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What do the Fama-French factors add to CCAPM?

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  • Pongrapeeporn Abhakorn
  • Peter N. Smith
  • Michael R.Wickens

Abstract

This study extends standard C-CAPM by including two additional factors related to firm size (SMB) and book-to-market value ratio (HML) - the Fama-French factors. CCAPM is least able to price firms with low book-to-market ratios. The explanation of these returns, as well as the returns on the SMB and HML portfolios, is significantly improved by the inclusion of the HML factor. The component of the risk premia explained by consumption varies across size. We suggest that a possible explanation for the role of HML is its association with the investment growth prospects of firms.

Suggested Citation

  • Pongrapeeporn Abhakorn & Peter N. Smith & Michael R.Wickens, 2013. "What do the Fama-French factors add to CCAPM?," CAMA Working Papers 2013-23, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    • Handle: RePEc:een:camaaa:2013-23
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    Cited by:

    1. Abhakorn, Pongrapeeporn & Smith, Peter N. & Wickens, Michael R., 2016. "Can stochastic discount factor models explain the cross-section of equity returns?," Review of Financial Economics, Elsevier, vol. 28(C), pages 56-68.
    2. Morana, Claudio, 2014. "Insights on the global macro-finance interface: Structural sources of risk factor fluctuations and the cross-section of expected stock returns," Journal of Empirical Finance, Elsevier, vol. 29(C), pages 64-79.
    3. Massimo Guidolin & Erwin Hansen & Martín Lozano-Banda, 2018. "Portfolio performance of linear SDF models: an out-of-sample assessment," Quantitative Finance, Taylor & Francis Journals, vol. 18(8), pages 1425-1436, August.
    4. Abhakorn, Pongrapeeporn & Smith, Peter N. & Wickens, Michael R., 2016. "Can stochastic discount factor models explain the cross-section of equity returns?," Review of Financial Economics, Elsevier, vol. 28(C), pages 56-68.
    5. Adeel Nasir & Kanwal Iqbal Khan & Mário Nuno Mata & Pedro Neves Mata & Jéssica Nunes Martins, 2021. "Optimisation of Time-Varying Asset Pricing Models with Penetration of Value at Risk and Expected Shortfall," Mathematics, MDPI, vol. 9(4), pages 1-38, February.
    6. Wickens, Michael R., 2014. "How did we get to where we are now? Reflections on 50 years of macroeconomic and financial econometrics," CEPR Discussion Papers 10197, C.E.P.R. Discussion Papers.
    7. Michael Wickens, 2015. "How Did We Get to Where We Are Now? Reflections on 50 Years of Macroeconomic and Financial Econometrics," Manchester School, University of Manchester, vol. 83, pages 60-82, December.
    8. Frank Schuhmacher & Hendrik Kohrs & Benjamin R. Auer, 2021. "Justifying Mean-Variance Portfolio Selection when Asset Returns Are Skewed," Management Science, INFORMS, vol. 67(12), pages 7812-7824, December.
    9. Huang, Lin & Wang, Zijun, 2014. "Is the investment factor a proxy for time-varying investment opportunities? The US and international evidence," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 219-232.

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy

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