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

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.