Abstract:
Stock returns volatility of daily closing prices of the Uganda Securities Exchange
(USE) all share index over a period of 04/01/2005 to 18/12/2013 is Modelled. We
employ di erent univariate Generalised Autoregressive Conditional Heteroscedastic(
GARCH) models; both symmetric and asymmetric. The models include;
GARCH(1,1), GARCH-M, EGARCH(1,1) and TGARCH(1,1). Quasi Maximum
Likelihood(QML) method was used to estimate the models and then the best
performing model obtained using two model selection criteria; Akaike Information
criterion(AIC) and Bayesian Information criterion(BIC). Their forecasting
abilities was determined using two loss functions; Mean square error (MSE) and
Mean absolute error (MAE). The GARCH(1; 1) model outperformed the other
competing models in modelling volatility while EGARCH(1; 1 )performed best in
forecasting volatility of USE returns.
