Can One Make Any Crash Prediction in Finance Using the Local Hurst Exponent Idea?

TL;DR

This paper explores whether the local Hurst exponent can be used to predict major financial crashes by analyzing historical stock data and identifying patterns prior to significant market downturns.

Contribution

It introduces a method to use the local Hurst exponent for crash prediction and discusses the optimal window size for meaningful analysis.

Findings

The local Hurst exponent shows patterns before crashes in historical data.

Optimal window length is crucial for accurate predictions.

Some agreements found between Hurst behavior and crash occurrences.

Abstract

We apply the Hurst exponent idea for investigation of DJIA index time-series data. The behavior of the local Hurst exponent prior to drastic changes in financial series signal is analyzed. The optimal length of the time-window over which this exponent can be calculated in order to make some meaningful predictions is discussed. Our prediction hypothesis is verified with examples of '29 and '87 crashes, as well as with more recent phenomena in stock market from the period 1995-2003.Some interesting agreements are found.