The class of generalized autoregressive conditional heteroscedastic (GARCH) models has proved particularly valuable in modelling time series with time varying volatility. These include financial data, ...

Journal of Applied Econometrics, Vol. 17, No. 5, Special Issue: Modelling and Forecasting Financial Volatility (Sep. - Oct., 2002), pp. 509-534 (26 pages) Theoretical and practical interest in ...

It has become common practice to fit Garch models to financial time series by means of pseudo-maximum likelihood. In this study we investigate the behavior of several maximum likelihood-based methods ...

Appropriate modeling of time-varying dependencies is very important for quantifying financial risk, such as the risk associated with a portfolio of financial assets. Most of the papers analyzing ...