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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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Bibliographic Info

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

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Cited by:
  1. Wayne E. Ferson & Andrew F. Siegel, 2006. "Testing Portfolio Efficiency with Conditioning Information," NBER Working Papers 12098, National Bureau of Economic Research, Inc.
  2. Garcia, Rene & Bonomo, Marco, 2001. "Tests of conditional asset pricing models in the Brazilian stock market," Journal of International Money and Finance, Elsevier, vol. 20(1), pages 71-90, February.
  3. Thierry Post & Haim Levy, 2002. "Does Risk Seeking drive Asset Prices?," Tinbergen Institute Discussion Papers 02-070/2, Tinbergen Institute.
  4. Ho-Chuan Huang & Wan-hsiu Cheng, 2005. "Tests of the CAPM under structural changes," International Economic Journal, Taylor & Francis Journals, vol. 19(4), pages 523-541.
  5. Stefano D'Addona & Mattia Ciprian, 2007. "Time Varying Sensitivities On A Grid Architecture," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 10(02), pages 307-329.
  6. 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.
  7. 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.
  8. Elena Andreou, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(2), pages 290-318.
  9. Touhami, A. & Martens, A., 1996. "Macroemesures in Computable General Equilibrium Models: a Probabilistic Treatment with an Application to Morocco," Cahiers de recherche 9621, Universite de Montreal, Departement de sciences economiques.
  10. Martin Scheicher, 2000. "Time-varying risk in the German stock market," The European Journal of Finance, Taylor & Francis Journals, vol. 6(1), pages 70-91.
  11. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
  12. 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.

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