Multifractal features of metal futures market based on multifractal detrended cross-correlation analysis

Purpose - Recently, many scholars have been paying more attention to studying the existence and application of multifractality. However, most researches concentrate on studying multifractal features of returns or volume separately, and ignore the correlation between them. The purpose of this paper,...

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Veröffentlicht in:Kybernetes 2012-10, Vol.41 (10), p.1509-1525
Hauptverfasser: Guo, Yaoqi, Huang, Jianbo, Cheng, Hui
Format: Artikel
Sprache:eng
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Zusammenfassung:Purpose - Recently, many scholars have been paying more attention to studying the existence and application of multifractality. However, most researches concentrate on studying multifractal features of returns or volume separately, and ignore the correlation between them. The purpose of this paper, therefore, is to give an empirical test on multifractal features of price-volume correlation in China metal futures market and then to conduct a comparative analysis from time and space dimensions, in order to better understand metals futures market behavior.Design methodology approach - This paper gives an empirical test by means of multifractal detrended cross-correlation analysis (MF-DCCA) approach, which is a technique employed in statistical physics to detect multifractal features of two cross-correlated nonstationary time series.Findings - Empirical results show that the price-volume correlation in China metal futures market is multifractal and that long range correlation and non-Gaussian probability distribution are the main reasons for the existence of multifractality. Also, a comparative analysis is conducted and it is found that although China metal futures market is becoming more and more effective, the effectiveness is lower than that in mature LME metal futures markets. The futures market still needs further development.Originality value - The paper's conclusions would help to understand the nonlinear dependency relationship and potential dynamics mechanism in price-volume correlation.
ISSN:0368-492X
1758-7883
DOI:10.1108/03684921211276710