Forecasting Market Price of Stock using Artificial Neural Network

determines the share of the ownership of a company. It represents the assets and earnings and overall contribution of the company in any country's economy. The stock of a company is partitioned into shares. Decision making in a stock market is not easy as it involves price trends, market nature, company's stability, different rumors, brand image, venture capitalist funds etc. It becomes very imperative to necessarily extract information that is vital for the people to understand and analyze the risk factors necessarily involved to forecast the stock market from the investor's viewpoint. Thus methods like technical analysis, time series analysis and statistical analysis are an attempt to predict the price but unfortunately none of these methods are a consistently acceptable tool. Hence artificial neural network i.e. a field of Artificial Intelligence is a desired way to discover unknown and hidden patterns of the data. There are two different phases i.e. training and other is predicting. Here Back propagation algorithm is used to training session and Multilayer feed forward network is a network model for predicting price accordingly. This prediction would be done on various parameters that would be considered as input to the multilayer perceptron model. These parameters are depends on data i.e. gained by the company.