Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models

Valentina Corradi and Norman Swanson ()

No 09-29, Working Papers from Federal Reserve Bank of Philadelphia

Abstract: This paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, the authors first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models. Then, they construct accuracy assessment tests that are in the spirit of Diebold and Mariano (1995) and White (2000). In order to establish the asymptotic properties of their tests, the authors also develop a recursive variant of the nonparametric simulated maximum likelihood estimator of Fermanian and Salani (2004). In an empirical illustration, the predictive densities from several models of the one-month federal funds rates are compared.

Keywords: Econometric models - Evaluation; Stochastic analysis (search for similar items in EconPapers)
Date: 2009
New Economics Papers: this item is included in nep-ecm, nep-ets and nep-for
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Related works:
Journal Article: Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models (2011)
Working Paper: Predictive density construction and accuracy testing with multiple possibly misspecified diffusion models (2011)
Working Paper: Predictive Density Construction and Accuracy Testing with Multiple Possibly Misspecified Diffusion Models (2011)
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