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- Publisher
- Oxford University Press
- Copyright
- © The Author 2005. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oupjournals.org.
- ISSN
- 1479-8409
- eISSN
- 1479-8417
- DOI
- 10.1093/jjfinec/nbi025
- Publisher site
- See Article on Publisher Site
Abstract
We examine tests for jumps based on recent asymptotic results; we interpret the tests as Hausman-type tests. Monte Carlo evidence suggests that the daily ratio z-statistic has appropriate size, good power, and good jump detection capabilities revealed by the confusion matrix comprised of jump classification probabilities. We identify a pitfall in applying the asymptotic approximation over an entire sample. Theoretical and Monte Carlo analysis indicates that microstructure noise biases the tests against detecting jumps, and that a simple lagging strategy corrects the bias. Empirical work documents evidence for jumps that account for 7% of stock market price variance.
Journal
Journal of Financial Econometrics – Oxford University Press
Published: Aug 12, 2005