Multiscaling and Stock Market Efficiency in China
Abstract
China has taken important steps to reform its economy and capital markets in the past 20 years. Despite these efforts there is a lack of quantitative evidence on how these measures have impacted price returns in the stock exchanges. The purpose of this research was to determine the randomness of Chinese equity returns and to measure the scaling property of volatility over time. The main assumption of the Efficient Market Hypothesis is that security returns follow the path of a random walk and that volatility scales with the square root of time. This notion was tested by analyzing daily stock returns of the Shanghai- and Shenzhen Composite Indexes between 1990 and 2013. The Kolmogorov–Smirnov (KS) test rejected the log-normal distribution and random walk hypothesis. The measured Hurst exponents revealed a multiscaling property of fractal Brownian motion and indicated the presence of long-range dependence. The findings also showed that the degree of persistence and cycle length has reduced over time.