Hilbert-Huang Transform based multifractal analysis of China stock market

In this paper, we employ the Hilbert-Huang Transform to investigate the multifractal character of Chinese stock market based on CSI 300 index. The measured Hilbert moment L-q(omega) shows a power-law behavior on the range 0.01 < omega < 0.1 min(-1), equivalent to a time scale range 10 < tau < 100 min. The measured scaling exponents zeta (q) is convex with q and deviates from the value q/2, implying that the property of self-similarity is broken. Moreover, zeta (q) and the corresponding singularity spectrum D(h) can be described by a lognormal model with a Hurst number H = 0.50 and an intermittency parameter mu = 0.12. Our results suggest that the Chinese stock fluctuation might be captured well by a multifractal random walk model with a proper intermittency parameter. (C) 2014 Elsevier B.V. All rights reserved.