Stock Market Forecast Using Bio-Inspired Computing

Stock Markets represent a complex, nonlinear, ever-changing, trading systems where traders (investors) are competing for profit. Stock market forecasting have attracted some special attention in the last years. However, the irregular nature and the complex behavior of stock data transform forecasting into a very hard task, and forecasting stock index has proven to be difficult. Recently, Bio-Inspired Algorithms has emerged extremely useful for forecasting dynamical systems e.g., stock market. Though a lot of research has already been done on various stock markets, relatively less attention is given for Dhaka Stock Exchange (DSE), Bangladesh in comparison to them. This work presents a stock market forecasting system based on hybridized Bio-Inspired Algorithms for DSE. Experimental result shows that the proposed system is very useful for forecasting stock market. Another contribution of this paper is to present a review of literature application of Bio-Inspired Algorithms for stock market forecasting.