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Title: On the use of neural networks for stock price forecasting
Author: Sousa, Virgínia
Alonso, Hugo
Keywords: Financial markets
Neural networks
Stock share
Variable selection
Issue Date: 2020
Publisher: Varazdin Development and Entrepreneurship Agency; University North
Abstract: Having the ability to predict the price of a particular stock share is undoubtedly a major challenge, because of the complexity and implied volatility of the financial markets. This is a topic of great interest to researchers and market players, as the effectiveness of the forecast might translate into huge monetary gains. This work aims to demonstrate the use of neural networks for stock price forecasting. Two financial titles are considered: Microsoft and Apple. The initial choice of the predictor variables comprises the most used and referenced in the scientific papers published on this subject. This work demonstrates the importance of a careful selection of some of those variables for a good neural network performance.
Peer review: yes
ISSN: 1849-7535
Publisher Version:
Appears in Collections:CIDMA - Comunicações
SCG - Comunicações

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