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Nonparametric methods for estimating and testing for constant betas in asset pricing models

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  • M. V. Esteban
  • E. Ferreira
  • S. Orbe-Mandaluniz

Abstract

In this article, we study the performance of a smoothing spline method in estimating and testing for constant betas in two well-known asset pricing models, the usual market model and the three-factor model. The spline estimator is computed taking into account the conditional heteroscedasticity of the errors. Using the right model and estimation procedure for the variance term plays a crucial role in gaining efficiency in beta estimators. A simulation study shows the good performance of our method; in all the scenarios simulated, it outperforms the benchmark rolling estimator. The method enables users to obtain confidence intervals and to test for the significance and constancy of betas. Finally, the method is applied to US data, comprising 25 portfolios formed based on size and the ratio of book equity to market equity. The results show that the time-variability of the betas plays an important role, mainly when sensitivity to the HML factor is considered.

Suggested Citation

  • M. V. Esteban & E. Ferreira & S. Orbe-Mandaluniz, 2015. "Nonparametric methods for estimating and testing for constant betas in asset pricing models," Applied Economics, Taylor & Francis Journals, vol. 47(25), pages 2577-2607, May.
    • Handle: RePEc:taf:applec:v:47:y:2015:i:25:p:2577-2607
    DOI: 10.1080/00036846.2015.1005812
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    1. Garbade, Kenneth & Rentzler, Joel, 1981. "Testing the Hypothesis of Beta Stationarity," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 22(3), pages 577-587, October.
    2. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    3. Ferreira, Eva & Gil-Bazo, Javier & Orbe, Susan, 2011. "Conditional beta pricing models: A nonparametric approach," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3362-3382.
    4. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    5. Sascha Mergner & Jan Bulla, 2008. "Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques," The European Journal of Finance, Taylor & Francis Journals, vol. 14(8), pages 771-802.
    6. Robert W. Faff & David Hillier & Joseph Hillier, 2000. "Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(5‐6), pages 523-554, June.
    7. Schwert, G William & Seguin, Paul J, 1990. "Heteroskedasticity in Stock Returns," Journal of Finance, American Finance Association, vol. 45(4), pages 1129-1155, September.
    8. S. N. Wood, 2000. "Modelling and smoothing parameter estimation with multiple quadratic penalties," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 413-428.
    9. Petkova, Ralitsa & Zhang, Lu, 2005. "Is value riskier than growth?," Journal of Financial Economics, Elsevier, vol. 78(1), pages 187-202, October.
    10. Ralitsa Petkova, 2006. "Do the Fama–French Factors Proxy for Innovations in Predictive Variables?," Journal of Finance, American Finance Association, vol. 61(2), pages 581-612, April.
    11. Fabozzi, Frank J. & Francis, Jack Clark, 1978. "Beta as a Random Coefficient," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 13(1), pages 101-116, March.
    12. Maria Victoria Esteban & Susan Orbe-Mandaluniz, 2010. "A nonparametric approach for estimating betas: the smoothed rolling estimator," Applied Economics, Taylor & Francis Journals, vol. 42(10), pages 1269-1279.
    13. Maik Eisenbeiss & Goran Kauermann & Willi Semmler, 2007. "Estimating Beta-Coefficients of German Stock Data: A Non-Parametric Approach," The European Journal of Finance, Taylor & Francis Journals, vol. 13(6), pages 503-522.
    14. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    15. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    16. Sunder, Shyam, 1980. "Stationarity of Market Risk: Random Coefficients Tests for Individual Stocks," Journal of Finance, American Finance Association, vol. 35(4), pages 883-896, September.
    17. Simon N. Wood, 2004. "Stable and Efficient Multiple Smoothing Parameter Estimation for Generalized Additive Models," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 673-686, January.
    18. Joost Driessen & Pascal J. Maenhout & Grigory Vilkov, 2009. "The Price of Correlation Risk: Evidence from Equity Options," Journal of Finance, American Finance Association, vol. 64(3), pages 1377-1406, June.
    19. Li, Yan & Yang, Liyan, 2011. "Testing conditional factor models: A nonparametric approach," Journal of Empirical Finance, Elsevier, vol. 18(5), pages 972-992.
    20. Simonds, Richard R. & LaMotte, Lynn Roy & McWhorter, Archer, 1986. "Testing for Nonstationarity of Market Risk: An Exact Test and Power Considerations," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 21(2), pages 209-220, June.
    21. Alexander, Gordon J. & Benson, P. George, 1982. "More on Beta as a Random Coefficient," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 17(1), pages 27-36, March.
    22. Andrew Clare & Richard Priestley & Stephen Thomas, 1997. "Is Beta dead? The role of alternative estimation methods," Applied Economics Letters, Taylor & Francis Journals, vol. 4(9), pages 559-562.
    23. Bos, T & Newbold, P, 1984. "An Empirical Investigation of the Possibility of Stochastic Systematic Risk in the Market Model," The Journal of Business, University of Chicago Press, vol. 57(1), pages 35-41, January.
    24. Robert W. Faff & David Hillier & Joseph Hillier, 2000. "Time Varying Beta Risk: An Analysis of Alternative Modelling Techniques," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 27(5‐6), pages 523-554, June.
    25. Fama, Eugene F & French, Kenneth R, 1995. "Size and Book-to-Market Factors in Earnings and Returns," Journal of Finance, American Finance Association, vol. 50(1), pages 131-155, March.
    26. Gonedes, Nicholas J., 1973. "Evidence on the Information Content of Accounting Numbers: Accounting-based and Market-based Estimates of Systematic Risk," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 8(3), pages 407-443, June.
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    2. Isabel Casas & Eva Ferreira & Susan Orbe, 2021. "Time-Varying Coefficient Estimation in SURE Models. Application to Portfolio Management," Journal of Financial Econometrics, Oxford University Press, vol. 19(4), pages 707-745.

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