A Phylogenetic Analysis for Stock Market Indices Using Time-Series String Alignments

Predicting stock is very difficult and complex since there are lots of variables we should consider. Most of stock system usually deals with the stock indices and their properties. But recent stock system can not provide clearly the classification according to similar stock properties. So we need smart clustering algorithm for stock market that can derive their hidden interactions from stock indices. In this paper, we propose phylogenetic analysis for stock market using the string alignments based on time-series to cluster stock indices. We also analyze KOSPI data from 2007/01/03 to 2008/02/28 using string alignments, our proposed algorithms can show the meaningful clusters which can not displayed by the recent other system.