文献类型：期刊文献

英文题名：A direct determination approach for the multifractal detrending moving average analysis

作者：Xu, Hai-Chuan[1,2]; Gu, Gao-Feng[1,2]; Zhou, Wei-Xing[1,2,3]

机构：[1] Research Center for Econophysics, East China University of Science and Technology, Shanghai, 200237, China; [2] Department of Finance, East China University of Science and Technology, Shanghai, 200237, China; [3] School of Science, East China University of Science and Technology, Shanghai, 200237, China

年份：2019

外文期刊名：arXiv

收录：EI(收录号：20200257170)

语种：英文

外文关键词：Brownian movement - Machine learning

摘要：In the canonical framework, we propose an alternative approach for the multifractal analysis based on the detrending moving average method (MF-DMA). We define a canonical measure such that the multifractal mass exponent τ(q) is related to the partition function and the multifractal spectrum f(α) can be directly determined. The performances of the direct determination approach and the traditional approach of the MF-DMA are compared based on three synthetic multifractal and monofractal measures generated from the one-dimensional p-model, the two-dimensional p-model and the fractional Brownian motions. We find that both approaches have comparable performances to unveil the fractal and multifractal nature. In other words, without loss of accuracy, the multifractal spectrum f(α) can be directly determined using the new approach with less computation cost. We also apply the new MF-DMA approach to the volatility time series of stock prices and confirm the presence of multifractality. Copyright ? 2019, The Authors. All rights reserved.