University of Adelaide
A Quantile Regression Analysis of the Cross Section of Stock Market Returns
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Keywords: CAPM; semi-parametric regression; errors-in-variables; Monte Carlo simulation; cross section analysis; under and over performing stocks.
JEL Classifications: G12, C14, C21
In recent years, many researchers have empirically tested the Capital Asset Pricing Model (CAPM) by considering a cross section regression of the excess market return of an asset or portfolio on beta and other conditioning variables. These studies generally follow the two-pass method originally considered by Fama and MacBeth (1973), where betas are estimated from a time series regression and these values are used to explain variation in the cross section of subsequent expected return. We focus on the second stage. The traditional approach su¤ers because it only considers the performance of the CAPM at the mean of the conditional distribution. In this paper, we extend the literature by using quantile regression, developed by Koenker and Bassett (1978) and recently popularized by Buchinsky (1998), to analyze this cross sectional stage of the problem. This method enables us to estimate the marginal e¤ect of a change in an independent variable on any conditional quantile of the dependent variable and thus test whether the conditional CAPM holds at all points of the conditional distribution. By doing this, we are able to model the performance of firms or portfolios that under or over perform, in the sense that the conditional mean over or under predicts the return of the portfolio.
PDF file of paper: hughes_abstract.pdf
Session: Asset Prices I
Time: Saturday, 7 July, 2:15pm - 3:45pm