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Robust Regression Estimation Methods and Intercept Bias: A Capital Asset Pricing Model Application

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  • James B. McDonald

    (Brigham Young University, USA)

  • Richard A. Michelfelder

    (Rutgers University, USA)

  • Panayiotis Theodossiou

    (Cyprus University of Technology, Cyprus)

Abstract

Robust estimation techniques based on symmetric probability distributions are often substituted for OLS to obtain efficient regression parameters with thick-tail distributed data. The empirical, simulation and theoretical results in this paper show that with skewed distributed data, symmetric robust estimation techniques produce biased regression intercepts. This paper evaluates robust methods in estimating the capital asset pricing model and shows skewed stock returns data used with symmetric robust estimation techniques produce biased alphas. The results support the recommendation that robust estimation using the skewed generalized T family of distributions may be used to obtain more efficient and unbiased estimates with skewness.

Suggested Citation

  • James B. McDonald & Richard A. Michelfelder & Panayiotis Theodossiou, 2009. "Robust Regression Estimation Methods and Intercept Bias: A Capital Asset Pricing Model Application," Multinational Finance Journal, Multinational Finance Journal, vol. 13(3-4), pages 293-321, September.
    • Handle: RePEc:mfj:journl:v:13:y:2009:i:3-4:p:293-321
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    References listed on IDEAS

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    Cited by:

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    2. Theodossiou, Alexandra K. & Theodossiou, Panayiotis, 2014. "Stock return outliers and beta estimation: The case of U.S. pharmaceutical companies," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 30(C), pages 153-171.
    3. Joe Hirschberg & Jenny Lye, 2021. "Estimating risk premiums for regulated firms when accounting for reference-day variation and high-order moments of return volatility," Environment Systems and Decisions, Springer, vol. 41(3), pages 455-467, September.
    4. Stephen Matteo Miller, 2012. "Booms and Busts as Exchange Options," Multinational Finance Journal, Multinational Finance Journal, vol. 16(3-4), pages 189-223, September.
    5. Andreou, Panayiotis C. & Louca, Christodoulos & Panayides, Photis M., 2014. "Corporate governance, financial management decisions and firm performance: Evidence from the maritime industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 63(C), pages 59-78.
    6. Sikora, Grzegorz & Michalak, Anna & Bielak, Łukasz & Miśta, Paweł & Wyłomańska, Agnieszka, 2019. "Stochastic modeling of currency exchange rates with novel validation techniques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1202-1215.

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    More about this item

    Keywords

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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