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This doctoral thesis is a collection of four papers on the analysis of the term structure of interest rates with a focus at the intersection of macroeconomics and finance. "Risk in Macroeconomic Fundamentals and Bond Return Predictability" documents that factors related to risks underlying the macroeconomy such as expectations, uncertainty and downside (upside) macroeconomic risks are able to explain variation in bond risk premia. The information provided is found to be, to a large extent, unrelated to that contained in forward rates and current macroeconomic conditions. "Out-of-sample bond excess returns predictability" provides evidence that macroeconomic variables, risks in macroeconomic outcomes as well as the combination of these different sources of information are able to generate statistical as well as economic bond excess returns predictability in an out-of-sample setting. Results suggest that this finding is not driven by revisions in macroeconomic data. The term spread (yield curve slope) is largely used as an indicator of future economic activity. "Re-examining the predictive power of the yield curve with quantile regression" provides new evidence on the predictive ability of the term spread by studying the whole conditional distribution of GDP growth. "Modeling and forecasting the yield curve by extended Nelson-Siegel class of models: a quantile regression approach" deals with yield curve prediction. More flexible Nelson-Siegel models are found to provide better fitting to the data, even when penalizing for additional model complexity. For the forecasting exercise, quantile-based models are found to overcome all competitors. / <p>Diss. Stockholm :  Stockholm School of Economics, 2014. Introduction together with 4 papers.</p>

The aim of this thesis is to model the dynamics of international term structure of interest rates taking into consideration several dependence channels.Thanks to a new international Treasury yield curve database, we observe that the explained variability decision criterion, suggested by the literature, is not able to select the best combination of factors characterizing the joint dynamics of yield curves. We propose a new methodology based on the maximisation of the likelihood function of a Gaussian state-space model with common and local factors. The associated identification problem is solved in an innovative way. By estimating several sets of countries, we select two global (and three local) factors which are also useful to forecast macroeconomic variables in each considered economy.In addition, our method allows us to detect hidden factors in the international bond returns. They are not visible through a classical principal component analysis of expected bond returns but they are helpful to forecast inflation and industrial production. Keywords: International treasury yield curves, common and local factors, state-space models, EM algorithm, International bond risk premia, principal components.

Cette thèse concerne la modélisation de la dynamique des courbes des taux internationales avec prise en compte de plusieurs canaux de dépendance. A l’aide d’une nouvelle base de données des taux souverains internationaux, nous observons que le critère de la variabilité expliquée, proposé par la littérature, n’est pas capable de sélectionner une meilleure combinaison des facteurs décrivant la dynamique jointe des courbes des taux. Nous proposons une méthode nouvelle de section des facteurs fondée sur la maximisation de vraisemblance d’un modèle espace-état linéaire gaussien avec facteurs communs et locaux. Le problème d’identification associée est résolu d’une façon novatrice. En estimant différents combinaisons de pays, nous sélectionnons des deux facteurs globaux et trois locaux ayant un pouvoir prédictif des variables macro-économiques (activité économique et taux d’inflation) dans chaque économie considérée. Notre méthode nous permet aussi de détecter des facteurs cachés dans les rendements obligataires. Ils ne sont pas visibles à travers une analyse classique en composant principales des rendements obligataires et ils contribuent à la prévision du taux d’inflation et du taux de croissance de la production industrielle. / The aim of this thesis is to model the dynamics of international term structure of interest rates taking into consideration several dependence channels.Thanks to a new international Treasury yield curve database, we observe that the explained variability decision criterion, suggested by the literature, is not able to select the best combination of factors characterizing the joint dynamics of yield curves. We propose a new methodology based on the maximisation of the likelihood function of a Gaussian state-space model with common and local factors. The associated identification problem is solved in an innovative way. By estimating several sets of countries, we select two global (and three local) factors which are also useful to forecast macroeconomic variables in each considered economy.In addition, our method allows us to detect hidden factors in the international bond returns. They are not visible through a classical principal component analysis of expected bond returns but they are helpful to forecast inflation and industrial production. Keywords: International treasury yield curves, common and local factors, state-space models, EM algorithm, International bond risk premia, principal components.