Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/72677
Authors: 
Giacomini, Raffaella
Gottschling, Andreas
Haefke, Christian
White, Halbert
Year of Publication: 
2007
Series/Report no.: 
Reihe Ökonomie / Economics Series, Institut für Höhere Studien (IHS) 216
Abstract: 
We explore convenient analytic properties of distributions constructed as mixtures of scaled and shifted t-distributions. A feature that makes this family particularly desirable for econometric applications is that it possesses closed-form expressions for its anti-derivatives (e.g., the cumulative density function). We illustrate the usefulness of these distributions in two applications. In the first application, we use a scaled and shifted t-distribution to produce density forecasts of U.S. inflation and show that these forecasts are more accurate, out-ofsample, than density forecasts obtained using normal or standard t-distributions. In the second application, we replicate the option-pricing exercise of Abadir and Rockinger (2003) using a mixture of scaled and shifted t-distributions and obtain comparably good results, while gaining analytical tractability.
Subjects: 
ARMA-GARCH models
neural networks
nonparametric density estimation
forecast accuracy
option pricing
risk neutral density
JEL: 
C63
C53
C45
Document Type: 
Working Paper

Files in This Item:
File
Size
370.96 kB





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.