A Comparative analysis of the mean-variance optimization theory and the Black-Litterman model; integrating the Monte Carlo simulation

Abstract

This comparative study analyzed portfolio optimization using the Black-Litterman model and Harry Markowitz’s mean-variance optimization model. Furthermore, the study employed GARCH (1,1) simulated returns to predict future returns. The study used the Sharpe ratio to measure the performance of the portfolios. The comparative study was conducted on the Nairobi Securities Exchange using nine selected stocks from nine sectors of the economy. The study aims to determine which of the two optimization models yields better results for an investor’s wealth. The study found that the Black Litterman model portfolios performed better than the mean-variance optimization model portfolios. Furthermore, the study revealed that portfolios constructed using the historical dataset, yielded better returns with a higher Sharpe ratio and the portfolios constructed using the simulated returns.