Long term memories of developed and emerging markets: using the scaling analysis to characterize their stage of development

TL;DR

This paper uses scaling analysis, specifically the generalized Hurst approach, to characterize and differentiate the development stages of various financial markets based on their volatility properties.

Contribution

It introduces a method to classify markets' development stages through empirical analysis of scaling exponents derived from financial time series.

Findings

Scaling exponents vary with market development stage

Results are robust across Monte-Carlo simulations

Frequency-domain analysis supports the findings

Abstract

The scaling properties encompass in a simple analysis many of the volatility characteristics of financial markets. That is why we use them to probe the different degree of markets development. We empirically study the scaling properties of daily Foreign Exchange rates, Stock Market indices and fixed income instruments by using the generalized Hurst approach. We show that the scaling exponents are associated with characteristics of the specific markets and can be used to differentiate markets in their stage of development. The robustness of the results is tested by both Monte-Carlo studies and a computation of the scaling in the frequency-domain.