Showing 1 - 7 of 7
In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable in the mean equation. The same extension...
Persistent link: https://www.econbiz.de/10011303314
Volatility (SV) and Generalised Autoregressive Conditional Heteroskedasticity (GARCH) models which are both extended to include … outperforms the GARCH model. …
Persistent link: https://www.econbiz.de/10011326944
parsimonious and effective GARCH(1,1) model with Student-t innovations. The estimation procedure is fully automatic and thus avoids …
Persistent link: https://www.econbiz.de/10011380176
Persistent link: https://www.econbiz.de/10010191413
over a small time frame (e.g., a crisis period). We apply our method to test GARCH model specifications for a large panel …
Persistent link: https://www.econbiz.de/10010250513
This study reflects on the inconsistency of the fixed-design residual bootstrap procedure for GARCH models under …
Persistent link: https://www.econbiz.de/10014457811
It is generally believed that for the power of unit root tests, only the time span and not the observation frequency matters. In this paper we show that the observation frequency does matter when the high-frequency data display fat tails and volatility clustering, as is typically the case for...
Persistent link: https://www.econbiz.de/10011342578