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作 者:黄晓彬[1] 王春峰[1] 房振明[1] 闫芳[1]
出 处:《系统工程》2012年第3期8-15,共8页Systems Engineering
基 金:国家自然科学基金资助项目(70771076)
摘 要: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 characteristics of time-varying intraday information composition structure,the non-parametric computation expression of time-varying PIN was deduced,and a method to measure the intraday high-frequency information risk was built.By applying this method a high-frequency information risk distributing graph of SSE50 ETF was drawn.Based on this result,a rolling and tracking algorithm was used to process the tick by tick transaction data of the period from 2009-7-27 to 2009-7-31,during which time the price of SSE50 ETF collapsed late in 2009-7-29.It was proved that this model was able to detect the changing state of information risk,and was also able to predict the sudden changes of asset price caused by the toxic information flow.
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