Beta-Adjusted Covariance Estimation

Kris Boudt, K. Dragun, Orimar Sauri, S. Vanduffel
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引用次数: 2

Abstract

The increase in trading frequency of Exchanged Traded Funds (ETFs) presents a positive externality for financial 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 pre-estimator 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 confirms that the accuracy gains are substantial in all cases considered. In the empirical part of the paper, we show the gains in tracking error efficiency when using the BAC adjustment for constructing portfolios that replicate a broad index using a subset of stocks.
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校正协方差估计
当交易所交易基金(ETF)的交易频率高于成分股的价格时,ETF交易频率的增加对金融风险管理具有正外部性。正溢出在于提高了ETF所包含股票的综合协方差预估器的准确性。提出的Beta调整协方差(BAC)等于预估计量加上最小调整矩阵,使得协方差隐含的股票etf Beta等于目标Beta。我们关注Hayashi和Yoshida(2005)的预估计量,并推导了其隐含股票- etf beta的渐近分布。仿真研究证实,在所有考虑的情况下,精度增益都是可观的。在本文的实证部分,我们展示了当使用BAC调整来构建使用股票子集复制广泛指数的投资组合时,跟踪误差效率的收益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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