The Drift Burst Hypothesis

2016-09-27

Journal of Econometrics

AI Summary

This study investigates the existence, market prevalence, and underlying mechanisms of transient, localized “drift bursts” in financial asset prices. To this end, we incorporate drift bursts into a continuous-time Itô semimartingale framework and develop a theoretical model under no-arbitrage conditions, alongside a nonparametric test statistic designed to reliably detect such events from high-frequency data contaminated by noise. Our work is the first to formally model drift bursts as a regular feature of financial markets, uncovering their intrinsic links to liquidity shocks and price reversals. Empirical analysis reveals that drift bursts are pervasive across equity, bond, foreign exchange, and commodity markets, occurring on average once per week; notably, negative bursts accompanied by high trading volume are more likely to trigger significant price reversals.

Technology Category

• Data Mining & Knowledge Management: Anomaly/Outlier Detection
• Natural Language Processing: Discourse, Pragmatics & Argument Mining
• Game Theory and Economic Paradigms: Auctions and Market-Based Systems

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• Economics, Online Markets and Human Computation: Advertising auctions, pricing, markets, and exchanges
• Security and Privacy: Data transparency and provenance
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

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 such as feedback trading. At a theoretical level, we show how to build drift bursts into the continuous-time Ito semi-martingale model in such a way that the fundamental arbitrage-free property is preserved. We then develop a non-parametric test statistic that allows for the identification of drift bursts from noisy high-frequency data. We apply this methodology to a comprehensive set of tick data and show that drift bursts form an integral part of the price dynamics across equities, fixed income, currencies and commodities. We find that the majority of identified drift bursts are accompanied by strong price reversals and these can therefore be regarded as “flash crashes” that span brief periods of severe market disruption without any material longer term price impacts.

Problem

• drift burst
• flash crash
• high-frequency data
• price dynamics
• financial markets

Innovation

• drift burst
• Itô semimartingale
• nonparametric test
• high-frequency data
• flash crash