The Prediction of the Corporate Governance and Economic Value Added of Listed Companies in the Stock Exchange of Thailand Based on an Artificial Intelligence
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Abstract
This research presents the corporate governance forecasting and economic value added value of listed companies in the stock exchange of Thailand by storing data from listed company’s financial statements. It uses the data from business trading during 2011-2015, excluding the financial businesses, the technology group real estate, the construction resource group, and the medical group. This forecast is based on the implementation of a structured system and the processes that relate to the management committee. The shareholders take into account the competitiveness that will lead to growth and it can add value to the shareholders in the long run. It also recognizes the relationship of economic value added to support decision making for financial investments to maximize shareholder value and future value. The research will analyze all variables that are related to the predicted values by the statistical method and the forecast used is the back-propagation neural network to an algorithm for prediction. The forecasting pattern using artificial neural networks show the four inputs and six inputs of the models. The prediction states that if the predicted value is in the range of 0-0.499, the answer is 0, and if the value is in the range of 0.5-1.00, the answer is with a value of 1.00. This result of the research test is more than 60% accurate that will lead to the answer. The work is based on past historical data for training and forecast in the year 2015 to see accuracy. This research can be developed to provide more accurate forecasting results in the future.
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