A test for model specification of diffusion processes

Song Chen, Jiti Gao and Chenghong Tang

MPRA Paper from University Library of Munich, Germany

Abstract: We propose a test for model specification of a parametric diffusion process based on a kernel estimation of the transitional density of the process. The empirical likelihood is used to formulate a statistic, for each kernel smoothing bandwidth, which is effectively a Studentized L2-distance between the kernel transitional density estimator and the parametric transitional density implied by the parametric process. To reduce the sensitivity of the test on smoothing bandwidth choice, the final test statistic is constructed by combining the empirical likelihood statistics over a set of smoothing bandwidths. To better capture the finite sample distribution of the test statistic and data dependence, the critical value of the test is obtained by a parametric bootstrap procedure. Properties of the test are evaluated asymptotically and numerically by simulation and by a real data example.

Keywords: Bootstrap; diffusion process; empirical likelihood; goodness-of-fit test; time series; transitional density (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Date: 2005-11, Revised 2007-02
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)

Published in Annals of Statistics 1.36(2008): pp. 162-198

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Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:11976

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