Electronic Journal of Statistics

Common price and volatility jumps in noisy high-frequency data

Markus Bibinger and Lars Winkelmann

Full-text: Open access

Abstract

We introduce a statistical test for simultaneous jumps in the price of a financial asset and its volatility process. The proposed test is based on high-frequency data and is robust to market microstructure frictions. For the test, local estimators of volatility jumps at price jump arrival times are designed using a nonparametric spectral estimator of the spot volatility process. A simulation study and an empirical example with NASDAQ order book data demonstrate the practicability of the proposed methods and highlight the important role played by price volatility co-jumps.

Article information

Source
Electron. J. Statist., Volume 12, Number 1 (2018), 2018-2073.

Dates
Received: June 2017
First available in Project Euclid: 18 June 2018

Permanent link to this document
https://projecteuclid.org/euclid.ejs/1529308886

Digital Object Identifier
doi:10.1214/18-EJS1444

Mathematical Reviews number (MathSciNet)
MR3815304

Zentralblatt MATH identifier
06917430

Subjects
Primary: 62G10: Hypothesis testing
Secondary: 62M10: Time series, auto-correlation, regression, etc. [See also 91B84]

Keywords
High-frequency data microstructure noise nonparametric volatility estimation volatility jumps

Rights
Creative Commons Attribution 4.0 International License.

Citation

Bibinger, Markus; Winkelmann, Lars. Common price and volatility jumps in noisy high-frequency data. Electron. J. Statist. 12 (2018), no. 1, 2018--2073. doi:10.1214/18-EJS1444. https://projecteuclid.org/euclid.ejs/1529308886


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