Weighted multifractal analysis of financial time series

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• 作者：Hui Xiong ; Pengjian Shang
• 关键词：Weighted multifractal analysis ; Variance ; Partition function ; Financial time series ; Volatility
• 刊名：Nonlinear Dynamics
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：87
• 期：4
• 页码：2251-2266
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Vibration, Dynamical Systems, Control; Classical Mechanics; Mechanical Engineering; Automotive Engineering;
• 出版者：Springer Netherlands
• ISSN：1573-269X
• 卷排序：87

文摘

In this paper, we propose the weighted multifractal analysis based on variance-weighted partition function (WMA), to evaluate the fractals of nonlinear time series containing amplitude information. The reliability of the proposed WMA is supported by simulations on generated and real-world financial volatility data. Numerical simulations with synthesized data show that WMA is comparative to the classic partition function-based standard multifractal analysis (SMA) and the multifractal detrending moving average analysis. More importantly, empirical analyses of Chinese stock indices illustrate that WMA outperforms SMA in distinguishing Hang Seng Index form SSE Composite Index and SZSE Component Index qualitatively and quantitatively, showing the power of WMA in discriminating series with distinctive amplitudes.