Hypernormal densities


Autoria(s): Giacomini, Raffaella; Gottschling, Andreas; Haefke, Christian; White, Halbert
Contribuinte(s)

Universitat Pompeu Fabra. Departament d'Economia i Empresa

Data(s)

15/09/2005

Resumo

We propose a new family of density functions that possess both flexibilityand closed form expressions for moments and anti-derivatives, makingthem particularly appealing for applications. We illustrate its usefulnessby applying our new family to obtain density forecasts of U.S. inflation.Our methods generate forecasts that improve on standard methods based on AR-ARCH models relying on normal or Student's t-distributional assumptions.

Identificador

http://hdl.handle.net/10230/1093

Idioma(s)

eng

Direitos

L'accés als continguts d'aquest document queda condicionat a l'acceptació de les condicions d'ús establertes per la següent llicència Creative Commons

info:eu-repo/semantics/openAccess

<a href="http://creativecommons.org/licenses/by-nc-nd/3.0/es/">http://creativecommons.org/licenses/by-nc-nd/3.0/es/</a>

Palavras-Chave #Statistics, Econometrics and Quantitative Methods #arma-garch models #neural networks #nonparametric density estimation #forecast accuracy
Tipo

info:eu-repo/semantics/workingPaper