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.
Highlights
It can be found that most of the above studies analyze the formation, development, and bursting of financial market bubbles from a backward perspective
Shu and Zhu [22] used the LPPLS confidence indicator to study the daily data of the CSI 300 index and to test the existence of bubbles in the Chinese stock market. e results suggested that this method can be used to predict the future positive and negative bubbles and their burst times, reducing the damage caused by the collapse of a bubble
This paper argues that the distinction between bubbles and negative bubbles is not enough to fully reflect the bubble phenomenon in the market. erefore, considering the impact of the speed of the price trend change on the market bubble, the bubble phenomenon in financial markets is instead divided into four categories: positive bubbles, negative bubbles, reverse bubbles, and reverse-negative bubbles. e specific forms are shown in Figures 1–4: (1) Positive bubble: the price has a sharply rising trend, with the price rising above its actual value, and the rising trend gradually increases
Summary
06-Nov-2015 e results of the Hurst exponent when N 50. Figure 8: 06-Nov-2015 e results of the Hurst exponent when N 120. Since the transitional stage does not conform to the characteristics of LPPL model fitting, we select three types of periods for the fitting analysis, i.e., up jump, down jump, and small jump of the transverse disk. We apply the LPPL model to the Dow Jones industrial index and the UK FTSE 100 index in the same period. We find that these two indices have only two bubbles: a reverse bubble and a reverse negative bubble (the calculation process is the same as the calculation in the paper, so please contact the corresponding author if necessary), and these two indices have large differences from the Chinese stock market.
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