Mixtures of t-distributions for Finance and Forecasting

Giacomini, Raffaella; Gottschling, Andreas; Haefke, Christian and White, Halbert (October 2007) Mixtures of t-distributions for Finance and Forecasting. Former Series > Working Paper Series > IHS Economics Series 216


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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-formexpressions 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-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 (2003) using a mixture of scaled and shifted t-distributions and obtain comparably good results, while gaining analytical tractability.;

Item Type: IHS Series
Keywords: 'ARMA-GARCH models' 'Neural networks' 'Nonparametric density estimation' 'Forecast accuracy' 'Option pricing' 'Risk neutral density'
Classification Codes (e.g. JEL): C63, C53, C45
Date Deposited: 26 Sep 2014 10:38
Last Modified: 27 Sep 2019 06:18
ISBN: 1605-7996
URI: https://irihs.ihs.ac.at/id/eprint/1800

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