Correcting microstructure comovement biases for integrated covariance |
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| Authors: | Jin-Huei Yeh Jying-Nan Wang |
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| Affiliation: | 1. Department of Finance, National Central University, Taiwan;2. Department of Finance, Minghsin University of Science and Technology, Taiwan;1. Goodman School of Business, Department of Finance, Operation and Information Systems, Brock University, Canada;2. College of Economics and Political Science, Department of Economics and Finance, Sultan Qaboos University, Oman;1. School of Economics and Management, Chongqing University of Posts and Telecommunications, 2 Chongwen Road, Chongqing, 400065, China;2. School of Finance, Jiangxi University of Finance and Economics, 169 East Shuanggang Road, Nanchang, 330013, China;3. Research Center of Finance, Shanghai Business School, 2271 West Zhongshan Road, Shanghai, 200235, China;1. Department of Economics, University of Ioannina, University Campus, 45110 Ioannina, Greece;2. Faculty of Economics, University of Athens, 1 Sofokleous Street, 10559 Athens, Greece |
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| Abstract: | Finding a precise variance–covariance matrix is the building block of empirical finance. While microstructure-noise-robust methods for realized volatility are in the mainstream of financial econometrics, little if any attention has been devoted to estimating a noise-free realized covariance for overlooking the well-documented manifestation of commonality in market microstructure factors such as order flows, liquidity or herding. By documenting and recognizing this fact, we propose a microstructure-noise-free nonparametric covariance estimator to uncover the virtual integrated covariance. The estimator is easy to implement and performs admirably. |
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