In the limit we analyze the generators of families of reversible jump processes in the n-dimensional space associated with a class of symmetric non-local Dirichlet forms and show exponential decay of the eigenfunctions. The exponential rate function is a Finsler distance, given as solution of certain eikonal equation. Fine results are sensitive to the rate functions being twice differentiable or just Lipschitz. Our estimates are similar to the semiclassical Agmon estimates for differential operators of second order. They generalize and strengthen previous results on the lattice.

Inflation indexed instruments are designed to help protect investors against the changes in the general level of prices. So, they are frequently preferred by investors and they have become increasingly developing part of the market. In this study, firstly, the HJM model and foreign currency analogy used to price of inflation indexed instruments are investigated. Then, the HJM model is extended with finite number of Poisson process. Finally, under the extended HJM model, a pricing derivation of inflation indexed swaps, which are the most liquid ones among inflation indexed instruments in the market, is given.

Day-ahead spot electricity markets are the most transparent spot markets where one can find integrated supply and demand curves of the market players for each settlement period. Since it is an indicator for the market players and regulators, in this thesis we model the spot electricity prices. Logarithmic daily average spot electricity prices are modeled as a summation of a deterministic function and multi-factor stochastic process. Randomness in the spot prices is assumed to be governed by three jump processes and a Brownian motion where two of the jump processes are mean reverting. While the Brownian motion captures daily regular price movements, the pure jump process models price shocks which have long term effects and two Ornstein Uhlenbeck type jump processes with different mean reversion speeds capturing the price shocks that affect the price level for relatively shorter time periods. After removing the seasonality which is modeled as a deterministic function from price observations, an iterative threshold function is used to filter the jumps. The threshold function is constructed on volatility estimation generated by a GARCH(1,1) model. Not only the jumps but also the mean reverting returns following the jumps are filtered. Both of the filtered jump processes and residual Brownian components are estimated separately. The model is applied to Austrian, Italian, Spanish and Turkish electricity markets data and it is found that the weekly forecasts, which are generated by the estimated parameters, turn out to be able to capture the characteristics of the observations. After examining the future contracts written on electricity, we also suggest a decision technique which is built on risk premium theory. With the help of this methodology derivative market players can decide on taking whether a long or a short position for a given contract. After testing our technique, we conclude that the decision rule is promising but needs more empirical research.

Ce travail présente des modèles d'écoulement en temps continu de flux de trafic routier. En premier lieu, il s'agit de modèles microscopiques de poursuite. Un modèle par systèmes d'équations différentielles couplées est proposé, basé sur le temps inter-véhiculaire. Ce modèle intègre un temps de réaction et des possibilités d'anticipation pour chaque véhicule. Les paramètres sont estimés par maximum de vraisemblance dans un modèle statistique à deux niveaux. Des simulations permettent de caractériser le comportement d'une file de véhicules. Dans une approche stochastique, un modèle d'évolution de la distance inter-véhiculaire est étudié à l'aide du processus Markovien de saut zero-range. L'introduction d'un temps de réaction tend à produire des ondes cinématiques. D'autre part, un modèle d'écoulement de trafic par le processus Markovien de saut des misanthropes est proposé. Il s'agit d'une modélisation au niveau mésoscopique, adaptée à la simulation de flux de trafic sur un réseau / This work presents different continuous-time traffic flow models. Microscopic models are considered first. A model by coupled differential equation system is proposed, based on the time gap. It incorporates a reaction time parameter and some anticipation possibilities, for each vehicle. The parameters are estimated by maximum likelihood over a two-level statistical model. Simulations allow to characterise the behaviour of a vehicles line. In a stochastic approach, a model of the distance gap evolution is studied with a zero-range process. The introduction of a reaction time parameter produces kinematics waves. On the other hand, traffic flow model by a misanthropes process is proposed. It is a mesoscopic approach, adapted to the simulation of traffic flow on a network

Title: Black-Scholes Models of Option Pricing Author: Martin Cekal Department: Department of Probability and Mathematical Statistics Supervisor: prof. RNDr. Bohdan Maslowski, DrSc., Charles University in Prague, Faculty of Mathematics and Physics, Department of Probability and Mathematical Statistics. Abstract: In the present master thesis we study a generalization of Black-Scholes model using fractional Brownian motion and jump processes. The main goal is a derivation of the price of call option in a fractional jump market model. The first chapter introduces long memory and its modelling by discrete and continuous time models. In the second chapter fractional Brownian motion is defined, appropriate stochastic analysis is developed and we generalize the notion of Lévy and jump processes. The third chapter introduces fractional Black-Scholes model. In the fourth chapter, tools developed in the second chapter are used for the construction of jump fractional Black-Scholes model and derivation of explicit formula for the price of european call option. In the fifth chapter, we analyze long memory contained in simulated and empirical time series. Keywords: Black-Scholes model, fractional Brownian motion, fractional jump process, long- memory, options pricing.

In this study, we show that realized bipower variation which is an extension of realized power variation is an alternative method that estimates integrated variance like realized variance. It is seen that realized bipower variation is robust to rare jumps. Robustness means that if we add rare jumps to a stochastic volatility process, realized bipower variation process continues to estimate integrated variance although realized variance estimates integrated variance plus the quadratic variation of the jump component. This robustness is crucial since it separates the discontinuous component of quadratic variation which comes from the jump part of the logarithmic price process. Thus, we demonstrate that if the logarithmic price process is in the class of stochastic volatility plus rare jumps processes then the difference between realized variance and realized bipower variation process estimates the discontinuous component of the quadratic variation. So, quadratic variation of the jump component can be estimated and jump detection can be achieved.

This study is concerned with the numerical solution of certain stochastic models of chemical reactions. Such descriptions have been shown to be useful tools when studying biochemical processes inside living cells where classical deterministic rate equations fail to reproduce actual behavior. The main contribution of this thesis lies in its theoretical and practical investigation of different methods for obtaining numerical solutions to such descriptions. In a preliminary study, a simple but often quite effective approach to the moment closure problem is examined. A more advanced program is then developed for obtaining a consistent representation of the high dimensional probability density of the solution. The proposed method gains efficiency by utilizing a rapidly converging representation of certain functions defined over the semi-infinite integer lattice. Another contribution of this study, where the focus instead is on the spatially distributed case, is a suggestion for how to obtain a consistent stochastic reaction-diffusion model over an unstructured grid. Here it is also shown how to efficiently collect samples from the resulting model by making use of a hybrid method. In a final study, a time-parallel stochastic simulation algorithm is suggested and analyzed. Efficiency is here achieved by moving parts of the solution phase into the deterministic regime given that a parallel architecture is available. Necessary background material is developed in three chapters in this summary. An introductory chapter on an accessible level motivates the purpose of considering stochastic models in applied physics. In a second chapter the actual stochastic models considered are developed in a multi-faceted way. Finally, the current state-of-the-art in numerical solution methods is summarized and commented upon.

The motile behaviour of bacteria underlies many important aspects of their actions, including pathogenicity, foraging efficiency, and ability to form biofilms. In this thesis, we apply mathematical modelling and analysis to various aspects of the planktonic motility of flagellated bacteria, guided by experimental observations. We use data obtained by tracking free-swimming Rhodobacter sphaeroides under a microscope, taking advantage of the availability of a large dataset acquired using a recently developed, high-throughput protocol. A novel analysis method using a hidden Markov model for the identification of reorientation phases in the tracks is described. This is assessed and compared with an established method using a computational simulation study, which shows that the new method has a reduced error rate and less systematic bias. We proceed to apply the novel analysis method to experimental tracks, demonstrating that we are able to successfully identify reorientations and record the angle changes of each reorientation phase. The analysis pipeline developed here is an important proof of concept, demonstrating a rapid and cost-effective protocol for the investigation of myriad aspects of the motility of microorganisms. In addition, we use mathematical modelling and computational simulations to investigate the effect that the microscope sampling rate has on the observed tracking data. This is an important, but often overlooked aspect of experimental design, which affects the observed data in a complex manner. Finally, we examine the role of rotational diffusion in bacterial motility, testing various models against the analysed data. This provides strong evidence that R. sphaeroides undergoes some form of active reorientation, in contrast to the mainstream belief that the process is passive.

Ce travail est centré sur la charactérisation de certaines classes de processus aléatoires par des formules de dualité. En particulier on considérera des processus réciproques à sauts, un cas jusqu'à présent négligé dans la littérature.Dans la première partie nous formulons de façon innovante une charactérisation des processus à accroissements indépendants. Celle-ci est basée sur une formule de dualité pour des processus infiniment divisibles, déjà connue dans le cadre du calcul de Malliavin. On va présenter deux nouvelles méthodes pour prouver cette formule, qui n'utilisent pas la décomposition en chaos de l'espace des fonctionnelles de carré intégrable. Une méthode s'appuie sur une formule d'intégration par parties satisfaite par des vecteurs aléatoires infiniment divisibles. Sous cet angle, notre charactérisation est une généralization du lemme de Stein dans le cas Gaussien et du lemme de Chen dans le cas Poissonien. La généralité de notre approche nous permet de plus, de présenter une charactérisation des mesures aléatoires infiniment divisibles.Dans la deuxième partie de notre travail nous nous concentrons sur l'étude des classes réciproques de processus de Markov avec ou sans sauts, et sur leur charactérisation. On commence avec un résumé des résultats déjà existants concernant les classes réciproques de diffusions browniennes comme solutions d'une formule de dualité. Nous obtenons notamment une nouvelle interprétation des classes réciproques comme les solutions d'une équation de Newton. Cela nous permet de relier nos résultats à la mécanique stochastique d'une part et à la théorie du contrôle optimale, d'autre part. La formule de dualité nous permet aussi de prouver une propriété d'invariance par retournement du temps de la classe réciproque d'une diffusion brownienne.En outre nous obtenons une série de nouveaux résultats concernant les processus de sauts purs. Nous décrivons d'abord la classe réciproque associée à un processus markovien de comptage, c'est-à-dire un processus de sauts de taille un, puis en présentons une charactérisation par une formule de dualité. Cette formule contient une dérivée stochastique, une intégrale stochastique compensée, et une fonctionnelle qui est une grandeur invariante de la classe réciproque. De plus nous livrons une interprétation de la classe réciproque comme ensemble des solutions d'un problème de contrôle optimal. Enfin, par une utilisation appropriée de la formule de dualité, nous montrons que la classe réciproque d'un processus markovien de comptage est invariante par retournement du temps.Quelques-uns de ces résultats restent valables pour des processus de sauts purs dont les sauts sont de taille variée. En particulier nous montrons que certaines fonctionnelles dites invariants réciproques permettent de distinguer différentes classes réciproques. Notre dernier résultat est la charactérisation de la classe réciproque d'un processus de Poisson composé dès lors que les (tailles des) différents sauts sont incommensurables. / This work is concerned with the characterization of certain classes of stochastic processes via duality formulae. In particular we consider reciprocal processes with jumps, a subject up to now neglected in the literature. In the first part we introduce a new formulation of a characterization of processes with independent increments. This characterization is based on a duality formula satisfied by processes with infinitely divisible increments, in particular Lévy processes, which is well known in Malliavin calculus. We obtain two new methods to prove this duality formula, which are not based on the chaos decomposition of the space of square-integrable functionals. One of these methods uses a formula of partial integration that characterizes infinitely divisible random vectors. In this context, our characterization is a generalization of Stein's lemma for Gaussian random variables and Chen's lemma for Poisson random variables. The generality of our approach permits us to derive a characterization of infinitely divisible random measures.The second part of this work focuses on the study of the reciprocal classes of Markov processes with and without jumps and their characterization. We start with a resume of already existing results concerning the reciprocal classes of Brownian diffusions as solutions of duality formulae. As a new contribution, we show that the duality formula satisfied by elements of the reciprocal class of a Brownian diffusion has a physical interpretation as a stochastic Newton equation of motion. Thus we are able to connect the results of characterizations via duality formulae with the theory of stochastic mechanics by our interpretation, and to stochastic optimal control theory by the mathematical approach. As an application we are able to prove an invariance property of the reciprocal class of a Brownian diffusion under time reversal.In the context of pure jump processes we derive the following new results. We describe the reciprocal classes of Markov counting processes, also called unit jump processes, and obtain a characterization of the associated reciprocal class via a duality formula. This formula contains as key terms a stochastic derivative, a compensated stochastic integral and an invariant of the reciprocal class. Moreover we present an interpretation of the characterization of a reciprocal class in the context of stochastic optimal control of unit jump processes. As a further application we show that the reciprocal class of a Markov counting process has an invariance property under time reversal. Some of these results are extendable to the setting of pure jump processes, that is, we admit different jump-sizes. In particular, we show that the reciprocal classes of Markov jump processes can be compared using reciprocal invariants. A characterization of the reciprocal class of compound Poisson processes via a duality formula is possible under the assumption that the jump-sizes of the process are incommensurable.

Cette thèse comporte un résumé avec des formules mathématiques. Vous pouvez le consulter via le texte intégral du document à la dernière page. / This thesis contains an abstract with mathematical formulae. You can consult it via the complete text of the document in the back page.