Information ratio test for model misspecification on parametric structures in stochastic diffusion models

Shulin Zhang, Peter X.-K. Song, Daimin Shi and Qian M. Zhou

Computational Statistics & Data Analysis, 2012, vol. 56, issue 12, 3975-3987

Abstract: We develop a hypothesis testing approach to checking model misspecification on parametric structures in continuous-time stochastic diffusion models. The key idea behind the development of our test statistic is rooted in a ratio of two types of information matrices, the negative sensitivity matrix and the variability matrix, in the context of martingale estimating equations. We propose a bootstrap resampling method to implement numerically the proposed diagnostic procedure. Through intensive simulation studies, we compare the proposed approach with several currently popular methods and show that our approach is advantageous in the aspects of type I error control, power improvement as well as computational efficiency. Two real-world data examples are included to illustrate the practical use of our proposed testing procedure.

Keywords: Bartlett identity; Drift; Godambe information; Information unbiasedness; Martingale estimating functions; Volatility (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:56:y:2012:i:12:p:3975-3987

DOI: 10.1016/j.csda.2012.05.013

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