AAAI Publications, The Twenty-Sixth International FLAIRS Conference

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Visualizing Stock Market Data with Self-Organizing Map
Joel Joseph, Indratmo Indratmo

Last modified: 2013-05-19

Abstract


Finding useful patterns in stock market data requires tremendous analytical skills and effort. To help investors manage their portfolios, we developed a tool for clustering and visualizing stock market data using an unsupervised learning algorithm called Self-Organizing Map. Our tool is intended to assist users in identifying groups of stocks that have similar price movement patterns over a period of time. We performed a visual analysis by comparing the resulting visualization with Yahoo Finance charts. Overall, we found that the Self-Organizing Map algorithm can analyze and cluster the stock market data reasonably.

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