Abstract
Today, investment by purchasing stock-share constitutes the greater part of economic exchange of countries and a considerable amount of capital is exchanged through the stock markets in the whole world. But one of the most important problems is finding efficient ways to summarize and visualize the stock market data to individual or institutions useful information about the market behavior for investment decision. This research proposes an intelligent stock market forecasting system using the ability of neural network and fuzzy inference system to discover patterns in nonlinear and chaotic systems. This research with a probe in a sample of the whole population of the study involves the data financial record of BEXIMCO Ltd. which is member of Chittagong stock exchange, Bangladesh, aims at the prediction of stock price. The prediction was done by a nonlinear fuzzy-neural network model using exogenous variable of stock market. General Terms Artificial Intelligence, Artificial Neural Network, Machine Learning, Back Propagation Algorithms, Fuzzy Inference System, Stock Market.
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