Giacomini, Raffaella (University College London) Gottschling, Andreas (Deutsche Bank AG, Credit RiskManagement) Haefke, Christian (Department of Economics and Finance, Institute for Advanced Studies, Vienna, Austria) White, Halbert (Department of Economics, University of California, San Diego)
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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-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.
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Paper provided by Institute for Advanced Studies in its series Economics Series with number
216.
Find related papers by JEL classification: C63 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - Computational Techniques C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
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