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IJSTR >> Volume 8 - Issue 8, August 2019 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Performance Analysis On Metaheuristic Based Hybrid Neural Network To Predict The Stock Movement

[Full Text]



K Venkatanarayana, B. Satyanarayana



Stock market, machine learning, artificial neural network, HMNN, metaheuristics,Optimization



Stock market prediction is a time series forecasting problem. For an efficient stock price prediction, in this paper optimization based neural network learning scheme has been developed that alleviates the existing Artificial Neural Network (ANN) limitations such as local minima and convergence issues. The existing gradient descent based algorithms are local search algorithms. To find global optimum solution, Metaheuristic based Hybrid Neural Network (HMNN) has been developed. The hybrid neural network executes optimization of activation nodes, optimization of weights and learning parameters. To illustrate this, we apply the proposed HMNN method to study the movement of closing prices of stock market. The algorithm has been practically examined for performance in terms of Mean Absolute Percentage Error, accuracy, precision, recall, completeness, F-measure where it has performed better as compared to major existing schemes. The proposed scheme exhibited 94.97% prediction accuracy while guarantee optimal precision, F-measure and recall.



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