Self-Organizing Maps
Neighborhood Preservation in Nonlinear Projection Methods: An Experimental Study
ICANN '01 Proceedings of the International Conference on Artificial Neural Networks
A Nonlinear Mapping for Data Structure Analysis
IEEE Transactions on Computers
Suitability of self-organising maps for analysing a macro-environment an empirical field survey
International Journal of Business Information Systems
Expert Systems with Applications: An International Journal
Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS
Expert Systems with Applications: An International Journal
Early Warning Systems: an approach via Self Organizing Maps with applications to emergent markets
Proceedings of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008
Fuzzy clustering of the self-organizing map: some applications on financial time series
WSOM'11 Proceedings of the 8th international conference on Advances in self-organizing maps
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Due to the recent wave of bank failures, stress tests have been conducted on banks within the European Union. The stress tests, however, only consider the adequacy of a bank's capital ratios, whereas the general financial performance of individual banks is disregarded. In this paper, we use the Self-Organizing Map SOM to perform a visual multidimensional and temporal financial performance analysis of European banks. We address several problems concerning financial performance analysis. We deal with the problem of selecting suitable financial ratios by performing dimensionality reduction using Principal Component Analysis. We also deal with difficult data using outlier trimming and normalization techniques, and use the SOM for imputing missing values. We use a decision-framework for choosing the final model, based upon a set of map and clustering quality measures. In addition, we implement a second-level fuzzified Ward clustering for visualization purposes and for assessing the crispness of the solution. The result is a visual SOM model for financial performance analysis of European banks.