Modélisation du smile de volatilité pour les produits dérivés de taux d'intérêt

• Main Author: Palidda, Ernesto
• Other Authors: Paris Est
• Language: en
• Published: 2015
• Subjects: Modèles de taux d'intérêt; Méthodes de Monte Carlo; Processus Affines; Term Structure models; Monte Carlo methods; Affine processes
• Online Access: http://www.theses.fr/2015PESC1027/document

L'objet de cette thèse est l'étude d'un modèle de la dynamique de la courbe de taux d'intérêt pour la valorisation et la gestion des produits dérivées. En particulier, nous souhaitons modéliser la dynamique des prix dépendant de la volatilité. La pratique de marché consiste à utiliser une représentation paramétrique du marché, et à construire les portefeuilles de couverture en calculant les sensibilités par rapport aux paramètres du modèle. Les paramètres du modèle étant calibrés au quotidien pour que le modèle reproduise les prix de marché, la propriété d'autofinancement n'est pas vérifiée. Notre approche est différente, et consiste à remplacer les paramètres par des facteurs, qui sont supposés stochastiques. Les portefeuilles de couverture sont construits en annulant les sensibilités des prix à ces facteurs. Les portefeuilles ainsi obtenus vérifient la propriété d’autofinancement === This PhD thesis is devoted to the study of an Affine Term Structure Model where we use Wishart-like processes to model the stochastic variance-covariance of interest rates. This work was initially motivated by some thoughts on calibration and model risk in hedging interest rates derivatives. The ambition of our work is to build a model which reduces as much as possible the noise coming from daily re-calibration of the model to the market. It is standard market practice to hedge interest rates derivatives using models with parameters that are calibrated on a daily basis to fit the market prices of a set of well chosen instruments (typically the instrument that will be used to hedge the derivative). The model assumes that the parameters are constant, and the model price is based on this assumption; however since these parameters are re-calibrated, they become in fact stochastic. Therefore, calibration introduces some additional terms in the price dynamics (precisely in the drift term of the dynamics) which can lead to poor P&L explain, and mishedging. The initial idea of our research work is to replace the parameters by factors, and assume a dynamics for these factors, and assume that all the parameters involved in the model are constant. Instead of calibrating the parameters to the market, we fit the value of the factors to the observed market prices. A large part of this work has been devoted to the development of an efficient numerical framework to implement the model. We study second order discretization schemes for Monte Carlo simulation of the model. We also study efficient methods for pricing vanilla instruments such as swaptions and caplets. In particular, we investigate expansion techniques for prices and volatility of caplets and swaptions. The arguments that we use to obtain the expansion rely on an expansion of the infinitesimal generator with respect to a perturbation factor. Finally we have studied the calibration problem. As mentioned before, the idea of the model we study in this thesis is to keep the parameters of the model constant, and calibrate the values of the factors to fit the market. In particular, we need to calibrate the initial values (or the variations) of the Wishart-like process to fit the market, which introduces a positive semidefinite constraint in the optimization problem. Semidefinite programming (SDP) gives a natural framework to handle this constraint