The jump characteristics of stock market from views of high frequency data

Tang Yong, Tang Zhen-peng, Huang You-po
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Abstract

Based on the framework of non-parametric approach, the new jump variance and continuous sample path variance are constructed and the jump variance is modeled by combining A-J jump detection statistic. With high frequency data from Shanghai composite index, the empirical analyses are carried out from four aspects: the characteristics and contribution of jump variance, jump sizes and the relationship between economic information and jump. It turns out that the jump variance series show leptokurtic, heavy tail and volatility clusters; the contribution of jump variance to whole variance nearly equals for different sampling frequency; the positive jump and negative jump are asymmetric and the adjusted returns are nearly normal distribution by the single jump adjustments; the correlation between the jumps and economic information release is always positive.
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从高频数据看股票市场的跳跃特征
基于非参数方法的框架,构造了新的跳跃方差和连续样本路径方差,并结合A-J跳跃检测统计量对跳跃方差进行建模。利用上证综合指数的高频数据,从跳跃方差的特征和贡献、跳跃大小以及经济信息与跳跃的关系四个方面进行实证分析。结果表明,跳跃方差序列表现为细峰型、重尾型和波动型;在不同采样频率下,跳跃方差对总方差的贡献几乎相等;单跳调整后的正跳和负跳不对称,调整后的收益接近正态分布;跳跃与经济信息发布之间的相关关系始终是正的。
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