基于高频数据的中国股市跳跃特征实证分析
发布时间：2018-07-16 19:08
【摘要】：研究跳跃的内在机制和理清不同类型的风险对波动估计和建模非常重要,这是风险管理的核心内容。当前,利用高频数据这方面研究仍然还不成熟,还有丰富的内容期待探索。文章基于非参数方法,结合A-J跳跃检验统计量,构建新的跳跃方差和连续样本路径方差、对跳跃方差建模。利用上证综指高频数据,对跳跃方差统计特征、跳跃方差贡献、跳跃幅度以及跳跃与经济信息关系进行分析。结果显示:跳跃方差存在尖峰厚尾与波动集聚性;在不同的抽样频率下,跳跃方差对总方差的贡献程度相近;正向、负向跳跃幅度不对称,剥离跳跃后的标准化收益率接近正态分布;经济信息公布与跳跃总是正相关的,并对一些异常现象给予解释。依据波动和跳跃的复杂性,此项研究有助于投资者优化投资策略和为监管部门提供监管基础。
[Abstract]:It is very important to study the internal mechanism of jumping and to identify different types of risks for volatility estimation and modeling, which is the core content of risk management. At present, the use of high-frequency data in this area is still immature, there are plenty of content to explore. Based on the nonparametric method and A-J jump test statistics, a new jump variance and continuous sample path variance are constructed, and the jump variance is modeled. Based on the high frequency data of Shanghai Composite Index, this paper analyzes the statistical characteristics of jump variance, the contribution of jump variance, jump amplitude and the relationship between jump and economic information. The results show that the jump variance has peak thick tail and fluctuation agglomeration, the contribution of jump variance to total variance is similar at different sampling frequencies, the positive and negative jump amplitude is asymmetric, The standardized rate of return after stripping and jumping is close to the normal distribution, and the announcement of economic information is always positively related to the jump, and some abnormal phenomena are explained. Depending on the complexity of volatility and jumping, the study helps investors optimize investment strategies and provide regulatory bases for regulators.
【作者单位】： 福州大学管理学院;
【基金】：国家自然科学基金资助项目(71171056,70973021) 福建省社科规划项目(2011B135)
【分类号】：F224;F832.51
[Abstract]:It is very important to study the internal mechanism of jumping and to identify different types of risks for volatility estimation and modeling, which is the core content of risk management. At present, the use of high-frequency data in this area is still immature, there are plenty of content to explore. Based on the nonparametric method and A-J jump test statistics, a new jump variance and continuous sample path variance are constructed, and the jump variance is modeled. Based on the high frequency data of Shanghai Composite Index, this paper analyzes the statistical characteristics of jump variance, the contribution of jump variance, jump amplitude and the relationship between jump and economic information. The results show that the jump variance has peak thick tail and fluctuation agglomeration, the contribution of jump variance to total variance is similar at different sampling frequencies, the positive and negative jump amplitude is asymmetric, The standardized rate of return after stripping and jumping is close to the normal distribution, and the announcement of economic information is always positively related to the jump, and some abnormal phenomena are explained. Depending on the complexity of volatility and jumping, the study helps investors optimize investment strategies and provide regulatory bases for regulators.
【作者单位】： 福州大学管理学院;
【基金】：国家自然科学基金资助项目(71171056,70973021) 福建省社科规划项目(2011B135)
【分类号】：F224;F832.51
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