Estimating the degree of activity of jumps in high frequency data
arXiv:0908.3095 · doi:10.1214/08-AOS640
Abstract
We define a generalized index of jump activity, propose estimators of that index for a discretely sampled process and derive the estimators' properties. These estimators are applicable despite the presence of Brownian volatility in the process, which makes it more challenging to infer the characteristics of the small, infinite activity jumps. When the method is applied to high frequency stock returns, we find evidence of infinitely active jumps in the data and estimate their index of activity.
Published in at http://dx.doi.org/10.1214/08-AOS640 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
References in corpus (1)
Cited by in corpus (19)
- Nonparametric tests for pathwise properties of semimartingales
- Testing whether jumps have finite or infinite activity
- Efficient estimation of integrated volatility in presence of infinite variation jumps
- Limit theorems for moving averages of discretized processes plus noise
- Modeling high-frequency financial data by pure jump processes
- Testing for pure-jump processes for high-frequency data
- Asymptotic theory of range-based multipower variation
- Realized Laplace transforms for pure-jump semimartingales
- Limit theorems for power variations of pure-jump processes with application to activity estimation
- Identifying the successive Blumenthal-Getoor indices of a discretely observed process
- Asymptotic lower bounds in estimating jumps
- Fact or friction: Jumps at ultra high frequency
- A new look at short-term implied volatility in asset price models with jumps
- Asymptotic results and statistical procedures for time-changed Lévy processes sampled at hitting times
- Parametric Inference for Discretely Observed Subordinate Diffusions
- Local shrinkage rules, Levy processes, and regularized regression
- Weak convergence of the empirical truncated distribution function of the Lévy measure of an Itō semimartingale
- Sequential Bayesian Learning for Merton's Jump Model with Stochastic Volatility
- Large deviations of the Threshold estimator of integrated (co-)volatility vector in the presence of jumps