Robo-Advisors: Machine Learning in Trend-Following ETF Investments

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

Robo Advising and Investor Profiling

“…Integration with traditional advisory services is a potential growth area [20]. Artificial intelligence and machine learning may enhance personalization [21][22][23][24]. Expansion into financial planning, retirement planning, and banking services aims for a comprehensive financial suite.…”

“…Expansion into financial planning, retirement planning, and banking services aims for a comprehensive financial suite. Advancements in data analytics, AI, and cybersecurity are crucial for enhanced efficiency and sophisticated advice [22].…”

Financial Robo-Advisor: Learning from Academic Literature

“…The term "Robo" in financial investment may refer to robotic-based trading or advisor in the applications that use a specific algorithm to automate the financial transaction based on time, price, quantity, and other economic attributes that emerge to provide a new opportunity for potential investors (Baek et al, 2020). It triggers the shifting of individual behaviour as the effect of information technology develops rapidly and give opportunities to build connectivity between gadgets, faster and easier access to information, and cheaper transaction costs.…”

Robo-Advice: The Digitalization and Automation of Financial Advice

“…Afterwards, I discuss theoretical and practical implications of these insights. Lastly, lim- Studies not focusing on RA or the digitalization and automation of traditional financial advice (Ahn et al 2020;Baek et al 2020;Bunnell et al 2021;Eickhoff et al 2017;Engin and Treleaven 2019;Haberly et al 2019; The app is free to download and provides additional features as in-app purchases…”