【摘要】 本文提出了基于高频数据的分类信息混合分布EGARCH模型,将上证指数的五分钟高频数据作为研究对象,引入修正混合分布(MMM)模型,将去除了趋势性和序列相关性的不同性质的对数交易量分解为进入市场的正的随机信息流和负的随机信息流两部分,作为分类信息流代理,加入EGARCH模型的方差方程中,考察"好消息"和"坏消息"对上证指数波动性的影响。更多还原

【Abstract】 <Abstrcat> The high-frequency-data-based classified information mixture distribution EGARCH model,which is put forward in this article,is based on market microstructure theory.We take an empirical test on the price-volume relation in the Chinese stock market by adding the high-frequency-data-based volume caused by good news and bad news in the EGARCH model as the classified information flow proxy.In addition,the result of our work can support that the classified volume is an interpretation of the persistence of the volatility of the stock market,and we can distinguish the different effect caused by the classified information.更多还原