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Decomposing the bias in time-series estimates of CAPM betas

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  • H. Malloch
  • R. Philip
  • S. Satchell

Abstract

We identify two sources of bias arising from time-series regression used to compute beta. This bias arises due to the classical error in variables problem and a ‘mechanical interaction’ which exists when the index comprises the asset of interest. Assuming that the market is proxied by a fixed-weight index, we demonstrate that the relative weighting of an asset within the index, and/or the magnitude of its idiosyncratic risk, directly biases the beta estimate for the individual stock and also for all stocks within the index. Via simulations, we show that the problem is most pronounced for markets with a small number of highly concentrated assets. Finally, we propose a procedure to reduce this bias and apply the methods to equity data.

Suggested Citation

  • H. Malloch & R. Philip & S. Satchell, 2016. "Decomposing the bias in time-series estimates of CAPM betas," Applied Economics, Taylor & Francis Journals, vol. 48(45), pages 4291-4298, September.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:45:p:4291-4298
    DOI: 10.1080/00036846.2016.1156233
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    Cited by:

    1. Pankaj K. Agarwal & H. K. Pradhan, 2018. "Mutual Fund Performance Using Unconditional Multifactor Models: Evidence from India," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 17(2_suppl), pages 157-184, August.

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