Downloads: 107 | Views: 352
Research Paper | Chemistry | India | Volume 4 Issue 7, July 2015 | Popularity: 6.8 / 10
Artificial Neural Network (ANN) for Stock Market Predictions
Dr. Sunil Kumar Dhal
Abstract: Artificial neural networks are universal and highly flexible function approximations first used in the fields of cognitive science and engineering. In recent years, neural network applications in finance for such tasks as pattern recognition, classification, and time series forecasting have dramatically increased. However, the large number of parameters that must be selected to develop a neural network forecasting model have meant that the design process still involves much trial and error. Neural Network is a challenging and daunting task to find out which is more effective and accurate method for stock rate prediction so that a buy or sell signal can be generated for given stocks. Predicting stock index with traditional time series analysis has proven to be difficult an Artificial Neural network may be suitable for the task. A Neural Network has the ability to extract useful information from large set of data. This paper presents an application of Artificial Neural Network for stock market predictions and is very useful for predicting world stock markets.
Keywords: Artificial Neural Network, Stock Index, Prediction
Edition: Volume 4 Issue 7, July 2015
Pages: 1655 - 1658
Make Sure to Disable the Pop-Up Blocker of Web Browser
Similar Articles
Downloads: 107
Research Paper, Chemistry, India, Volume 3 Issue 8, August 2014
Pages: 1116 - 1119QSAR Modeling for Predicting Anti HIV Activity of PETT Derivatives
Megha Choure, Nameeta Bende, Arpan Bharadwaj, Suresh Kumar Verma
Downloads: 129
Research Paper, Chemistry, Morocco, Volume 4 Issue 3, March 2015
Pages: 460 - 468DFT-Based QSAR Studies of Some Structurally Diverse Azaaurones Derivatives as Potential Antimalarials
Hanine HADNI, Menana El Hallaoui