Dissertations / Theses on the topic 'Processus stochastique'
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Benchettah, Azzedine. "Commande optimale stochastique et processus reciproques." Paris 7, 1991. http://www.theses.fr/1991PA077135.
Full textGravereaux, Jean-Bernard. "Calcul stochastique et processus de Markov." Grenoble 2 : ANRT, 1988. http://catalogue.bnf.fr/ark:/12148/cb37613974b.
Full textYounès, Sana. "Model checking stochastique par les méthodes de comparaison stochastique." Versailles-St Quentin en Yvelines, 2008. http://www.theses.fr/2008VERS0008.
Full textNous proposons dans cette thèse une nouvelle méthode de vérification des chaînes de Markov. La vérification de ces modèles est effectuée à partir des distributions transitoires ou stationnaire de la chaîne de Markov considérée. Nous utilisons les méthodes de comparaison stochastique pour obtenir des mesures bornantes afin de vérifier la chaîne considérée. Ces mesures sont obtenues par la construction d'une chaîne bornante à la chaîne initiale qui est en générale de très grande taille. Les chaînes bornantes construites doivent être plus simples à analyser permettant de construire des bornes pour les modèles dont la résolution numérique est difficile voire impossible. Nous avons exploré certains schémas pour construire des chaînes bornantes comme la lumpabilité et la classe C. Nous avons développé également d'autres schémas de construction de chaînes bornantes sur les chaînes de Markov censurées. Il est évident que les mesures bornantes ne permettent pas toujours de conclure. Dans ce cas il faut affiner le modèle bornant si le schéma de borne le permet. Nous avons montré que les méthodes de bornes que nous proposons sont pertinentes pour la vérification de chaînes de Markov et permettent de réduire remarquablement le temps de vérification
Paredes, Moreno Daniel. "Modélisation stochastique de processus d'agrégation en chimie." Thesis, Toulouse 3, 2017. http://www.theses.fr/2017TOU30368/document.
Full textWe center our interest in the Population Balance Equation (PBE). This equation describes the time evolution of systems of colloidal particles in terms of its number density function (NDF) where processes of aggregation and breakage are involved. In the first part, we investigated the formation of groups of particles using the available variables and the relative importance of these variables in the formation of the groups. We use data in (Vlieghe 2014) and exploratory techniques like principal component analysis, cluster analysis and discriminant analysis. We used this scheme of analysis for the initial population of particles as well as in the resulting populations under different hydrodynamics conditions. In the second part we studied the use of the PBE in terms of the moments of the NDF, and the Quadrature Method of Moments (QMOM) and the Generalized Minimal Extrapolation (GME), in order to recover the time evolution of a finite set of standard moments of the NDF. The QMOM methods uses an application of the Product-Difference algorithm and GME recovers a discrete non-negative measure given a finite set of its standard moments. In the third part, we proposed an discretization scheme in order to find a numerical approximation to the solution of the PBE. We used three cases where the analytical solution is known (Silva et al. 2011) in order to compare the theoretical solution to the approximation found with the discretization scheme. In the last part, we proposed a method for estimate the parameters involved in the modelization of aggregation and breakage processes in PBE. The method uses the numerical approximation found, as well as the Extended Kalman Filter. The method estimates iteratively the parameters at each time, using an non- linear Least Square Estimator
Barbachoux, Cécile. "Contribution a l'etude d'un processus stochastique relativiste." Paris 6, 2000. http://www.theses.fr/2000PA066026.
Full textFlint, Ian. "Analyse stochastique de processus ponctuels : au-delà du processus de Poisson." Thesis, Paris, ENST, 2013. http://www.theses.fr/2013ENST0085/document.
Full textDeterminantal point processes have sparked interest in very diverse fields, such as random matrix theory, point process theory, and networking. In this manuscript, we consider them as random point processes, i.e. a stochastic collection of points in a general space. Hence, we are granted access to a wide variety of tools from point process theory, which allows for a precise study of many of their probabilistic properties. We begin with the study of determinantal point processes from an applicative point of view. To that end, we propose different methods for their simulation in a very general setting. Moreover, we bring to light a series of models derived from the well-known Ginibre point process, which are quite suited for applications. Thirdly, we introduce a differentiable gradient on the considered probability space. Thanks to some powerful tools from Dirichlet form theory, we discuss integration by parts for general point processes, and show the existence of the associated diffusion processes correctly associated to the point processes. We are able to apply these results to the specific case of determinantal point processes, which leads us to characterizing these diffusions in terms of stochastic differential equations. Lastly, we turn our attention to the difference gradient on the same space. In a certain sense, we define a Skohorod integral, which satisfies an integration by parts formula, i.e. its adjoint is the difference operator. An application to the study of a random transformation of the point process is given, wherein we characterize the distribution of the transformed point process under mild hypotheses
Flint, Ian. "Analyse stochastique de processus ponctuels : au-delà du processus de Poisson." Electronic Thesis or Diss., Paris, ENST, 2013. http://www.theses.fr/2013ENST0085.
Full textDeterminantal point processes have sparked interest in very diverse fields, such as random matrix theory, point process theory, and networking. In this manuscript, we consider them as random point processes, i.e. a stochastic collection of points in a general space. Hence, we are granted access to a wide variety of tools from point process theory, which allows for a precise study of many of their probabilistic properties. We begin with the study of determinantal point processes from an applicative point of view. To that end, we propose different methods for their simulation in a very general setting. Moreover, we bring to light a series of models derived from the well-known Ginibre point process, which are quite suited for applications. Thirdly, we introduce a differentiable gradient on the considered probability space. Thanks to some powerful tools from Dirichlet form theory, we discuss integration by parts for general point processes, and show the existence of the associated diffusion processes correctly associated to the point processes. We are able to apply these results to the specific case of determinantal point processes, which leads us to characterizing these diffusions in terms of stochastic differential equations. Lastly, we turn our attention to the difference gradient on the same space. In a certain sense, we define a Skohorod integral, which satisfies an integration by parts formula, i.e. its adjoint is the difference operator. An application to the study of a random transformation of the point process is given, wherein we characterize the distribution of the transformed point process under mild hypotheses
Nicaise, Florent. "Calcul stochastique anticipant pour des processus avec sauts." Clermont-Ferrand 2, 2001. http://www.theses.fr/2001CLF2A003.
Full textBordenave, Charles. "Analyse stochastique des réseaux spatiaux." Phd thesis, Ecole Polytechnique X, 2006. http://pastel.archives-ouvertes.fr/pastel-00001902.
Full textGobard, Renan. "Fluctuations dans des modèles de boules aléatoires." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S025/document.
Full textIn this thesis, we study the macroscopic fluctuations in random balls models. A random balls model is an aggregation of balls in Rd whose centers and radii are random. We also mark each balls with a random weight. We consider the mass M induced by the system of weighted balls on a configuration μ of Rd. In order to investigate the macroscopic fluctuations of M, we realize a zoom-out on the configuration of balls. Mathematically, we reduce the mean radius while increasing the mean number of centers by volume unit. The question has already been studied when the centers, the radii and the weights are independent and the triplets (center, radius, weight) are generated according to a Poisson point process on Rd ×R+ ×R. Then, we observe three different behaviors depending on the comparison between the speed of the decreasing of the radii and the speed of the increasing of the density of centers. We propose to generalize these results in three different directions. The first part of this thesis consists in introducing dependence between the radii and the centers and inhomogeneity in the distribution of the centers. In the model we propose, the stochastic behavior of the radii depends on the location of the ball. In the previous works, the convergences obtained for the fluctuations of M are at best functional convergences in finite dimension. In the second part of this work, we obtain functional convergence on an infinite dimensional set of configurations μ. In the third and last part, we study a random balls model (non-weighted) on C where the couples (center, radius) are generated according to determinantal point process. Unlike to the Poisson point process, the determinantal point process exhibits repulsion phenomena between its points which allows us to model more physical problems
Manou-Abi, Solym Mawaki. "Théorèmes limites et ordres stochastiques relatifs aux lois et processus stables." Thesis, Toulouse 3, 2015. http://www.theses.fr/2015TOU30025/document.
Full textThis PhD Thesis is composed of three independent parts about stable laws and processes. In the first part, we establish convergence theorems (invariance principle) to stable processes, for additive functionals of a discrete time Markov chain that are not assumed to be square-integrable. The method is based on the use of mixing coefficients for Markov chains. In the second part, we obtain some rates of convergence to stable laws in the generalized central limit theorem by means of the Zolotarev ideal probability metric. The last part of the thesis is devoted to the study of convex ordering or convex comparison inequalities between stochastic integrals driven by stable processes. The main idea of our results is based on the forward-backward stochastic calculus for the stable case
Biane, Philippe. "Quelques applications du calcul stochastique." Paris 7, 1985. http://www.theses.fr/1985PA077103.
Full textAvenel, Christophe. "Suivi de courbes libres fermées déformables par processus stochastique." Phd thesis, Université Rennes 1, 2012. http://tel.archives-ouvertes.fr/tel-00763157.
Full textGradinaru, Mihai. "Applications du calcul stochastique à l'étude de certains processus." Habilitation à diriger des recherches, Université Henri Poincaré - Nancy I, 2005. http://tel.archives-ouvertes.fr/tel-00011826.
Full textentre 1996 et 2005, après la thèse de doctorat de l'auteur, et concerne l'étude fine de
certains processus stochastiques : mouvement brownien linéaire ou plan, processus de diffusion,
mouvement brownien fractionnaire, solutions d'équations différentielles stochastiques ou
d'équations aux dérivées partielles stochastiques.
La thèse d'habilitation s'articule en six chapitres correspondant aux thèmes
suivants : étude des intégrales par rapport aux temps locaux de certaines diffusions,
grandes déviations pour un processus obtenu par perturbation brownienne d'un système
dynamique dépourvu de la propriété d'unicité des solutions, calcul stochastique
pour le processus gaussien non-markovien non-semimartingale mouvement brownien fractionnaire,
étude des formules de type Itô et Tanaka pour l'équation de la chaleur stochastique,
étude de la durée de vie du mouvement brownien plan réfléchi dans un domaine à
frontière absorbante et enfin, estimation non-paramétrique et construction d'un
test d'adéquation à partir d'observations discrètes pour le coefficient de diffusion d'une
équation différentielle stochastique.
Les approches de tous ces thèmes sont probabilistes et basées sur l'analyse stochastique.
On utilise aussi des outils d'équations différentielles, d'équations aux dérivées partielles
et de l'analyse.
Khach, Rim Al. "Calcul stochastique ; calcul des variations pour les processus -stables." Paris 6, 1999. http://www.theses.fr/1999PA066011.
Full textAnagnostakis, Alexis. "Étude trajectorielle de diffusions singulières." Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0164.
Full textThe main object of this thesis is the study of singular diffusion processes with a focus on sticky diffusions. Sticky diffusions were first introduced by Feller in the fifties as a case of boundary condition that can arise in the analytic description of a diffusion. Their paths spend positive amount of time at points of the state-space, giving them the appearance to "stick" on these points. When such points are located at an attainable boundary of the state-space of the process, we call it sticky reflection. The first contribution of this thesis is to provide a suitable approximation of the local time of a sticky Itô diffusion, with statistical applications in view. We define the notion of sticky Itô diffusion and prove their path-wise descriptions. We prove that the local time of the sticky Brownian motion can be approximated by a class of high-frequency path functionals. We use the path-wise characterization to extend the result to non-explosive Itô diffusions. We prove the consistency of a stickiness estimator based on the local time approximation. We give numerical results on the stickiness estimation of a sticky Brownian motion. The second contribution of this thesis is an approximation in law of any one-dimensional diffusion by a grid-valued conditional moment-matching random walk. The convergence occurs as the maximal grid step goes to 0. We call this type of approximation Space-Time Markov Chain Approximation or STMCA. We also show how one can achieve optimal convergence rate by suitable choices of grids. We call "grid tuning" the process of computing such a grid. One can use STMCAs to set up approximation schemes for any one-dimensional diffusion process. We give various illustrated approximations examples of diffusions even in the presence of sticky behavior, discontinuous or degenerate coefficients
Constant, Camille. "Modélisation stochastique et analyse statistique de la pulsatilité en neuroendocrinologie." Thesis, Poitiers, 2019. http://www.theses.fr/2019POIT2330.
Full textThe aim of this thesis is to propose several models representing neuronal calcic activity and unsderstand its applicatition in the secretion of GnRH hormone. This work relies on experience realised in INRA Centre Val de Loire. Chapter 1 proposes a continuous model, in which we examine a Markov process of shot-noise type. Chapter 2 studies a discrete model type AR(1), based on a discretization of the model from Chapter 1 and proposes a first estimation of the parameters. Chapter 3 proposes another dicrete model, type AR(1), in which the innovations are the sum of a Bernouilli variable and a Gaussian variable representing a noise, and taking into account a linear drift . Estimations of the parameters are given in order to detect spikes in neuronal paths. Chapter 4 studies a biological experience involving 33 neurons. With the modelisation of Chapter 3, we detect synchronization instants (simultaneous spkike of a high proportion of neurons of the experience) and then, using simulations, we test the quality of the method that we used and we compare it to an experimental approach
Menozzi, Stephane. "Discrétisation de processus stochastiques, estimées de densités et applications." Habilitation à diriger des recherches, Université Paris-Diderot - Paris VII, 2010. http://tel.archives-ouvertes.fr/tel-00533333.
Full textKobylanski, Magdalena. "Quelques applications de méthodes d'analyse non-linéaire à la théorie des processus stochastique." Tours, 1998. http://www.theses.fr/1998TOUR4014.
Full textPhi, Tien Cuong. "Décomposition de Kalikow pour des processus de comptage à intensité stochastique." Thesis, Université Côte d'Azur, 2022. http://www.theses.fr/2022COAZ4029.
Full textThe goal of this thesis is to construct algorithms which are able to simulate the activity of a neural network. The activity of the neural network can be modeled by the spike train of each neuron, which are represented by a multivariate point processes. Most of the known approaches to simulate point processes encounter difficulties when the underlying network is large.In this thesis, we propose new algorithms using a new type of Kalikow decomposition. In particular, we present an algorithm to simulate the behavior of one neuron embedded in an infinite neural network without simulating the whole network. We focus on mathematically proving that our algorithm returns the right point processes and on studying its stopping condition. Then, a constructive proof shows that this new decomposition holds for on various point processes.Finally, we propose algorithms, that can be parallelized and that enables us to simulate a hundred of thousand neurons in a complete interaction graph, on a laptop computer. Most notably, the complexity of this algorithm seems linear with respect to the number of neurons on simulation
Vu, Thanh Nam. "Contrôle stochastique appliqué à la finance." Paris 9, 2011. http://basepub.dauphine.fr/xmlui/handle/123456789/8008.
Full textThis PhD dissertation presents three independent research topics in the field of stochastic target and optimal control problems with applications to financial mathematics. In a first part, we provide a PDE characterization of the super hedging price of an American option of barrier types in a Markovian model of financial market. This extends to the American case a recent works of Bouchard and Bentahar (2006), who considered European barrier options, and Karatzas and Wang (2000), who discussed the case of perpetual American barrier options in a Black and Scholes type model. Contrary to their result, we do not use the usual dual formulation, which allows to reduce to a standard control problem, but instead prove and appeal to an American version of the geometric dynamic programming principle for stochastic targets of Soner and Touzi (2002). This allows us to avoid the non-degeneracy assumption on the volatility coefficients, and therefore extends their results to possibly degenerate cases which typically appear when the market is not complete. As a by-product, we provide an extension to the case of American type targets, which is of own interest. In the second part, within a Brownian diffusion Markovian framework, we provide a direct PDE characterization of the minimal initial endowment required so that the terminal wealth of a financial agent (possibly diminished by the pay off of a random claim) can match a set of constraints in probability. Such constraints should be interpreted as a rough description of a targeted profit and loss (P&L) distribution. This allows to give a price to options under a P&L constraint, or to provide a description of the discrete P&L profiles that can be achieved given an initial capital. This approach provides an alternative to the standard utility indifference (or marginal) pricing rules which is better adapted to market practices. From the mathematical point of view, this is an extension of the stochastic target problem under controlled loss, studied in Bouchard, Elie and Touzi (2008), to the case of multiple constraints. Although the associated Hamilton-Jacobi-Bellman operator is fully discontinuous, and the terminal condition is irregular, we are able to construct a numerical scheme that converges at any continuity points of the pricing function. The last part of this thesis is concerned with the extension of the optimal control of direction of reflection problem introduced in Bouchard (2007) to the jump diffusion case. In a Brownian diffusion framework with jumps, the controlled process is defined as the solution of a stochastic differential equation reflected at the boundary of a domain along oblique directions of reflection which are controlled by a predictable process which may have jumps. We also provide a version of the weak dynamic programming principle of Bouchard and Touzi (2009) adapted to our context and which is sufficient to provide a viscosity characterization of the associated value function without requiring the usual heavy measurable selection arguments nor the a-priori continuity of the value function
Bandini, Elena. "Représentation probabiliste d'équations HJB pour le contrôle optimal de processus à sauts, EDSR (équations différentielles stochastiques rétrogrades) et calcul stochastique." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLY005/document.
Full textIn the present document we treat three different topics related to stochastic optimal control and stochastic calculus, pivoting on thenotion of backward stochastic differential equation (BSDE) driven by a random measure.After a general introduction, the three first chapters of the thesis deal with optimal control for different classes of non-diffusiveMarkov processes, in finite or infinite horizon. In each case, the value function, which is the unique solution to anintegro-differential Hamilton-Jacobi-Bellman (HJB) equation, is probabilistically represented as the unique solution of asuitable BSDE. In the first chapter we control a class of semi-Markov processes on finite horizon; the second chapter isdevoted to the optimal control of pure jump Markov processes, while in the third chapter we consider the case of controlled piecewisedeterministic Markov processes (PDMPs) on infinite horizon. In the second and third chapters the HJB equations associatedto the optimal control problems are fully nonlinear. Those situations arise when the laws of the controlled processes arenot absolutely continuous with respect to the law of a given, uncontrolled, process. Since the corresponding HJB equationsare fully nonlinear, they cannot be represented by classical BSDEs. In these cases we have obtained nonlinear Feynman-Kacrepresentation formulae by generalizing the control randomization method introduced in Kharroubi and Pham (2015)for classical diffusions. This approach allows us to relate the value function with a BSDE driven by a random measure,whose solution hasa sign constraint on one of its components.Moreover, the value function of the original non-dominated control problem turns out to coincide withthe value function of an auxiliary dominated control problem, expressed in terms of equivalent changes of probability measures.In the fourth chapter we study a backward stochastic differential equation on finite horizon driven by an integer-valued randommeasure $mu$ on $R_+times E$, where $E$ is a Lusin space, with compensator $nu(dt,dx)=dA_t,phi_t(dx)$. The generator of thisequation satisfies a uniform Lipschitz condition with respect to the unknown processes.In the literature, well-posedness results for BSDEs in this general setting have only been established when$A$ is continuous or deterministic. We provide an existence and uniqueness theorem for the general case, i.e.when $A$ is a right-continuous nondecreasing predictable process. Those results are relevant, for example,in the frameworkof control problems related to PDMPs. Indeed, when $mu$ is the jump measure of a PDMP on a bounded domain, then $A$ is predictable and discontinuous.Finally, in the two last chapters of the thesis we deal with stochastic calculus for general discontinuous processes.In the fifth chapter we systematically develop stochastic calculus via regularization in the case of jump processes,and we carry on the investigations of the so-called weak Dirichlet processes in the discontinuous case.Such a process $X$ is the sum of a local martingale and an adapted process $A$ such that $[N,A] = 0$, for any continuouslocal martingale $N$.Given a function $u:[0,T] times R rightarrow R$, which is of class $C^{0,1}$ (or sometimes less), we provide a chain rule typeexpansion for $u(t,X_t)$, which constitutes a generalization of It^o's lemma being valid when $u$ is of class $C^{1,2}$.This calculus is applied in the sixth chapter to the theory of BSDEs driven by random measures.In several situations, when the underlying forward process $X$ is a special semimartingale, or, even more generally,a special weak Dirichlet process,we identify the solutions $(Y,Z,U)$ of the considered BSDEs via the process $X$ and the solution $u$ to an associatedintegro PDE
Bandini, Elena. "Représentation probabiliste d'équations HJB pour le contrôle optimal de processus à sauts, EDSR (équations différentielles stochastiques rétrogrades) et calcul stochastique." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLY005.
Full textIn the present document we treat three different topics related to stochastic optimal control and stochastic calculus, pivoting on thenotion of backward stochastic differential equation (BSDE) driven by a random measure.After a general introduction, the three first chapters of the thesis deal with optimal control for different classes of non-diffusiveMarkov processes, in finite or infinite horizon. In each case, the value function, which is the unique solution to anintegro-differential Hamilton-Jacobi-Bellman (HJB) equation, is probabilistically represented as the unique solution of asuitable BSDE. In the first chapter we control a class of semi-Markov processes on finite horizon; the second chapter isdevoted to the optimal control of pure jump Markov processes, while in the third chapter we consider the case of controlled piecewisedeterministic Markov processes (PDMPs) on infinite horizon. In the second and third chapters the HJB equations associatedto the optimal control problems are fully nonlinear. Those situations arise when the laws of the controlled processes arenot absolutely continuous with respect to the law of a given, uncontrolled, process. Since the corresponding HJB equationsare fully nonlinear, they cannot be represented by classical BSDEs. In these cases we have obtained nonlinear Feynman-Kacrepresentation formulae by generalizing the control randomization method introduced in Kharroubi and Pham (2015)for classical diffusions. This approach allows us to relate the value function with a BSDE driven by a random measure,whose solution hasa sign constraint on one of its components.Moreover, the value function of the original non-dominated control problem turns out to coincide withthe value function of an auxiliary dominated control problem, expressed in terms of equivalent changes of probability measures.In the fourth chapter we study a backward stochastic differential equation on finite horizon driven by an integer-valued randommeasure μ on ℝ+ x E, where E is a Lusin space, with compensator v(dt,dx)=dAt φ(dx). The generator of thisequation satisfies a uniform Lipschitz condition with respect to the unknown processes.In the literature, well-posedness results for BSDEs in this general setting have only been established when A is continuous or deterministic. We provide an existence and uniqueness theorem for the general case, i.e. when A is a right-continuous nondecreasing predictable process. Those results are relevant, for example, in the frameworkof control problems related to PDMPs. Indeed, when μ is the jump measure of a PDMP on a bounded domain, then A is predictable and discontinuous.Finally, in the two last chapters of the thesis we deal with stochastic calculus for general discontinuous processes.In the fifth chapter we systematically develop stochastic calculus via regularization in the case of jump processes,and we carry on the investigations of the so-called weak Dirichlet processes in the discontinuous case.Such a process X is the sum of a local martingale and an adapted process A such that [N,A] = 0, for any continuouslocal martingale N.Given a function u:[0,T] x ℝ → R, which is of class C⁰′¹ (or sometimes less), we provide a chain rule type expansion for u(t, Xt), which constitutes a generalization of Itô's lemma being valid when u is of class C¹′².This calculus is applied in the sixth chapter to the theory of BSDEs driven by random measures.In several situations, when the underlying forward process X is a special semimartingale, or, even more generally,a special weak Dirichlet process,we identify the solutions (Y,Z,U) of the considered BSDEs via the process X and the solution u to an associated integro PDE
Choukroun, Sébastien. "Equations différentielles stochastiques rétrogrades et contrôle stochastique et applications aux mathématiques financières." Sorbonne Paris Cité, 2015. https://theses.hal.science/tel-01168589.
Full textThis 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 [75]. 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 lambda(a,. ) characterizing the jump part depends on a parameter a. We do not assume that the family lambda(a,. ) 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 faste 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
Tudor, Ciprian A. "Calcul stochastique anticipant et mouvement brownien fractionnaire." La Rochelle, 2002. http://www.theses.fr/2002LAROS089.
Full textThe main object of this thesis is the anticipating stochastic calculus with respect to the Wiener process and with respect to the fractional Brownian motion. The first chapter of this work contains a generalization of the Skorohod stochasic calculus for more general integrators without any martingale property. In the second part we study the existence and the properties of the local time of the fractional Brownian motion. Next we considered the problem of the weak convergence to the fractional Brownian motion. The last part of the thesis contains the study of a class of stochastic evolution equations with a fractional noise
Dang, Ngoc-Minh. "Contrôle stochastique appliqué à la finance." Paris 9, 2011. http://basepub.dauphine.fr/xmlui/handle/123456789/7237.
Full textThis PhD thesis considers the optimal trading problem from the stochastic control approach and consists of four parts. In the first part, we begin with the study of the impacts generated by volumes on the price process. We introduce a structural model in which price movements are due to not only the last trade’s volume but also to those of earlier trades, weakened by a decay factor. Considering a similar continuous version, we provide a condition ensuring the optimality of a strategy for the minimization of the execution cost in a mean-variance framework, and solve it numerically. In the second part, we propose a general model to optimize the way trading algorithms are used. Using an impulse control approach, we model the execution of a large order by a sequence (τi,δi,Ei)i, which is defined so that the i-th slice is executed in [τi,τi+δi] with parameter Ei. We characterize the value function as a viscosity solution of a system of PDE. We provide a numerical scheme and prove its convergence. Numerical illustrations are given for a real case. We deal with the problem of pricing an option on the book liquidation in presence of impact where the classical pricing by neutral risk measure fails. We begin with an abstract model generalized from the work of Bouchard- Eile-Touzi (2008), and then apply to compute the price of a VWAP guaranteed contract. We establish in the last part an equivalence result between stochastic target problems and standard optimal control. We derive the classical HJB equation from the PDE obtained in the stochastic target framework
Viseur, Sophie. "Simulation stochastique basée-objet de chenaux." Vandoeuvre-les-Nancy, INPL, 2001. http://www.theses.fr/2001INPL036N.
Full textEspinouze, Sandrine. "Loi du maximum d'un processus stationnaire solution d'une équation différentielle stochastique." Clermont-Ferrand 2, 2002. http://www.theses.fr/2002CLF21361.
Full textPuig, Bénédicte. "Modélisation et simulation de processus stochastiques non gaussiens." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2003. http://tel.archives-ouvertes.fr/tel-00003526.
Full textSlaoui, Meryem. "Analyse stochastique et inférence statistique des solutions d’équations stochastiques dirigées par des bruits fractionnaires gaussiens et non gaussiens." Thesis, Lille 1, 2019. http://www.theses.fr/2019LIL1I079.
Full textThis doctoral thesis is devoted to the study of the solutions of stochastic differential equations driven by additive Gaussian and non-Gaussian noises. As a non-Gaussian driving noise, we use the Hermite processes. These processes form a family of self-similar stochastic processes with stationary increments and long memory and they can be expressed as multiple Wiener-Itô integrals. The class of Hermite processes includes the well-known fractional Brownian motion which is the only Gaussian Hermite process, and the Rosenblatt process. In a first chapter, we consider the solution to the linear stochastic heat equation driven by a multiparameter Hermite process of any order and with Hurst multi-index H. We study the existence and establish various properties of its mild solution. We discuss also its probability distribution in the non-Gaussian case. The second part deals with the asymptotic behavior in distribution of solutions to stochastic equations when the Hurst parameter converges to the boundary of its interval of definition. We focus on the case of the Hermite Ornstein-Uhlenbeck process, which is the solution of the Langevin equation driven by the Hermite process, and on the case of the solution to the stochastic heat equation with additive Hermite noise. These results show that the obtained limits cover a large class of probability distributions, from Gaussian laws to distribution of random variables in a Wiener chaos of higher order. In the last chapter, we consider the stochastic wave equation driven by an additive Gaussian noise which behaves as a fractional Brownian motion in time and as a Wiener process in space. We show that the sequence of generalized variations satisfies a Central Limit Theorem and we estimate the rate of convergence via the Stein-Malliavin calculus. The results are applied to construct several consistent estimators of the Hurst index
Filali, Siham. "Application du calcul stochastique à une classe d'EDP nonlinéaires." Lille 1, 2005. https://pepite-depot.univ-lille.fr/RESTREINT/Th_Num/2005/50376-2005-266.pdf.
Full textFallot, Pierre. "Etude d'un modèle stochastique du rayonnement solaire." Grenoble 1, 1992. http://www.theses.fr/1992GRE10146.
Full textLoumi, Moulay Taïeb. "Intégration stochastique multivoque et application aux équations différentielles multivoques." Montpellier 2, 1986. http://www.theses.fr/1986MON20181.
Full textde, Saporta Benoîte. "Contribution à l'estimation et au contrôle de processus stochastiques." Habilitation à diriger des recherches, Université Sciences et Technologies - Bordeaux I, 2013. http://tel.archives-ouvertes.fr/tel-00905873.
Full textDia, Baye Moussa. "Méthodes et modèles d'évaluation d'options avec dividende stochastique." Paris 1, 2007. http://www.theses.fr/2007PA010035.
Full textFourati, Sonia. "Tribus homogènes, commutations des projections entre tribus du futur et tribus du passé, une application à un formalisme de processus de Markov indexes par IR." Paris 6, 1986. http://www.theses.fr/1986PA066040.
Full textAmraoui, Mohamed. "Le marché financier sous la dynamique de la volatilité stochastique." Paris 2, 2008. http://www.theses.fr/2008PA020031.
Full textHuguenin, Pierre Huguenin Pierre. "Extension d'algorithmes d'ordre zéro pour l'optimisation stochastique : application au processus d'électro-érosion /." [S.l.] : [s.n.], 2005. http://library.epfl.ch/theses/?nr=3197.
Full textIsabelle, Camilier. "Etude des taux d'interet long terme Analyse stochastique des processus ponctuels determinantaux." Phd thesis, Ecole Polytechnique X, 2010. http://pastel.archives-ouvertes.fr/pastel-00573437.
Full textCamilier, Isabelle. "Etude des taux d'interet long terme Analyse stochastique des processus ponctuels determinantaux." Palaiseau, Ecole polytechnique, 2010. http://pastel.archives-ouvertes.fr/docs/00/57/34/37/PDF/These_Camilier.pdf.
Full textThe first part of this thesis concerns a nancial point of view of the study of long term interest rates. We seek an alternative to classical interest rates models for longer maturities (15 years and more). Our work is inspired by the work of economists, but takes into account the existence of a (complete) financial market. We show that classical expected utility maximization techniques lead to the Ramsey Rule, linking the yield curve and marginal utility from consumption. We extend the Ramsey Rule to the case of an incomplete financial market and examine how the yield curve is modied. It is then possible to consider the case where there is incertainty on a parameter of the model, then to extend these results to the case of dynamic utility functions, where the yield curve depends on level of wealth in the economy. The other main result we present is a new way of considering the consumption, as a quantity of supplies that the investor puts aside and uses in case of a default event. Then the expected utility maximization from consumption and terminal wealth can be interpreted as a problem of maximization of expected utility from terminal wealth with a random horizon. The topic of the second part of this thesis is the stochastic analysis of determinantal point processes. Determinantal and permanental processes are point processes with a correlation function given by a determinant or a permanent. Their atoms exhibit mutual attraction or repulsion, thus these processes are very far from the uncorrelated situation encountered in Poisson models. We establish a quasi-invariance result : we show that if atoms locations are perturbed along a vector eld, the resulting process is still a determinantal (respectively permanental) process, the law of which is absolutely continuous with respect to the original distribution. Based on this formula, following Bismut approach of Malliavin calculus, we then give an integration by parts formula
Martiano, Jean-Jacques. "Sur quelques processus a derive singuliere et leurs applications en mecanique stochastique." Paris 11, 1999. http://www.theses.fr/1999PA112070.
Full textLu, Yi. "Calcul fonctionnel non-anticipatif et applications aux processus stochastiques." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066418/document.
Full textThis thesis focuses on various mathematical questions arising in the non-anticipative functional calculus, which is based on a notion of pathwise directional derivatives for functionals. We extend the scope and results of this calculus to functionals which may not admit such derivatives, either through approximations (Part I) or by defining a notion of weak vertical derivative (Part II). In the first part, we consider the representation of conditional expectations as non-anticipative functionals. We show that it is possible under very general conditions to approximate such functionals by a sequence of smooth functionals in an appropriate sense. This approach provides a systematic method for computing explicit approximations to martingale representations for a large class of Brownian functionals. We also derive explicit convergence rates of the approximations. These results are then applied to the problem of sensitivity analysis and dynamic hedging of (path-dependent) contingent claims. In the second part, we propose a concept of weak vertical derivative for non-anticipative functionals which may fail to possess directional derivatives. The definition of the weak vertical derivative is based on the notion of pathwise quadratic variation and makes use of the duality associated to the associated bilinear form. We show that the notion of weak vertical derivative leads to a functional characterization of local martingales with respect to a reference process, and allows to define a concept of pathwise weak solution for path-dependent partial differential equations
Dumitrescu, Roxana. "Contributions au contrôle stochastique avec des espérances non linéaires et aux équations stochastiques rétrogrades." Thesis, Paris 9, 2015. http://www.theses.fr/2015PA090033/document.
Full textThis thesis consists of two independent parts which deal with stochastic control with nonlinear expectations and backward stochastic differential equations (BSDE), as well as with the numerical methods for solving these equations.We begin the first part by introducing and studying a new class of backward stochastic differential equations, whose characteristic is that the terminal condition is not fixed, but only satisfies a nonlinear constraint expressed in terms of "f - expectations". This new mathematical object is closely related to the approximative hedging of an European option, when the shortfall risk is quantified in terms of dynamic risk measures, induced by the solution of a nonlinear BSDE. In the next chapter we study an optimal stopping problem for dynamic risk measures with jumps.More precisely, we characterize in a Markovian framework the minimal risk measure associated to a financial position as the unique viscosity solution of an obstacle problem for partial integrodifferential equations. In the third chapter, we establish a weak dynamic programming principle for a mixed stochastic control problem / optimal stopping with nonlinear expectations, which is used to derive the associated PDE. The specificity of this work consists in the fact that the terminal reward does not satisfy any regularity condition (it is considered only measurable), which was not the case in the previous literature. In the next chapter, we introduce a new game problem, which can be seen as a generalized Dynkin game (with nonlinear expectations ). We show that this game admits a value function and establish sufficient conditions ensuring the existence of a saddle point . We prove that the value function corresponds to the unique solution of a doubly reected backward stochastic equation (DRBSDE) with a nonlinear general driver. This characterization allows us to obtain new results on DRBSDEs with jumps. The generalized Dynkin game is finally addressed in a Markovian framework.In the second part, we are interested in numerical methods for doubly reected BSDEs with jumps and irregular barriers, admitting both predictable and totally inaccesibles jumps. In the first chapter we provide a numerical scheme based on the penalisation method and the approximation of the solution of a BSDE by a sequence of discrete BSDEs driven by two independent random walks (one approximates the Brownian motion and the other one the compensated Poisson process). In the second chapter, we construct an alternative scheme based on the direct discretisation of the DRBSDE, scheme which presents the advantage of not depending anymore on the penalization parameter. We prove the convergence of the two schemes and illustrate the theoretical results with some numerical examples
Kirgizov, Sergey. "Analyse empirique et modélisation de la dynamique de la topologie de l'internet." Electronic Thesis or Diss., Paris 6, 2014. http://www.theses.fr/2014PA066355.
Full textMany works have studied the Internet topology, but few have investigated the question of how it evolves over time. This thesis focuses on the Internet routing IP-Level topology dynamics and offer a first step towards a realistic modeling of these dynamics. For this end we study data from periodic measurements of routing trees from a single monitor to a fixed destination set. Next we propose a simple model that simulates the dynamics of a topology real network. By studying the results of the simulation, we show this model catches some observed invariant properties of the real-World data. In addition, analysing the simulation results of different types of networks, we found several structural features that have great impact on the dynamics of the topology. We study also how the frequency of measurement affects the observed dynamics. We are interested in the underlying process causing the observed dynamics. We introduce a method non-Classical parameter estimation of a stochastic process apply this method to the real-World and modelled measures in order to characterise the rate of the topology evolution. We also show that the network have non-Uniform dynamics: different parts of the network can have different rates of change
Ackermann, Christophe. "Processus associés à l'équation de diffusion rapide. Indépendance du temps et de la position pour un processus stochastique." Nancy 1, 2003. http://www.theses.fr/2003NAN10186.
Full textThe aim of this thesis is twofold. First, we give a stochastic modelisation of a partial differential equation known as equation of "fast" diffusion. The latter describes a diffusion phenomenon which occurs in the plasma physics. Thus, we study the solution of a differential stochastic equation, the density of which satisfies the equation of "fast" diffusion: we treat in particular the case when the initial measure is the Dirac measure at 0. Secondly, we deal with the question of the independence of time and position for a stochastic process. We consider a random walk S(n) with independent identically distributed increments and we study the standard stopping times T such that T and S(T) are independent. We give a description of the stopping distributions of S(T) in the case of a Bernoulli symmetric random walk. We finally complete this work by giving a characterization of the stopping distributions of the Brownian motion
Messaci, Fatiha. "Estimation de la densité spectrale d'un processus en temps continu par échantillonage poissonnien." Rouen, 1986. http://www.theses.fr/1986ROUES036.
Full textTemine, Laura. "Modélisation déterministe et stochastique de processus épidémiques : application à la résistance aux antibiotiques." Paris 6, 2003. http://www.theses.fr/2003PA066491.
Full textBravo, Gonzàlez Mario. "Dynamiques d’apprentissage et d’évolution en théorie des jeux." Paris 6, 2012. http://www.theses.fr/2012PA066360.
Full textThis thesis is devoted to the study of several related models of dynamical interaction from a game theoretical perpective. In the first part, we are interested in repeated interactions in discrete time in a minimal information framework. In the second part, we analyse several models in continuous time with special interest in the replicator dynamics. The sequel is devoted to the study of a learning process in continuous time where players observe a perturbed version of their actual payoff, and its link with the evolutionary game theory. The final part focuses on a two-level dynamics in order to model a multi-level selection phenomenon
Leoncini, Emanuele. "Towards a global and systemic understanding of protein production in prokaryotes." Palaiseau, Ecole polytechnique, 2013. http://pastel.archives-ouvertes.fr/docs/00/92/42/32/PDF/LEONCINI-These.pdf.
Full textBiochemical reactions underlying the functioning of cells are inherently stochastic processes. As a consequence, the whole system is noisy and undergoes fluctuations in its fundamental components. Proteins are major players in the life of a cell; their stochastic character manifests itself through striking differences in phenotypes, even in the case of cloned cells exposed to identical environmental conditions. Given the context, it is crucial that models embrace realistic assumptions. In this thesis we have introduced a new mathematical framework based on Marked Poisson Point Processes (MPPP) to describe the main steps of the production of a specific protein. We were able to overcome the restrictive assumption, crucial in the classical framework, of an exponentially distributed duration of all steps. The non-Markovian description of gene expression obtained through this new framework has allowed us to propose a more realistic model of gene expression, which includes protein elongation step and protein dilution due to volume growth. We also made the first steps towards a modeling of the production of many proteins, considering interactions as the result of the competition for common resources. The system of production is studied via a mean-field approach. The multi-protein model brings a completely new approach in the domain and marks a new direction in the investigation of protein fluctuations at the cellular level. In conclusion, the thesis has focused on the study of the stochastic nature of gene expression, by developing different models in order to progress towards a more realistic description of the phenomena
Javaheri, Alireza. "Le processus de la volatilité." Phd thesis, Paris, ENMP, 2004. http://www.theses.fr/2004ENMP1250.
Full textIt is widely accepted today that an assumption of a constant standard-deviation for the stock-return is not realistic. Indeed the traditional Samuelson-Black-Scholes framework of a lognormal distribution fails to explain the existence of leptokurticity (fat tails) as well as the asymmetry (negative skew) observed in the stock-return distribution. Many different theories have been recently suggested to deal with this phenomenon, but they could all be classified under the title of Stochastic Volatility (SV). Popular SV models include GARCH, Jump-Diffusion, Heston and the Variance-Gamma models. Most of them use either Gaussian innovations with Poisson jumps or other Levy distributions such as Gamma or Ornstein-Uhlenbeck. One of the main difficulties while working with an SV model is that the actual instantaneous volatility is not observable in the market and therefore needs to be modeled as a hidden state. This means that in order to calibrate a model to the stock market, one needs to use a usually nonlinear and/ or non-Gaussian Filter. An alternative would be to use a Bayesian Markov-Chain Monte-Carlo approach. This calibration will then provide us with an estimation of the statistical (or real-world) distribution of the stock-return. This thesis focuses on Nonlinear and Non-Gaussian Filtering as well as the comparison between the Statistical and Risk-Neutral distributions