Collective synchronization and high frequency systemic instabilities in financial markets

TL;DR

This paper investigates the increasing synchronization of large price movements in US financial markets, revealing endogenous systemic risks driven by high-frequency trading dynamics and modeling them with Hawkes processes.

Contribution

It provides empirical evidence of rising asset synchronization and introduces a parsimonious Hawkes process model to explain systemic instabilities endogenously.

Findings

Synchronization of large price movements has increased since 2001.

Less than 40% of systemic events are linked to macroeconomic news.

Higher systemicity correlates with increased likelihood of subsequent events.

Abstract

Recent years have seen an unprecedented rise of the role that technology plays in all aspects of human activities. Unavoidably, technology has heavily entered the Capital Markets trading space, to the extent that all major exchanges are now trading exclusively using electronic platforms. The ultra fast speed of information processing, order placement, and cancelling generates new dynamics which is still not completely deciphered. Analyzing a large dataset of stocks traded on the US markets, our study evidences that since 2001 the level of synchronization of large price movements across assets has significantly increased. Even though the total number of over-threshold events has diminished in recent years, when an event occurs, the average number of assets swinging together has increased. Quite unexpectedly, only a minor fraction of these events -- regularly less than 40% along all years -- can be connected with the release of pre-announced macroeconomic news. We also document that the larger is the level of sistemicity of an event, the larger is the probability -- and degree of sistemicity -- that a new event will occur in the near future. This opens the way to the intriguing idea that systemic events emerge as an effect of a purely endogenous mechanism. Consistently, we present a high-dimensional, yet parsimonious, model based on a class of self- and cross-exciting processes, termed Hawkes processes, which reconciles the modeling effort with the empirical evidence.