摘要：
This dissertation consists of three chapters. Each chapter analyzes one of the most interesting topics in economics, finance and statistics using modern econometric techniques. Chapter one investigates the dependence structure in international equity markets based on Markov switching model and copula theory. While the former provides us natural and tractable models for processes with switching regimes, the latter can give us flexibility in describing asymmetric interdependence across observations. Combining these two theories, therefore, enables us to model regime switching dependence structure with sufficient flexibility. Using this flexible framework I find there are two regimes: a high dependence regime with low and volatile returns, and a low dependence regime with high and stable returns. I also show that the bear regime is better described by the usage of an asymmetric distribution with lower tail dependence, compared to using a multivariate normal distribution. In addition, I show ignoring this further asymmetry in bear markets could be very costly for risk management. Chapter Two explores extreme quantile estimation using extreme value theory. In particular, I consider the version of Weissman's estimators based on extreme value theory in cases F ∈ D(Λ), or F ∈ D(Λ) with x F = ∞ or F ∈ D(Φ α). We derive the asymptotic distribution of these estimators for pn → 1 and n(1 - pn) → ∞ as n → ∞. It turns out that those estimators use only the first k largest observations from the samples and the optimal choice of k is also treated in both asymptotic and finite sample cases. Chapter three examines the dynamics of inflation persistence using fractionally integrated processes and reconcile previous diverging conclusions. Using the fractional integration technique I find there was indeed a decline in inflation persistence in the U.S. around the early 1980's. Also I show that the presence of fractional integration in inflation successfully explains previous diverging res
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