Asset Allocation Model for a Robo-Advisor Using the Financial Market Instability Index and Genetic Algorithms

Wonbin Ahn, Hee Soo Lee, Hosun Ryou and Kyong Joo Oh
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Wonbin Ahn: Center of Bionics, Korea Institute of Science and Technology, Seoul 02792, Korea
Hee Soo Lee: Department of Business Administration, Sejong University, Seoul 05006, Korea
Hosun Ryou: Department of Industrial Engineering, Yonsei University, Seoul 03722, Korea
Kyong Joo Oh: Department of Industrial Engineering, Yonsei University, Seoul 03722, Korea

Sustainability, 2020, vol. 12, issue 3, 1-15

Abstract: There has been a growing demand for portfolio management using robo-advisors, and hence, research on the automation of portfolio composition has been increasing. In this study, we propose a model that automates the portfolio structure by using the instability index of the financial time series and genetic algorithms (GAs). We use the instability index to filter the investment assets and optimize the threshold value used as a filtering criterion by applying a GA. For an empirical analysis, we use stocks, bonds, commodities exchange traded funds (ETFs), and exchange rate. We compare the performance of our model with that of risk parity and mean-variance models and find our model has better performance. Several additional experiments with our model using various internal parameters are conducted, and the proposed model with a one-month test period after one year of learning is found to provide the highest Sharpe ratio.

Keywords: financial market instability index; genetic algorithm; asset allocation; exchange traded funds (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (4)

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