Many empirical studies have analysed the effect of good news and bad news on equity market return volatility using both developed and emerging markets data, with scant literature for frontier stock markets. This study evaluates how news affects stock market return volatility in a frontier market using Uganda data. It specifically analyses the reaction of stock return volatility to news filtering into a frontier market using the exponential generalized autoregressive conditional heteroscedasticity (GARCH) model on daily data ranging from 1 September 2011 to 31 December 2017. Estimates of the shape parameter from generalized error distribution indicate the existence of leptokurtic return distribution. Results from the exponential GARCH model show that the effect of bad news and good news on the frontier market return volatility differs, thus suggesting existence of leverage effect in the period studied. Overall results from the study suggest that positive news impacts stock market returns volatility more than negative news of the same magnitude. An important implication of our results is that investors, analysts, brokers and dealers should be conscious of the nature of news filtering into the stock market as such information might improve their expected volatility forecast.
Stock return volatility based on intraday high frequency data: double-threshold ACD-GARCH model
