Visual Predictions of Currency Crises: A Comparison of Self- Organizing Maps with Probit Models

Throughout the 1990s, four global waves of financial turmoil occurred. The beginning of the 21st century has also suffered from several crisis episodes, including the severe subprime crisis. However, to date, the forecasting results are still disappointing. This paper examines whether new insights can be gained from the application of the SelfOrganizing Map (SOM) – a non-parametric neural network-based visualization tool. In this paper, we present a SOM model for prediction of currency crises, and compare it with a probit model. The results indicate that the SOM is a feasible tool for predicting currency crises. Moreover, its visual capabilities facilitate the understanding of the factors and conditions that contribute to the emergence of currency crises in various parts of the world.