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Olive: A Simple Method For Estimating Betas When Factors Are Measured With Error

Author

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  • J. Ginger Meng
  • Gang Hu
  • Jushan Bai

Abstract

We propose a simple and intuitive method for estimating betas when factors are measured with error: ordinary least squares instrumental variable estimator (OLIVE). OLIVE performs well when the number of instruments becomes large, while the performance of conventional instrumental variable methods becomes poor or even infeasible. In an empirical application, OLIVE beta estimates improve R-squared significantly. More importantly, our results help resolve two puzzling findings in the prior literature: first, the sign of average risk premium on the beta for market return changes from negative to positive; second, the estimated value of average zero-beta rate is no longer too high.
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Suggested Citation

  • J. Ginger Meng & Gang Hu & Jushan Bai, 2011. "Olive: A Simple Method For Estimating Betas When Factors Are Measured With Error," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 34(1), pages 27-60, March.
    • Handle: RePEc:bla:jfnres:v:34:y:2011:i:1:p:27-60
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    Cited by:

    1. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    2. Jushan Bai & Shuzhong Shi, 2011. "Estimating High Dimensional Covariance Matrices and its Applications," Annals of Economics and Finance, Society for AEF, vol. 12(2), pages 199-215, November.
    3. Sebastien Valeyre & Denis S. Grebenkov & Sofiane Aboura, 2019. "The Reactive Beta Model," Papers 1911.00919, arXiv.org.
    4. Christian Calm¨¨s & Raymond Th¨¦oret, 2016. "The Asymmetric Impact of Portfolio Mix on Bank Performance over the Business Cycle: U.S. and Canadian Evidence," Review of Economics & Finance, Better Advances Press, Canada, vol. 6, pages 57-74, February.
    5. Christian Calmès & Denis Cormier & Francois Éric Racicot & Raymond Théoret, 2012. "Firms' Accruals and Tobin’s q," RePAd Working Paper Series UQO-DSA-wp032012, Département des sciences administratives, UQO.
    6. Prono, Todd, 2011. "When A Factor Is Measured with Error: The Role of Conditional Heteroskedasticity in Identifying and Estimating Linear Factor Models," MPRA Paper 33593, University Library of Munich, Germany.
    7. Sebastien Valeyre, 2020. "Refined model of the covariance/correlation matrix between securities," Papers 2001.08911, arXiv.org.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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