Mean-Variance Portfolio Optimization of Energy Stocks Supported with Second Order Stochastic Dominance Efficiency

Second order stochastic dominance pairwise efficiency could be considered as a milestone among the improvements, which eliminates the shortcomings of mean-variance theory. This paper applies mean-variance optimization on the global fossil fuels stocks, as a leading representative of energy sector, with the help of the pre-elimination of second order stochastic dominance pairwise inefficient stocks. The performance of the application is additionally measured with an out-of-sample back-testing analysis, which indicates a contribution to the existing literature; second order stochastic dominance pre-elimination method increases the success of some of the selected mean-variance optimized portfolios on the efficient frontier which stand out with a better back-testing performance.