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Thin‐Trading Effects in Beta: Bias v. Estimation Error

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  • Piet Sercu
  • Martina Vandebroek
  • Tom Vinaimont

Abstract

Two regression coefficients often used in Finance, the Scholes‐Williams (1977) quasi‐multiperiod ‘thin‐trading’ beta and the Hansen‐Hodrick (1980) overlapping‐periods regression coefficient, can both be written as instrumental‐variables estimators. Competitors are Dimson's beta and the Hansen‐Hodrick original OLS beta. We check the performance of all these estimators and the validity of the t‐tests in small and medium samples, in and outside their stated assumptions, and we report their performances in a hedge‐fund style portfolio‐management application. In all experiments as well as in the real‐data estimates, less bias comes at the cost of a higher standard error. Our hedge‐portfolio experiment shows that the safest procedure even is to simply match by size and industry; any estimation just adds noise. There is a clear relation between portfolio variance and the variance of the beta estimator used in market‐neutralizing the portfolio, dwarfing the beneficial effect of bias.

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  • Piet Sercu & Martina Vandebroek & Tom Vinaimont, 2008. "Thin‐Trading Effects in Beta: Bias v. Estimation Error," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 35(9‐10), pages 1196-1219, November.
    • Handle: RePEc:bla:jbfnac:v:35:y:2008:i:9-10:p:1196-1219
    DOI: 10.1111/j.1468-5957.2008.02110.x
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    Cited by:

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    2. Dębski Wiesław & Feder-Sempach Ewa & Świderski Bartosz, 2016. "Beta Stability Over Bull and Bear Market on the Warsaw Stock Exchange," Folia Oeconomica Stetinensia, Sciendo, vol. 16(1), pages 75-92, December.
    3. Doan, Minh Phuong & Sercu, Piet, 2021. "Modelling multiperiod patterns in stock-market reactions to events, with an application to serial acquisitions," International Review of Financial Analysis, Elsevier, vol. 77(C).

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