Nonlinear Noise Estimation in International Stock Markets: Coarse-grained Entropy Method

Abstract

With the step-by-step opening of China Stock Market and gradual strengthening of international linkage, how to efficiently measure and manage risk, evaluate and improve market operation efficiency is an important project in present financial research. According to nonlinear dynamics and chaos and fractal theory, we apply phase space reconstruction technique and coarse-grained entropy method to estimate the nonlinear noise levels in stock markets of Chinese Mainland, Hong Kong, US, UK and Japan, and we emphasize on discussing the standard deviation of nonlinear noise  and noise-to-signal ratio NSR which are two important indexes about risk measurement and efficiency evaluation, and further we make a comprehensive comparison analysis on the risk and operation efficiency of stock markets of above countries or areas.