The Drift Burst Hypothesis

58 Pages Posted: 24 Sep 2016 Last revised: 8 Aug 2018

See all articles by Kim Christensen

Kim Christensen

Aarhus University - CREATES

Roel C. A. Oomen

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

Roberto Renò

ESSEC Business School

Date Written: August 1, 2018


The drift burst hypothesis postulates the existence of short-lived locally explosive trends in the price paths of financial assets. The recent US equity and treasury flash crashes can be viewed as two high profile manifestations of such dynamics, but we argue that drift bursts of varying magnitude are an expected and regular occurrence in financial markets that can arise through established mechanisms of liquidity provision. We show how to build drift bursts into the continuous-time Itô semimartingale model, discuss the conditions required for the process to remain arbitrage-free, and propose a nonparametric test statistic that identifies drift bursts from noisy high-frequency data. We apply the test to demonstrate that drift bursts are a stylized fact of the price dynamics across equities, fixed income, currencies and commodities. Drift bursts occur once a week on average, and the majority of them are accompanied by subsequent price reversion and can thus be regarded as "flash crashes." The reversal is found to be stronger for negative drift bursts with large trading volume, which is consistent with endogenous demand for immediacy during market crashes.

Keywords: flash crashes; gradual jumps; volatility bursts; liquidity; nonparametric statistics; microstructure noise

JEL Classification: G10; C58

Suggested Citation

Christensen, Kim and Oomen, Roel C.A. and Renò, Roberto, The Drift Burst Hypothesis (August 1, 2018). Available at SSRN: or

Kim Christensen (Contact Author)

Aarhus University - CREATES ( email )

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

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

Roberto Renò

ESSEC Business School ( email )

3 Avenue Bernard Hirsch
CS 50105 CERGY

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