Distributionally Robust Portfolio Optimization

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Page 3 of 4

Introduces convex optimization, focusing on the importance of convexity in algorithms and optimization problems.

Explores primal-dual optimization, minimax problems, and gradient descent-ascent methods for optimization algorithms.

Explores convex optimization duality, KKT conditions, and financial arbitrage detection.

Covers the KKT conditions and Slater's condition in convex optimization problems.

Explores the Rockafellar Theorem in optimal transport, focusing on c-cyclical monotonicity and convex functions.

Explores asset pricing, equity premium puzzle solutions, stock prices, dividends, CAPE, and interest rate structures.

Explores primal-dual optimization, conjugation of functions, strong duality, and quadratic penalty methods in data mathematics.

Explores primal-dual optimization methods, emphasizing Lagrangian gradient techniques and their applications in data optimization.

Explores portfolio optimization, efficient frontier, CAPM, and risk management in finance.

Covers Farkas' lemma, exploring the relationship between linear programs and the conditions for its validity.