Portfolio Optimization: An Evaluation of the Downside Risk Framework on the Nordic Equity Markets

Abstract: Risk management in portfolio construction is a widely discussed topic and the tradeoff between risk and return is always considered before an investment is made. Modern portfolio theory is a mathematical framework which describes how a rational investor can use diversification to optimize a portfolio, which suggests using variance to measure financial risk. However, since variance is a symmetrical metric, the framework fails to correctly account for the loss aversion preferences most investors exhibit. Therefore, the use of downside risk measures were proposed, which only measures the variance of the portfolio below a certain threshold, usually set to zero or the risk-free rate. This thesis empirically investigates the differences in performance between the two risk measures when used to solve a real world portfolio optimization problem. Backtests using the different measures on all major Nordic equity markets are performed to highlight the dynamics between the frameworks, and when one should be preferred over the other. It is concluded that the optimization frameworks indeed provides a useful tool for investors to construct great performing portfolios. However, even though the downside risk framework is more mathematically rigorous, implementing this risk measure instead of variance seems to be of less importance for the actual results.