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Stock Market Prediction Model by Combining Numeric and News Textual Mining
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 57 - Number 19 |
| Year of Publication: 2012 |
| Authors: Kranti M. Jaybhay, Rajesh V. Argiddi, S. S. Apte |
10.5120/9222-3779
|
Kranti M. Jaybhay, Rajesh V. Argiddi, S. S. Apte . Stock Market Prediction Model by Combining Numeric and News Textual Mining. International Journal of Computer Applications. 57, 19 ( November 2012), 16-22. DOI=10.5120/9222-3779
Abstract
This paper proposes a novel method for the prediction of stock market closing price. Many researchers have contributed in this area of chaotic forecast in their ways. Data mining techniques can be used more in financial markets to make qualitative decisions for investors. Fundamental and technical analyses are the traditional approaches so far. ANN is a popular way to identify unknown and hidden patterns in data is used for share market prediction. A multilayered feed-forward neural network is built by using combination of data and textual mining. The Neural Network is trained on the stock quotes and extracted key phrases using the Backpropagation Algorithm which is used to predict share market closing price. This paper is an attempt to determine whether the BSE market news in combination with the historical quotes can efficiently help in the calculation of the BSE closing index for a given trading day.
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