Publication Type
Journal Article
Version
publishedVersion
Publication Date
6-2011
Abstract
I develop an omnibus specification test for diffusion models based on the infinitesimal operator. The infinitesimal operator based identification of the diffusion process is equivalent to a “martingale hypothesis” for the processes obtained by a transformation of the original diffusion model. My test procedure is then constructed by checking the “martingale hypothesis” via a multivariate generalized spectral derivative based approach that delivers a asymptotical null distribution for the test statistic. The infinitesimal operator of the diffusion process is a closed-form function of drift and diffusion terms. Consequently, my test procedure covers both univariate and multivariate diffusion models in a unified framework and is particularly convenient for the multivariate case. Moreover, different transformed martingale processes contain separate information about the drift and diffusion specifications. This motivates me to propose a separate inferential test procedure to explore the sources of rejection when a parametric form is rejected. Simulation studies show that the proposed tests have reasonable size and excellent power performance. An empirical application of my test procedure using Eurodollar interest rates finds that most popular short-rate models are rejected and the drift misspecification plays an important role in such rejections.
Keywords
diffusion, infinitesimal operator, Markov, martingale problem, semi-group
Discipline
Finance | Finance and Financial Management
Research Areas
Finance
Areas of Excellence
Growth in Asia
Publication
Journal of Econometrics
Volume
162
Issue
2
First Page
189
Last Page
212
ISSN
0304-4076
Identifier
10.1016/j.jeconom.2010.12.005
Publisher
Elsevier
Citation
SONG, Zhaogang.
A martingale approach for testing diffusion models based on infinitesimal operator. (2011). Journal of Econometrics. 162, (2), 189-212.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/7916
Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
External URL
https://api.elsevier.com/content/abstract/scopus_id/79955063273
Additional URL
https://doi.org/10.1016/j.jeconom.2010.12.005