The relative contribution of jumps to total price variance

Published

Journal Article

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. © The Author 2005. Published by Oxford University Press. All rights reserved.

Full Text

Cited Authors

  • Huang, X; Tauchen, G

Published Date

  • September 1, 2005

Published In

Volume / Issue

  • 3 / 4

Start / End Page

  • 456 - 499

International Standard Serial Number (ISSN)

  • 1479-8409

Digital Object Identifier (DOI)

  • 10.1093/jjfinec/nbi025

Citation Source

  • Scopus