标题： 异步噪声高频数据的有效协方差估计 显示英文标题

标题： Efficient covariance estimation for asynchronous noisy high-frequency data

摘要： 我们着重于在市场微观结构噪声存在的情况下估计对数价格过程的积分协方差。 我们在高频异步离散收益在市场微观结构噪声下被观测到的情形下，构造了两个伊藤过程二次协变的高效无偏估计量。 该估计量基于同步化和多尺度方法，并达到了最优收敛速度。 蒙特卡洛研究分析了我们估计量的有限样本特性。 显示英文摘要

摘要： We focus on estimating the integrated covariance of log-price processes in the presence of market microstructure noise. We construct an efficient unbiased estimator for the quadratic covariation of two It\^{o} processes in the case where high-frequency asynchronous discrete returns under market microstructure noise are observed. This estimator is based on synchronization and multi-scale methods and attains the optimal rate of convergence. A Monte Carlo study analyzes the finite sample size characteristics of our estimator.