Role of soft computing techniques in predicting stock market direction

Abstract

The stock market is a complex and dynamic system with noisy, non-stationary and chaotic data series. Prediction of a financial market is more challenging due to chaos and uncertainty of the system. Soft computing techniques are progressively gaining presence in the financial world. Compared to traditional techniques to predict the market direction, soft computing is gaining the advantage of accuracy and speed. However the input data selection is the major issue in soft computing. The aim of this paper is to explain the potential day by day research contribution of soft computing to solve complex problem such as stock market direction prediction. This study paper synthesizes five reference papers and explains how soft computing is gaining the popularity in the field of financial market. The selection of papers are based on various models wich are processing different input parameters for predicting the direction of stock market.