Nistler CoBPA Faculty Research

Celebrate the impact of our research.

Dr. Kwan Yong Lee, Associate Professor of Economics and Finance, paper accepted in the Journal of Sustainability

Kwan Yong Lee

Please join us in congratulating Dr. Kwan Yong Lee, Associate Professor in the Department of Economics and Finance for his recent publication!

Title: “Robo-Advisors: Machine Learning in Trend-Following ETF Investments”
Journal: Sustainability (Level 3 on the NCoBPA JQL)
Authors: Seungho Baek (City University of New York), Kwan Yong Lee (University of North Dakota), Merih Uctum (City University of New York), Seok Hee Oh (Gachon University)
Abstract: We examine an application of machine learning to exchange traded fund investments in the U.S. market. To find how the changes in exchange traded fund prices are associated with expected market fundamentals, we propose three parsimonious risk factors extracted from various U.S. economic and market indicators. Based on the information set including these three factors, we build a predictive support vector machine model that can detect long or short investment signals. We find that the high probability of an upward momentum from our forecasting model suggests a long exchange traded fund signal, whereas the low probability of a downward momentum indicates a short exchange traded fund signal. We further design an algorithmic trading system with the support vector machine factor model. We find that the trading system shows practically desirable and robust performances over in-sample and out-of-sample trading periods