Hurst exponent and prediction based on weak-form efficient market hypothesis of stock markets

TL;DR

This study explores the link between market efficiency and predictability using the Hurst exponent and nearest-neighbor prediction across 60 global stock indexes, revealing that higher efficiency correlates with better prediction accuracy.

Contribution

It demonstrates that the Hurst exponent effectively predicts future price movements and distinguishes between emerging and mature markets.

Findings

Higher Hurst exponent correlates with increased predictability.

Hurst exponent and hit rate differentiate emerging from mature markets.

Results support the usefulness of the Hurst exponent in market analysis.

Abstract

We empirically investigated the relationships between the degree of efficiency and the predictability in financial time-series data. The Hurst exponent was used as the measurement of the degree of efficiency, and the hit rate calculated from the nearest-neighbor prediction method was used for the prediction of the directions of future price changes. We used 60 market indexes of various countries. We empirically discovered that the relationship between the degree of efficiency (the Hurst exponent) and the predictability (the hit rate) is strongly positive. That is, a market index with a higher Hurst exponent tends to have a higher hit rate. These results suggested that the Hurst exponent is useful for predicting future price changes. Furthermore, we also discovered that the Hurst exponent and the hit rate are useful as standards that can distinguish emerging capital markets from mature capital markets.