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Jaksa Cvitanic (), Ali Lazrak (), Marie Claire Quenez () and Fernando Zapatero ()
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Ali Lazrak: Equipe d'analyse et de probabilité, Université d'Evry, Bd. F. Mitterrand 91025 Evry Cedex, France
Marie Claire Quenez: Université de Marne la Vallée, Equipe d'analyse et de mathématiques appliquées, Cité Descartes, 5. bd Descartes Champs-sur-Marne 77454 Marne la Vallée, France
Fernando Zapatero: FBE, Marshall School of Business, USC, Los Angeles, CA 90089, USA

International Journal of Theoretical and Applied Finance (IJTAF), 2001, vol. 04, issue 02, 245-261

Abstract: We consider the case of an agent with recursive preferences (Stochastic Differential Utility or SDU) who cannot observe the random drift of the stock price process. This partial information problem can be transformed into a problem with full information, in which the drift is replaced by its expected value conditional on the information given by the stock price history. We are then in a position to use recent results for maximizing SDUs under full information and their connection to Forward-Backward Stochastic Differential Equations. They enable us to study qualitative differences between the cases with full and partial information. We also analyze some special cases in which we obtain semi-explicit results and compute the SDU numerically.

Date: 2001
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DOI: 10.1142/S0219024901000948

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