Microfinance as an Emerging Asset Class: A robo-advisory solution to broaden financial inclusion

Abstract

Impact investing has received increasing attention from asset managers, who are looking to maximize social impact alongside traditional financial risk-return measures. This thesis examines microfinance as an emerging asset class. We develop robo-advisory algorithms that automates investments in online lending loans portfolios based on individuals' risk tolerance and investment horizon. Our risk factor-based investment strategy suggest that micro-loans tend to have less exposure to global macro risk factors and can complement traditional investment portfolios with an 8%-10% return and a 1%-2% volatility. Furthermore, higher returns for given level of risks can be achieved with leverage. These findings highlight a growing opportunity for a higher level of investment in these microfinance activities.