The Econometrics of Ultra-high-frequency Data
用标记点过程理论分析超高频交易数据，将Engle和Russell的ACD模型应用于IBM逐笔交易数据，估计半参数风险函数和瞬时条件方差，发现意外长间隔对方差有负向影响。
Ultra-high frequency data are complete transactions data which inherently arrive at random times. Marked point processes provide a theoretical framework for analysis of such data sets. The ACD model developed by Engle and Russell (1995) is then applied to IBM transactions data to develop semi-parametric hazard estimates and measures of instantaneous conditional variances. The variances are negatively influenced by surprisingly long durations as suggested by some of the market micro-structure literature