POSSIBILITIES OF PERFORMING BANKRUPTCY DATA ANALYSIS USING TIME SERIES CLUSTERING
DOI:
https://doi.org/10.17770/lner2010vol1.2.1779Keywords:
bankruptcy prediction, financial ratio, time series, clusteringAbstract
Prediction of corporate bankruptcy is a study topic of great interest. Under the conditions of the modern free market, early diagnostics of unfavourable development trends of company’s activity or bankruptcy becomes a matter of great importance. There is no general method which would allow one to forecast unfavourable consequence with a high confidence degree. This paper focuses on the analysis of the approaches that can be used to perform an early bankruptcy diagnostics- in previous research multivariate discriminant analysis (MDA), neural network based approach and rule extraction method have been examined. Lately, time series clustering approach has become popular and its feasibility for bankruptcy data analysis is being investigated. Experiments carried out validate the use of such methods in the given class of tasks. As a novelty, an attempt to apply time series clustering method to the analysis of bankruptcy data is made.Downloads
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http://godefroy.sdf-eu.org/apl95/ratios95.zip - skatīts 26.02.2010.
