Mixtures of t-distributions for finance and forecasting

Arbeitspapier

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.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Reihe Ökonomie / Economics Series ; No. 216

Klassifikation und Themen

• Klassifikation: Wirtschaft ; Computational Techniques; Simulation Modeling ; Forecasting Models; Simulation Methods ; Neural Networks and Related Topics
• Thema: ARMA-GARCH models ; neural networks ; nonparametric density estimation ; forecast accuracy ; option pricing ; risk neutral density ; ARCH-Modell ; Neuronale Netze ; Prognoseverfahren ; Nichtparametrisches Verfahren ; Schätztheorie

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Giacomini, Raffaella ; Gottschling, Andreas ; Haefke, Christian ; White, Halbert
• Ereignis: Veröffentlichung
• (wer): Institute for Advanced Studies (IHS)
• (wo): Vienna
• (wann): 2007

Weitere Informationen

• Handle: http://hdl.handle.net/10419/72677
• Letzte Aktualisierung: 10.03.2025, 11:44 MEZ