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.

中文翻译：

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使用人工神经网络（ANN）对股票选择进行建模以进入投资组合

进入投资组合的股票选择在财务和管理中是一个不错的话题，因为它会影响由基金经理管理的投资组合的绩效。在这项研究中，我们旨在创建一个人工神经网络模型，根据其财务因素和有关公司财务状况的大数据来选择要进入投资组合的股票。人工神经网络模型具有15个与公司财务状况相关联的属性输入节点，8个隐藏层节点和1个输出节点。该模型的准确性为85.71％，在2000次迭代中的学习率为0.05。