A presente dissertação de conclusão de mestrado tem por objetivo contribuir com a literatura existente que versa acerca da estimação da Taxa de Câmbio Real (RER) através de fundamentos econômicos. O objetivo deste trabalho é utilizar o instrumental teórico de modelos com mudança de regime (Markov Switching) aplicado sobre os fundamentos que determinam a RER em um modelo de Cointegração. O modelo teórico utilizado para a estimação foi o proposto por Montiel (1999), modelo este que é mais indicado para países em desenvolvimento, para o período de 1994 até 2005. Os resultados obtidos na estimação da Taxa de Câmbio Real foram contundentes em demonstrar que havia três regimes distintos (definidos como sendo regimes de estabilidade, transição e risco extremo) na determinação da RER, indicando que havia uma relação não linear entre está última e os fundamentos econômicos. Verificou-se ainda que a magnitude e os sinais dos parâmetros dos fundamentos estimados para cada regime distinto eram diferentes, sugerindo que a RER reagia de maneira distinta a choques nos fundamentos econômicos de acordo com o regime que a economia se encontrava. Os coeficientes obtidos nas estimações foram utilizados para estimar uma Taxa de Câmbio de Equilíbrio, sendo possível identificar os desvios (misalignments) da taxa observa com relação à taxa estimada a parti r de 1994. / The present dissertation aims to contribute with the studies over Real Exchange Rate in Brazil and the impact of the economic fundamentals on its determination. The main purpose of the dissertation is to use the Markov Switching framework over the fundamentals in the estimation of the Real exchange Rate to the period between 1994 and 2005, using a model based on Montiel (1999), which is more appropriate to developing countries. The results show strong evidences that there are different regimes (interpreted as stability, transition and extremely risk), which can be understood as a non linear relationship between the Real Exchange Rate and the fundamentals. In other words, it was possible to show that the impact of the fundamentals over the Real Exchange Rate is submitted to three different regimes, where the magnitude and signal of their coefficients are different in each regime. The parameters of the model were used to estimate an Equilibrium Real Exchange Rate, which was possible to demonstrate the misalignments after 1994.

The valuation of weather derivatives is greatly dependent on accurate modeling and forecasting of the underlying temperature indices. The complexity and uncertainty in such modeling has led to several temperature processes being developed for the Monte Carlo simulation of daily average temperatures. In this report, we aim to compare the results of two recently developed models by Gyamerah et al. (2018) and Evarest, Berntsson, Singull, and Yang (2018). The paper gives a thorough introduction to option theory, Lévy and Wiener processes, and generalized hyperbolic distributions frequently used in temperature modeling. Implementations of maximum likelihood estimation and the expectation-maximization algorithm with Kim's smoothed transition probabilities are used to fit the Lévy process distributions and both models' parameters, respectively. Later, the use of both models is considered for the pricing of European HDD and CDD options by Monte Carlo simulation. The evaluation shows a tendency toward the shifted temperature regime over the base regime, in contrast to the two articles, when evaluated for three data sets. Simulation is successfully demonstrated for the model of Evarest, however Gyamerah's model was unable to be replicated. This is concluded to be due to the two articles containing several incorrect derivations, why the thesis is left unanswered and the articles' conclusions are questioned. We end by proposing further validation of the two models and summarize the alterations required for a correct implementation.

Cette thèse présente trois essais qui fournissent un aperçu global de la manière dont les chocs au niveau du marché immobilier affectent l'économie et vice versa.Dans le premier essai, nous utilisons des modèles de Markov à changement de régimes avec des probabilités qui dépendent du temps et des probabilités fixes afin d'évaluer l'ampleur des mécanismes de transmission entre le marché de placements immobiliers, le marché du logement et le marché boursier au Royaume-Uni et aux États-Unis. Nous montrons que la relation entre les marchés immobiliers et les marchés des actions est plus significative quand les marchés immobiliers sont considérés comme des variables explicatives.Dans le deuxième essai, nous introduisons le marché d'immobilier commercial afin d'identifier les interactions entre différents marchés immobiliers et certaines variables macroéconomiques. Nous utilisons une fonction de cohérence dynamique dans un cadre d'analyse spectrale pour évaluer ces liens. Les résultats montrent une tendance commune à long terme des différents marchés immobiliers. Aux États-Unis, les canaux de transmissions: richesse et dépenses de logement sont très conducteurs en cas de crise immobilière. Cependant, au Royaume-Uni, seulement le canal de la richesse s'avère conducteur dans les périodes de ralentissement du marché immobilier. Le troisième essai développe un cadre pour modéliser le marché de logement français. Nous élaborons et estimons un modèle de recherche d'équilibre du marché du logement segmenté entre locataires et propriétaires se caractérisant par une hétérogénéité des besoins de logement. Notre modèle reproduit l'évolution des prix de l'immobilier sur le marché français de 1996 à 2006, ainsi que la corrélation entre le prix, l'âge et la durée. En outre, nous montrons que l'inadéquation des individus avec leur logement est fortement corrélée avec le cycle de vie, et que l'agrégation de ces événements peut empêcher l'équilibre du marché à long terme. / This thesis contains three essays on the linkages between real estate and the wider economy. We provide a global snapshot of how shocks in the real estate market affect the economy and vice versa. In the first essay, we use Markov Switching models with time varying transition probabilities and fixed time transition probabilities in order to assess the magnitude of the transmission mechanisms between real estate markets and stock markets in the UK and the US. The results show a more significant credit price effect than a wealth effect. In addition, the different features of the linkages between real estate markets and stock markets are explained by the difference in the indices constructions of the housing prices and the REIT models in the two countries.In the second essay, an additional property market is included to further investigate the links of different real estate markets with some key macroeconomic variables. We use a dynamic coherence function in a spectral framework to assess these linkages. We find a common trend that drives all the real estate markets, particularly in the long run. The results show that in the US, wealth and housing expenditure channels are very conductive during real estate crises. However, for the UK, only the wealth is significant as a transmission channel during real estate market downturns. The third essay develops a framework that models the French housing market. We specify and estimate an equilibrium search model of the housing market that features a segmented housing market with heterogeneity in housing need. Our model reproduces almost exactly the evolution of French housing prices from 1996 to 2006, along with the correlation between price, age and duration. In addition we show that individuals mismatch is highly correlated with the life-cycle, and that aggregation of such events can prevent the market from clearing over a long period of time.

Cette thèse de doctorat composée de trois chapitres contribue au développement de la problématique sur la sélection de modèle de volatilité de type GARCH. Le premier chapitre propose une étude de simulation sur la sélection de modèles dans le cadre spécifique des modèles à changement de régimes. On propose des expériences de simulation permettant de mettre en évidence l'inefficacité des critères de sélection usuels dans des cas particuliers, ce qui peut conduire à des erreurs de spécification lors du choix de modèle. Le deuxième chapitre propose un test du multiplicateur de Lagrange de mauvaise spécification dans les modèles GARCH univariés. L'hypothèse nulle admet que le processus générateur des données est un modèle GARCH linéaire tandis que sous l'hypothèse alternative il correspond à une forme fonctionnelle inconnue qui est linéarisée à l’aide d’un développement de Taylor. On illustre le test dans une application empirique sur les taux de change. Le dernier chapitre étudie l'impact du prix du pétrole sur les spreads de Credit Default Swaps souverains de deux pays exportateurs de pétrole: le Vénézuela et la Russie. Utilisant des données récentes, nous trouvons que les rendements du prix du pétrole impactent les spread de CDS souverains du Vénézuela directement alors que cela passe par le canal du taux de change pour la Russie. Ce chapitre emploie des méthodes statistiques avancées, notamment l'utilisation de modèles à changement de régimes Markoviens. Finalement, l'appendice propose le manuel de la toolbox MSGtool (Matlab) qui propose une collection de fonctions pour l'étude des modèles à changement de régimes Markoviens. La toolbox est très user-friendly. / This Ph.D. thesis composed by three chapters contributes to the development of model selection in GARCH-type models.The first chapter investigates whether the most common selection criteria lead to choose the right specification in a regime switching framework. We propose simulation experiments which reveal the inefficiency of some selection criteria in particular cases which lead to misspecification. Depending on the Data Generating Process used in the experiments, great care is needed when choosing a criterion.In the second chapter, a misspecication test for GARCH-type models is presented. We propose a Lagrange Multiplier type test based on a Taylor expansion to distinguish between (G)ARCH models and unknown nonlinear GARCH-type models. This test can be seen as a general misspecication test. We investigate the size and the power of this test through Monte Carlo experiments. We show the usefulness of our test with an illustrative empirical example based on daily exchange rate returns.In the third chapter, we study the impact of oil price returns on sovereign Credit Default Swaps (CDS) spreads for two major oil producers, Russia and Venezuela. Using daily spreads from 2008 to 2015, we find that crude oil price returns are a critical determinant of Venezuela CDS spreads changes, but does not explain significantly Russian CDS spreads. Indeed, oil prices seem to impact Russian CDS spreads through the exchange rates canal. Finally, we propose as an appendix the manual of the MSGtool, a MATLAB toolbox, which provides a collection of functions for the simulation and estimation of a large variety of Markov Switching GARCH (MSG) models.