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  • 标题:Volatility Forecasting during Extreme Market Events Using the (JSE) Small Cap Share Index
  • 本地全文:下载
  • 作者:Siya Marcus Selemela ; Sune Ferreira ; Danny Mokatsanyane
  • 期刊名称:Acta Universitatis Danubius. Oeconomica
  • 印刷版ISSN:2065-0175
  • 电子版ISSN:2067-340X
  • 出版年度:2021
  • 卷号:17
  • 期号:4
  • 页码:149-176
  • 语种:English
  • 出版社:Danubius University
  • 摘要:The lost decade of the JSE in small-cap companies from 2010 to 2019 as a result of a decline in investments indicated the high risk of investing in small-cap shares. Therefore, the study aimed to make use of two volatility models, the exponentially weighted moving average (EWMA) and the general autoregressive conditional heteroskedasticity model (GARCH) to forecast volatility of share price returns. Considering the South African market, the outbreak of COVID-19 had an impact on small-cap shares and the optimal lambda used throughout the analysis. Also, the study aimed to determine the optimal lambda amid COVID-19. A comparison was made between the two models where the use of the small-cap index (J202) was applied. The models highlighted the key weakness of the standard deviation, assigning the same weight to all share price returns in the period under analysis. The models captured share price shocks during extreme events whereas a negative relationship between share price returns and volatility in small-cap shares was encountered.
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