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Explore risk-averse optimization techniques through stochastic dominance constraints in this 53-minute lecture by Darinka Dentcheva from Stevens Institute of Technology, presented as part of the Fields Institute's 2025-2026 Quantitative Finance Seminar series. Delve into advanced mathematical frameworks for decision-making under uncertainty, examining how stochastic dominance principles can be incorporated as constraints in optimization problems to model risk-averse behavior. Learn about the theoretical foundations of stochastic dominance relations and their practical applications in portfolio optimization, financial planning, and other areas where risk management is crucial. Discover computational approaches and algorithmic strategies for solving optimization problems with stochastic dominance constraints, understanding both the mathematical challenges and solution methodologies. Gain insights into how these techniques compare to traditional risk measures and their advantages in capturing investor preferences and risk attitudes in quantitative finance applications.
