Unmanned Aerial Vehicles (UAVs) equipped with lightweight, inexpensive cameras have grown in popularity by enabling new uses of UAV technology. However, the video retrieved from small UAVs is often unwatchable due to high frequency jitter. Beginning with an investigation of previous stabilization work, this thesis discusses the challenges of stabilizing UAV based video. It then presents a software based computer vision framework and discusses its use to develop a real-time stabilization solution. A novel approach of estimating intended video motion is then presented. Next, the thesis proceeds to extend previous target localization work by allowing the operator to easily identify targets—rather than relying solely on color segmentation—to improve reliability and applicability in real world scenarios. The resulting approach creates a low cost and easy to use solution for aerial video display and target localization.

[pt] Entender a formação da estrutura a termo da taxa de juros é de suma importância para a autoridade monetária e demais agentes do mercado. No presente trabalho, replicamos o modelo proposto por Adrian, Crump e Moench (2013) para decompor a curva de juros brasileira e criar séries históricas para as expectativas das taxas de juros futuras, e para os prêmios de risco variantes no tempo. Este modelo gaussiano afim de 5 fatores latentes estima a curva de juros brasileira a partir de um método por mínimos quadrados ordinários em três etapas e obtém a precificação neutra ao risco. Por fim, apesar de a literatura empírica de macroeconomia e finanças reconhecer as limitações dos modelos gaussianos afins, nossas previsões fora da amostra apresentaram resultados ligeiramente superiores ao modelo de random walk. / [en] Understanding the term structure of interest rate has an important role as a tool for the monetary authority and other market players. In the present work, we replicate the model proposed by Adrian, Crump and Moench (2013) to decompose the Brazilian yield curve and create historical series for expectations of future interest rates, and for time-varying risk premiums. This five-factor Gaussian model estimates the Brazilian yield curve using a three-step ordinary least squares method and obtains riskneutral pricing. Finally, although the empirical macroeconomics and finance literature recognizes the limitations of Affine models, our out-of-sample estimations showed results slightly superior to the random walk model.

Actuellement la nécessité des systèmes d’alimentation d’énergie, capables d’assurer un fonctionnement stable dans des domaines de fonctionnement assez larges avec des bonnes performances dynamiques (rapidité du système, variations limitées de la tension de sortie en réponse aux perturbations de charge ou de tension d’alimentation), devient de plus en plus importante. De ce fait, cette thèse est orientée sur la commande des convertisseurs de puissance DC-DC représentés par des modèles hybrides.En tenant compte de la structure variable de ces systèmes à commutation, un modèle hybride permet de décrire plus précisément le comportement dynamique d’un convertisseur dans son domaine de fonctionnement. Dans cette optique, l’approximation PWA est utilisée afin de modéliser les convertisseurs DC-DC. A partir des modèles hybrides développés, on s’est intéressé à la stabilisation des convertisseurs au moyen des correcteurs à gains commutés élaborés sur la base de fonctions de Lyapunov PWQ, et à l’implantation d’une commande prédictive explicite, en considérant des contraintes sur l’entrée de commande. La méthode de modélisation et les stratégies de commande proposées ont été appliquées sur deux topologies : un convertisseur buck, afin de mieux maîtriser le réglage des correcteurs et un convertisseur flyback avec filtre d’entrée. Cette dernière topologie nous a permis de répondre aux difficultés du point de vue de la commande (comportement à déphasage non-minimal) rencontrées dans la majorité des convertisseurs DC-DC. Les performances des commandes élaborées ont été validées en simulation sur les topologies considérées et expérimentalement sur une maquette du convertisseur buck. / Lately, power supply systems, guaranteeing the global stability for large enough operation ranges with good dynamic performances (small settling time, bounded overshoot of the output voltage in the presence of load or supply voltage variations), are strongly needed. Therefore, this thesis deals with control problems of DC-DC power converters represented by hybrid models.Considering the variable structure of these switched systems, a hybrid model describes more precisely the converter’s dynamics in its operating domain. From this perspective, a PWA (piecewise affine) approximation is used in order to model the DC-DC converters. Based on the developed hybrid models, first we have designed a stable piecewise linear state-feedback controller using piecewise quadratic (PWQ) Lyapunov functions, and secondly, we have implemented an explicit predictive control law taking into account constraints on the control input. The hybrid modeling technique and the proposed control strategies were applied on two different topologies of converters: a buck converter, in order to have a thorough knowledge of the controllers’ tuning, and a flyback converter with an input filter. This last topology, allowed us to manage different control problems (non-minimum phase behavior) encountered in the majority of topologies of DC-DC power converters. The controllers’ performances were validated in simulation on both considered topologies and also experimentally on buck converter.

En finance, le risque de modèle est le risque de pertes financières résultant de l'utilisation de modèles. Il s'agit d'un risque complexe à appréhender qui recouvre plusieurs situations très différentes, et tout particulièrement le risque d'estimation (on utilise en général dans un modèle un paramètre estimé) et le risque d'erreur de spécification de modèle (qui consiste à utiliser un modèle inadéquat). Cette thèse s'intéresse d'une part à la quantification du risque de modèle dans la construction de courbes de taux ou de crédit et d'autre part à l'étude de la compatibilité des indices de Sobol avec la théorie des ordres stochastiques. Elle est divisée en trois chapitres. Le Chapitre 1 s'intéresse à l'étude du risque de modèle dans la construction de courbes de taux ou de crédit. Nous analysons en particulier l'incertitude associée à la construction de courbes de taux ou de crédit. Dans ce contexte, nous avons obtenus des bornes de non-arbitrage associées à des courbes de taux ou de défaut implicite parfaitement compatibles avec les cotations des produits de référence associés. Dans le Chapitre 2 de la thèse, nous faisons le lien entre l'analyse de sensibilité globale et la théorie des ordres stochastiques. Nous analysons en particulier comment les indices de Sobol se transforment suite à une augmentation de l'incertitude d'un paramètre au sens de l'ordre stochastique dispersif ou excess wealth. Le Chapitre 3 de la thèse s'intéresse à l'indice de contraste quantile. Nous faisons d'une part le lien entre cet indice et la mesure de risque CTE puis nous analysons, d'autre part, dans quelles mesures une augmentation de l'incertitude d'un paramètre au sens de l'ordre stochastique dispersif ou excess wealth entraine une augmentation de l'indice de contraste quantile. Nous proposons enfin une méthode d'estimation de cet indice. Nous montrons, sous des hypothèses adéquates, que l'estimateur que nous proposons est consistant et asymptotiquement normal / In finance, model risk is the risk of loss resulting from using models. It is a complex risk which recover many different situations, and especially estimation risk and risk of model misspecification. This thesis focuses: on model risk inherent in yield and credit curve construction methods and the analysis of the consistency of Sobol indices with respect to stochastic ordering of model parameters. it is divided into three chapters. Chapter 1 focuses on model risk embedded in yield and credit curve construction methods. We analyse in particular the uncertainty associated to the construction of yield curves or credit curves. In this context, we derive arbitrage-free bounds for discount factor and survival probability at the most liquid maturities. In Chapter 2 of this thesis, we quantify the impact of parameter risk through global sensitivity analysis and stochastic orders theory. We analyse in particular how Sobol indices are transformed further to an increase of parameter uncertainty with respect to the dispersive or excess wealth orders. Chapter 3 of the thesis focuses on contrast quantile index. We link this latter with the risk measure CTE and then we analyse on the other side, in which circumstances an increase of a parameter uncertainty in the sense of dispersive or excess wealth orders implies and increase of contrast quantile index. We propose finally an estimation procedure for this index. We prove under some conditions that our estimator is consistent and asymptotically normal

In the first part of this thesis, we introduce a new methodology for stress-test exercises. Our approach allows to consider richer stress-test exercises, which assess the impact of a modification of the whole distribution of asset prices' factors, rather than focusing as the common practices on a single realization of these factors, and take into account the potential reaction to the shock of the portfolio manager. The second part of the thesis is devoted to the pricing of bonds with very long-term time-to-maturity (more than ten years). Modeling the volatility of very long-term rates is a challenge, due to the constraints put by no-arbitrage assumption. As a consequence, most of the no-arbitrage term structure models assume a constant limiting rate (of infinite maturity). The second chapter investigates the compatibility of the so-called "level" factor, whose variations have a uniform impact on the modeled yield curve, with the no-arbitrage assumptions. We introduce in the third chapter a new class of arbitrage-free term structure factor models, which allows the limiting rate to be stochastic, and present its empirical properties on a dataset of US T-Bonds.

Stocks, Bonds, and Long-Run Consumption Risks. Bansal and Yaron (2004) show that long-run consumption risks and time-varying economic uncertainty in conjunction with recursive preferences can account for important features of equity markets. I bring the model to the term structure of interest rates and show that a calibrated version of the model can simultaneously explain properties of bonds and equities. Specifically, the model accounts for deviations from the expectations hypothesis, the upward sloping nominal yield curve, and the predictive power of the nominal yield spread. However, an estimation of the model using Simulated Method of Moments yields less convincing results and illustrates the difficulty of precisely estimating parameters of the model. Real (nominal) interest rates in the model are positively (negatively) correlated with consumption growth and real stock returns move inversely with inflation. The cyclicality of nominal interest rates and yield spreads is shown to depend on the relative values of the elasticity of intertemporal substitution and the correlation between real consumption growth and inflation. The “Fed-model” and the Changing Correlation of Stock and Bond Returns: An Equilibrium Approach. This paper presents an equilibrium model that provides a rational explanation for two features of data that have been considered puzzling: The positive relation between US dividend yields and nominal interest rates, often called the Fed-model, and the time-varying correlation of US stock and bond returns. Key ingredients are time-varying first and second moments of consumption growth, inflation, and dividend growth in conjunction with Epstein-Zin and Weil recursive preferences. Historically in the US, inflation has signaled low future consumption growth. The representative agent therefore dislikes positive inflation shocks and demands a positive risk premium for holding assets that are poor inflation hedges, such as equity and nominal bonds. As a result, risk premiums on equity and nominal bonds comove positively through their exposure to macroeconomic volatility. This generates a positive correlation between dividend yields and nominal yields and between stock and bond returns. High levels of macro volatility in the late 1970s and early 1980s caused stock and bond returns to comove strongly. The subsequent moderation in aggregate economic risk has brought correlations lower. The model is able to produce correlations that can switch sign by including the covariances between consumption growth, inflation, and dividend growth as state variables. International Bond Risk Premia. We extend Cochrane and Piazzesi (2005, CP) to international bond markets by constructing forecasting factors for bond excess returns across different countries. While the international evidence for predictability is weak using Fama and Bliss (1987) regressions, we document that local CP factors have significant predictive power. We also construct a global CP factor and provide evidence that it predicts bond returns with high R2 across countries. The local and global factors are jointly significant when included as regressors, which suggests that variation in bond excess returns are driven by country-specific factors and a common global factor. Shocks to US bond risk premia seem to be particularly important determinants for international bond premia. Motivated by these results, we estimate a parsimonious no-arbitrage affine term structure model in which risk premia are driven by one local and one global CP factor. We find that international bond risk premia are driven by a local slope factor and a world interest rate level factor.

La première partie de cette thèse introduit une nouvelle méthodologie pour la réalisation d’exercices de stress-tests. Notre approche permet de considérer des scénarios de stress beaucoup plus riches qu’en pratique, qui évaluent l’impact d’une modification de la distribution statistique des facteurs influençant les prix d’actifs, pas uniquement les conséquences d’une réalisation particulière de ces facteurs, et prennent en compte la réaction du gestionnaire de portefeuille au choc. La deuxième partie de la thèse est consacrée à la valorisation des obligations à maturité très longues (supérieure à 10 ans). La modélisation de la volatilité des taux de très long terme est un défi, notamment du fait des contraintes posées par l’absence d’opportunités d’arbitrage, et la plupart des modèles de taux d’intérêt en absence d’opportunités d’arbitrage impliquent un taux limite (de maturité infinie) constant. Le deuxième chapitre étudie la compatibilité du facteur "niveau", dont les variations ont un impact uniforme sur l’ensemble des taux modélisés, a fortiori les plus longs, avec l’absence d’opportunités d’arbitrage. Nous introduisons dans le troisième chapitre une nouvelle classe de modèle de taux d’intérêt, sans opportunités d’arbitrage, où le taux limite est stochastique, dont nous présentons les propriétés empiriques sur une base de données de prix d’obligations du Trésor américain. / In the first part of this thesis, we introduce a new methodology for stress-test exercises. Our approach allows to consider richer stress-test exercises, which assess the impact of a modification of the whole distribution of asset prices’ factors, rather than focusing as the common practices on a single realization of these factors, and take into account the potential reaction to the shock of the portfolio manager.
 The second part of the thesis is devoted to the pricing of bonds with very long-term time-to-maturity (more than ten years). Modeling the volatility of very long-term rates is a challenge, due to the constraints put by no-arbitrage assumption. As a consequence, most of the no-arbitrage term structure models assume a constant limiting rate (of infinite maturity). The second chapter investigates the compatibility of the so-called "level" factor, whose variations have a uniform impact on the modeled yield curve, with the no-arbitrage assumptions. We introduce in the third chapter a new class of arbitrage-free term structure factor models, which allows the limiting rate to be stochastic, and present its empirical properties on a dataset of US T-Bonds.