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Mixtures of t-distributions for finance and forecasting
Authors:Raffaella Giacomini  Andreas Gottschling  Christian Haefke  Halbert White
Institution:1. Department of Economics, University College London, Gower Street, London WC1E 6BT, UK;2. UCLA, Los Angeles, USA;3. CeMMAP, UK;4. Deutsche Bank AG, Winchester House, 1, Great Winchester Street, London EC2N 2DB, UK;5. Department of Economics, Institute for Advanced Studies (IHS), Stumpergasse 56, A-1060 Vienna, Austria;6. Instituto de Análisis Económico, CSIC, Barcelona, Spain;g IZA, Germany;h Department of Economics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0508, USA
Abstract: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.
Keywords:C63  C53  C45
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