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A quantile regression analysis of the cross section of stock market returns

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  • Michelle L. Barnes
  • Anthony W. Hughes
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    Abstract

    Traditional methods of testing the Capital Asset Pricing Model (CAPM) do so at the mean of the conditional distribution. Instead, we test whether the conditional CAPM holds at other points of the distribution by utilizing the technique of quantile regression (Koenker and Bassett 1978, Buchinsky 1998). This method allows us to model the performance of firms or portfolios that underperform or overperform in the sense that the conditional mean under- or overpredicts the return of the portfolio; we interpret firms that fall in the lower (upper) quantiles as having received bad (good) news during the sample period. Quantile regression also helps to alleviate some of the statistical problems which plague the conditional CAPM literature, such as errors-in-variables, omitted variables bias, sensitivity to outliers and non-normal error distributions. We find, among other results, that in the context of a conditional CAPM, beta is significant in both tails of the distribution of returns - negative for firms that underperform and positive for firms that overperform - but is insignificant around the median.

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    Bibliographic Info

    Paper provided by Federal Reserve Bank of Boston in its series Working Papers with number 02-2.

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    Date of creation: 2002
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    Handle: RePEc:fip:fedbwp:02-2

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    Keywords: Capital assets pricing model;

    References

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    Cited by:
    1. El-Osta, Hisham S., 2011. "The Impact of Human Capital on Farm Operator Household Income," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 40(1), April.
    2. Lee, Bong Soo & Li, Ming-Yuan Leon, 2012. "Diversification and risk-adjusted performance: A quantile regression approach," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2157-2173.
    3. Meligkotsidou, Loukia & Vrontos, Ioannis D. & Vrontos, Spyridon D., 2009. "Quantile regression analysis of hedge fund strategies," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 264-279, March.
    4. Chiang, Thomas C. & Li, Jiandong & Tan, Lin, 2010. "Empirical investigation of herding behavior in Chinese stock markets: Evidence from quantile regression analysis," Global Finance Journal, Elsevier, vol. 21(1), pages 111-124.
    5. John Boyd & Bruce Champ, 2003. "Inflation and financial market performance: what have we learned in the last ten years," Working Paper 0317, Federal Reserve Bank of Cleveland.
    6. Rodriguez, Abel & Wang, Ziwei & Kottas, Athanasios, 2014. "Assessing systematic risk in the S&P500 index between 2000 and 2011: A Bayesian nonparametric approach," Santa Cruz Department of Economics, Working Paper Series qt6dh099g2, Department of Economics, UC Santa Cruz.

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