Hilbert–Huang Transform based multifractal analysis of China stock market

Abstract

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 Lq(ω) shows a power-law behavior on the range 0.01<ω<0.1min−1, equivalent to a time scale range 10<τ<100min. The measured scaling exponents ζ(q) is convex with q and deviates from the value q/2, implying that the property of self-similarity is broken. Moreover, ζ(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 μ=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.