The Long-Memory Property of Returns and Volatility in the Chinese Stock Market and the Issue of Contemporaneous Aggregation
Authors:   Asia-Europe Perspective Association, Jiang Zhuhua , Yoon Seong-Min 
Published: June 2018

Whether the long-memory property is inherent in the movement of the stock market returns and volatility (risk) time series is known as a very important issue practically or theoretically regard to the efficiency of the stock market. The efficient market hypothesis describes that the information obtained from past statistics can not be used to predict the future stock price. This is because when generating the information that may affect the price of the stock reflects this value of the information on the price quickly and enough. Since the future information is unknown, the future stock price will not be predictable if the stock market is efficient. However, if the long-memory property exists in the stock market returns and volatility time series, it could predict a certain portion of the future returns and risks by using past data. This predictability means the assumption of classical investment theory, that the stock market is efficient, may not be proper. Thus, the existence of long-memory property has been addressed as an important research topic by the financial investment researchers and stock market investors.
By using the stock prices of 50 stocks representing the Chinese stock market and their weighted average statistical index - SSE 50 Index, this study analyzes whether the long-memory property is inherent in Chinese stock market price movement as well as explains whether the existence of long-memory property is spurious result of the contemporaneous aggregation. The Chinese stock market is extremely proper market to perform the research related to the long-memory property because it is large and highly dynamic market. Using the returns and volatility of daily closing price (i.e. the absolute value of returns and its squared value) from January 2, 2004 to December 10, 2014 to conduct the Lo’s modified (R/S) analysis and the Geweke-Porter-Hudak (GPH) test.
The main results of the empirical analysis from this study are as follows. First, although SSE 50 Index return series has long-memory property, there are not many evidences for its 50 constituent company stock prices. This means that predicting the return series for SSE 50 Index is relatively easier than individual stock prices. Second, in the case of volatility, both of the SSE 50 Index and its 50 individual stock prices have the presence of a long-memory property. Third, most of the 50 individual stock prices in Chinese market have the long-memory property. These are the unique properties inherent in the stock market time series instead of causing by the spurious consequence of a contemporaneous aggregation bias. Fourth, volatility has the stronger presence of a long-memory property than returns. This means that predicting the risk is relatively easier than returns due to volatility clustering. Based on the overall statistical test results, volatility has the stronger presence of a long-memory property than returns. The long-memory property exists in the Chinese stock market and this is the unique property inherent in the stock market time series instead of causing by the spurious consequence of a contemporaneous aggregation bias.
These analytical findings indicate that the Chinese stock market is not fully efficient due to the existence of the long-memory property. The reasons that Chinese stock market is not efficient enough are that many Chinese investors have the speculative purposes and market information is not delivered transparently and quickly. Because of these characteristics, global investors will have room to reduce the risk and increase profits by leveraging long-memory properties in the Chinese stock market.