The issue of forecasting the future price of risky financial assets has attracted academia and business practice since the inception of the stock exchange. Also due to the just finished financial crisis, which was the worst crisis since the Great Depression, it is clear that research in this area has not been finished yet. On the contrary, new challenges have been raised. The main goal of the thesis is the demonstration of the significant information potential which is hidden in option market prices. These prices contain informations on probability distribution of the underlying asset returns and the risk connected with these returns. Other objectives of the thesis are the forecast of the underlying asset price distribution using parametric and nonparametric estimates, the improvement of this forecast using the utility function of the representative investor, the description of the current market sentiment and the determination of the risk premium, especially the risk premium on Czech market. The thesis deals with the forecast of the underlying asset price probability distribution implied by the current option market prices using parametric and nonparametric estimates. The resulting distribution is described by the moment characteristics which represent a valuable tool for analyzing the current market sentiment. According to the theory, the probability distribution of the underlying asset price implied by option prices is risk neutral, i.e. it applies only to risk neutral investors. The theory further implies that the distribution of real world can be derived from the risk neutral distribution using utility function of the representative investor. The inclusion of a utility function of representative investor improves the forecast of the underlying asset price distribution. Three different utility functions of traditional risk theory are used in the thesis. These functions range from the simple power function to the general function of hyperbolic absolute risk aversion (HARA). Further, Friedman-Savage utility function is used. This function allows both a risk averse investor and a risk loving investor. The thesis also answers the question: Are the current asset prices at so high level that the purchase of the asset means a gamble? The risk premium associated with investing in the risky asset is derived in the thesis. The risk premium can be understood as the premium demanded by investors for investment in a risky asset against the investment in a riskless asset. All the theoretical methods introduced in the thesis are demonstrated on real data coming from two different markets. Developing market is represented by shares of CEZ and developed market is represented by S&P 500 futures. The thesis deals with demonstrations in single point in time as well as in available history of the data. The forecasts of the underlying asset price distribution and the relating risk premium are constructed in the available data history. The goals and the objectives of the thesis have been achieved. The contribution of the thesis is the development of parametric and nonparametric methodology for estimating the underlying asset price probability distribution implied by the option market prices so that the nature of the particular market and instrument is captured. The further contribution of the thesis is the construction of the forecasts of the underlying asset price distribution and the construction of the market sentiment in the available history of data. The contribution of the thesis is also the construction of the market risk premium in the available history and the establishment of the hypothesis that the markets gamble before the crisis.

Investments in space systems are substantial, indivisible, and irreversible, characteristics that make them high-risk, especially when coupled with an uncertain demand environment. Traditional approaches to system design and acquisition, derived from a performance- or cost-centric mindset, incorporate little information about the spacecraft in relation to its environment and its value to its stakeholders. These traditional approaches, while appropriate in stable environments, are ill-suited for the current, distinctly uncertain and rapidly changing technical, and economic conditions; as such, they have to be revisited and adapted to the present context. This thesis proposes that in uncertain environments, decision-making with respect to space system design and acquisition should be value-based, or at a minimum value-informed. This research advances the value-centric paradigm by providing the theoretical basis, foundational frameworks, and supporting analytical tools for value assessment of priced and unpriced space systems. For priced systems, stochastic models of the market environment and financial models of stakeholder preferences are developed and integrated with a spacecraft-sizing tool to assess the system's net present value. The analytical framework is applied to a case study of a communications satellite, with market, financial, and technical data obtained from the satellite operator, Intelsat. The case study investigates the implications of the value-centric versus the cost-centric design and acquisition choices. Results identify the ways in which value-optimal spacecraft design choices are contingent on both technical and market conditions, and that larger spacecraft for example, which reap economies of scale benefits, as reflected by their decreasing cost-per-transponder, are not always the best (most valuable) choices. Market conditions and technical constraints for which convergence occurs between design choices under a cost-centric and a value-centric approach are identified and discussed. In addition, an innovative approach for characterizing value uncertainty through partial moments, a technique used in finance, is adapted to an engineering context and applied to priced space systems. Partial moments disaggregate uncertainty into upside potential and downside risk, and as such, they provide the decision-maker with additional insights for value-uncertainty management in design and acquisition. For unpriced space systems, this research first posits that their value derives from, and can be assessed through, the value of information they provide. To this effect, a Bayesian framework is created to assess system value in which the system is viewed as an information provider and the stakeholder an information recipient. Information has value to stakeholders as it changes their rational beliefs enabling them to yield higher expected pay-offs. Based on this marginal increase in expected pay-offs, a new metric, Value-of-Design (VoD), is introduced to quantify the unpriced system's value. The Bayesian framework is applied to the case of an Earth Science satellite that provides hurricane information to oil rig operators using nested Monte Carlo modeling and simulation. Probability models of stakeholders' beliefs, and economic models of pay-offs are developed and integrated with a spacecraft payload generation tool. The case study investigates the information value generated by each payload, with results pointing to clusters of payload instruments that yielded higher information value, and minimum information thresholds below which it is difficult to justify the acquisition of the system. In addition, an analytical decision tool, probabilistic Pareto fronts, is developed in the Cost-VoD trade space to provide the decision-maker with additional insights into the coupling of a system's probable value generation and its associated cost risk.

The performance of building envelopes and roofing systems significantly depends on accurate knowledge of wind loads and the response of envelope components under realistic wind conditions. Wind tunnel testing is a well-established practice to determine wind loads on structures. For small structures much larger model scales are needed than for large structures, to maintain modeling accuracy and minimize Reynolds number effects. In these circumstances the ability to obtain a large enough turbulence integral scale is usually compromised by the limited dimensions of the wind tunnel meaning that it is not possible to simulate the low frequency end of the turbulence spectrum. Such flows are called flows with Partial Turbulence Simulation. In this dissertation, the test procedure and scaling requirements for tests in partial turbulence simulation are discussed. A theoretical method is proposed for including the effects of low-frequency turbulences in the post-test analysis. In this theory the turbulence spectrum is divided into two distinct statistical processes, one at high frequencies which can be simulated in the wind tunnel, and one at low frequencies which can be treated in a quasi-steady manner. The joint probability of load resulting from the two processes is derived from which full-scale equivalent peak pressure coefficients can be obtained. The efficacy of the method is proved by comparing predicted data derived from tests on large-scale models of the Silsoe Cube and Texas-Tech University buildings in Wall of Wind facility at Florida International University with the available full-scale data. For multi-layer building envelopes such as rain-screen walls, roof pavers, and vented energy efficient walls not only peak wind loads but also their spatial gradients are important. Wind permeable roof claddings like roof pavers are not well dealt with in many existing building codes and standards. Large-scale experiments were carried out to investigate the wind loading on concrete pavers including wind blow-off tests and pressure measurements. Simplified guidelines were developed for design of loose-laid roof pavers against wind uplift. The guidelines are formatted so that use can be made of the existing information in codes and standards such as ASCE 7-10 on pressure coefficients on components and cladding.

The result of my dissertation justifies the use of fuzzy-sets theory to make a prediction of cost risk of a PPP project, when there is not enough information available to clearly describe the project, and, when the probability distributions of the variables that characterize the project are unknown. I showed that fuzzy-sets theory and linguistic variables may be effectively used in such a case. In this thesis were classified different types of uncertainty and investigated traditional methods for estimating efficiency of a investment project in conditions of uncertainty. On the basis of the analysis were offered new ways of conducting risk analysis for PPP projects with use of fuzzy sets theory. The main goal was to create an application model for risk assessment of the PPP project which, with a high degree of reliability, suggests a general assessment of situation. The goal set in my work was met. Model of risk assessment of the project proposed by me gives more stable results in comparison with the probabilistic model. For comparison were used different types of probability distribution functions and membership functions. The following conclusions and statements describe the novelty of the work on fuzzy logic and economic theory: develops a method of cash-flow (future expenditure connected with the appearance of risk) modeling of investment project in fuzzy environment, demonstrates the use of fuzzy sets theory in projects analyses and describes how to calculate and interpret this value, demonstrates example of the use of results applied to the analysis of infrastructure development project in Moscow, Russia. The possibility of using this method is not only in the analysis of infrastructure development projects, but also in realization of non-commercial projects by social institutes and government agencies.

Dans cette thèse nous développons et améliorons des attaques de systèmes cryptographiques. Un nouvel algorithme de décomposition de signal appelé transformation de Hilbert-Huang a été adapté pour améliorer l’efficacité des attaques parcanaux auxiliaires. Cette technique permet de contrecarrer certaines contre-mesures telles que la permutation d’opérations ou l’ajout de bruit à la consommation de courant. La seconde contribution de ce travail est l’application de certaines distributions statistiques de poids de Hamming à l’attaque d’algorithmes de chiffrement par bloc tels que AES, DES ou LED. Ces distributions sont distinctes pour chaque valeur de sous-clef permettent donc de les utiliser comme modèles intrinsèques. Les poids de Hamming peuvent être découverts par des analyses de canaux auxiliaires sans que les clairs ni les chiffrés ne soient accessibles. Cette thèse montre que certaines contremesures peuvent parfois faciliter des attaques. Les contre-mesures contagieuses proposées pour RSA protègent contre les attaques par faute mais ce faisant et moyennant des calculs additionnels facilitent la découverte de la clef. Finalement, des contre-mesures à faible complexité calculatoire sont proposées. Elles sont basées sur le masquage antagoniste, c’est-à-dire, l’exécution d’une opération d’équilibrage sur des données sensibles pour masquer la consommation de courant. / The goal of the thesis is to develop and improve methods for defeating protected cryptosystems. A new signal decompositionalgorithm, called Hilbert Huang Transform, was adapted to increase the efficiency of side-channel attacks. This technique attempts to overcome hiding countermeasures, such as operation shuffling or the adding of noise to the power consumption. The second contribution of this work is the application of specific Hamming weight distributions of block cipher algorithms, including AES, DES, and LED. These distributions are distinct for each subkey value, thus they serve as intrinsic templates. Hamming weight data can be revealed by side-channel and fault attacks without plaintext and ciphertext. Therefore these distributions can be applied against implementations where plaintext and ciphertext are inaccessible. This thesis shows that some countermeasures serve for attacks. Certain infective RSA countermeasures should protect against single fault injection. However, additional computations facilitate key discovery. Finally, several lightweight countermeasures are proposed. The proposed countermeasures are based on the antagonist masking, which is an operation occurring when targeting data processing, to intelligently mask the overall power consumption.

The diploma thesis describes the bootstrap method and its applications in the estimate accuracy statement, in the confidence intervals generation and in the testing of statistical hypotheses. Further the method of the discrete probability estimation of the categorical quantity is presented, making use the gradient of the quasi-norm hereof distribution. On concrete examples the bootstrap method is applied in the confidence intervals forming of the categorical quantity probability function. The diploma thesis was supported by the project of MŠMT of the Czech Republic no. 1M06047 "Centre for Quality and Reliability of Production", by the grant of Grant Agency of the Czech Republic (Czech Science Foundation) reg. no. 103/08/1658 "Advanced optimum design of composed concrete structures" and by the research plan of MŠMT of the Czech Republic no. MSM0021630519 "Progressive reliable and durable structures".

The diploma thesis describes the bootstrap method and its applications in the confidence intervals generation, in the testing of statistical hypotheses and in the regression analysis. We present the confidence interval for individual value. Further the method of discrete probability estimation of the categorical quantity is presented, making use the gradient and the line estimate.

Es werden verschiedene Stetigkeitskonzepte, die in der statistischen Theorie und Methodik eine Rolle spielen, erläutert.

Generating functions express a sequence as coefficients arising from a power series in variables. They have many applications in combinatorics and probability. In this paper, we will investigate the important properties of four kinds of generating functions in one variables: ordinary generating unction, exponential generating function, probability generating function and moment generating function. Many examples with applications in combinatorics and probability, will be discussed. Finally, some well-known contest problems related to generating functions will be addressed.

Dans le cadre des recherches de la qualité des ressources en eau, l’étude du processus de transfert de masse du sol vers la nappe phréatique constitue un élément primordial pour la compréhension de la pollution de cette dernière. En effet, les éléments polluants solubles à la surface (produits liés aux activités humaines tels engrais, pesticides...) peuvent transiter vers la nappe à travers le milieu poreux qu’est le sol. Ce scénario de transfert de pollution repose sur deux phénomènes : la pluie qui génère la masse d’eau à la surface et la dispersion de celle-ci à travers le milieu poreux. La dispersion de masse dans un milieu poreux naturel comme le sol forme un sujet de recherche vaste et difficile aussi bien au plan expérimental que théorique. Sa modélisation constitue une préoccupation du laboratoire EMMAH, en particulier dans le cadre du projet Sol Virtuel dans lequel un modèle de transfert (modèle PASTIS) a été développé. Le couplage de ce modèle de transfert avec en entrée un modèle décrivant la dynamique aléatoire de la pluie est un des objectifs de la présente thèse. Ce travail de thèse aborde cet objectif en s’appuyant d’une part sur des résultats d’observations expérimentaux et d’autre part sur de la modélisation inspirée par l’analyse des données d’observation. La première partie du travail est consacrée à l’élaboration d’un modèle stochastique de pluie. Le choix et la nature du modèle sont basés sur les caractéristiques obtenus à partir de l’analyse de données de hauteur de pluie recueillies sur 40 ans (1968-2008) sur le Centre de Recherche de l’INRA d’Avignon. Pour cela, la représentation cumulée des précipitations sera assimilée à une marche aléatoire dans laquelle les sauts et les temps d’attente entre les sauts sont respectivement les amplitudes et les durées aléatoires entre deux occurrences d’événements de pluie. Ainsi, la loi de probabilité des sauts (loi log-normale) et celle des temps d’attente entre les sauts (loi alpha-stable) sont obtenus en analysant les lois de probabilité des amplitudes et des occurrences des événements de pluie. Nous montrons alors que ce modèle de marche aléatoire tend vers un mouvement brownien géométrique subordonné en temps (quand les pas d’espace et de temps de la marche tendent simultanément vers zéro tout en gardant un rapport constant) dont la loi de densité de probabilité est régie par une équation de Fokker Planck fractionnaire (FFPE). Deux approches sont ensuite utilisées pour la mise en œuvre du modèle. La première approche est de type stochastique et repose sur le lien existant entre le processus stochastique issu de l’équation différentielle d’Itô et la FFPE. La deuxième approche utilise une résolution numérique directe par discrétisation de la FFPE. Conformément à l’objectif principal de la thèse, la seconde partie du travail est consacrée à l’analyse de la contribution de la pluie aux fluctuations de la nappe phréatique. Cette analyse est faite sur la base de deux relevés simultanées d’observations de hauteurs de pluie et de la nappe phréatique sur 14 mois (février 2005-mars 2006). Une étude statistique des liens entre les signaux de pluie et de fluctuations de la nappe est menée comme suit : Les données de variations de hauteur de nappe sont analysées et traitées pour isoler les fluctuations cohérentes avec les événements de pluie. Par ailleurs, afin de tenir compte de la dispersion de masse dans le sol, le transport de la masse d’eau pluviale dans le sol sera modélisé par un code de calcul de transfert (modèle PASTIS) auquel nous appliquons en entrée les données de hauteurs de pluie mesurées. Les résultats du modèle permettent entre autre d’estimer l’état hydrique du sol à une profondeur donnée (ici fixée à 1.6m). Une étude de la corrélation entre cet état hydrique et les fluctuations de la nappe sera ensuite effectuée en complément à celle décrite ci-dessus pour illustrer la possibilité de modéliser l’impact de la pluie sur les fluctuations de la nappe / Within the research quality of water resources, the study of the process of mass transfer from soil to groundwater is a key element for understanding the pollution of the latter. Indeed, soluble contaminants to the surface (related to human activities such fertilizers, pesticides products ...) can transit to the web through the porous medium that is the ground. This scenario transfer pollution based on two phenomena: the rain that generates the body of water to the dispersion and the surface thereof through the porous medium. The dispersion of mass in a natural porous medium such as soil forms a subject of extensive research and difficult both experimental and theoretical grounds. Its modeling is a concern EMMAH laboratory, particularly in the context of Virtual Sol project in which a transfer model (PASTIS model) was developed. The coupling of this transfer model with input a model describing the dynamics of random rain is one of the objectives of this thesis. This thesis addresses this goal by relying in part on the results of experimental observations and also on modeling inspired by the analysis of observational data. The first part of the work is devoted to the development of a stochastic model of rain. The choice and nature of the model are based on the features obtained from the analysis of data collected rainfall over 40 years (1968-2008) on the Research Centre INRA Avignon. For this, the cumulative rainfall representation will be treated as a random walk in which the jumps and waiting times between jumps are the amplitudes and durations between two random occurrences of rain events. Thus, the probability jumps (log-normal distribution) and that of waiting between jumps (Law alpha-stable) time is obtained by analyzing the laws of probability amplitudes and occurrences of rain events. We show that the random walk model tends towards a subordinate in time geometric Brownian motion (when space step and time step walking simultaneously tend to zero while maintaining a constant ratio), the law of probability density is governed by a Fokker Planck fractional (FFPE). Two approaches are then used to implement the model. The first approach is based on stochastic type and the relationship between the stochastic process derived from the differential equation of Itô and FFPE. The second approach uses a direct numerical solution by discretization of the FFPE. Accordance with the main objective of the thesis, the second part of the work is devoted to the analysis of the contribution of rain to fluctuations in groundwater. We approach this analysis on the basis of two simultaneous records of observations of rainfall amounts and groundwater over 14 months (February 2005-March 2006). A statistical study of the relationship between the signals of rain and fluctuating water will be conducted. Data sheet height variations are analyzed and processed to isolate coherent fluctuations with rain events. In addition, to take account of the mass dispersion in the soil, the mass transport of storm water in the soil layer is modeled by a calculation code transfer (PASTIS model) which we apply input data measured heights of rain. The model results allow between another estimate soil water status at a given depth (here set at 1.6m). A study of the correlation between the water status and fluctuating water will then be performed in addition to that described above to illustrate the ability to model the impact of rain on the water table fluctuations