Publication Type
Journal Article
Version
acceptedVersion
Publication Date
12-2014
Abstract
We propose new tests of the martingale hypothesis based on generalized versions of the Kolmogorov–Smirnov and Cramér–von Mises tests. The tests are distribution-free and allow for a weak drift in the null model. The methods do not require either smoothing parameters or bootstrap resampling for their implementation and so are well suited to practical work. The article develops limit theory for the tests under the null and shows that the tests are consistent against a wide class of nonlinear, nonmartingale processes. Simulations show that the tests have good finite sample properties in comparison with other tests particularly under conditional heteroscedasticity and mildly explosive alternatives. An empirical application to major exchange rate data finds strong evidence in favor of the martingale hypothesis, confirming much earlier research.
Keywords
Brownian functional, Cramér-von Mises test, Exchange rates, Explosive process, Kolmogorov-Smirnov test
Discipline
Econometrics
Research Areas
Econometrics
Publication
Journal of Business and Economic Statistics
Volume
32
First Page
537
Last Page
554
ISSN
0735-0015
Identifier
10.1080/07350015.2014.908780
Publisher
Taylor and Francis
Citation
Phillips, Peter C. B. and JIN, Sainan.
Testing the Martingale Hypothesis. (2014). Journal of Business and Economic Statistics. 32, 537-554.
Available at: https://ink.library.smu.edu.sg/soe_research/1633
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1080/07350015.2014.908780