Portfolio optimization for an P2P investor on Zonky

This thesis analyzes the Czech peer-to-peer lending platform Zonky. The goal was to find the optimal portfolio for a risk-averse investor investing in Zonky loans. For this purpose, the Modern portfolio theory from Markowitz was used. Based on the provided loan book containing information about loans which Zonky has provided since its foundation we examined the statistical properties of the individual risk categories represented by the interest rate charged. The optimization was done using the Excel Solver tool assuming that the loan categories are uncorrelated as well as considering the correlation we found using the variance- covariance matrix. For both cases, the portfolio minimizing the standard deviation as well as the portfolio which maximizes the Sharpe ratio was found. Generally, both types of portfolios were comprised mainly of loans with lower interest rate. According to our results, it seems that such loans offer better relationship between risk and return compared to categories which are riskier. Also, we showed that the platform's recovery rate has a significant impact on the performance of the loan categories especially of those which are among the riskiest. Furthermore, we demonstrated that the correlation between individual risk categories should not be ignored when a portfolio..