Predictive Density Construction and Accuracy Testing with Multiple Possibly Misspecified Diffusion Models

Norman Swanson () and Valentina Corradi ()
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Valentina Corradi: University of Warwick

Departmental Working Papers from Rutgers University, Department of Economics

Abstract: This paper develops tests for comparing the accuracy of predictive densities derived from (possibly misspecified) diffusion models. In particular, we first outline a simple simulation-based framework for constructing predictive densities for one-factor and stochastic volatility models. Then, we 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 our tests, we also develop a recursive variant of the nonparametric simulated maximum likelihood estimator of Fermanian and Salani´e (2004). In an empirical illustration, the predictive densities from several models of the one-month federal funds rates are compared.

Keywords: block bootstrap; diffusion processes; jumps; nonparametric simulated quasi maximum likelihood; parameter estimation error (search for similar items in EconPapers)
JEL-codes: C22 C51 (search for similar items in EconPapers)
Pages: 20 pages
Date: 2011-05-15
New Economics Papers: this item is included in nep-ets and nep-ore
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Citations: View citations in EconPapers (9)

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http://www.sas.rutgers.edu/virtual/snde/wp/2011-12.pdf (application/pdf)

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 (2009)
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Persistent link: https://EconPapers.repec.org/RePEc:rut:rutres:201112

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