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Econometric Asset Pricing Modelling

Author

Listed:
  • Henri Bertholon

    (Crest)

  • Alain Monfort

    (Crest)

  • Fulvio Pegoraro

    (Crest)

Abstract

The purpose of this paper is to propose a general econometric approach to asset pricing modelling based onthree main ingredients : (i) the historical discrete-time dynamics of the factor representing the information, (ii)the Stochastic Discount Factor (SDF), and (iii) the discrete-time risk-neutral (R.N.) factor dynamics. Retaining anexponential-affine specification of the SDF, its modelling is equivalent to the specification of the factor loading vectorand of the short rate, if the latter is neither exogenous nor a known function of the factor. In this general framework,we distinguish three modelling strategies: the Direct Modelling, the Risk-Neutral Constrained Direct Modelling andthe Back Modelling. In all the approaches we study the internal consistency constraints, implied by the absence ofarbitrage opportunity (AAO) assumption, and the identification problem. We also propose interpretations of thefactor loading vector in terms of market price of risk. The general modelling strategies are applied to two importantcases: security market models and term structure of interest rates models. In the context of security market models,we show the relevance of our methods for various kinds of specifications: switching regime models, stochastic volatilitymodels, Gaussian and Inverse Gaussian GARCH-type models (with or without regime-switching). In the interestrates modelling context, we consider several illustrations: VAR modelling, Switching VAR modelling and Wishartmodelling. We also propose, using a Gaussian VAR(1) approach, an example of joint modelling of geometric returns,dividends and short rate. In these contexts we stress the usefulness of the Risk-Neutral Constrained Direct Modellingapproach and of the Back Modelling approach, both allowing to conciliate a flexible historical dynamics and a CarR.N. dynamics leading to explicit or quasi explicit pricing formulas for various derivative products. Moreover, wehighlight the possibility to specify asset pricing models able to accommodate non-affine historical and R.N. factordynamics with tractable pricing formulas. In this respect we introduce the new notion of Extended Car process whichis particularly promising.

Suggested Citation

  • Henri Bertholon & Alain Monfort & Fulvio Pegoraro, 2007. "Econometric Asset Pricing Modelling," Working Papers 2007-18, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2007-18
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    Cited by:

    1. Alain Monfort & Jean-Paul Renne, 2013. "Default, Liquidity, and Crises: an Econometric Framework," Journal of Financial Econometrics, Oxford University Press, vol. 11(2), pages 221-262, March.
    2. Timothy M. Christensen, 2014. "Nonparametric identification of positive eigenfunctions," CeMMAP working papers CWP37/14, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    3. Da Fonseca José & Grasselli Martino & Ielpo Florian, 2014. "Estimating the Wishart Affine Stochastic Correlation Model using the empirical characteristic function," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(3), pages 253-289, May.
    4. Corsi, Fulvio & Fusari, Nicola & La Vecchia, Davide, 2013. "Realizing smiles: Options pricing with realized volatility," Journal of Financial Economics, Elsevier, vol. 107(2), pages 284-304.
    5. Rombouts, Jeroen V.K. & Stentoft, Lars, 2014. "Bayesian option pricing using mixed normal heteroskedasticity models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 588-605.
    6. Augustyniak, Maciej & Badescu, Alexandru & Bégin, Jean-François & Jayaraman, Sarath Kumar, 2025. "A general option pricing framework for affine fractionally integrated models," Journal of Banking & Finance, Elsevier, vol. 171(C).
    7. Milad Nozari, 2021. "Information content of the risk-free rate for the pricing kernel bound," Journal of Asset Management, Palgrave Macmillan, vol. 22(4), pages 267-276, July.
    8. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Advances in Econometrics, in: Missing Data Methods: Time-Series Methods and Applications, pages 1-86, Emerald Group Publishing Limited.
    9. Timothy M. Christensen, 2014. "Nonparametric identification of positive eigenfunctions," CeMMAP working papers 37/14, Institute for Fiscal Studies.
    10. Monfort, Alain & Renne, Jean-Paul & Roussellet, Guillaume, 2015. "A Quadratic Kalman Filter," Journal of Econometrics, Elsevier, vol. 187(1), pages 43-56.
    11. Monfort, Alain & Pegoraro, Fulvio, 2012. "Asset pricing with Second-Order Esscher Transforms," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1678-1687.
    12. Matthias R. Fengler & Helmut Herwartz & Christian Werner, 2012. "A Dynamic Copula Approach to Recovering the Index Implied Volatility Skew," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 457-493, June.
    13. Yow-Jen Jou & Chih-Wei Wang & Wan-Chien Chiu, 2013. "Is the realized volatility good for option pricing during the recent financial crisis?," Review of Quantitative Finance and Accounting, Springer, vol. 40(1), pages 171-188, January.
    14. Aleksandar Mijatović & Paul Schneider, 2014. "Empirical Asset Pricing with Nonlinear Risk Premia," Journal of Financial Econometrics, Oxford University Press, vol. 12(3), pages 479-506.
    15. Chevallier, Julien & Ielpo, Florian & Mercier, Ludovic, 2009. "Risk aversion and institutional information disclosure on the European carbon market: A case-study of the 2006 compliance event," Energy Policy, Elsevier, vol. 37(1), pages 15-28, January.
    16. Massimo Guidolin, 2013. "Markov switching models in asset pricing research," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 1, pages 3-44, Edward Elgar Publishing.
    17. Rombouts, Jeroen V.K. & Stentoft, Lars, 2015. "Option pricing with asymmetric heteroskedastic normal mixture models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 635-650.
    18. Alain Monfort & Olivier Féron, 2012. "Joint econometric modeling of spot electricity prices, forwards and options," Review of Derivatives Research, Springer, vol. 15(3), pages 217-256, October.
    19. Han, Hyojin & Khrapov, Stanislav & Renault, Eric, 2020. "The leverage effect puzzle revisited: Identification in discrete time," Journal of Econometrics, Elsevier, vol. 217(2), pages 230-258.
    20. Jean-Paul Renne, 2009. "Frequency-domain analysis of debt service in a macro-finance model for the euro area," Working papers 261, Banque de France.
    21. Badescu, Alex & Elliott, Robert J. & Siu, Tak Kuen, 2009. "Esscher transforms and consumption-based models," Insurance: Mathematics and Economics, Elsevier, vol. 45(3), pages 337-347, December.
    22. Alain Monfort & Jean-Paul Renne, 2011. "Credit and Liquidity Risks in Euro-area Sovereign Yield Curves," Working Papers 2011-26, Center for Research in Economics and Statistics.
    23. Augustyniak, Maciej & Badescu, Alexandru & Bégin, Jean-François, 2023. "A discrete-time hedging framework with multiple factors and fat tails: On what matters," Journal of Econometrics, Elsevier, vol. 232(2), pages 416-444.

    More about this item

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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