From the beginning of 20th century many studies proved randomness in price evolution of investment instruments. Therefore models respecting this randomness must be used in portfolio management. This thesis' aim is to provide basic theory regarding some of the stochastic methods and show their practical use in real situations.

<div>The dissertation consists of two research topics.</div><div><br></div><div>The first research direction is to study stability of functional and geometric inequalities. Stability problem is to estimate the deficit of a functional or geometric inequality in terms of the distance from the class of optimizers or a functional that identifies the optimizers. In particular, we investigate the logarithmic Sobolev inequality, the Beckner-Hirschman inequality (the entropic uncertainty principle), and isoperimetric type inequalities for the expected lifetime of Brownian motion. </div><div><br></div><div>The second topic of the thesis is a stochastic representation of fractional integrals and nonlocal operators. We extend the Hardy-Littlewood-Sobolev inequality to symmetric Markov semigroups. To this end, we construct a stochastic representation of the fractional integral using the background radiation process. The inequality follows from a new inequality for the fractional Littlewood-Paley square function. We also prove the Hardy-Stein identity for non-symmetric pure jump Levy processes and the L^p boundedness of a certain class of Fourier multiplier operators arising from non-symmetric pure jump Levy processes. The proof is based on Ito's formula for general jump processes and the symmetrization of Levy processes. <br></div>

Apresentamos uma tentativa de estender o alcance da teoria clássica na previsão de fenômenos microscópicos. Baseamos nosso enfoque na hipótese de que a mecânica quântica é uma teoria estocástica cujas origens são as flutuações eletromagnéticas de ponto zero. Discutimos uma abordagem nova para a descrição do movimento browniano, clássico e quântico, através de uma equação clássica estocástica do tipo Schröedinger eficiência dessa equação é testada para sistemas lineares em contato com diferentes reservatórios de ruídos. Ambientes diferentes do espaço vazio levam naturalmente a interações do tipo força de Casimir. Para a descrição de rotações intrínsecas introduzimos na teoria clássica a representação espinorial e obtemos uma equação do tipo Pauli-Schrödinger, com flutuação e dissipação, que nos permite gerar distribuições no espaço de fase para partículas com spin arbitrário. Concluímos que a eletrodinâmica estocástica é uma teoria clássica apta a descrever os processos quânticos que se originam das autuações do vácuo. / We present an attempt to extend the range of the classical theory in the description of microscopic phenomena. We base our point of view in the hypothesis that quantum mechanics is a stochastic theory whose origin is in the electromagnetic zero-point fluctuations. We discuss a new approach for the description of Brownian motion, both classical and quantum with a stochastic Schrödinger type equation. The effectiveness of this equation is tested for linear systems in contact with different noise reservoirs. Environments different from the vacuum lead naturally to the Casimir force interaction. For the description of particles with spin we introduce in the classical theory a spinorial representation for rotations and obtain a Pauli-Schrödinger type equation, with fluctuation and dissipation, that allows us to generate phase space distributions for particles with arbitrary spin. We conclude that stochastic electrodynamics is a classical theory that is able to describe those quantum processes whose origins are in the vacuum fluctuations.

The eCommerce industry introduced new business principles, as well as new strategies for achieving these principles, and as a result some traditional measures of success are no longer valid. We classified and ranked the performance of twenty business-to-consumer eCommerce companies by developing critical benchmarks using the Balanced scorecard methodology. We applied a Latent class model, a statistical model along the Bayesian framework, to facilitate the determination of the best and worst performing companies. An eCommerce site's greatest asset is its customers, which is why some of the most valued and sophisticated metrics used today evolve around customer behavior. The results from our classification and ranking procedure showed that companies that ranked high overall also ranked comparatively well in the customer analysis ranking, For example, Amazon.com, one of the highest rated eCommerce companies with a large customer base ranked second in the critical benchmark developed towards measuring customer analysis. The results from our simulation also showed that the Latent class model is a good fit for the classification procedure, and it has a high classification rate for the worst and best performing companies. The resulting work offers a practical tool with the ability to identify profitable investment opportunities for financial managers and analysts.

To understand the phenomena associated with such stochastic processes and to predict, at least qualitatively, the behavior of mechanical systems within environments which are completely random in time, new mechanical tools are necessary. Fortunately, the derivation of these tools does not necessitate a complete departure from existing theories. In fact, they may be considered as an extension of the well-defined theory of the integral transform, in particular, the exponential Fourier integral transform.

Sequential decision making problems are ubiquitous in a number of research areas such as operations research, finance, engineering and computer science. The main challenge with these problems comes from the fact that, firstly, there is uncertainty about the future. And secondly, decisions have to be made over a period of time, sequentially. These problems, in many cases, are modeled as Markov Decision Process (MDP). Most real-life MDPs are ‘high dimensional’ in nature making them challenging from a numerical point of view. We consider a number of such high dimensional MDPs. In some cases such problems can be approximately solved using Approximate Dynamic Programming. In other cases problem specific analysis can be solved to device tractable policies that are near-optimal. In Chapter 2, we presents a novel and practical non-parametric approximate dynamic programming (ADP) algorithm that enjoys graceful, dimension-independent approximation and sample complexity guarantees. In particular, we establish both theoretically and computationally that our proposal can serve as a viable replacement to state of the art parametric ADP algorithms, freeing the designer from carefully specifying an approximation architecture. We accomplish this by ‘kernelizing’ a recent mathematical program for ADP (the ‘smoothed’ approximate LP) proposed by [Desai et al., 2011]. In Chapter 3, we consider a class of stochastic control problems where the action space at each time can be described by a class of matching or, more generally, network flow polytopes. Special cases of this class of dynamic matching problems include many problems that are well-studied in the literature, such as: (i) online keyword matching in Internet advertising (the adwords problem); (ii) the bipartite matching of donated kidneys from cadavers to recipients; and (iii) the allocation of donated kidneys through exchanges over cycles of live donor-patient pairs. We provide an approximate dynamic program (ADP) algorithm for dynamic matching with stochastic arrivals and departures. Our framework is more general than the methods prevalent in the literature in that it is applicable to a broad range of problems characterized by a variety of action polytopes and generic arrival and departure processes. In Chapter 4, we consider the problem of A-B testing when the impact of the treatment is marred by a large number of covariates. Randomization can be highly inefficient in such settings, and thus we consider the problem of optimally allocating test subjects to either treatment with a view to maximizing the efficiency of our estimate of the treatment effect. Our main contribution is a tractable algorithm for this problem in the online setting, where subjects arrive, and must be assigned, sequentially. We characterize the value of optimized allocations relative to randomized allocations and show that this value grows large as the number of covariates grows. In particular, we show that there is a lot to be gained from ‘optimizing’ the process of A-B testing relative to the simple randomized trials that are the mainstay of A-B testing in the ‘big data’ regime of modern e-commerce applications, where the number of covariates is often comparable to the number of experimental trials.

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.

Na presente dissertação fazemos um resumo das idéias fundamentais do método de Quantização Estocástica de Parisi e Wu, com aplicações a teorias de campo Escalares, de Gauge e Fermiônicas. Em particular, nós utilizamos o esquema de Regularização Analítica Estocástica no cálculo do tensor de polarização para a Eletrodinâmica Quântica com Bósons ou Fêrmions de Dirac. A influência da regularização na invariância de Gauge e estudada para ambas as teorias, e é sugerida uma extensão do método para alguns modelos supersimétricos. / In the present dissertation, we made a survey of the fundamental ideas about Parisi-Wu\'s Stochastic Quantization Method, with applications to Scalar, Gauge and Fermionic theories. In particular, we use the Analytic Stochastic Regularization Scheme to calculate the polarization tensor for Quantum Electrodynamics with bosons or Dirac Fermions. The regularization influence is studied for both theories and an extension of this method for some supersymmetrical models is suggested.

Apresentamos uma tentativa de estender o alcance da teoria clássica na previsão de fenômenos microscópicos. Baseamos nosso enfoque na hipótese de que a mecânica quântica é uma teoria estocástica cujas origens são as flutuações eletromagnéticas de ponto zero. Discutimos uma abordagem nova para a descrição do movimento browniano, clássico e quântico, através de uma equação clássica estocástica do tipo Schröedinger eficiência dessa equação é testada para sistemas lineares em contato com diferentes reservatórios de ruídos. Ambientes diferentes do espaço vazio levam naturalmente a interações do tipo força de Casimir. Para a descrição de rotações intrínsecas introduzimos na teoria clássica a representação espinorial e obtemos uma equação do tipo Pauli-Schrödinger, com flutuação e dissipação, que nos permite gerar distribuições no espaço de fase para partículas com spin arbitrário. Concluímos que a eletrodinâmica estocástica é uma teoria clássica apta a descrever os processos quânticos que se originam das autuações do vácuo. / We present an attempt to extend the range of the classical theory in the description of microscopic phenomena. We base our point of view in the hypothesis that quantum mechanics is a stochastic theory whose origin is in the electromagnetic zero-point fluctuations. We discuss a new approach for the description of Brownian motion, both classical and quantum with a stochastic Schrödinger type equation. The effectiveness of this equation is tested for linear systems in contact with different noise reservoirs. Environments different from the vacuum lead naturally to the Casimir force interaction. For the description of particles with spin we introduce in the classical theory a spinorial representation for rotations and obtain a Pauli-Schrödinger type equation, with fluctuation and dissipation, that allows us to generate phase space distributions for particles with arbitrary spin. We conclude that stochastic electrodynamics is a classical theory that is able to describe those quantum processes whose origins are in the vacuum fluctuations.

We use modern approach of stochastic dominance in portfolio optimization, where we want the portfolio to dominate a benchmark. Since the distribution of returns is often just estimated from data, we look for the worst distribution that differs from empirical distribution at maximum by a predefined value. First, we define in what sense the distribution is the worst for the first and second order stochastic dominance. For the second order stochastic dominance, we use two different formulations for the worst case. We derive the robust stochastic dominance test for all the mentioned approaches and find the worst case distribution as the optimal solution of a non-linear maximization problem. Then we derive programs to maximize an objective function over the weights of the portfolio with robust stochastic dominance in constraints. We consider robustness either in returns or in probabilities for both the first and the second order stochastic dominance. To the best of our knowledge nobody was able to derive such program before. We apply all the derived optimization programs to real life data, specifically to returns of assets captured by Dow Jones Industrial Average, and we analyze the problems in detail using optimal solutions of the optimization programs with multiple setups. The portfolios calculated using...