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Robo-Advisors: Machine Learning in Trend-Following ETF Investments
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 highdoi:10.3390/su12166399 fatcat:3hj7aiqjivhuxh5u6vnwvicukq