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Un MEDAF à plusieurs moments réalisés

Author

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  • Christophe Hurlin
  • Patrick Kouontchou
  • Bertrand Maillet

Abstract

Cet article généralise l'approche de Bollerslev et Zhang (2003) qui consiste à utiliser des mesures et co-mesures de risque « réalisées » pour l'estimation des sensibilités dans les modèles d'évaluation des actifs financiers. Nous proposons ici d'étendre cette approche en introduisant les moments d'ordre supérieur et développons des méthodologies d'estimation visant à neutraliser les erreurs de spécification et de modèle. A partir d'une base de données des prix de haute fréquence du marché français des actions, nous établissons que le recours à des mesures réalisées d'ordre supérieur contribue à améliorer l'ajustement global aux données de marché. / This paper generalizes the Bollerslev and Zhang (2003) approach for the estimation of loadings of asset pricing models using “realized” measures and co-measures of risk. We propose here to extend this approach by including higher-moments in asset pricing models. Estimations are conducted using several methodologies aiming to neutralize data measurement and model misspecification errors, explicitly dealing with the inter-relations between financial asset returns. An empirical application performed on a high-frequency French stock price database shows that realized higher-moment measures contribute to improve the global adjustment of the extended model with market data.

Suggested Citation

  • Christophe Hurlin & Patrick Kouontchou & Bertrand Maillet, 2010. "Un MEDAF à plusieurs moments réalisés," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 53(3/4), pages 457-480.
  • Handle: RePEc:bxr:bxrceb:2013/81164
    Note: Special Issue "26th Symposium on Money, Banking and Finance" Guest Editors :Sébastien Galanti and Grégory Levieuge
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    References listed on IDEAS

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    1. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Paul Labys, 2003. "Modeling and Forecasting Realized Volatility," Econometrica, Econometric Society, vol. 71(2), pages 579-625, March.
    2. Andersen, Torben G & Bollerslev, Tim, 1998. "Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 885-905, November.
    3. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
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    Cited by:

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    2. Dimitrios Vortelinos & Angeliki Menegaki & Ioannis Passas & Alexandros Garefalakis & Georgios Viskadouros, 2024. "Heterogeneous Responses of Energy and Non-Energy Assets to Crises in Commodity Markets," Energies, MDPI, vol. 17(21), pages 1-25, October.

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    JEL classification:

    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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