Evaluating the Application of Copula Models in Measuring Dependence Structures Across Financial and Environmental Data

Posted: Sep 22, 2018

• Maria Wilson
• Michael Miller
• Lucas Thomas

Abstract

The intersection of financial markets and environmental systems represents a critical yet underexplored domain in quantitative analysis. Traditional approaches to understanding relationships between economic and ecological variables have relied predominantly on linear correlation measures, which fundamentally fail to capture the complex, non-linear dependencies that characterize these interconnected systems. This research introduces a novel application of copula theory to model dependence structures between financial and environmental data, addressing a significant methodological gap in cross-disciplinary analytics. Copula functions, which originated in probability theory and statistics, provide a powerful framework for modeling multivariate distributions by separating the marginal distributions from the dependence structure. While copulas have found extensive applications in finance for modeling dependencies between asset returns and in environmental science for modeling spatial and temporal dependencies, their application to cross-domain dependencies between financial and environmental variables remains largely unexplored. This research bridges this gap by developing a comprehensive methodological framework for applying copula models to quantify and characterize the complex interdependence patterns between economic activities and environmental conditions.