Stock Market Series Analysis Using Self-Organizing Maps
نویسندگان
چکیده
In this work a new clustering technique is implemented and tested. The proposed approach is based on the application of a SOM (self-organizing map) neural network and provides means to cluster U-MAT aggregated data. It relies on a flooding algorithm operating on the U-MAT and resorts to the Calinski and Harabask index to assess the depth of flooding, providing an adequate number of clusters. The method is tuned for the analysis of stock market series. Results obtained are promising although limited in scope. keywords: financial markets, SOM, clustering, U-Matrix, flooding, neural networks.
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