Study on financial data hybrid clustering based on stock trading rule

Abstract

We have built a SOM&K-means based trading rules system on financial markets at intraday trading frequencies and conduct empirical research on the 5 min Hushen 300 Index of China. We also have obtained the result that K-means clustering after the training of the SOM can categorize successfully. The new proposed SOM&K-means based trading rules can provides purchase decision to investors easily. The results support the evidences that SOM&K-means based trading rules system will discover intraday patterns and help stock investors gain more returns for the stock investors. © 2013 Springer Science+Business Media.