Fractal Characteristics, Multiple Bubbles, and Jump Anomalies in the Chinese Stock Market

Abstract

To consider the jump problem of the Chinese stock market, this paper takes the CSI 300 Index from April 2005 to November 2015 as the research object, uses the rescaled range analysis (R/S analysis) method to examine the fractal characteristics of the Chinese stock market in the past ten years, and deduces the possibility of multiple bubbles in the Chinese stock market. Based on this, combined with the log-periodic power law (LPPL) model, the stock market bubbles are identified in different periods. The results show that China’s stock market has some anomalies in terms of positive bubbles, negative bubbles, and reverse bubbles, as well as the cross occurrence of reverse-negative bubbles. Besides, through a comparison with the major foreign stock markets, it is found that the fluctuation range of the Chinese stock market is much larger than that of the Dow Jones Industrial Average and the FTSE 100 indices in the same period and there are also more types of multibubbles, which is a connotative anomaly that makes the Chinese stock market different from other major stock markets. Furthermore, the bubble phenomenon in the Chinese stock market during the periods of 2005/4–2007/10 and 2015/6–2015/11 is studied, and it is found that there is a jump anomaly in the Chinese stock market. Finally, based on the above empirical analysis and the current state of the stock market, this paper provides some suggestions for improving the mechanism of the Chinese stock market.

The (In)Efficiency of Emerging and Developed Markets: An Analysis from Fractal Theory

“…The graphic representation allows verifying the EIs. Thus, the oscillations in the behavior of efficiency are evident, and at no time a perfect efficient market was verified, which corroborates previous analyses of the validity of the FMH on this phenomenon, as presented by Meng et al (2020) and Dima et al (2021).…”

“…However, it is also important to note that the Chinese index was the one that presented the greatest discrepancy in the behavior of the metrics used to assess market efficiency, with the highest concentration of deviations from the expected values of an efficient market when compared to the others. Thus, the validity of studies that focus specifically on China, such as Meng et al (2020), is verified, given the particularities of the shocks that this market tends to suffer in relation to other markets.…”

A Stock Closing Price Prediction Model Based on CNN‐BiSLSTM

“…With the rapid growth of China's economy and the continuous expansion of the financial market, more and more investors have begun to pay attention to the methods to improve return on investment and effectively avoid certain risks. Among these methods, the stock price prediction is of great significance in the commercial and financial fields [1,2]. In the face of the rise and fall of stock price, investors will get unpredictable profits and even losses, so it has become an issue of concern for investors to predict stock price and select stock worthy of investment.…”