TY - JOUR
T1 - Mixtures of t-distributions for finance and forecasting
AU - Giacomini, Raffaella
AU - Gottschling, Andreas
AU - Haefke, Christian
AU - White, Halbert
N1 - Funding Information:
The authors wish to thank Karim Abadir, John Bilson, Manfred Deistler, Carl FitzGerald, Jens Jackwerth, Eugene Kandel, Christian Krattenthaler, Andrew Patton, Michael Rockinger, Michael Wolf, and participants of the European Summer Symposium in Financial Markets in Gerzensee for helpful discussions and valuable suggestions. Two anonymous referees and an associate editor provided helpful suggestions that substantially improved this paper. Haefke acknowledges financial support from EU Grant HPMF-CT-2001-01252. Part of this paper was written while Haefke was visiting UCLA. He thanks the Department of Economics for its hospitality. White's participation was supported by NSF Grants SBR 9811562 and SES 0111238.
PY - 2008/5
Y1 - 2008/5
N2 - We explore convenient analytic properties of distributions constructed as mixtures of scaled and shifted t-distributions. Particularly desirable for econometric applications are closed-form expressions for antiderivatives (e.g., the cumulative density function). We illustrate the usefulness of these distributions in two applications. In the first application, we produce density forecasts of U.S. inflation and show that these forecasts are more accurate, out-of-sample, than density forecasts obtained using normal or standard t-distributions. In the second application, we replicate the option-pricing exercise of Abadir and Rockinger [Density functionals, with an option-pricing application. Econometric Theory 19, 778-811.] and obtain comparably good results, while gaining analytical tractability.
AB - We explore convenient analytic properties of distributions constructed as mixtures of scaled and shifted t-distributions. Particularly desirable for econometric applications are closed-form expressions for antiderivatives (e.g., the cumulative density function). We illustrate the usefulness of these distributions in two applications. In the first application, we produce density forecasts of U.S. inflation and show that these forecasts are more accurate, out-of-sample, than density forecasts obtained using normal or standard t-distributions. In the second application, we replicate the option-pricing exercise of Abadir and Rockinger [Density functionals, with an option-pricing application. Econometric Theory 19, 778-811.] and obtain comparably good results, while gaining analytical tractability.
KW - ARMA-GARCH models
KW - Forecast accuracy
KW - Neural networks
KW - Nonparametric density estimation
KW - Option pricing
KW - Risk-neutral density
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U2 - 10.1016/j.jeconom.2008.01.004
DO - 10.1016/j.jeconom.2008.01.004
M3 - Article
AN - SCOPUS:43049109436
SN - 0304-4076
VL - 144
SP - 175
EP - 192
JO - Journal of Econometrics
JF - Journal of Econometrics
IS - 1
ER -