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Abstract

This dissertation consists of four research articles that deal with different aspects of the modeling of financial volatility and dynamic correlations. They all focus on the U.S. stock market and its link to macroeconomic fundamentals by applying MIDAS techniques. The contributions of the articles are of theoretical, methodological, and empirical nature. Each chapter is self-contained and can be read independently.

Chapter 1 and 2 consider GARCH-MIDAS component models and the relationship between long-term financial volatility, the variance risk premium, and the stance of the macroeconomy. Chapter 3 presents a new GARCH model that links time-varying volatility persistence to explanatory variables. Finally, Chapter 4 applies the multivariate DCC-MIDAS model to returns on the stock and the oil market and analyzes their relation to macroeconomic fundamentals.