The Relative Contribution of Jumps to Total Price Variance
Preprint
- 1 July 2005
- preprint
- Published by Elsevier in SSRN Electronic Journal
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 seven percent of stock market price variance.Keywords
This publication has 26 references indexed in Scilit:
- Microstructure Noise, Realized Variance, and Optimal SamplingThe Review of Economic Studies, 2008
- LIMIT THEOREMS FOR BIPOWER VARIATION IN FINANCIAL ECONOMETRICSEconometric Theory, 2006
- A Central Limit Theorem for Realised Power and Bipower Variations of Continuous SemimartingalesPublished by Springer Nature ,2006
- Separating microstructure noise from volatilityPublished by Elsevier ,2005
- Econometrics of Testing for Jumps in Financial Economics Using Bipower VariationJournal of Financial Econometrics, 2005
- Variation, Jumps, Market Frictions and High Frequency Data in Financial EconometricsSSRN Electronic Journal, 2005
- How Accurate is the Asymptotic Approximation to the Distribution of Realised Variance?Published by Cambridge University Press (CUP) ,2005
- Power and Bipower Variation with Stochastic Volatility and JumpsJournal of Financial Econometrics, 2004
- Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial EconomicsJournal of the Royal Statistical Society Series B: Statistical Methodology, 2001
- Non-Parametric Estimation for Non-Decreasing Lévy ProcessesJournal of the Royal Statistical Society Series B: Statistical Methodology, 1982