基于上证指数高频数据的中国资本市场微观特性研究

以上证指数高频数据为研究对象,基于上涨、平缓和下跌三个市场状态分析我国金融市场的微观特性.通过分析上证指数在不同时间间隔下的概率分布、自相关性和多分形三个特性,发现上证指数对数增量序列存在厚尾、列维非高斯分布特征,且随着时间间隔的增大,收益序列愈收敛于正态分布,其中,下降趋势收敛于正态分布的速度更快,拟合于列维分布的效果更好.最为突出的是,在自相关函数分析中,上证指数的收益率无长期记忆性,而波动率则具有较强的记忆性.同时,波动率的自相关性存在明显的周期性特征,即T=240 min,且在下降趋势时其相关性最高.在以时间增量刻画的多重分形结构中,对于不同的时间序列、时间间隔,由于受投资期限和流动性的影响,三种股市状态的收益率波动存在着短期和长期性的差异.上证指数的总体宏观行为与国际成熟股市较为一致,但在微观特性上仍存在显著差异,其所特有的周期性是投资者的惯性反冲所致,而自相关性函数较之成熟股市衰减较慢,则表明投资者的投资行为更多地受历史信息的影响.

Microscopic characteristics of Chinese capital market based on the high frequency data of Shanghai composite index

This paper mainly uncovers the typical microscopic characteristics of Chinese capital market in three different stock price stages of rising, steady and falling based on the high frequency data of Shanghai composite index. Firstly, by analyzing the probability distribution of the Shanghai composite index in different time intervals, we clearly find that the logarithmic change of the index presents an obvious heavy tail feature as well as non-Gaussian Levy distribution, and the return series converges to a normal distribution with the increase of the time interval, which becomes more significant especially in the falling stage of stock prices. Secondly, by calculating the autocorrelation function, we observe that unlike the return rate, the fluctuation ratio of Shanghai composite index demonstrates remarkable long memory volatility with a periodicity of about 240 min, and the autocorrelation curve in falling stage is much higher than in rising and steady stages. Thirdly, in the multi-fractal structure, the volatility of return series has significant short-term and long-term differences among three different stages of rising, steady and falling due to the effects of time limitation and liquidity of investment. Finally, the macroscopic behavior of the Shanghai composite index is relatively consistent with that of the international mature stock market, however, the corresponding microscopic characteristics demonstrate significant differences due to the fact that the Chinese capital market is strongly dependent on the macroeconomic policy, investor sentiment, and liquidity levels. It is quite remarkable that the tail distribution of mature stock market is much fatter than that of Chinese stock market because of the special control and limit mechanism of stock prices in China, which finally causes the considerably lower amplitude of price fluctuation. Moreover, it is also found that the attenuation speed of the autocorrelation function in the Chinese capital market is obviously slower than that in the mature stock market, which suggests that the behaviors of investors in Chinese stock market are more likely to be influenced by the historic exchange information. At the same time, the periodicity of autocorrelation function is actually caused by the inertia recoil of investors, which further verifies the information asymmetry of Chinese stock market. Especially, by changing the starting values of the samples, we find that the periodicity of autocorrelation function still remains the same, which indicates that the periodicity characteristic of stock price is not dominated only by the intraday pattern of trading activity. Therefore, the investors should discover the underlying rules of high-frequency data and extract more useful knowledge in order to guide their investment decisions more effectively.