I’m a young investor, and I know I still have a lot to learn. Some of that learning comes from books, great investors, and experts. Some of it comes from experience, including both the times I get things right and the times I make mistakes.
But I’ve also realized that some of the questions I’m most curious about do not have clear answers in books, articles, or videos. That is what pushed me to start doing my own research. When I cannot find a good enough answer, I want to dig deeper, explore the question myself 🤔, and see what I can discover.
For me, these research papers are more than school projects. They are part of how I learn to become a better investor. Each study helps me think more carefully, understand investing from a new angle, and add another useful tool to the way I make decisions.
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.
