Local Parametric Estimation in High Frequency Data
提出一个时变参数模型，允许参数包含跳跃，并构建局部参数估计量来估计参数过程的积分值，推导了中心极限定理条件，适用于波动率及其幂次等估计。
<b>In this paper, we give a general time-varying parameter model, where the multidimensional parameter possibly includes jumps. The quantity of interest is defined as the integrated value over time of the parameter process</b>Θ=T−1∫0Tθt*dt<b>. We provide a local parametric estimator (LPE) of Θ and conditions under which we can show the central limit theorem. Roughly speaking those conditions correspond to some uniform limit theory in the parametric version of the problem. The framework is restricted to the specific convergence rate</b>n1/2<b>. Several examples of LPE are studied: estimation of volatility, powers of volatility, volatility when incorporating trading information and time-varying MA(1).</b>