Applications of physical methods in high-frequency futures markets

TL;DR

This paper explores the use of physical methods like Hurst exponent and inverse statistics on high-frequency futures data, revealing that order book relaxation times follow stretched exponential laws similar to physical systems.

Contribution

It introduces the application of physical analytical techniques to financial high-frequency data and models order book relaxation times with laws from physics.

Findings

Hurst exponent and inverse statistics applied to futures data

Order book relaxation times follow stretched exponential laws

Physical models describe demand-supply imbalances in order books

Abstract

In the present work we demonstrate the application of different physical methods to high-frequency or tick-by-tick financial time series data. In particular, we calculate the Hurst exponent and inverse statistics for the price time series taken from a range of futures indices. Additionally, we show that in a limit order book the relaxation times of an imbalanced book state with more demand or supply can be described by stretched exponential laws analogous to those seen in many physical systems.