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On Stable Factor Structures in the Pricing of Risk

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Eric Ghysels ()

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Abstract

Much of the research describing the cross-sectional and time series behavior of asset returns can be characterized as a search for the relevant state variables and also a search for the relevant model specification. Ultimately the scope of such efforts is to find a satisfactory and stable asset pricing structure. In this paper we discuss various methods to accomplish this and appraise the success of two recently proposed classes of asset pricing models in tracking predictable patterns in risk and return trade-offs. The two classes are the conditional CAPM and the nonlinear APT. The parameters of both models are estimated via a set of moment conditions using the GMM estimator and the model fit is judged on the basis of the overidentifying restrictions. The fundamental problem is that overidentifying restrictions tests are not designed to diagnose whether a model, provides a stable relationship between the return series and risk factors. We use a set of recently developed tests for structural stability of parameter estimates for the GMM estimator to diagnose which factor structures appear stable through time in the context of the two aforementioned classes of models. In the course of trying to sort out whether there is systematic mispricing we shall also try to determine what type of model looks most promising for further development. In that regard we find the nonlinear APT more satisfactory than the conditional APT and CAPM.

Dans cette étude nous réexaminons les modèles à facteurs qui ont été proposés récemment, c'est à dire le CAPM conditionnel et l'APT non-linéaire. Ces modèles ont été estimés par la méthode des moments généralisée. La diagnostique usuelle pour juger ces modèles est la statistique de suridentification. Le problème fondamental de cette statistique est qu'elle n'a pas de puissance par rapport à des alternatives caractérisés par des variations de paramètres. Évidement, ces variations entraînent des erreurs sur l'évaluation du risque. Nous proposons d'appliquer des tests de changement structurel pour les paramètres et analysons plusieurs modèles du type APT non-linéaire et CAPM conditionnel. Peu de modèles semblent être stable. Nous trouvons que la spécification du APT non-linéaire semble être quand même la plus satisfaisante.

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Paper provided by CIRANO in its series CIRANO Working Papers with number 95s-16.

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Date of creation: 01 Mar 1995
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Handle: RePEc:cir:cirwor:95s-16

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Related research
Keywords: Structural change; Factor models; APT; Changement structurel ; Modèles à facteurs; APT;

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Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

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    Other versions:
  3. Harvey, Campbell R, 1995. "Predictable Risk and Returns in Emerging Markets," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 8(3), pages 773-816. [Downloadable!] (restricted)
    Other versions:
  4. Ghysels, Eric & Hall, Alastair, 1990. "A Test for Structural Stability of Euler Conditions Parameters Estimated via the Generalized Method of Moments Estimator," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 31(2), pages 355-64, May. [Downloadable!] (restricted)
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  5. Ferson, Wayne E & Korajczyk, Robert A, 1995. "Do Arbitrage Pricing Models Explain the Predictability of Stock Returns?," Journal of Business, University of Chicago Press, vol. 68(3), pages 309-49, July. [Downloadable!] (restricted)
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  8. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July. [Downloadable!] (restricted)
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  13. Ghysels, Eric & Hall, Alastair, 1990. "Are consumption-based intertemporal capital asset pricing models structural?," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 121-139. [Downloadable!] (restricted)
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  15. Bansal, Ravi & Hsieh, David A & Viswanathan, S, 1993. " A New Approach to International Arbitrage Pricing," Journal of Finance, American Finance Association, vol. 48(5), pages 1719-47, December. [Downloadable!] (restricted)
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Full references

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Wayne E. Ferson & Campbell R. Harvey, 1999. "Conditioning Variables and the Cross-Section of Stock Returns," NBER Working Papers 7009, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
    Other versions:
  2. Marco Bonomo & René Garcia, 1997. "Tests of Conditional Asset Pricing Models in the Brazilian Stock Market," CIRANO Working Papers 97s-20, CIRANO. [Downloadable!]
    Other versions:
  3. Wayne E. Ferson & Andrew F. Siegel, 2006. "Testing Portfolio Efficiency with Conditioning Information," NBER Working Papers 12098, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  4. Schrimpf, Andreas & Schröder, Michael & Stehle, Richard, 2006. "Evaluating conditional asset pricing models for the German stock market," ZEW Discussion Papers 06-43, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research. [Downloadable!]
  5. Martin Scheicher, 2000. "Time-varying risk in the German stock market," European Journal of Finance, Taylor and Francis Journals, vol. 6(1), pages 70-91, March. [Downloadable!] (restricted)
  6. Post, G.T., 2003. "Statistical Inference on Stochastic Dominance Efficiency. Do Omitted Risk Factors Explain the Size and Book-to-Market Effects?," Research Paper ERS-2003-017-F&A Revision, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni. [Downloadable!]
  7. Mattia Ciprian & Stefano d'Addona, 2005. "Time Varying Sensitivities on a GRID architecture," Finance 0511007, EconWPA. [Downloadable!]
    Other versions:
  8. Patrick Coggi & Bogdan Manescu, 2004. "A multifactor model of stock returns with endogenous regime switching," University of St. Gallen Department of Economics working paper series 2004 2004-01, Department of Economics, University of St. Gallen. [Downloadable!]
  9. Thierry Post & Haim Levy, 2002. "Does Risk Seeking drive Asset Prices?," Tinbergen Institute Discussion Papers 02-070/2, Tinbergen Institute. [Downloadable!]
  10. Ho-Chuan Huang & Wan-hsiu Cheng, 2005. "Tests of the CAPM under structural changes," International Economic Journal, Korean International Economic Association, vol. 19(4), pages 523-541, December. [Downloadable!] (restricted)
  11. Michael W. Brandt & David A. Chapman, 2006. "Linear Approximations and Tests of Conditional Pricing Models," NBER Working Papers 12513, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  12. Elena Andreou & Eric Ghysels, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," CIRANO Working Papers 2004s-25, CIRANO. [Downloadable!]
  13. Geert Bekaert & Guojun Wu, 1997. "Asymmetric Volatility and Risk in Equity Markets," NBER Working Papers 6022, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
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