Shares choice to enter a portfolio is a good topic in finance and management, as it affects the portfolio performance which is managed by a Fund Manager. In this research, we aim to create an artificial neural network model to choose a share to enter a portfolio based on its financial factors and big data about the financial condition of companies. The artificial neural network model has 15 input nodes of attributes associated with a company’s financial situation, 8 hidden layer nodes, and 1 output node. The accuracy of the model is 85.71%, with a learning rate of 0.05 trained over 2000 iterations.
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Modelling shares choice to enter in a portfolio using artificial neural networks (ANN)
Semantic Scholar · Computer Science · 2020
Abstract
Shares choice to enter a portfolio is a good topic in finance and management, as it affects the portfolio performance which is managed by a Fund Manager. In this research, we aim to create an artificial neural network model to choose a share to enter a portfolio based on its financial factors and big data about the financial condition of companies. The artificial neural network model has 15 input nodes of attributes associated with a company’s financial situation, 8 hidden layer nodes, and 1 output node. The accuracy of the model is 85.71%, with a learning rate of 0.05 trained over 2000 iterations.
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