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The Price of Risk and Ambiguity in an Intertemporal General Equilibrium Model of Asset Prices

Author

Listed:
  • Gonçalo Faria

    (CEF.UP, Faculdade de Economia, Universidade do Porto, RGEA, Universidad de Vigo)

  • João Correia-da-Silva

    (CEF.UP, Faculdade de Economia, Universidade do Porto)

Abstract

We consider a version of the intertemporal general equilibrium model of Cox et al. (1985a) with a single production process and two correlated state variables. It is assumed that only one of them, Y2, has shocks correlated with those of the economy's output rate and, simultaneously, that the representative agent is ambiguous about its stochastic process. This implies that changes in Y2 should be hedged and its uncertainty priced, with this price containing risk and ambiguity components. Ambiguity impacts asset pricing through two channels: the price of uncertainty associated with the ambiguous state variable, Y2, and the interest rate. With ambiguity, the equilibrium price of uncertainty associated with Y2 and the equilibrium interest rate can increase or decrease, depending on the relation between (i) the correlations between the shocks in Y2 and those in the output rate and in the other state variable; (ii) the diffusion functions of the stochastic processes for Y2 and for the output rate; and (iii) the gradient of the value function with respect to Y2. As applications of our generic setting, we deduct the model of Longstaff and Schwartz (1992) for interest-rate-sensitive contingent claim pricing and the variance risk price specification in the option pricing model of Heston (2003).

Suggested Citation

  • Gonçalo Faria & João Correia-da-Silva, 2011. "The Price of Risk and Ambiguity in an Intertemporal General Equilibrium Model of Asset Prices," FEP Working Papers 399, Universidade do Porto, Faculdade de Economia do Porto.
  • Handle: RePEc:por:fepwps:399
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    Cited by:

    1. Gonçalo Faria & João Correia-da-Silva, 2014. "A closed-form solution for options with ambiguity about stochastic volatility," Review of Derivatives Research, Springer, vol. 17(2), pages 125-159, July.
    2. Escobar, Marcos & Ferrando, Sebastian & Rubtsov, Alexey, 2015. "Robust portfolio choice with derivative trading under stochastic volatility," Journal of Banking & Finance, Elsevier, vol. 61(C), pages 142-157.
    3. Luciano I. Castro & Marialaura Pesce & Nicholas C. Yannelis, 2020. "A new approach to the rational expectations equilibrium: existence, optimality and incentive compatibility," Annals of Finance, Springer, vol. 16(1), pages 1-61, March.
    4. Meglena Jeleva & Jean-Marc Tallon, 2016. "Ambiguïté, comportements et marchés financiers," L'Actualité Economique, Société Canadienne de Science Economique, vol. 92(1-2), pages 351-383.
    5. Tarik Driouchi & Lenos Trigeorgis & Raymond H. Y. So, 2018. "Option implied ambiguity and its information content: Evidence from the subprime crisis," Annals of Operations Research, Springer, vol. 262(2), pages 463-491, March.
    6. Gonçalo Faria & João Correia-da-Silva, 2016. "Is stochastic volatility relevant for dynamic portfolio choice under ambiguity?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(7), pages 601-626, May.

    More about this item

    Keywords

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    JEL classification:

    • C68 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computable General Equilibrium Models
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing

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