Backward stochastic differential equations and stochastic control and applications to mathematical finance

Abstract : This thesis is divided into two parts that may be read independently. In the first part, three uses of backward stochastic differential equations are presented. The first chapter is an application of these equations to the mean-variance hedging problem in an incomplete market where multiple defaults can occur. We make a conditional density hypothesis on the default times. We then decompose the value function into a sequence of value functions between consecutive default times and we prove that each of them admits a quadratic form. Finally, we illustrate our results for a specific case where 2 default times follow independent exponential laws. The two following applications are extensions of the paper "Feynman-Kac representation for Hamilton- Jacobi-Bellman IPDEs". The second chapter is the study of a class of backward stochastic differential equations with nonpositive jumps and upper barrier. Existence and uniqueness of a minimal solution are proved by a double penalization approach under regularity assumptions on the obstacle. This method allows us to solve the case where the diffusion coefficient is degenerate. We also show, in a suitable markovian framework, the connection between our class of backward stochastic differential equations and fully nonlinear variational inequalities. In particular, our backward equation representation provides a Feynman-Kac type formula for PDEs associated to general zero-sum stochastic differential controller-and-stopper games, where control affects both drift and diffusion term, and the diffusion coefficient can be degenerate. Moreover, we state a dual game formula of this backward equation minimal solution, which gives a new representation for zero-sum stochastic differential controller-and-stopper games The third chapter is linked to model uncertainty, where the uncertainty affects both volatility and intensity. This kind of stochastic control problems is associated to a fully nonlinear integro-partial differential equation, such that the measure characterizing the jump part depends on a parameter. We do not assume that the family of measures is dominated. We obtain a nonlinear Feynman-Kac formula for the value function associated to these control problems. To this aim, we introduce a class of backward stochastic differential equations with jumps and partially constrained diffusive part. Here the case where the diffusion coefficient is degenerate is solved as well. In the second part, a conditional asset liability management problem is solved. We first derive the proper domain of definition of the value function associated to the problem by identifying the minimal wealth for which there exists an admissible investment strategy allowing to satisfy the constraint at maturity. This minimal wealth is identified as a solution of viscosity of a PDE. We also show that its Fenschel-Legendre transform is a solution of viscosity of another PDE, which allows to obtain a scheme with a faster convergence. We then identify the value function linked to the problem of interest as a solution of viscosity of a PDE on its domain of definition. Finally, we solve numerically the problem and we provide graphs of the minimal wealth, of the value function of the problem and of the optimal strategy.
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Submitted on : Friday, June 26, 2015 - 11:13:37 AM
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Sébastien Choukroun. Backward stochastic differential equations and stochastic control and applications to mathematical finance. Mathematics [math]. LPMA - Laboratoire de Probabilités et Modèles Aléatoires, 2015. English. ⟨tel-01168589⟩

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