, and the presence of mean reversing process on all assets. This paper also explores the relationship between different asset performances and the causality impact over one another.
  • 关键词:GARCH;TGARCH;EGARCH;GARCH-M Model;Granger Causalit
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