Fact or Friction: Jumps at Ultra High Frequency

44 Pages Posted: 22 May 2011 Last revised: 19 Jul 2016

Kim Christensen

Aarhus University - CREATES

Roel C. A. Oomen

Deutsche Bank AG (London); London School of Economics & Political Science (LSE) - Department of Statistics

Mark Podolskij

University of Aarhus - School of Economics and Management

Date Written: January 31, 2014

Abstract

This paper shows that jumps in financial asset prices are often erroneously identified and are, in fact, rare events accounting for a very small proportion of the total price variation. We apply new econometric techniques to a comprehensive set of ultra high-frequency equity and foreign exchange tick data recorded at milli-second precision, allowing us to examine the price evolution at the individual order level. We show that in both theory and practice traditional measures of jump variation based on lower-frequency data tend to spuriously assign a burst of volatility to the jump component. As a result, the true price variation coming from jumps is overstated. Our estimates based on tick data suggest that the jump variation is an order of magnitude smaller than typical estimates found in the existing literature.

The appendices for this paper are available at the following URL: http://ssrn.com/abstract=2177370.

Keywords: jump variation, high-frequency data, market microstructure noise, pre-averaging, realised variation, outliers

JEL Classification: C10, C80

Suggested Citation

Christensen, Kim and Oomen, Roel C. A. and Podolskij, Mark, Fact or Friction: Jumps at Ultra High Frequency (January 31, 2014). Journal of Financial Economics (2014), vol. 114 (3), pp. 576-599.. Available at SSRN: https://ssrn.com/abstract=1848774 or http://dx.doi.org/10.2139/ssrn.1848774

Kim Christensen (Contact Author)

Aarhus University - CREATES ( email )

Department of Economics and Business Economics
Fuglesangs Allé 4
Aarhus V, 8210
Denmark

Roel C.A. Oomen

Deutsche Bank AG (London) ( email )

Winchester House
1 Great Winchester Street
London, EC2N 2DB
United Kingdom

London School of Economics & Political Science (LSE) - Department of Statistics ( email )

Houghton Street
London, England WC2A 2AE
United Kingdom

Mark Podolskij

University of Aarhus - School of Economics and Management ( email )

Building 350
DK-8000 Aarhus C
Denmark

Paper statistics

Downloads
591
Rank
35,595
Abstract Views
3,641