考虑对称性冲击的时变信息风险测量

Measure of time-varying information risk with symmetric order-flow shock

准确测量股票信息风险对资产定价、风险管理和市场业绩的衡量均具有重要的作用.针对Duarte和Young模型中参数假设为常数这一缺陷,采用已有金融文献使用交易量建模消息状态概率和对称性订单流冲击概率的方法,允许Duarte和Young模型中的消息发生概率和对称性订单流冲击概率均时变,从而提出了时变信息风险测量模型,该模型可以测量日间和日内两个时间窗口的APIN和PSOS.进一步通过选取我国股市交易活跃股票的交易数据,实证比较了所建构的时变信息风险测量模型与Duarte和Young模型对数据的拟合效果及其对价差的解释能力.最后,实证研究了我国股市的周内信息风险的特征.

Accurate measure of the risk of stock information is of great significance for asset pricing,risk management,and the measure of market performance. To overcome the shortcoming of assuming constant probabilities of the states of news and symmetric order-flow shock of the model of Duarte and Young,we extend the methodology of Duarte and Young. We model the probabilities of the states of news and the probabilities of symmetric Order-Flow shock by using trade volumes. Our method allows both the probabilities of the states of news and the probabilities of symmetric Order-Flow shock to vary. Our APIN and PSOS estimates can be computed daily as well as over intraday intervals. Then,we select some actively traded stocks to do an empirical research and our model are compared with the model of Duarte and Young. Our empirical results show that our model provides a better fit for our data and has better explanatory power for spread. At last,we do an empirical research for the inter-day pattern of information risk.