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The dissertation consists of three self-contained essays, with a focus on empirical capital market research. The first essay "Time-Varying Conditional Market Returns: Is Variance or Tail-Risk Priced", empirically investigates the question whether there is a positive relationship between aggregate market tail risk and expected returns. Based on the classical risk return trade-off, intuition suggests a statistically positive relationship between aggregate market tail risk and expected returns. The paper contributes to previous literature in several ways. First it offers an statistically well founded method for aggregate tail risk estimation in relying on EVT. In the second place it empirically determines a positive relationship between lagged aggregate market tail risk and market returns, based on a time-series approach, which can be further characterized by a non-linear dependence structure. The second essay "Credit Cycle Dependent Spread Determinants in Emerging Sovereign Debt Markets", empirically estimates non-linear dependence structures of determinants of changes in sovereign bond spreads. Empirical results of the paper clearly identify a non-linear influence of determinants of changes in emerging markets sovereign credit spreads. The statistical and economical significance as well as the sign of some determinants changes with respect to the underlying sovereign credit cycle. The third paper "Modeling the Dependence Structure between Aggregate Market Tail Risk and Expected Returns" takes on the results of the first paper regarding the non-linear positive dependence structure between aggregate market tail risk and expected returns. In order to implement a more profound analysis of the non-linear pattern, the paper employs several copula functions to model the conditional bivariate time series dependence structure. The inspection of the empirical results clearly indicates the Clayton copula function to provide the best formula describing the conditional dependence structure. |
