In Chapter 1 the classical secretary problem is introduced. Chapters 2 and 3 are variations of this problem. Chapter 2, discusses the problem of maximizing the probability of stopping with one of the two highest values in a Bernoulli random walk with arbitrary parameter p and finite time horizon n. The optimal strategy (continue or stop) depends on a sequence of threshold values (critical probabilities) which has an oscillating pattern. Several properties of this sequence have been proved by Dr. Allaart. Further properties have been recently proved. In Chapter 3, a gambler will observe a finite sequence of continuous random variables. After he observes a value he must decide to stop or continue taking observations. He can play two different games A) Win at the maximum or B) Win within a proportion of the maximum. In the first section the sequence to be observed is independent. It is shown that for each n>1, theoptimal win probability in game A is bounded below by (1-1/n)^{n-1}. It is accomplished by reducing the problem to that of choosing the maximum of a special sequence of two-valued random variables and applying the sum-the-odds theorem of Bruss (2000). Secondly, it is assumed the sequence is i.i.d. The best lower bounds are provided for the winning probabilities in game B given any continuous distribution. These bounds are the optimal win probabilities of a game A which was examined by Gilbert and Mosteller (1966).

Dans ce travail nous abordons deux problèmes non résolus en Probabilité appliquée. Nous les approchons tous deux sous un angle nouveau, en utilisant des outils aussi variés que les chaînes de Markov, les mouvements Browniens, les transformations de Schwarz-Christoffel, les processus de Poisson et la théorie des temps d'arrêts optimaux. Problème de la ruine pour N joueurs Le problème de la ruine pour $N$ joueurs est un problème célèbre dont la solution pour $N=2$ est connue depuis longtemps. Nous l'abordons premièrement en toute généralité, en le modélisant comme un problème d'absorption pour une chaîne de Markov. Nous obtenons les distributions associées à ce problème et nous décrivons un algorithme (appelé {it folding algorithm}) permettant de diminuer considérablement le nombre d'opérations nécessaires à une résolution complète. Cette étude nous permet de mettre en avant un certain nombres de relations de récurrence satisfaites par les probabilités de ruines associées à chaque état de la chaîne de Markov. Nous étudions ensuite une version asymptotique du problème de la ruine pour 3 joueurs. Nous utilisons les propriétés d'invariance des mouvements Browniens par transformations conformes pour décrire une résolution de ce problème via les transformations de Schwarz-Christoffel. Cette méthode dépasse le cadre strict du problème de la ruine pour 3 joueurs et s'applique à d'autres problèmes de temps d'atteinte d'un bord par un mouvement Brownien. Problème de Robbins Ce problème s'inscrit dans le cadre de la théorie des temps d'arrêts optimaux. C'est un problème d'analyse séquentielle dans lequel un observateur examine $n$ variables aléatoires indépendantes de manière séquentielle et doit en sélectionner exactement une sans rappel. L'objectif est de déterminer une stratégie qui permette de minimiser le rang moyen de l'observation sélectionnée. Nous décrivons un modèle alternatif de ce problème, dans lequel le décideur observe un nombre aléatoire d'arrivées distribuées suivant un processus de Poisson homogène sur un horizon fixe $t$. Nous prouvons l'existence d'une stratégie optimale pour chaque horizon, et nous montrons que la fonction de perte associée à cette stratégie est uniformément continue sur $R$. Nous décrivons une fonction de perte restreinte qui permet d'obtenir une estimation de la valeur asymptotique du problème, et nous obtenons la valeur asymptotique associée à des stratégies spécifiques. Nous obtenons ensuite une équation intégro-diffférentielle sur la fonction de perte associée à la stratégie optimale. Finalement nous étudions les valeurs asymptotiques du problème et nous les comparons à celles du problème en temps discret. Nous concluons cette thèse en décrivant des stratégies spécifiques qui permettent d'obtenir des estimations sur le comportement asymptotique de la fonction de perte.

A cornerstone in the theory of optimal stopping for the maximum process is a result known as Peskir’s maximality principle. It has proved to be a powerful tool to solve optimal stopping problems involving the maximum process under the assumption that the driving process X is a time-homogeneous diffusion. In this thesis we adapt Peskir’s maximality principle to allow for X a spectrally negative L´evy processes, thereby providing a general method to approach optimal stopping problems for the maximum process driven by spectrally negative L´evy processes. We showcase this by explicitly solving three optimal stopping problems and the capped versions thereof. Here capped version means a modification of the original optimal stopping problem in the sense that the payoff is bounded from above by some constant. Moreover, we discuss applications of the aforementioned optimal stopping problems in option pricing in financial markets whose price process is driven by an exponential spectrally negative L´evy process. Finally, to further highlight the applicability of our general method, we present the solution to the problem of predicting the time at which a positive self-similar Markov process with one-sided jumps attains its maximum or minimum.

The main contribution of this thesis is to derive the properties and present a closed from solution of the exotic options under some specific types of Levy processes, such as American put options, American call options, British put options, British call options and American knock-out put options under either double exponential jump-diffusion processes or one-sided exponential jump-diffusion processes. Compared to the geometric Brownian motion, exponential jump-diffusion processes can better incorporate the asymmetric leptokurtic features and the volatility smile observed from the market. Pricing the option with early exercise feature is the optimal stopping problem to determine the optimal stopping time to maximize the expected options payoff. Due to the Markovian structure of the underlying process, the optimal stopping problem is related to the free-boundary problem consisting of an integral differential equation and suitable boundary conditions. By the local time-space formula for semi-martingales, the closed form solution for the options value can be derived from the free-boundary problem and we characterize the optimal stopping boundary as the unique solution to a nonlinear integral equation arising from the early exercise premium (EEP) representation. Chapter 2 and Chapter 3 discuss American put options and American call options respectively. When pricing options with early exercise feature under the double exponential jump-diffusion processes, a non-local integral term will be found in the infinitesimal generator of the underlying process. By the local time-space formula for semi-martingales, we show that the value function and the optimal stopping boundary are the unique solution pair to the system of two integral equations. The significant contributions of these two chapters are to prove the uniqueness of the value function and the optimal stopping boundary under less restrictive assumptions compared to previous literatures. In the degenerate case with only one-sided jumps, we find that the results are in line with the geometric Brownian motion models, which extends the analytical tractability of the Black-Scholes analysis to alternative models with jumps. In Chapter 4 and Chapter 5, we examine the British payoff mechanism under one-sided exponential jump-diffusion processes, which is the first analysis of British options for process with jumps. We show that the optimal stopping boundaries of British put options with only negative jumps or British call options with only positive jumps can also be characterized as the unique solution to a nonlinear integral equation arising from the early exercise premium representation. Chapter 6 provides the study of American knock-out put options under negative exponential jump-diffusion processes. The conditional memoryless property of the exponential distribution enables us to obtain an analytical form of the arbitrage-free price for American knock-out put options, which is usually more difficult for many other jump-diffusion models.

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Thesis (Ph. D.)--Ohio State University, 2006. / Title from first page of PDF file. Includes bibliographical references (p. 145-151).

A central bank is usually assigned two functions: the control of inflation and the maintenance of a safetybanking sector. What are the precise conditions under which trigger strategies from the private sector can solve the time inconsistency problem and induce the central bank to choose zero inflation under a nonstationary natural rate? Can an optimal contract be used together with reputation forces to implement a desired socially optimal monetary policy rule? How to design a truthtelling contract to control the risk taking behaviors of the bank? My dissertation attempts to deal with these issues using three primary methodologies: monetary economics, game theory and optimal stochastic control theory.

Optimal stopping and mathematical finance are intimately connected since the value of an American option is given as the solution to an optimal stopping problem. Such a problem can be viewed as a game in which we are trying to maximize an expected reward. The solution involves finding the best possible strategy, or equivalently, an optimal stopping time for the game. Moreover, the reward corresponding to this optimal time should be determined. It is also of interest to know how the solution depends on the model parameters. For example, when pricing and hedging an American option, the volatility needs to be estimated and it is of great practical importance to know how the price and hedging portfolio are affected by a possible misspecification. The first paper of this thesis investigates the performance of the delta hedging strategy for a class of American options with non-convex payoffs. It turns out that an option writer who overestimates the volatility will obtain a superhedge for the option when using the misspecified hedging portfolio. In the second paper we consider the valuation of a so-called stock loan when the lender is allowed to issue a margin call. We show that the price of such an instrument is equivalent to that of an American down-and-out barrier option with a rebate. The value of this option is determined explicitly together with the optimal repayment strategy of the stock loan. The third paper considers the problem of how to optimally stop a Brownian bridge. A finite horizon optimal stopping problem like this can rarely be solved explicitly. However, one expects the value function and the optimal stopping boundary to satisfy a time-dependent free boundary problem. By assuming a special form of the boundary, we are able to transform this problem into one which does not depend on time and solving this we obtain candidates for the value function and the boundary. Using stochastic calculus we then verify that these indeed satisfy our original problem. In the fourth paper we consider an investor wanting to take advantage of a mispricing in the market by purchasing a bull spread, which is liquidated in case of a market downturn. We show that this can be formulated as an optimal stopping problem which we then, using similar techniques as in the third paper, solve explicitly. In the fifth and final paper we study convexity preservation of option prices in a model with jumps. This is done by finding a sufficient condition for the no-crossing property to hold in a jump-diffusion setting.

We provide contributions to two classical areas of queueing. The first part of this thesis focuses on finding new conditions for a Markov chain on a general state space to be Harris recurrent, positive Harris recurrent or geometrically ergodic. Most of our results show that establishing each property listed above is equivalent to finding a good enough feasible solution to a particular optimal stopping problem, and they provide a more complete understanding of the role Foster's criterion plays in the theory of Markov chains. The second and third parts of the thesis involve analyzing queues from a transient, or time-dependent perspective. In part two, we are interested in looking at a queueing system from the perspective of a customer that arrives at a fixed time t. Doing this requires us to use tools from Palm theory. From an intuitive standpoint, Palm probabilities provide us with a way of computing probabilities of events, while conditioning on sets of measure zero. Many studies exist in the literature that deal with Palm probabilities for stationary systems, but very few treat the non-stationary case. As an application of our main results, we show that many classical results from queueing (in particular ASTA and Little's law) can be generalized to a time-dependent setting. In part three, we establish a continuity result for what we refer to as jump processes. From a queueing perspective, we basically show that if the primitives and the initial conditions of a sequence of queueing processes converge weakly, then the corresponding queue-length processes converge weakly as well in some sense. Here the notion of convergence used depends on properties of the limiting process, therefore our results generalize classical continuity results that exist in the literature. The way our results can be used to approximate queueing systems is analogous to the way phase-type random variables can be used to approximate other types of random variables.

We propose a dynamic programming (DP) approach for pricing American options over a finite time horizon. We model uncertainty in stock price that follows geometric Brownian motion (GBM) and let interest rate and volatility be fixed. A procedure based on dynamic programming combined with piecewise linear interpolation approximation is developed to price the value of options. And we introduce the free boundary problem into our model. Numerical experiments illustrate the relation between value of option and volatility.