Fisher's Information for Discretely Sampled Lvy Processes
研究高频离散采样下Lévy过程的Fisher信息渐近行为，推导参数有效估计的最优收敛速度，并证明可区分连续部分与跳跃部分及不同跳跃类型。
This paper studies the asymptotic behavior of Fisher's information for a Lévy process discretely sampled at an increasing frequency. As a result, we derive the optimal rates of convergence of efficient estimators of the different parameters of the process and show that the rates are often nonstandard and differ across parameters. We also show that it is possible to distinguish the continuous part of the process from its jumps part, and even different types of jumps from one another. Copyright Copyright 2008 by The Econometric Society.