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Proposed system for predicting Buy, Hold and Sell recommendations for a publicly listed Philippine company using computational intelligence

Stock Price movement is a non-linear Financial Time Series. Short-term stock price prediction is best done through Technical Analysis using Artificial Intelligence to detect patterns and trigger buy and sell signals. This paper aims to develop an expert system using Technical Analysis and Support Vector Machines that emulates the reasoning and decision-making process of a technical analyst as applied to the Buy, Hold and Sell recommendations of Stock Price of two publicly listed companies in the Philippines.