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Applying Artificial Neural Network Optimized by Fireworks Algorithm for Stock Price Estimation


Affiliations
1 DATIC Laboratory, The University of Danang, University of Science and Technology, Viet Nam
     

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Stock prediction is to determine the future value of a company stock dealt on an exchange. It plays a crucial role to raise the profit gained by firms and investors. Over the past few years, many methods have been developed in which plenty of efforts focus on the machine learning framework achieving the promising results. In this paper, an approach based on Artificial Neural Network (ANN) optimized by Fireworks algorithm and data preprocessing by Haar Wavelet is applied to estimate the stock prices. The system was trained and tested with real data of various companies collected from Yahoo Finance. The obtained results are encouraging.

Keywords

Fireworks Algorithm, Artificial Neural Network, Stock Price Forecasting, Back-Propagation Algorithm, Wavelet Transform.
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  • Applying Artificial Neural Network Optimized by Fireworks Algorithm for Stock Price Estimation

Abstract Views: 246  |  PDF Views: 2

Authors

Khuat Thanh Tung
DATIC Laboratory, The University of Danang, University of Science and Technology, Viet Nam
Nguyen Thi Bich Loan
DATIC Laboratory, The University of Danang, University of Science and Technology, Viet Nam
Le Quang Chanh
DATIC Laboratory, The University of Danang, University of Science and Technology, Viet Nam
Le Thi My Hanh
DATIC Laboratory, The University of Danang, University of Science and Technology, Viet Nam

Abstract


Stock prediction is to determine the future value of a company stock dealt on an exchange. It plays a crucial role to raise the profit gained by firms and investors. Over the past few years, many methods have been developed in which plenty of efforts focus on the machine learning framework achieving the promising results. In this paper, an approach based on Artificial Neural Network (ANN) optimized by Fireworks algorithm and data preprocessing by Haar Wavelet is applied to estimate the stock prices. The system was trained and tested with real data of various companies collected from Yahoo Finance. The obtained results are encouraging.

Keywords


Fireworks Algorithm, Artificial Neural Network, Stock Price Forecasting, Back-Propagation Algorithm, Wavelet Transform.