Factor copula models and their applications

Factor copula models are useful for modeling high-dimensional data sets that typically exhibit complex dependence structures. However, the practical merits of factor copula models have not been fully explored from an estimation point of view. This thesis proposes a simple, yet useful framework for estimating factor copula models, which allows for a richer and more precise understanding of the underlying dependence in the data sets.