Efficient covariance estimation for asynchronous noisy high-frequency data
Statistics Theory
2008-12-19 v1 Statistics Theory
Abstract
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.
Cite
@article{arxiv.0812.3536,
title = {Efficient covariance estimation for asynchronous noisy high-frequency data},
author = {Markus Bibinger},
journal= {arXiv preprint arXiv:0812.3536},
year = {2008}
}
Comments
29 pages, including 4 pictures