Hypernormal densities

Raffaella Giacomini (), Andreas Gottschling, Christian Haefke and Halbert White

Economics Working Papers from Department of Economics and Business, Universitat Pompeu Fabra

Abstract: We propose a new family of density functions that possess both flexibility and closed form expressions for moments and anti-derivatives, making them particularly appealing for applications. We illustrate its usefulness by applying our new family to obtain density forecasts of U.S. inflation. Our methods generate forecasts that improve on standard methods based on AR-ARCH models relying on normal or Student's t-distributional assumptions.

Keywords: ARMA-GARCH models; neural networks; nonparametric density estimation; forecast accuracy (search for similar items in EconPapers)
JEL-codes: C45 C53 C63 (search for similar items in EconPapers)
Date: 2002-09
New Economics Papers: this item is included in nep-ecm and nep-ets
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Hypernormal Densities (2002)
Working Paper: Hypernormal Densities (2002)
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Persistent link: https://EconPapers.repec.org/RePEc:upf:upfgen:638

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