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基于日内信息组成结构的时变特性,推导时变知情交易概率的非参数计算表达式,并构建测度日内高频信息风险的方法。应用此方法绘制上证50ETF产品2009年日内高频信息风险分布图。基于此测绘结果,对2009年7月29日该产品发生尾盘暴跌当日及其前后两日的高频分笔交易数据进行滚动跟踪测算,证明本文模型能够实时捕捉不断变化的信息风险状态,对由有毒信息流引起的资产价格突变具有预测功能。
Based on the time-varying characteristics of intra-day information composition, a non-parametric calculation expression for the probability of informed transaction is deduced and a method to measure the risk of intra-day high-frequency information is proposed. Apply this method to draw the risk distribution chart of the high frequency information of the SSE 50ETF products in 2009 days. Based on the result of the mapping, the rolling trace of the high frequency transaction data on the day of the last trading day and the day before and after the last trading day of the product on July 29, 2009 is calculated and the result shows that this model can capture the changing information risk status in real time. Abrupt changes in asset prices due to toxic information flow have predictive power.