Frequent Turbulence? A Dynamic Copula Approach

Abstract

How common and how persistent are turbulent periods? We address these questions by developing and applying a dynamic dependence framework. In order to answer the first question we estimate an unconditional mixture model of normal copulas, based on both economic and econometric justification. In order to answer the second question, we develop and estimate a hidden markov model of copulas, which allows for dynamic clustering of correlations. These models permit one to infer the relative importance of turbulent and quiescent periods in international markets. Empirically, the three most striking findings are as follows. First, for the unconditional model, turbulent regimes are more common. Second, the conditional copula model dominates the unconditional model. Third, turbulent regimes tend to be more persistent.