A Research On The Difference Of Stock Market Efficiency And Its Mechanism Between China And The US

Capital markets,especially the emerging ones,sometimes may exhibit behaviors that are inconsistent with the Efficient Market Hypothesis(EMH).When that happens,can the complexity changes in those markets over time be reliably detected?To answer this question,we have compared the behaviors of the US and the Chinese stock markets by computing the permutation entropy(PE)from three stock composite indices,the Shanghai Stock Exchange Composite Index(SSE),the Shenzhen Stock Exchange Composite Index and the Dow Jones Industrial Average(DJ).We have found that the US stock market is largely fully random and consistent with EMH,irrespective of whether low and high-frequency stock index data are used.The Chinese stock market is also largely consistent with EMH when low frequency data are used.However,a completely different picture emerges when the high-frequency stock index data are used.In particular,the Chinese stock market is inconsistent with EMH,since the PE decreases substantially in two significant time windows,each encompassing a rapid market rise and then a few gigantic stock crashes.Comparing with the empirical studies which test the validity of EHM using traditional statistical methods,PE can characterize the dynamic complexity(randomness)changes and give more strong evidences for testing the efficiency of a market.To further clarify the mechanism of complexity changes,we have examined the memory effect from both the US and the Chinese stock index data by computing the Hurst parameters(H).It is found that H deviates from 1/2 significantly for time scales up to a few tens of minutes for the Chinese stock market.In stark contrast,H is close to 1/2 for the US stock market,which is expected if EMH largely applies.