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The Application of Errors-in-Variables Methodology to Capital Market Research: Evidence on the Small-Firm Effect

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  • Booth, James R.
  • Smith, Richard L.

Abstract

Errors in variables due to nonsynchronous trading and benchmark error are significant problems for capital market research. This paper develops the use of direct and reverse regression to bound true coefficient estimates when the data exhibit error structures arising from these two sources both separately and jointly. The approach appears to have broad applicability for capital markets research. As an example, the paper reexamines the small-firm effect to show that it cannot be attributed to nonsynchronous trading or benchmark error in the estimated variance of the market portfolio. This result is shown to hold even when the tax-selling effect is controlled for by excluding January returns.

Suggested Citation

  • Booth, James R. & Smith, Richard L., 1985. "The Application of Errors-in-Variables Methodology to Capital Market Research: Evidence on the Small-Firm Effect," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 20(04), pages 501-515, December.
  • Handle: RePEc:cup:jfinqa:v:20:y:1985:i:04:p:501-515_01
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    Cited by:

    1. Chris Tofallis, 2011. "Investment Volatility: A Critique of Standard Beta Estimation and a Simple Way Forward," Papers 1109.4422, arXiv.org.
    2. Tofallis, Chris, 2008. "Investment volatility: A critique of standard beta estimation and a simple way forward," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1358-1367, June.
    3. K. C. John Wei & Stanley R. Stansell, 1991. "Benchmark Error And The Small Firm Effect: A Revisit," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 14(4), pages 359-369, December.

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