Econometrics of co-jumps in high-frequency data with noise

Arbeitspapier

We establish estimation methods to determine co-jumps in multivariate high-frequency data with nonsynchronous observations and market microstructure noise. The ex-post quadratic covariation of the signal part, which is modeled by an Itˆo-semimartingale, is estimated with a locally adaptive spectral approach. Locally adaptive thresholding allows to disentangle the co-jump and continuous part in quadratic covariation. Our estimation procedure implicitly renders spot (co-)variance estimators. We derive a feasible stable limit theorem for a truncated spectral estimator of integrated covariance. A test for common jumps is obtained with a wild bootstrap strategy. We give an explicit guideline how to implement the method and test the algorithm in Monte Carlo simulations. An empirical application to intra-day tick-data demonstrates the practical value of the approach.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: SFB 649 Discussion Paper ; No. 2013-021

Classification and Topics

• Classification: Wirtschaft ; Semiparametric and Nonparametric Methods: General ; Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill ; Central Banks and Their Policies
• Subject: co-jumps ; covolatility estimation ; jump detection ; microstructure noise ; non-synchronous observations ; quadratic covariation ; spectral estimation ; truncation

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Bibinger, Markus ; Winkelmann, Lars
• Event: Veröffentlichung
• (who): Humboldt University of Berlin, Collaborative Research Center 649 - Economic Risk
• (where): Berlin
• (when): 2013

Further information

• Handle: http://hdl.handle.net/10419/79576
• Last update: 10.03.2025, 11:43 AM CET