An estimator for the quadratic covariation of asynchronously observed Itô processes with noise: Asymptotic distribution theory

By Markus Bibinger. 2011

70 citations recorded by the source corpus.

The article is devoted to the nonparametric estimation of the quadratic covariation of non-synchronously observed Ito processes in an additive microstructure noise model. In a high-frequency setting, we aim at establishing an asymptotic distribution theory for a generalized multiscale estimator including a feasible central limit theorem with optimal convergence rate on convenient regularity assumptions. The inevitably remaining impact of asynchronous deterministic sampling schemes and noise corruption on the asymptotic distribution is precisely elucidated. A case study for various important examples, several generalizations of the model and an algorithm for the implementation warrant the utility of the estimation method in applications.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e57ad08238dd32e9ca468632ac7594cb818a779c

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Citations in the corpus

Econometric Analysis of Vast Covariance Matrices Using Composite Realized Kernels and Their Application to Portfolio Choice (2016, background): “…for noise as well as nonsynchronous trading is the focus of Zhang (2011a), Christensen, Kinnebrock, and Podolskij (2010), Aı̈tSahalia, Fan, and Xiu (2010), Park and Linton (2012), Bibinger (2011), Bibinger (2012), Bibinger et al. (2014), Shephard and Xiu (2014), and Barndorff-Nielsen et al. (2011).”
Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data (2019, unknown): “…(2011), the quasi-maximum likelihood estimator by Aït-Sahalia et al. (2010) and Shephard and Xiu (2017), the pre-averaging estimator by Christensen et al. (2010), the local method of moments by Bibinger et al. (2014), and the twoscale and multi-scale estimators by Zhang (2011) and Bibinger (2012).”