A FRAMEWORK FOR STATE TRANSITIONS ON THE SELF-ORGANIZING MAP: SOME TEMPORAL FINANCIAL APPLICATIONS

Self-organizing maps (SOMs) have commonly been used in temporal applications. This paper enhances the SOM paradigm for temporal data by presenting a framework for computing, summarizing and visualizing transition probabilities on the SOM. The framework includes computing matrices of node-to-node and node-to-cluster transitions and summarizing maximum state transitions. The computations are linked to the SOM grid using transition-plane visualizations. We demonstrate the usefulness of the framework on two SOM models for temporal financial analysis: financial performance comparison of banks and monitoring indicators of currency crises. Copyright (C) 2012 John Wiley & Sons, Ltd.