Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient covariance estimation for asynchronous noisy high-frequency
  data   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.

28
The categories of this paper are: alg-geom
3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
30
The categories of this paper are: q-alg
14
The categories of this paper are: math-ph
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an
35
The categories of this paper are: mtrl-th