文献类型：期刊文献

英文题名：The components of empirical multifractality in financial returns

作者：Zhou, Wei-Xing[1,2,3,4]

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;[4]Chinese Acad Sci, Res Ctr Fictitious Econ & Data Sci, Beijing 100080, Peoples R China

年份：2009

卷号：88

期号：2

外文期刊名：EPL

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000271963700037)】；

基金：I am grateful to GAO-FENG GU, ZHI-QIANG JIANG and GUO-HUA MU for fruitful discussions. This work was partly supported by Shanghai Educational Development Foundation (2008SG29) and the Program for New Century Excellent Talents in University (NCET-07-0288).

语种：英文

摘要：We perform a systematic investigation on the components of the empirical multifractality of financial returns using the daily data of Dow Jones Industrial Average from 26 May 1896 to 27 April 2007 as an example. The temporal structure and fat-tailed distribution of the returns are considered as possible influence factors. The multifractal spectrum of the original return series is compared with those of four kinds of surrogate data: 1) shuffled data that contain no temporal correlation but have the same distribution, 2) surrogate data in which any nonlinear correlation is removed but the distribution and linear correlation are preserved, 3) surrogate data in which large positive and negative returns are replaced with small values, and 4) surrogate data generated from alternative fat-tailed distributions with the temporal correlation preserved. We find that all these factors have influence on the multifractal spectrum. We also find that the temporal structure (linear or nonlinear) has minor impact on the singularity width Delta alpha of the multifractal spectrum while the fat tails have major impact on Delta alpha, which confirms the earlier results. In addition, the linear correlation is found to have only a horizontal translation effect on the multifractal spectrum in which the distance is approximately equal to the difference between its DFA scaling exponent and 0.5. Our method can also be applied to other financial or physical variables and other multifractal formalisms. Copyright (C) EPLA, 2009