Stock Price Forecasting With neural Network Using a New Training Algorithm
Journal Title: Scholars Journal of Engineering and Technology - Year 2016, Vol 4, Issue 10
Abstract
Abstract:Publication of bond and stockthrough stock market, is a way in order to prepare the capital for investment. According to this fact that stock price is the first and important issue for an investor,evaluating and forecasting of the future price will be propounded. Artificial Neural Network (NN) is a way of stock price forecasting.High efficiency of NNsin forecasting and importance of forecastingin different fields, have caused researchers to search the ways of improving the strategies used for increase of the accuracy of forecasting by neural networks.Accuracy level of aNNgreatly depends on its weight and bias values. In a NN, weight and bias valuesdepend on the kind of training algorithm. In this article, theNN using for stock price forecastingis trained by a new metaheuristic training algorithm, namedbird mating optimizer (BMO). Effectiveness and efficiency of this algorithmis compared with NN trained by Genetic Algorithm (GA) algorithm based on the average, median and standard deviation of the Mean Square Error (MSE).The experimental results show that the BMO lends itself very well to forecast of stock price. Keywords:Learning neural network, BirdMatingOptimizer algorithm (BMO), Stock price forecasting.
Authors and Affiliations
Mehrnaz Piroozbakht, Majid Rostami
Keywords
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