Thesis (M.Sc. (Statistics)) - Rhodes University, 2009. / A thesis submitted to Rhodes University in partial fulfillment of the requirements for the degree of Master of Science in Mathematical Statistics.

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Este texto apresenta alguns dos elementos básicos envolvidos em um estudo introdutório das equações diferencias estocásticas. Tais equações modelam problemas a tempo contínuo em que as grandezas de interesse estão sujeitas a certos tipos de perturbações aleatórias. Em nosso estudo, a aleatoriedade nessas equações será representada por um termo que envolve o processo estocástico conhecido como Movimento Browniano. Para um tratamento matematicamente rigoroso dessas equações, faremos uso da Integral Estocástica de Itô. A construção dessa integral é um dos principais objetivos do texto. Depois de desenvolver os conceitos necessários, apresentaremos alguns exemplos e provaremos existência e unicidade de solução para equações diferenciais estocásticas satisfazendo certas hipóteses. / This text presents some of the basic elements involved in an introductory study of stochastic differential equations. Such equations describe certain kinds of random perturbations on continuous time models. In our study, the randomness in these equations will be represented by a term involving the stochastic process known as Brownian Motion. For a mathematically rigorous treatment of these equations, we use the Itô Stochastic Integral. The construction of this integral is one of the main goals of the text. After developing the necessary concepts, we present some examples and prove existence and uniqueness of solution of stochastic differential equations satisfying some hypothesis.

Définies il y a quelques décennies, les martingales dans les variétés sont maintenant des objets bien connus. Des questions très simples restent en suspens cependant. Par exemple,étant donnée une variable aléatoire à valeurs dans une variété complète, et une filtration continue(dont toute martingale réelle possède une version continue), existe-t-il une martingale continue dans cette variété qui a pour valeur terminale donnée cette variable aléatoire ? Que dire des semimartingales de valeur terminale et dérives données ? Le but principal de cette thèse est d’apporter des réponses à ces questions. Sous des hypothèses de géométrie convexe, des réponses sont données dans les articles de Kendall (1990), Picard (1991), Picard (1994), Darling (1995) ou encore Arnaudon (1997). Le cas des semimartingales a plus largement été traité par Blache (2004). Les martingales dans les variétés permettent de définir les barycentres associés à une filtration, qui sont parfois plus simples à calculer que les barycentres usuels ou les moyennes, et qui possèdent une propriété d’associativité. Ils sont fortement reliés à la théorie du contrôle, à l’optimisation stochastique, ainsi qu’aux équations différentielles stochastiques rétrogrades (EDSRs). La résolution du problème avec des arguments géométriques donne par ailleurs des outils pour résoudre des EDSRs quadratiques multidimensionnelles.Au cours de cette thèse deux principales méthodes ont été employées pour étudier le problème de l’existence de martingale de valeur terminale donnée. La première est basée sur un algorithme stochastique. La variable aléatoire que l’on cherchera à atteindre sera d’abord déformée en une famille x (a) de classe C 1, et on se posera la question suivante : existe-t-il une martingale X(a) de valeur terminale x (a) ? Une méthode de tir, selon un principe similaire au tir géodésique déterministe, sera employée relativement au paramètre a en direction de la variable aléatoire x (a). La seconde est basée sur la résolution générale d’une EDSR multidimensionnelle à croissance quadratique. La principale problématique de cette partie sera d’adapter au cadre multidimensionnel une stratégie récente développée par Briand et Elie (2013) permettant de traiter les EDSRs quadratiques multidimensionnelles. Cette approche nouvelle permet de retrouver la plupart des résultats partiels obtenus par des méthodes différentes. Au-delà de l’intérêt unifiant,cette nouvelle approche ouvre la voie à de potentiels futurs travaux. / Defined several decades ago, martingales in manifolds are very canonical objects. About these objects very simple questions are still unresolved. For instance, given a random variable with values in a complete manifold and a continuous filtration (one with respect to which all real-valued martingales admit a continuous version), does there exist a continuous martingale in the manifold with terminal value given by this random variable ? What about semimartingales with prescribed drift and terminal value ? The main aim of this thesis is to provide answers to these questions. Under convex geometry assumption, answers are given in the articles of Kendall (1990), Picard (1991), Picard (1994), Darling (1995) or Arnaudon (1997). The case of semimartingales was widely treated by Blache (2004). The martingales in the manifolds make it possible to define the barycenters associated to a filtration, which are sometimes simpler to compute than the usual barycenters or averages, and which have an associative property. They are strongly related to control theory, stochastic optimization, and backward stochastic differential equations (BSDEs). Solving the problem with geometric arguments also gives tools for solving multidimensional quadratic EDSRs.During the thesis, two methods have been used for studying the problem of existence of a martingale with prescribed terminal value. The first one is based on a stochastic algorithm. The random variable that we try to reach will be deformed into a $mcC^1$-family $xi(a)$, and we deal with the following newer problem: does there exist a martingale $X(a)$ with terminal value $xi(a)$ ? A shooting method, using the same kind of principle as the deterministic geodesic shooting, will be used with respect to a parameter $a$ towards $xi(a)$.The second one is the resolution of a multidimensional quadratic BSDE. The aim of this part will be to adapt to the multidimensional framework a recent strategy developed by Briand and Elie (2013) to treat multidimensional quadratic BSDEs. This new approach makes it possible to rediscover the results obtained by different methods. Beyond the unification, this new approach paves the way for potential future works.

Este texto apresenta alguns dos elementos básicos envolvidos em um estudo introdutório das equações diferencias estocásticas. Tais equações modelam problemas a tempo contínuo em que as grandezas de interesse estão sujeitas a certos tipos de perturbações aleatórias. Em nosso estudo, a aleatoriedade nessas equações será representada por um termo que envolve o processo estocástico conhecido como Movimento Browniano. Para um tratamento matematicamente rigoroso dessas equações, faremos uso da Integral Estocástica de Itô. A construção dessa integral é um dos principais objetivos do texto. Depois de desenvolver os conceitos necessários, apresentaremos alguns exemplos e provaremos existência e unicidade de solução para equações diferenciais estocásticas satisfazendo certas hipóteses. / This text presents some of the basic elements involved in an introductory study of stochastic differential equations. Such equations describe certain kinds of random perturbations on continuous time models. In our study, the randomness in these equations will be represented by a term involving the stochastic process known as Brownian Motion. For a mathematically rigorous treatment of these equations, we use the Itô Stochastic Integral. The construction of this integral is one of the main goals of the text. After developing the necessary concepts, we present some examples and prove existence and uniqueness of solution of stochastic differential equations satisfying some hypothesis.

Este texto apresenta alguns dos elementos básicos envolvidos em um estudo introdutório das equações diferencias estocásticas. Tais equações modelam problemas a tempo contínuo em que as grandezas de interesse estão sujeitas a certos tipos de perturbações aleatórias. Em nosso estudo, a aleatoriedade nessas equações será representada por um termo que envolve o processo estocástico conhecido como Movimento Browniano. Para um tratamento matematicamente rigoroso dessas equações, faremos uso da Integral Estocástica de Itô. A construção dessa integral é um dos principais objetivos do texto. Depois de desenvolver os conceitos necessários, apresentaremos alguns exemplos e provaremos existência e unicidade de solução para equações diferenciais estocásticas satisfazendo certas hipóteses. / This text presents some of the basic elements involved in an introductory study of stochastic differential equations. Such equations describe certain kinds of random perturbations on continuous time models. In our study, the randomness in these equations will be represented by a term involving the stochastic process known as Brownian Motion. For a mathematically rigorous treatment of these equations, we use the Itô Stochastic Integral. The construction of this integral is one of the main goals of the text. After developing the necessary concepts, we present some examples and prove existence and uniqueness of solution of stochastic differential equations satisfying some hypothesis.

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Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1979. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND SCIENCE. / Vita. / Bibliography: leaves 364-373. / by Robert Buchanan Washburn, Jr. / Ph.D.

In this thesis, we address two problems arising from the application of stochastic differential equations (SDEs). The first one pertains to the detection of asset bubbles, where the price process solves an SDE. We combine the strict local martingale model together with a statistical tool to instantaneously check the existence and severity of asset bubbles through the asset’s historical price process. Our approach assumes that the price process of interest is a CEV process. We relate the exponent parameter in the CEV process to an asset bubble by studying the future expectation and the running maximum of the CEV process. The detection of asset bubbles then boils down to the estimation of the exponent. With a dynamic linear regression model, inference on the exponent can be carried out using historical price data. Estimation of the volatility and calibration of the parameters in the dynamic linear regression model are also studied. When using SDEs in practice, for example, in the detection of asset bubbles, one often would like to simulate its paths using the Euler scheme to study the behavior of the solution. The second part of this thesis focuses on the convergence property of the Euler scheme under the assumption that the coefficients of the SDE are locally Lipschitz and that the solution has no finite explosion. We prove that if a numerical scheme converges uniformly on any compact time set (UCP) in probability with a certain rate under the globally Lipschitz condition, then when the globally Lipschitz condition is replaced with a locally Lipschitz one plus a no finite explosion condition, UCP convergence with the same rate holds. One contribution of this thesis is the proof of √n-weak convergence of the asymptotic normalized error process. The limit error process is also provided. We further study the boundedness for the second moment of the weak limit process and its running maximum under both the globally Lipschitz and the locally Lipschitz conditions. The convergence of the Euler scheme in the sense of approximating expectations of functionals is also studied under the locally Lipschitz condition