A num¡¦eraire is the unit of account in which other assets are denominated. One usually takes the num¡¦eraire to be the currency of a country. In some applications one must change the num¡¦eraire due to the finance considerations. And sometimes it is convenient to change the num¡¦eraire because of modeling considerations. A model can be complicated or simple, depending on the choice of thenum¡¦eraire for the method. When change the num¡¦eraire, denominating the asset in some other unit of account, it is no longer a martingale under ˜P . When we change the num¡¦eraire, we need to also change the risk-neutral measure in order to maintain risk neutrality. The details and some applications of this idea developed in this thesis.

>Magister Scientiae - MSc / We present various methods of pricing Asian options. The methods include Monte Carlo simulations designed using control and antithetic variates, numerical solution of partial differential equation and using lower bounds.The price of the Asian option is known to be a certain risk-neutral expectation. Using the Feynman-Kac theorem, we deduce that the problem of determining the expectation implies solving a linear parabolic partial differential equation. This partial differential equation does not admit explicit solutions due to the fact that the distribution of a sum of lognormal variables is not explicit. We then solve the partial differential equation numerically using finite difference and Monte Carlo methods.Our Monte Carlo approach is based on the pseudo random numbers and not deterministic sequence of numbers on which Quasi-Monte Carlo methods are designed. To make the Monte Carlo method more effective, two variance reduction techniques are discussed.Under the finite difference method, we consider explicit and the Crank-Nicholson’s schemes. We demonstrate that the explicit method gives rise to extraneous solutions because the stability conditions are difficult to satisfy. On the other hand, the Crank-Nicholson method is unconditionally stable and provides correct solutions. Finally, we apply the pricing methods to a similar problem of determining the price of a European-style arithmetic basket option under the Black-Scholes framework. We find the optimal lower bound, calculate it numerically and compare this with those obtained by the Monte Carlo and Moment Matching methods.Our presentation here includes some of the most recent advances on Asian options, and we contribute in particular by adding detail to the proofs and explanations. We also contribute some novel numerical methods. Most significantly, we include an original contribution on the use of very sharp lower bounds towards pricing European basket options.

Les caractéristiques des rayonnements solaires dépendent fortement de certains événements météorologiques non observés comme fréquence, taille et type des nuages et leurs propriétés optiques (aérosols atmosphériques, al- bédo du sol, vapeur d’eau, poussière et turbidité atmosphérique) tandis qu’une séquence du rayonnement solaire peut être observée et mesurée à une station donnée. Ceci nous a suggéré de modéliser les processus de rayonnement solaire (ou d’indice de clarté) en utilisant un modèle Markovien caché (HMM), paire corrélée de processus stochastiques. Notre modèle principal est un HMM à temps continu (Xt, yt)t_0 est tel que (yt), le processus observé de rayonnement, soit une solution de l’équation différentielle stochastique (EDS) : dyt = [g(Xt)It − yt]dt + _(Xt)ytdWt, où It est le rayonnement extraterrestre à l’instant t, (Wt) est un mouvement Brownien standard et g(Xt), _(Xt) sont des fonctions de la chaîne de Markov non observée (Xt) modélisant la dynamique des régimes environnementaux. Pour ajuster nos modèles aux données réelles observées, les procédures d’estimation utilisent l’algorithme EM et la méthode du changement de mesures par le théorème de Girsanov. Des équations de filtrage sont établies et les équations à temps continu sont approchées par des versions robustes. Les modèles ajustés sont appliqués à des fins de comparaison et classification de distributions et de prédiction. / Characteristics of solar radiation highly depend on some unobserved meteorological events such as frequency, height and type of the clouds and their optical properties (atmospheric aerosols, ground albedo, water vapor, dust and atmospheric turbidity) while a sequence of solar radiation can be observed and measured at a given station. This has suggested us to model solar radiation (or clearness index) processes using a hidden Markov model (HMM), a pair of correlated stochastic processes. Our main model is a continuous-time HMM (Xt, yt)t_0 is such that the solar radiation process (yt)t_0 is a solution of the stochastic differential equation (SDE) : dyt = [g(Xt)It − yt]dt + _(Xt)ytdWt, where It is the extraterrestrial radiation received at time t, (Wt) is a standard Brownian motion and g(Xt), _(Xt) are functions of the unobserved Markov chain (Xt) modelling environmental regimes. To fit our models to observed real data, the estimation procedures combine the Expectation Maximization (EM) algorithm and the measure change method due to Girsanov theorem. Filtering equations are derived and continuous-time equations are approximated by robust versions. The models are applied to pdf comparison and classification and prediction purposes.

Stochastic partial differential equations have proven useful in many applied areas of mathematics, such as physics or mathematical finance. A major part of such equations consists of linear equations with additive noise. In certain cases, however, the drift part of the differential equation additionally contains a possibly problematic non-linear term, which makes it unsolvable by the standard methods and even a solution in the mild sense may be out of reach. In such situations, we may still find a solution in the weak sense by employing a suitable transformation of the probability space. This thesis deals with semilinear stochastic evolution equations in a separable Hilbert space, where the driving process is an element of a large class of processes - so called Volterra processes, which can be understood as a generalisation of the Wiener process and may be of use to model a wide range of phenomena. The weak solutions, however, have been studied so far only for equations with the cylindrical fractional Brownian motion as the driving process. In this thesis, we introduce a generalisation of the Girsanov theorem for cylindrical Gaussian Volterra processes and give, in full generality, sufficient conditions for the existence of a weak solution and the uniqueness of the equation in law. Further, we introduce...