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

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  • Norman R. Swanson

    ()

    (Rutgers University)

  • Valentina Corradi

    ()

    (University of Warwick)

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.

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Paper provided by Rutgers University, Department of Economics in its series Departmental Working Papers with number 201112.

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Length: 20 pages
Date of creation: 15 May 2011
Date of revision:
Handle: RePEc:rut:rutres:201112
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Keywords: block bootstrap; diffusion processes; jumps; nonparametric simulated quasi maximum likelihood; parameter estimation error;

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Find related papers by JEL classification:
  • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
  • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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Cited by:

  1. Norman R. Swanson & Lili Cai, 2011. "In- and Out-of-Sample Specification Analysis of Spot Rate Models: Further Evidence for the Period 1982-2008," Departmental Working Papers 201102, Rutgers University, Department of Economics.
  2. Swanson, Norman R. & Urbach, Richard, 2015. "Prediction and simulation using simple models characterized by nonstationarity and seasonality," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 312-323.
  3. Zu, Yang, 2015. "Nonparametric specification tests for stochastic volatility models based on volatility density," Journal of Econometrics, Elsevier, vol. 187(1), pages 323-344.

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