Multifractal characterization of gold market: a multifractal detrended fluctuation analysis

TL;DR

This study applies multifractal detrended fluctuation analysis to gold market data from China, India, and Turkey, revealing multifractality sources and modeling the series with a generalized binomial multifractal approach.

Contribution

It introduces a comprehensive multifractal analysis of gold market indices across three countries and identifies the origins of multifractality in these financial series.

Findings

All series exhibit multifractality.

Long-range correlations cause multifractality in CPI and Indian markets.

Fat-tailed distributions are responsible for multifractality in Chinese and Turkish markets.

Abstract

The multifractal detrended fluctuation analysis technique is employed to analyze the time series of gold consumer price index (CPI) and the market trend of three world's highest gold consuming countries, namely China, India and Turkey for the period: 1993-July 2013. Various multifractal variables, such as the generalized Hurst exponent, the multifractal exponent and the singularity spectrum, are calculated and the results are fitted to the generalized binomial multifractal (GBM) series that consists of only two parameters. Special emphasis is given to identify the possible source(s) of multifractality in these series. Our analysis shows that the CPI series and all three market series are of multifractal nature. The origin of multifractality for the CPI time series and Indian market series is found due to a long-range time correlation, whereas it is mostly due to the fat-tailed probability distributions of the values for the Chinese and Turkey markets. The GBM model series more or less describes all the time series analyzed here.