Showing 1 - 10 of 160
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are crosssectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10009545313
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10009570680
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10014170199
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are crosssectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10013105008
This paper extends the transformed maximum likelihood approach for estimation of dynamic panel data models by Hsiao, Pesaran, and Tahmiscioglu (2002) to the case where the errors are cross-sectionally heteroskedastic. This extension is not trivial due to the incidental parameters problem that...
Persistent link: https://www.econbiz.de/10013315902
This paper considers a multivariate t version of the Gaussian dynamic conditional correlation (DCC) model proposed by Engle (2002), and suggests the use of devolatized returns computed as returns standardized by realized volatilities rather than by GARCH type volatility estimates. The t-DCC...
Persistent link: https://www.econbiz.de/10005822787
Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated...
Persistent link: https://www.econbiz.de/10008572473
This paper considers a multivariate t version of the Gaussian dynamic conditional correlation(DCC) model proposed by Engle (2002), and suggests the use of devolatized returnscomputed as returns standardized by realized volatilities rather than by GARCH type volatilityestimates. The t-DCC...
Persistent link: https://www.econbiz.de/10005862589
Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated...
Persistent link: https://www.econbiz.de/10003965868
Modelling of conditional volatilities and correlations across asset returns is an integral part of portfolio decision making and risk management. Over the past three decades there has been a trend towards increased asset return correlations across markets, a trend which has been accentuated...
Persistent link: https://www.econbiz.de/10013094817