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 © 2012 John Wiley & Sons, Ltd.