Weighted Least Squares Realized Covariation Estimation

Yifan Li, Ingmar Nolte, Michalis Vasios, Valeri Voev and Qi Xu

Journal of Banking & Finance, 2022, vol. 137, issue C

Abstract: We introduce a novel weighted least squares approach to estimate daily realized covariation and microstructure noise variance using high-frequency data. We provide an asymptotic theory and conduct a comprehensive Monte Carlo simulation to demonstrate the desirable statistical properties of the new estimator, compared with existing estimators in the literature. Using high-frequency data of 27 DJIA constituting stocks over a period from 2014 to 2020, we confirm that the new estimator performs well in comparison with existing estimators. We also show that the noise variance extracted based on our method can be used to improve volatility forecasting and asset allocation performance.

Keywords: Market Microstructure Noise; Realized Volatility; Realized Covariation; Weighted Least Squares; Volatility Forecasting; Asset Allocation (search for similar items in EconPapers)
JEL-codes: C13 C22 G10 (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:jbfina:v:137:y:2022:i:c:s0378426622000206

DOI: 10.1016/j.jbankfin.2022.106420

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