High-Frequency Covariance Estimates With Noisy and Asynchronous Financial Data

By Yacine Aït-Sahalia, Jianqing Fan, D. Xiu. 2010

268 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/8f28cd9443594173d6867c448f1deaef56069c9c

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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, methodology): “Multivariate versions of this work were developed by Andersen et al. (2003) and Barndorff-Nielsen & Shephard (2004). This work used sparse sampling of returns of 5-20 minutes to try to mitigate the impact of noise and non-synchronous trading. In the univariate case extensive work has developed which”
Estimating the Quadratic Covariation Matrix from Noisy Observations: Local Method of Moments and Efficiency (2013, methodology): “2.”
Statistical Properties of Microstructure Noise (2013, methodology): “…method as in Barndorff-Nielsen et al. (2008), Barndorff-Nielsen et al. (2011); the pre-averaging method as in Jacod et al. (2009), Kinnebrock et al. (2010); the multi-scale method as in Zhang (2006); the quasi-maximum likelihood method as in Xiu (2010), Aït-Sahalia et al. (2010), among others.”
Estimating the Spot Covariation of Asset Prices—Statistical Theory and Empirical Evidence (2014, background): “Estimators accounting for both types of frictions are, among others, the quasi maximum likelihood estimator by Ait-Sahalia, Fan, and Xiu (2010), the multivariate realized kernel estimator by Barndorff-Nielsen et al. (2011), the multivariate preaveraging estimator by Christensen, Podolskij, and…”
Robust Markowitz mean‐variance portfolio selection under ambiguous covariance matrix (2016, unknown): “…inaccurate due to asynchronous data and lead-lag eﬀect, especially when the number of assets is large, and the correlation estimate converges to its true value less rapidly than the estimates of volatilities that are based on the full sets of marginal observations, see e.g. [18], [16] and [1].”
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.”
Image Classification with Deep Learning in the Presence of Noisy Labels: A Survey (2019, unknown): “[33, 34], financial analysis [35] and many more.”