Currency Matrices for the Visual Analysis of Currency Correlations

In this paper we investigate the problem of creating an interactive visual overview for dynamic pairwise currency correlations in the form of an interactive visual analytics tool. To reach this goal we extract real-time data and compute pairwise correlations for user-defined time windows on which the correlation values are based. To structure the generated matrix of pairwise currency correlations we further extend our approach by matrix reordering based on a hierarchical clustering with which we can visually identify groups and subgroups of currency pairs that stand in a certain correlation behavior. Moreover, we explore the dynamic data from the perspective of economic and pandemic events like COVID-19. We illustrate the usefulness of our technique by applying it to currency data from countries all over the world and explore several data dimensions in it while focusing on the Swiss Francs currency in particular. Based on our algorithmic and visual analysis we can find out that COVID-19 as well as economic events have impacts on the currencies and currency groups. Finally, we discuss scalability issues and limitations of our interactive visual analytics tool, coming in the form of an interactive dashboard.