Theory of earthquakes interevent times applied to financial markets

TL;DR

This paper applies earthquake interevent time modeling, specifically the Hawkes process, to financial markets, demonstrating its effectiveness in capturing the distribution of waiting times between market losses across various assets.

Contribution

It introduces the use of the Hawkes process with a power law memory kernel to model financial loss interevent times, extending earthquake modeling techniques to finance.

Findings

Hawkes process fits empirical waiting time distributions well

Long memory kernels are effective in modeling market loss intervals

Method applies successfully across multiple financial assets

Abstract

We analyze the probability density function (PDF) of waiting times between financial loss exceedances. The empirical PDFs are fitted with the self-excited Hawkes conditional Poisson process with a long power law memory kernel. The Hawkes process is the simplest extension of the Poisson process that takes into account how past events influence the occurrence of future events. By analyzing the empirical data for 15 different financial assets, we show that the formalism of the Hawkes process used for earthquakes can successfully model the PDF of interevent times between successive market losses.