Beta-Adjusted Covariance Estimation

Kirill Dragun (), Kris Boudt, Orimar Sauri and Steven Vanduffel ()

Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium from Ghent University, Faculty of Economics and Business Administration

Abstract: The increase in trading frequency of Exchanged Traded Funds (ETFs) presents a positive externality for nancial risk management when the price of the ETF is available at a higher frequency than the price of the component stocks. The positive spillover consists in improving the accuracy of pre-estimators of the integrated covariance of the stocks included in the ETF. The proposed Beta Adjusted Covariance (BAC) equals the preestimator plus a minimal adjustment matrix such that the covariance-implied stock-ETF beta equals a target beta. We focus on the Hayashi and Yoshida (2005) pre-estimator and derive the asymptotic distribution of its implied stock-ETF beta. The simulation study conrms that the accuracy gains are substantial in all cases considered. In the empirical part of the paper, we show the gains in tracking error eciency when using the BAC adjustment for constructing portfolios that replicate a broad index using a subset of stocks.

Keywords: High-frequency data; realized covariances; ETF; asynchronicity; stock-ETF beta; Localized Hayashi-Yoshida; Index tracking (search for similar items in EconPapers)
JEL-codes: C22 C51 C53 C58 (search for similar items in EconPapers)
Pages: 51 pages
Date: 2021-02
New Economics Papers: this item is included in nep-ecm, nep-ore and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:rug:rugwps:21/1010

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