This dissertation studies the pricing of Outside barrier call options, when their activation starts at a hitting time. The pricing of Outside barrier options when their activation starts at time zero, and the pricing of standard barrier options when their activation starts at a hitting time of a pre speci ed barrier level, have been studied previously (see [21], [24]). The new work that this dissertation will do is to price Outside barrier call options, where they will be activated when the triggering asset crosses or hits a pre speci ed barrier level, and also the pricing of Outside barrier call options where they will be activated when the triggering asset crosses or hits a sequence of two pre specifed barrier levels. Closed form solutions are derived using Girsanov's theorem and the re ection principle. Existing results are derived from the new results, and properties of the new results are illustrated numerically and discussed. / Mathematical Sciences / M. Sc. (Applied Mathematics)

This dissertation studies the pricing of Outside barrier call options, when their activation starts at a hitting time. The pricing of Outside barrier options when their activation starts at time zero, and the pricing of standard barrier options when their activation starts at a hitting time of a pre speci ed barrier level, have been studied previously (see [21], [24]). The new work that this dissertation will do is to price Outside barrier call options, where they will be activated when the triggering asset crosses or hits a pre speci ed barrier level, and also the pricing of Outside barrier call options where they will be activated when the triggering asset crosses or hits a sequence of two pre specifed barrier levels. Closed form solutions are derived using Girsanov's theorem and the re ection principle. Existing results are derived from the new results, and properties of the new results are illustrated numerically and discussed. / Mathematical Sciences / M. Sc. (Applied Mathematics)

In this work, we study return and hitting times in measure-preserving dy- namical systems. We consider a special type of skew-products of two Bernoulli schemes, called a random walk in random scenery. For these systems, the limit distribution of normalized hitting times for cylinders of increasing length is proved to be exponential under the assumption of finite variance of the first order dis- tribution of the Bernoulli scheme representing the walk, and provided the drift is non-zero or the scenery alphabet is finite. Mixing properties of the skew-products are discussed in order to relate our work with some known results on rescaled hitting times for strongly-mixing systems. 1

Em Ciência da Computação, os caminhos aleatórios são utilizados em algoritmos randômicos, especialmente em algoritmos de busca, quando desejamos encontrar um estado marcado numa cadeia de Markov. Nesse tipo de algoritmo é interessante estudar o Tempo de Alcance, que está associado a sua complexidade computacional. Nesse contexto, descrevemos a teoria clássica de cadeias de Markov e caminhos aleatórios, assim como o seu análogo quântico. Dessa forma, definimos o Tempo de Alcance sob o escopo das cadeias de Markov quânticas. Além disso, expressões analíticas calculadas para o tempo de Alcance quântico e para a probabilidade de encontrarmos um elemento marcado num grafo completo são apresentadas como os novos resultados dessa dissertação. / In Computer Science, random walks are used in randomized algorithms, specially in search algorithms, where we desire to find a marked state in a Markov chain.In this type of algorithm,it is interesting to study the Hitting Time, which is associated to its computational complexity. In this context, we describe the classical theory of Markov chains and random walks,as well as their quantum analogue.In this way,we define the Hitting Time under the scope of quantum Markov chains. Moreover, analytical expressions calculated for the quantum Hitting Time and for the probability of finding a marked element on the complete graph are presented as the new results of this dissertation.

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Le premier chapitre présente les axes principaux de recherche ainsi que les problèmes traités dans cette thèse. Plus précisément, il expose une synthèse sur le sujet, en y donnant les propriétés essentielles pour la bonne compréhension de cette étude, accompagnée des références bibliographiques les plus importantes. Il présente également les motivations de ce travail en précisant les contributions originales dans ce domaine. Le deuxième chapitre est composé d’une recherche originale sur l’estimation du risque sismique, dans la zone du nord de la mer Egée (Grèce), en faisant usage de la théorie des processus semi-markoviens à temps continue. Il propose des estimateurs des mesures importantes qui caractérisent les processus semi-markoviens, et fournit une modélisation dela prévision de l’instant de réalisation d’un séisme fort ainsi que la probabilité et la grandeur qui lui sont associées. Les chapitres 3 et 4 comprennent une première tentative de modélisation du processus de génération des séismes au moyen de l’application d’un temps discret des modèles cachés markoviens et semi-markoviens, respectivement. Une méthode d’estimation non paramétrique est appliquée, qui permet de révéler des caractéristiques fondamentales du processus de génération des séismes, difficiles à détecter autrement. Des quantités importantes concernant les niveaux des tensions sont estimées au moyen des modèles proposés. Le chapitre 5 décrit les résultats originaux du présent travail à la théorie des processus stochastiques, c’est- à-dire l’étude et l’estimation du « Intensité du temps d’entrée en temps discret (DTIHT) » pour la première fois dans des chaînes semi-markoviennes et des chaînes de renouvellement markoviennes cachées. Une relation est proposée pour le calcul du DTIHT et un nouvel estimateur est présenté dans chacun de ces cas. De plus, les propriétés asymptotiques des estimateurs proposés sont obtenues, à savoir, la convergence et la normalité asymptotique. Le chapitre 6 procède ensuite à une étude de comparaison entre le modèle markovien caché et le modèle semi-markovien caché dans un milieu markovien et semi-markovien en vue de rechercher d’éventuelles différences dans leur comportement stochastique, déterminé à partir de la matrice de transition de la chaîne de Markov (modèle markovien caché) et de la matrice de transition de la chaîne de Markov immergée (modèle semi-markovien caché). Les résultats originaux concernent le cas général où les distributions sont considérées comme distributions des temps de séjour ainsi que le cas particulier des modèles qui sont applique´s dans les chapitres précédents où les temps de séjour sont estimés de manière non-paramétrique. L’importance de ces différences est spécifiée à l’aide du calcul de la valeur moyenne et de la variance du nombre de sauts de la chaîne de Markov (modèle markovien caché) ou de la chaîne de Markov immergée (modèle semi-markovien caché) pour arriver dans un état donné, pour la première fois. Enfin, le chapitre 7 donne des conclusions générales en soulignant les points les plus marquants et des perspectives pour développements futurs. / The first chapter describes the definition of the subject under study, the current state of science in this area and the objectives. In the second chapter, continuous-time semi-Markov models are studied and applied in order to contribute to seismic hazard assessment in Northern Aegean Sea (Greece). Expressions for different important indicators of the semi- Markov process are obtained, providing forecasting results about the time, the space and the magnitude of the ensuing strong earthquake. Chapters 3 and 4 describe a first attempt to model earthquake occurrence by means of discrete-time hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs), respectively. A nonparametric estimation method is followed by means of which, insights into features of the earthquake process are provided which are hard to detect otherwise. Important indicators concerning the levels of the stress field are estimated by means of the suggested HMM and HSMM. Chapter 5 includes our main contribution to the theory of stochastic processes, the investigation and the estimation of the discrete-time intensity of the hitting time (DTIHT) for the first time referring to semi-Markov chains (SMCs) and hidden Markov renewal chains (HMRCs). A simple formula is presented for the evaluation of the DTIHT along with its statistical estimator for both SMCs and HMRCs. In addition, the asymptotic properties of the estimators are proved, including strong consistency and asymptotic normality. In chapter 6, a comparison between HMMs and HSMMs in a Markov and a semi-Markov framework is given in order to highlight possible differences in their stochastic behavior partially governed by their transition probability matrices. Basic results are presented in the general case where specific distributions are assumed for sojourn times as well as in the special case concerning the models applied in the previous chapters, where the sojourn time distributions are estimated non-parametrically. The impact of the differences is observed through the calculation of the mean value and the variance of the number of steps that the Markov chain (HMM case) and the EMC (HSMM case) need to make for visiting for the first time a particular state. Finally, Chapter 7 presents concluding remarks, perspectives and future work.

Made available in DSpace on 2015-03-04T18:51:17Z (GMT). No. of bitstreams: 1 dissertacao_raqueline.pdf: 1022175 bytes, checksum: 12f505a41f92171e321e1b57c568631a (MD5) Previous issue date: 2010-03-05 / Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior / In Computer Science, random walks are used in randomized algorithms, specially in search algorithms, where we desire to find a marked state in a Markov chain.In this type of algorithm,it is interesting to study the Hitting Time, which is associated to its computational complexity. In this context, we describe the classical theory of Markov chains and random walks,as well as their quantum analogue.In this way,we define the Hitting Time under the scope of quantum Markov chains. Moreover, analytical expressions calculated for the quantum Hitting Time and for the probability of finding a marked element on the complete graph are presented as the new results of this dissertation. / Em Ciência da Computação, os caminhos aleatórios são utilizados em algoritmos randômicos, especialmente em algoritmos de busca, quando desejamos encontrar um estado marcado numa cadeia de Markov. Nesse tipo de algoritmo é interessante estudar o Tempo de Alcance, que está associado a sua complexidade computacional. Nesse contexto, descrevemos a teoria clássica de cadeias de Markov e caminhos aleatórios, assim como o seu análogo quântico. Dessa forma, definimos o Tempo de Alcance sob o escopo das cadeias de Markov quânticas. Além disso, expressões analíticas calculadas para o tempo de Alcance quântico e para a probabilidade de encontrarmos um elemento marcado num grafo completo são apresentadas como os novos resultados dessa dissertação.

This dissertation is cumulative and encompasses three self-contained research articles. These essays share one common theme: the probability that a given stochastic process crosses a certain boundary function, namely the boundary crossing probability, and the related financial and statistical applications. In the first paper, we propose a new Monte Carlo method to price a type of barrier option called the Parisian option by simulating the first and last hitting time of the barrier. This research work aims at filling the gap in the literature on pricing of Parisian options with general curved boundaries while providing accurate results compared to the other Monte Carlo techniques available in the literature. Some numerical examples are presented for illustration. The second paper proposes a Monte Carlo method for analyzing the sensitivity of boundary crossing probabilities of the Brownian motion to small changes of the boundary. Only for few boundaries the sensitivities can be computed in closed form. We propose an efficient Monte Carlo procedure for general boundaries and provide upper bounds for the bias and the simulation error. The third paper focuses on the inverse first-passage-times. The inverse first-passage-time problem deals with finding the boundary given the distribution of hitting times. Instead of a known distribution, we are given a sample of first hitting times and we propose and analyze estimators of the boundary. Firstly, we consider the empirical estimator and prove that it is strongly consistent and derive (an upper bound of) its asymptotic convergence rate. Secondly, we provide a Bayes estimator based on an approximate likelihood function. Monte Carlo experiments suggest that the empirical estimator is simple, computationally manageable and outperforms the alternative procedure considered in this paper.

In this thesis, nonlinearly perturbed stochastic models in discrete time are considered. We give algorithms for construction of asymptotic expansions with respect to the perturbation parameter for various quantities of interest. In particular, asymptotic expansions are given for solutions of renewal equations, quasi-stationary distributions for semi-Markov processes, and ruin probabilities for risk processes. / <p>At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: Manuscript. Paper 5: Manuscript. Paper 6: Manuscript.</p>

The most useful feature used in finance of the Ornstein-Uhlenbeck (OU) stochastic process is its mean-reverting property: the OU process tends to drift towards its long- term mean (its equilibrium state) over time. This important feature makes the OU process arguably the most popular statistical model for developing best pair-trading strategies. However, optimal strategies depend crucially on the first passage time (FPT) of the OU process to a suitably chosen boundary and its probability density is not analytically available in general. Even for crossing a simple constant boundary, the FPT of the OU process would lead to crossing a square root boundary by a Brownian motion process whose FPT density involves the complicated parabolic cylinder function. To overcome the limitations of the existing methods, we propose a novel class of non-linear boundaries for obtaining optimal decision thresholds. We prove the existence and uniqueness of the maximizer of our decision rules. We also derive simple formulas for some FPT moments without analytical expressions of its density functions. We conduct some Monte Carlo simulations and analyze several pairs of stocks including Coca-Cola and Pepsi, Target and Walmart, Chevron and Exxon Mobil. The results demonstrate that our method outperforms the existing procedures.