  The financial market and turbulence have been broadly compared on account of
the same quantitative methods and several common stylized facts they shared. In
this paper, the She-Leveque (SL) hierarchy, proposed to explain the anomalous
scaling exponents deviated from Kolmogorov monofractal scaling of the velocity
fluctuation in fluid turbulence, is applied to study and quantify the
hierarchical structure of stock price fluctuations in financial markets. We
therefore observed certain interesting results: (i) The hierarchical structure
related to multifractal scaling generally presents in all the stock price
fluctuations we investigated. (ii) The quantitatively statistical parameters
that describes SL hierarchy are different between developed financial markets
and emerging ones, distinctively. (iii) For the high-frequency stock price
fluctuation, the hierarchical structure varies with different time period. All
these results provide a novelty analogy in turbulence and financial market
dynamics and a insight to deeply understand the multifractality in financial
markets.
