Abstract

Forecast stock market prices are an essential pace while building investment portfolios. On the stock\nmarket study and forecast, investigation has been paid attention to by people. Stock price movement is a complex\nnonlinear function, so the price has convinced predictability. Artificial neural networks have been implemented in stock\nmarket prediction throughout the last decade. Studies were carried out for the prediction of stock index values also daily\ndirection of variation in the index. Back propagation is one of the approaches to realize neural networks. Back\npropagation is a type of supervised learning intended for multi-layer network. Error facts at the output layer is back\npropagated to former ones, allowing arriving weights to these layers to be updated. In our study, we employ data mining\nand neural network concepts to stock market in order to investigate the trend of price. It intends to forecast the future\nprices of the stock market and the fluctuation of price. Our aim is achieve better predictive system to improve forecast\naccuracy.