A practical guide to measuring the Hurst parameter

TL;DR

This paper provides detailed methods for measuring the Hurst parameter, testing their robustness on artificial and real data, and offers accessible tools and instructions for researchers to replicate the process.

Contribution

It introduces practical measurement techniques for the Hurst parameter, including robustness checks and openly available tools and datasets for reproducibility.

Findings

Measurement techniques tested on artificial data

Robustness of tools evaluated under data corruption

Application to real-world datasets

Abstract

This paper describes, in detail, techniques for measuring the Hurst parameter. Measurements are given on artificial data both in a raw form and corrupted in various ways to check the robustness of the tools in question. Measurements are also given on real data, both new data sets and well-studied data sets. All data and tools used are freely available for download along with simple ``recipes'' which any researcher can follow to replicate these measurements.