dc.description.abstract | This study applies data mining techniques to construct a predictive model for stock dividend market trends, aiming to predict the stock market trends after Taiwanese listed companies announce their dividends. The research targets are listed companies in Taiwan′s securities market. The research variables include dividend policy, fundamental indicators, technical indicators, and capital flow indicators. Examine whether there′s a 10% increase in stock price after the announcement of dividend policy in the shareholders′ meeting of individual stocks, and identify the key factors affecting the dividend market trends. The target variable of the study is "Whether there is a 10% increase in stock price after the announcement of dividend policy", with each piece of data labeled as ′Y′ or ′N′ for identification. This study covers the period from 2010 to 2021 and uses various technical indicators and financial indicators as key factors, including dividend policy, fundamental, technical, and capital flow indicators. Data mining techniques and feature selection methods are used to identify the key factors affecting the market trends prior to the ex-dividend date, providing investors with a reference for investing during the annual ex-dividend period.
This study uses five supervised learning algorithms to construct a predictive model: decision trees, random forests, naive Bayes, support vector machines, and artificial neural networks. The predictive model is trained through ten-fold cross-validation, and the prediction accuracy of the model is evaluated using a confusion matrix. The experimental design uses four different prediction datasets to investigate the impact of each dataset on the prediction results.
Out of the 67 research variables established in this study, feature selection results show that the key factors for dividend market trends are the number of days between the shareholders′ meeting and the ex-dividend date, the dividend yield, DIF, gross profit growth rate, earnings per share changes, volatility index, deviation rate, investment trust holding ratio, and self-operating holding ratio. Furthermore, the predictive ability of fundamental indicators combined with dividend policy surpasses that of technical indicators and capital flow indicators. | en_US |