Exploiting the self-organizing financial stability map

This paper enhances the visualization and extraction of information on the self-organizing financial stability map (SOFSM). The SOFSM uses the self-organizing map to represent a multidimensional financial stability space on a two-dimensional grid and allows monitoring economies in the financial stability cycle represented by four states. The SOFSM lacks, however, means for thorough assessment of general structures and individual data. We enhance the visualization and information extraction of the SOFSM by the means of four tasks: (1) fuzzification of the map, (2) probabilistic modeling of state transitions, (3) contagion analysis and (4) outlier detection. The usefulness of the extensions is shown with sample visualizations and predictive performance.