文献类型：期刊文献

英文题名：Finite-size effect and the components of multifractality in financial volatility

作者：Zhou, Wei-Xing[1,2,3]

机构：[1]E China Univ Sci & Technol, Sch Business, Shanghai 200237, Peoples R China;[2]E China Univ Sci & Technol, Sch Sci, Shanghai 200237, Peoples R China;[3]E China Univ Sci & Technol, Res Ctr Econophys, Shanghai 200237, Peoples R China

年份：2012

卷号：45

期号：2

起止页码：147

外文期刊名：CHAOS SOLITONS & FRACTALS

收录：;EI(收录号：20120214679786);WOS:【SCI-EXPANDED(收录号:WOS:000301019800007)】；

基金：I am grateful to Professor Didier Sornette for allowing me to use the computer cluster in his group at ETH Zurich and to Professor Stanislaw Drozdz for invaluable discussions. This work was partially supported by the "Shu Guang" project sponsored by Shanghai Municipal Education Commission and Shanghai Education Development Foundation (Grant No. 2008SG29), the Fundamental Research Funds for the Central Universities, and the National Natural Science Foundation of China (Grant No. 11075054).

语种：英文

外文关键词：Time series - Fractals - Size determination - Size distribution

摘要：Many financial variables are found to exhibit multifractal nature, which is usually attributed to the influence of temporal correlations and fat-tailedness in the probability distribution (PDF). Based on the partition function approach of multifractal analysis, we show that there is a marked finite-size effect in the detection of multifractality, and the effective multifractality is the apparent multifractality after removing the finite-size effect. We find that the effective multifractality can be further decomposed into two components, the PDF component and the nonlinearity component. Referring to the normal distribution, we can determine the PDF component by comparing the effective multifractality of the original time series and the surrogate data that have a normal distribution and keep the same linear and nonlinear correlations as the original data. We demonstrate our method by taking the daily volatility data of Dow Jones Industrial Average from 26 May 1896 to 27 April 2007 as an example. Extensive numerical experiments show that a time series exhibits effective multifractality only if it possesses nonlinearity and the PDF has an impact on the effective multifractality only when the time series possesses nonlinearity. Our method can also be applied to judge the presence of multifractality and determine its components of multifractal time series in other complex systems. (C) 2011 Elsevier Ltd. All rights reserved.