Volatility Forecasting during Extreme Market Events Using the Mid Cap Share Index

ABSTRACT

The JSE underperformance in 2010 to 2019 as a consequence of a collapse in mid-cap share investments signified a high risk of investing in mid-cap companies. The outbreak of Covid-19 affected the optimal lambda and mid-cap share price returns during the analysis that was extended to 31 July 2020. For this purpose, the objective of the study is to forecast volatility at the end of day n-1 using the exponential weighted moving average and the general autoregressive conditional heteroscedasticity using the mid-cap share index (J201). Furthermore, the study aims to calculate the optimal lambda during the Covid-19 global pandemic. The models examined the negative relationship between share price returns and volatility during extreme events which led to fat tailed distribution of returns in share price returns. On December 2020 an unfavourable South African investment grade of negative BBB was assigned by Fitch Ratings and the days following the Covid-19 lockdown, share price returns plunged encouraging panic selling by risk averse investors.