In this thesis we present the Laplace transform method of option pricing and it's realization, also compare it with another methods. We consider vanilla and exotic options, but more attention we pay to the two-asset correlation options. We chose the one of the modifications of Black-Scholes model, the Kou double exponential jump-diffusion model with the double exponential distribution of jumps, as model of the underlying stock prices development. The computations was done by the Laplace transform and it's inversion by the Euler method. We will present in details proof of finding Laplace transforms of put and call two-asset correlation options, the calculations of the moment generation function of the jump-diffusion by Levy-Khintchine formulae in cases without jumps and with independent jumps, and direct calculation of the risk-neutral expectation by solving double integral. Our work also contains the programme code for two-asset correlation call and put options. We will show the realization of our programme in the real data. As a result we see how our model complies on the NASDAQ OMX Stock-holm Market, considering the two-asset correlation options on three cases by stock prices of Handelsbanken, Ericsson and index OMXS30.

Le travail présenté dans cette thèse est consacré à la modélisation de la dynamique de locomotion des "soft robots", i.e. les systèmes multi-corps mobiles compliants. Ces compliances peuvent être localisées et considérées comme des liaisons passives du système,ou bien introduites par des flexibilités distribuées le long des corps. La dynamique de ces systèmes est modélisée en adoptant une approche Lagrangienne basée sur les outils mathématiques développés par l’école américaine de mécanique géométrique. Du point de vue algorithmique, le calcul de ces modèles dynamiques s’appuie sur un algorithme récursif et efficace de type Newton-Euler, ici étendu aux robots locomoteurs munis d’organes compliants. Poursuivant des objectifs de commande et de simulation rapide pour la robotique, l’algorithme proposé est capable de résoudre la dynamique externe directe ainsi que la dynamique inverse des couples internes. Afin de mettre en pratique l’ensemble de ces outils de modélisation, nous avons pris le vol battant des insectes comme exemple illustratif. Les équations non-linéaires qui régissent les déformations passives de l’aile sont établies en appliquant deux méthodes différentes. La première consiste à séparer le mouvement de l’aile en une composante rigide dite de "repère flottant" et une composante de déformation. Cette dernière est paramétrée dans le repère flottant par la méthode des modes supposés ici appliquée à l’aile vue comme une poutre d’Euler-Bernoulli soumise à la flexion et à la torsion. Quant à la seconde approche, les mouvements de l’aile n’y sont pas séparés mais directement paramétrés par les transformations finies rigides et absolues d’une poutre Cosserat. Cette approche est dite Galiléenne ou "géométriquement exacte" en raison du fait qu’elle ne requiert aucune approximation en dehors des inévitables discrétisations spatiale et temporelle imposées parla résolution numérique de la dynamique du vol. Dans les deux cas,les forces aérodynamiques sont prises en compte via un modèle analytique simplifié de type Dickinson. Les modèles et algorithmes résultants sont appliqués à la conception d’un simulateur du vol, ainsi qu’à la conception d’un prototype d’aile, dans le contexte du projet coopératif (ANR) EVA. / The objective of the present work is to model the locomotion dynamics of "soft robots", i.e. compliant mobile multi-body systems. These compliances can be either localized and treated as passive joints of the system, or introduced by distributed flexibilities along the bodies. The dynamics of these systems is modeled in a Lagrangian approach based on the mathematical tools developed by the American school of geometric mechanics. From the algorithmic viewpoint, the computation of these dynamic models is based on a recursive and efficient Newton-Euler algorithm which is extended here to the case of robots equipped with compliant organs. The proposed algorithm is compatible with control, fast simulation and real time robotic applications. It is able to solve the direct external dynamics as well as the inverse internal torque dynamics. The modeling tools and algorithms developed in this thesis are applied to one of the most advanced cases of compliante locomotion i.e. the flapping flight MAVs bio-inspired by insects. The nonlinear equations governing the passive deformations of the wing are derived using two different methods. In the first method, we separate the wing movement into a rigid component (which corresponds to the movements of a "floating frame"), and a deformation component. The latter one is parameterized in the floating frame using the assumed modes approach where the wing is considered as an Euler-Bernoulli beam undergoing flexion and torsion deformations. Regarding the second method, the wing movements are no longer separated but directly parameterize dusing rigid finite absolute transformations of a Cosserat beam. This method is called Galilean or "geometrically exact" because it does not require any approximation apart from the unavoidable spatial and temporal discretizations imposed by numerical resolution of the flight dynamics. In both cases, the aerodynamic forces are taken into account through a simplified analytical model. The resulting models and algorithms are used in the context of the collaborative project (ANR) EVA to develop a flight simulator, and to design wing prototype.

Several manufacturers of road vehicles today are working on developing autonomous vehicles. One subject that is often up for discussion when it comes to integrating autonomous road vehicles into the infrastructure is the safety aspect. There is in the context no common view of how safety should be quantified. As a contribution to this discussion we propose describing each potential hazardous event of a vehicle as a Semi-Markov Process (SMP). A reliability-based method for using the semi-Markov representation to calculate the probability of a hazardous event to occur is presented. The method simplifies the expression for the reliability using the Laplace-Stieltjes transform and calculates the transform of the reliability exactly. Numerical inversion algorithms are then applied to approximate the reliability up to a desired error tolerance. The method is validated using alternative techniques and is thereafter applied to a system for automated steering based on a real example from the industry. A desired evolution of the method is to involve a framework for how to represent each hazardous event as a SMP. / Flertalet tillverkare av vägfordon jobbar idag på att utveckla autonoma fordon. Ett ämne ofta på agendan i diskussionen om att integrera autonoma fordon på vägarna är säkerhet. Det finns i sammanhanget ingen klar bild över hur säkerhet ska kvantifieras. Som ett bidrag till denna diskussion föreslås här att beskriva varje potentiellt farlig situation av ett fordon som en Semi-Markov process (SMP). En metod presenteras för att via beräkning av funktionssäkerheten nyttja semi-Markov representationen för att beräkna sannolikheten för att en farlig situation ska uppstå. Metoden nyttjar Laplace-Stieltjes transformen för att förenkla uttrycket för funktionssäkerheten och beräknar transformen av funktionssäkerheten exakt. Numeriska algoritmer för den inversa transformen appliceras sedan för att beräkna funktionssäkerheten upp till en viss feltolerans. Metoden valideras genom alternativa tekniker och appliceras sedan på ett system för autonom styrning baserat på ett riktigt exempel från industrin. En fördelaktig utveckling av metoden som presenteras här skulle vara att involvera ett ramverk för hur varje potentiellt farlig situation ska representeras som en SMP.

This thesis considers new methods that exploit recent developments in computer technology to address three extant problems in the area of Finance and Econometrics. The problem of Asian option pricing has endured for the last two decades in spite of many attempts to find a robust solution across all parameter values. All recently proposed methods are shown to fail when computations are conducted using standard machine precision because as more and more accuracy is forced upon the problem, round-off error begins to propagate. Using recent methods from numerical analysis based on multi-precision arithmetic, we show using the Mathematica platform that all extant methods have efficacy when computations use sufficient arithmetic precision. This creates the proper framework to compare and contrast the methods based on criteria such as computational speed for a given accuracy. Numerical methods based on a deformation of the Bromwich contour in the Geman-Yor Laplace transform are found to perform best provided the normalized strike price is above a given threshold; otherwise methods based on Euler approximation are preferred. The same methods are applied in two other contexts: the simulation of stable distributions and the computation of unit root densities in Econometrics. The stable densities are all nested in a general function called a Fox H function. The same computational difficulties as above apply when using only double-precision arithmetic but are again solved using higher arithmetic precision. We also consider simulating the densities of infinitely divisible distributions associated with hyperbolic functions. Finally, our methods are applied to unit root densities. Focusing on the two fundamental densities, we show our methods perform favorably against the extant methods of Monte Carlo simulation, the Imhof algorithm and some analytical expressions derived principally by Abadir. Using Mathematica, the main two-dimensional Laplace transform in this context is reduced to a one-dimensional problem.