Application of Financial Prediction for Share Price Improvement in the Business Sector by means of Artificial Neural Network

Rafael Roosell Paez Advincula; Celso Gonzales Chavesta; Lilian Ocares Cunvarahi

doi:https://doi.org/10.14445/22315381/IJETT-V71I3P211

Research Article | Open Access | Download PDF

Volume 71 | Issue 3 | Year 2023 | Article Id. IJETT-V71I3P211 | DOI : https://doi.org/10.14445/22315381/IJETT-V71I3P211

Application of Financial Prediction for Share Price Improvement in the Business Sector by means of Artificial Neural Network

Rafael Roosell Paez Advincula, Celso Gonzales Chavesta, Lilian Ocares Cunvarahi

Received	Revised	Accepted	Published
15 Nov 2022	14 Jan 2023	23 Jan 2023	25 Feb 2023

Citation :

Rafael Roosell Paez Advincula, Celso Gonzales Chavesta, Lilian Ocares Cunvarahi, "Application of Financial Prediction for Share Price Improvement in the Business Sector by means of Artificial Neural Network," International Journal of Engineering Trends and Technology (IJETT), vol. 71, no. 3, pp. 91-104, 2023. Crossref, https://doi.org/10.14445/22315381/IJETT-V71I3P211

Abstract

The use of artificial neural networks has an important role; nowadays, they represent an advantage for solving complex problems with different constraints in comparison with traditional methods. The research presents the theory and model; addresses the analysis of corporate financial statements, using the research tool to apply financial forecasting to improve the corporate stock price. The objective is to determine the results of the application of financial prediction for the improvement of stock prices in the corporate sector by means of artificial neural networks. Also, to build different models to evaluate the behavior of networks in different numbers of input variables or neurons in the hidden layer and the probabilities of success by means of the prediction results in the input variables. The predictive capacity in the methods used is based on perceptron-type layers and a strategy that allows alternative system modelling in the predictive control of financial statements.

Keywords

Artificial Neural Network, Business, Prediction, Financial, Neurons, Model.

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