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What is Early Warning System (EWS)

Handbook of Research on Computational Science and Engineering: Theory and Practice
An early warning system is a system that gives warning signals of an unwanted event. In this chapter, in order to avoid sovereign defaults, it helps identifying weak macroeconomic variable values. EWSs are most often based on conventional statistical modeling methods, which give a probability of an imminent unwanted event. In order to classify the probability as a warning signal, a threshold is put on the probability of this particular event. All probabilities above this threshold indicate an occurrence of this unwanted event.
Published in Chapter:
Visualizing Indicators of Debt Crises in a Lower Dimension: A Self-Organizing Maps Approach
Peter Sarlin (Åbo Akademi University, Finland)
DOI: 10.4018/978-1-61350-116-0.ch017
Since the 1980s, two severe global waves of sovereign defaults have occurred in less developed countries (LDCs): the LDC defaults in the 1980s and the LDC defaults at the turn of the 21st century. To date, the topic is contemporary, while the forecasting and monitoring results of debt crises are still at a preliminary stage. This chapter explores whether the application of the Self-Organizing Map (SOM), a neural network-based visualization tool, facilitates the monitoring of multidimensional financial data. Thus, this chapter presents a SOM model for visualizing the evolution of sovereign debt crises’ indicators. The results of this chapter indicate that the SOM is a feasible tool for visualization of early warning signals of sovereign defaults.
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