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Visualizing Indicators of Debt Crises in a Lower Dimension: A Self-Organizing Maps Approach

Visualizing Indicators of Debt Crises in a Lower Dimension: A Self-Organizing Maps Approach

Peter Sarlin
Copyright: © 2012 |Pages: 18
ISBN13: 9781613501160|ISBN10: 1613501161|EISBN13: 9781613501177
DOI: 10.4018/978-1-61350-116-0.ch017
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MLA

Sarlin, Peter. "Visualizing Indicators of Debt Crises in a Lower Dimension: A Self-Organizing Maps Approach." Handbook of Research on Computational Science and Engineering: Theory and Practice, edited by J. Leng and Wes Sharrock, IGI Global, 2012, pp. 414-431. https://doi.org/10.4018/978-1-61350-116-0.ch017

APA

Sarlin, P. (2012). Visualizing Indicators of Debt Crises in a Lower Dimension: A Self-Organizing Maps Approach. In J. Leng & W. Sharrock (Eds.), Handbook of Research on Computational Science and Engineering: Theory and Practice (pp. 414-431). IGI Global. https://doi.org/10.4018/978-1-61350-116-0.ch017

Chicago

Sarlin, Peter. "Visualizing Indicators of Debt Crises in a Lower Dimension: A Self-Organizing Maps Approach." In Handbook of Research on Computational Science and Engineering: Theory and Practice, edited by J. Leng and Wes Sharrock, 414-431. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-116-0.ch017

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Abstract

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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