Mean-variance (MV) optimization is one of the most impactful frameworks in the world of financial markets; however, mean-variance analysis adopts relatively strict assumptions including, but not limited to, investor preferences and normal probability distribution. Because of these strong assumptions, the effectiveness of MV optimization becomes a major concern, especially in various market conditions. Stochastic dominance (SD), utilized in numerous fields, develops a preference-ranking strategy that attempts to relax the limitations of mean-variance analysis. The central question of this research is to determine whether stochastic dominance techniques outperform their mean-variance counterparts over the course of the 2008 Global Financial Crisis. This question is empirically tested by applying the MV and second-order SD criteria to the College of Wooster’s Jenny Investment Club portfolio. Further contemplation of the prevailing strategy’s performance on a quarterly basis, relative to macroeconomic factors that affect equity markets, is considered. Due to the lack of a proper weighting strategy, stochastic dominance techniques appear to be better suited as a complement to mean-variance strategies, rather than as a replacement.
Cerniglia, Jason, "An Empirical Analysis of Stochastic Dominance & Markowitz' Mean-Variance Optimization: Contrasting Portfolio Performance over the 2008 Global Financial Crisis" (2020). Senior Independent Study Theses. Paper 9136.
Portfolio and Security Analysis
Portfolio Theory, Stochastic Dominance, 2008 GFC
Bachelor of Arts
Senior Independent Study Thesis
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