Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … outperforms the GARCH model. …

quarterly basis - for commonly used GARCH models in a large-scale study, using more than twelve years (2000-2012) of daily … following conclusions. First, updating the parameter estimates of the GARCH equation on a daily frequency improves only … overlap, reflecting that the performance is not significantly different. Second, the asymmetric GARCH model with non …

GARCH models which capture volatility clustering and, therefore, are appropriate to analyse financial market data. Models …

We compare small-sample properties of Bayes estimation and maximum likelihood estimation (MLE) of ARMA-GARCH models … method of testing strict stationarity and ergodicity of the conditional variance in the GARCH(1,1) process, near epoch … depencenve (NED), and finiteness of unconditional moments of the GARCH(1,1) process by using a Markov chain Monte Carlo (MCMC …

heteroscedasticity GARCH (1, 1) model. Also, to control if political uncertainty before the elections influences the return of MBI 10, a …