Quantile information share |
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Authors: | Donald Lien Zijun Wang |
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Institution: | Department of Economics and Department of Finance, College of Business, University of Texas, San Antonio, Texas |
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Abstract: | This paper presents a new method to estimate Hasbrouck-type market information share in price discovery. The prevailing market information share is calculated on the basis of conditional mean. We propose a conditional quantile regression approach to obtain a new market information share measure, quantile information share, which varies across the combinations of different price quantiles. The method is illustrated with two data sets, one on the spot and futures markets in pricing S&P 500 equity index, and the other on price discovery for a cross-listed stock. |
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Keywords: | bivariate quantile regression market information share price discovery |
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