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Bayesian clustering of many GARCH models

Bauwens, Luc; Rombouts, Jeroen V. K. - In: Econometric reviews 26 (2007) 2, pp. 365-386

Persistent link: https://www.econbiz.de/10003509134

Bayesian inference in dynamic disequilibrium models : an application to the Polish credit market

Bauwens, Luc; Lubrano, Michel - In: Econometric reviews 26 (2007) 2, pp. 469-486

Persistent link: https://www.econbiz.de/10003509150

Modelling financial high frequency data using point processes

Bauwens, Luc (contributor); Hautsch, Nikolaus (contributor) - 2006

Persistent link: https://www.econbiz.de/10003392659

News announcements, market activity and volatility in the euro/dollar foreign exchange market

Bauwens, Luc; Ben Omrane, Walid; Giot, Pierre - In: Journal of international money and finance 24 (2005) 7, pp. 1180-1125

Persistent link: https://www.econbiz.de/10003210043

Exchange rate volatility and the mixture of distribution hypothesis

Bauwens, Luc (contributor); Rime, Dagfinn (contributor); … - 2005

Persistent link: https://www.econbiz.de/10003155180

Special Issue on "Recent developments on high frequency financial econometrics"

Bauwens, Luc (contributor) - 2006

Persistent link: https://www.econbiz.de/10003233753

Exchange rate volatility and the mixture of distribution hypothesis

Bauwens, Luc; Rime, Dagfinn; Sucarrat, Genaro - In: Empirical economics : a journal of the Institute for … 30 (2005) 4, pp. 889-911

Persistent link: https://www.econbiz.de/10003233824

Multivariate GARCH models : a survey

Bauwens, Luc; Laurent, Sébastien; Rombouts, Jeroen V. K. - In: Journal of applied econometrics 21 (2006) 1, pp. 79-109

Persistent link: https://www.econbiz.de/10003310013

Bayesian inference for the mixed conditional heteroskedasticity model

Bauwens, Luc (contributor); … - 2005

Persistent link: https://www.econbiz.de/10003311396

Adaptive polar sampling : a new MC technique for the analysis of ill-behaved surfaces

Bauwens, Luc; Bos, Charles S.; Dijk, Herman K. van - 1998 - August 25, 1998, rev. B

Adaptive Polar Sampling is proposed as an algorithm where random drawings aredirectly generated from the target function (posterior) in all-but-onedirections of the parameter space. The method is based on the mixed integrationtechnique of Van Dijk, Kloek & Boender (1985) but extends this one by...

Persistent link: https://www.econbiz.de/10011299991