I’m a young investor, and I know I still have a lot to learn. Some knowledge can come from reading books, studying great investors, and listening to experts. Some lessons also come from real experience—both my successes and my mistakes. But I’ve realized that some questions I care about do not have clear answers in books, articles, or videos. That is why I decided to do my own research. I want to explore the questions in my mind 🤔 and find answers for myself when existing sources are not enough . For me, these research papers are not just school-style projects. They are part of my journey as an investor. Every study helps me think more deeply, understand investing better, and add another useful tool to my decision-making process.
Predicting Dividend Statuses of Thai Listed Companies Using Machine Learning
Published in
The Curieux Review •
March 2026
This study addresses the dividend puzzle by utilizing machine learning techniques to forecast dividend status of 515 non-financial companies listed on the Stock Exchange of Thailand (SET). By using random forest, boosted tree, and decision tree models, we classified dividend status into 4 categories: grow, maintain, decline, and remain unpaid. The results indicate that the boosted tree method provided superior predictive power compared to the random forest and decision tree methods. Predicting dividend policy in emerging markets is valuable for investors and analysts to understand future dividend prospects, which is a critical signal of a company's financial well-being.
