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• W3132882609 abstract "This paper develops two efficient Artificial Intelligence models and compare their performances in predicting the value and direction of the Philippine Stock Exchange indices. The models are based on the two most prominent classification techniques, artificial neural networks (ANN) and support vector machines (SVM). These models are trained on the eight Indices of the Philippine Stock Exchange: PSEi, All Shares, Financials, Industrial, Holding Firms, Services, Mining and Oil, and Property. Although both models can adequately forecast the stock indices, ANN performs better than SVM. Finally, this study concludes that the Philippine stock market is indeed predictable and inefficient" @default.
• W3132882609 created "2021-03-01" @default.
• W3132882609 creator A5060414286 @default.
• W3132882609 date "2017-03-05" @default.
• W3132882609 modified "2023-09-26" @default.
• W3132882609 title "Is Artificial Intelligence the Oracle of Delphi for Stock Markets? Artificial Intelligence and Stock Market Predictability" @default.
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