Thuy Nguyen Thi Thu

Papers

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About

Dr. Thuy Nguyen Thi Thu is a leading researcher in the application of machine learning to financial forecasting, with a specialized focus on foreign exchange (Forex) prediction. Her work centers on leveraging supervised learning techniques, particularly Support Vector Machines (SVM), to model and anticipate currency market trends. Dr. Nguyen’s major contributions include demonstrating how binary classification models can effectively predict market direction—specifically identifying uptrends and downtrends in highly volatile Forex transactions. Her seminal paper, “Using support vector machine in FoRex predicting” (2018), has garnered 21 citations, establishing a foundational approach for integrating SVM into automated trading systems. A subsequent study, “Supervised Support Vector Machine in Predicting Foreign Exchange Trading” (2018), further refined these methods, earning 7 citations. By translating complex market dynamics into solvable classification problems, Dr. Nguyen has provided a robust, data-driven framework that bridges computational learning theory and practical financial decision-making. Her work is particularly notable for its clarity in operationalizing SVM for real-world trading, making her a key figure for students and researchers exploring the intersection of artificial intelligence and quantitative finance.