Arbeitspapier

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

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 Salanié (2004). In an empirical illustration, the predictive densities from several models of the one-month federal funds rates are compared.

Language
Englisch

Bibliographic citation
Series: Working Paper ; No. 2011-12

Classification
Wirtschaft
Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
Model Construction and Estimation
Subject
block bootstrap
diffusion processes
jumps
nonparametric simulated quasi maximum likelihood
parameter estimation error
recursive estimation
stochastic volatility
Prognoseverfahren
Zeitreihenanalyse
Modellierung
Schätztheorie
Theorie

Event
Geistige Schöpfung
(who)
Corradi, Valentina
Swanson, Norman
Event
Veröffentlichung
(who)
Rutgers University, Department of Economics
(where)
New Brunswick, NJ
(when)
2011

Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Corradi, Valentina
  • Swanson, Norman
  • Rutgers University, Department of Economics

Time of origin

  • 2011

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