基于上证指数高频数据的中国资本市场微观特性研究

发布时间：2018-06-25 19:22

本文选题：资本市场 + 微观特性　；参考：《物理学报》2017年12期

【摘要】：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.
[Abstract]:Taking the high frequency data of Shanghai stock index as the research object, this paper analyzes the microscopic characteristics of China's financial market based on the three market states of rising, levelling and falling. By analyzing the probability distribution, autocorrelation and multifractal characteristics of Shanghai stock index at different time intervals, it is found that the logarithmic increment sequence of Shanghai stock index has the characteristics of thick tail and non-Gaussian distribution, and increases with the time interval. The income series converges to normal distribution, in which the decreasing trend converges to normal distribution faster, and the effect of fitting to Levi distribution is better. Most notably, in the autocorrelation function analysis, the yield of Shanghai stock index has no long-term memory, while the volatility has a strong memory. At the same time, the autocorrelation of volatility has obvious periodicity characteristic, that is, TX 240 mins, and its correlation is the highest in the downward trend. In the multifractal structure characterized by time increment, for different time series, time interval, due to the influence of investment term and liquidity, there are short-term and long-term differences between the three stock market return fluctuations. The overall macro behavior of Shanghai stock index is consistent with that of the international mature stock market, but there are still significant differences in microscopic characteristics. Its unique periodicity is caused by the inertia backfire of investors, while the autocorrelation function decays more slowly than the mature stock market. It shows that investors' investment behavior is more influenced by historical information.
【作者单位】：福州大学经济与管理学院;福建省金融科技创新重点实验室;福建省企业发展研究中心;
【基金】：国家自然科学基金(批准号:71573042,71171056) 福建省社科基金青年博士项目(批准号:FJ2016C200)资助的课题~~
【分类号】：F832.5

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