An Analysis of the Performance of Artificial Neural Network Technique for Stock Market Forecasting
Journal Title: International Journal on Computer Science and Engineering - Year 2010, Vol 2, Issue 6
Abstract
In this paper, we showed a method to forecast the daily stock rice using neural networks and the result of the Neural Network forecast is compared with the Statistical forecasting result. tock price prediction is one of the emerging field in neural network forecasting area. This paper also presents the Neural etworks ability to forecast the daily Stock Market Prices. Stock market prediction is very difficult since it depends on several known nd unknown factors while the Artificial Neural Network is a popular technique for the stock market Forecasting. The Neural etwork is based on the concept of ‘Learn by Example’. In this paper, eural Networks and Statistical techniques are employed to odel and forecast the daily stock market prices and then the results of these two models are compared. The forecasting bility of these two models is accessed using MAPE, MSE and RMSE. The results show that Neural Networks, when trained with sufficient data, proper inputs and with proper architecture, can predict the stock market prices very well. Statistical chnique though well built but their forecasting ability is educed as the series ecome complex. Therefore, Neural Networks can be used as an better alternative technique for orecasting the aily stock arket prices.
Authors and Affiliations
Kunwar Singh Vaisla , Dr. Ashutosh Kumar Bhatt
Keywords
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