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Tests of multifactor pricing models, volatility bounds and portfolio performance

In: Handbook of the Economics of Finance

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  • Ferson, Wayne E.

Abstract

Three concepts: stochastic discount factors, multi-beta pricing and mean-variance efficiency, are at the core of modern empirical asset pricing. This chapter reviews these paradigms and the relations among them, concentrating on conditional asset-pricing models where lagged variables serve as instruments for publicly available information. The different paradigms are associated with different empirical methods. We review the variance bounds of Hansen and Jagannathan (1991), concentrating on extensions for conditioning information. Hansen's (1982) Generalized Method of Moments (GMM) is briefly reviewed as an organizing principle. Then, cross-sectional regression approaches as developed by Fama and MacBeth (1973) are reviewed and used to interpret empirical factors, such as those advocated by Fama and French, 1993 and Fama and French, 1996 . Finally, we review the multivariate regression approach, popularized in the finance literature by Gibbons (1982) and others. A regression approach, with a beta pricing formulation, and a GMM approach with a stochastic discount factor formulation, may be considered competing paradigms for empirical work in asset pricing. This discussion clarifies the relations between the various approaches. Finally, we bring the models and methods together, with a review of the recent conditional performance evaluation literature, concentrating on mutual funds and pension funds.

Suggested Citation

  • Ferson, Wayne E., 2003. "Tests of multifactor pricing models, volatility bounds and portfolio performance," Handbook of the Economics of Finance,in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 12, pages 743-802 Elsevier.
  • Handle: RePEc:eee:finchp:2-12
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    Citations

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    Cited by:

    1. Chrétien, Stéphane, 2012. "Bounds on the autocorrelation of admissible stochastic discount factors," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 1943-1962.
    2. Fukuta, Yuichi & Yamane, Akiko, 2015. "Value premium and implied equity duration in the Japanese stock market," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 102-121.
    3. Ferson, Wayne E., 2013. "Investment Performance: A Review and Synthesis," Handbook of the Economics of Finance, Elsevier.
    4. Gourieroux, C. & Monfort, A. & Sufana, R., 2010. "International money and stock market contingent claims," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1727-1751, December.
    5. Da, Zhi & Guo, Re-Jin & Jagannathan, Ravi, 2012. "CAPM for estimating the cost of equity capital: Interpreting the empirical evidence," Journal of Financial Economics, Elsevier, vol. 103(1), pages 204-220.
    6. Fletcher, Jonathan, 2014. "Benchmark models of expected returns in U.K. portfolio performance: An empirical investigation," International Review of Economics & Finance, Elsevier, vol. 29(C), pages 30-46.
    7. Fletcher, Jonathan & Kihanda, Joseph, 2005. "An examination of alternative CAPM-based models in UK stock returns," Journal of Banking & Finance, Elsevier, vol. 29(12), pages 2995-3014, December.
    8. André, Eric, 2014. "Optimal portfolio with vector expected utility," Mathematical Social Sciences, Elsevier, vol. 69(C), pages 50-62.
    9. Abel, Ernest & Fletcher, Jonathan, 2004. "An empirical examination of UK emerging market unit trust performance," Emerging Markets Review, Elsevier, vol. 5(4), pages 389-408, December.
    10. repec:sbe:breart:v:37:y:2017:i:1:a:62104 is not listed on IDEAS

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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