Stock Market Be¬havior Prediction Using Pattern Matching Approach (International Journal of Engineering and Computer Science, 2014)
In this paper we propose a new model for prediction of stock market behavior using pattern matching approach. The fluctuation of stock market is characterized by a number 0 and 1, ‘0’ denoting non-increasing state and ‘1’ denoting an increasing state. The behavior of the stock market is put into sequence of 0’s and 1’s which was converted to the sequence of nucleotides A, T, C, G. This sequence so obtained is matched to the text DNA sequence by using BLAST. Comparing their results using hamming distance and predict the future increasing or non-increasing behavior of stock market. Possibility using this approach to predict the stock market behavior is explored.