Abstract
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.