Testing and detecting jumps based on a discretely observed process
AbstractWe propose a new nonparametric test for detecting the presence of jumps in asset prices using discretely observed data. Compared with the test in Aït-Sahalia and Jacod (2009), our new test enjoys the same asymptotic properties but has smaller variance. These results are justified both theoretically and numerically. We also propose a new procedure to locate the jumps. The jump identification problem reduces to a multiple comparison problem. We employ the false discovery rate approach to control the probability of type I error. Numerical studies further demonstrate the power of our new method.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Econometrics.
Volume (Year): 164 (2011)
Issue (Month): 2 (October)
Contact details of provider:
Web page: http://www.elsevier.com/locate/jeconom
Jump diffusion process Test for jumps High frequency Stable convergence False discovery rate;
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