Volatility forecasting during extreme market events using the (JSE) small cap share index


  • Siya Marcus Selemela North-West University
  • Sune Ferreira North West University
  • Danny Mokatsanyane North-West University


EWMA model; GARCH (1, 1) model; historical standard deviation; volatility forecasting; extreme event; optimal lambda


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. The outbreak of COVID-19, had an impact on small-cap shares and the optimal lambda used throughout the analysis that was extended to 31 July 2020. For this purpose, the study aims to use the exponentially weighted moving average and the general autoregressive conditional heteroskedasticity models to forecast volatility of share price returns at the end of day n-1. Also, the study aims to determine the optimal lambda amid COVID-19. A comparison was made between the models and 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 an extreme event on December 2015 as a result of heightened political risk and on the days following the announcement made by the President Cyril Ramaphosa regarding the COVID-19 21-day lockdown whereas a negative relationship between share price returns and volatility in small-cap shares was encountered.

Author Biography

Danny Mokatsanyane, North-West University



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Financial Economics