Testing and detecting jumps based on a discretely observed process
We 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.
Year of publication: |
2011
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Authors: | Fan, Yingying ; Fan, Jianqing |
Published in: |
Journal of Econometrics. - Elsevier, ISSN 0304-4076. - Vol. 164.2011, 2, p. 331-344
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Publisher: |
Elsevier |
Keywords: | Jump diffusion process Test for jumps High frequency Stable convergence False discovery rate |
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