Hurst Exponents For Short Time Series

TL;DR

This paper introduces a balanced estimator of diffusion entropy to detect scaling behaviors in short time series, demonstrating its effectiveness on artificial data and real stock market series.

Contribution

It proposes a novel balanced estimator of diffusion entropy specifically designed for short time series analysis.

Findings

Effective detection of scaling in artificial fractional Brownian motions

Successful identification of scaling properties in stock market data

Ability to detect structural breaks in financial time series

Abstract

A new concept, called balanced estimator of diffusion entropy, is proposed to detect scalings in short time series. The effectiveness of the method is verified by means of a large number of artificial fractional Brownian motions. It is used also to detect scaling properties and structural breaks in stock price series of Shanghai Stock market.