Portfolio Optimization - Palomar, Daniel P. (Hong Kong University of Science and Technology)
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This text offers a deep dive into practical algorithms, departing from conventional Gaussian assumptions and exploring a wide range of portfolio formulations. A must-read for anyone interested in financial data modeling and portfolio design, it is suitable as a textbook for portfolio optimization and financial data modeling courses.

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Produktbeschreibung
This text offers a deep dive into practical algorithms, departing from conventional Gaussian assumptions and exploring a wide range of portfolio formulations. A must-read for anyone interested in financial data modeling and portfolio design, it is suitable as a textbook for portfolio optimization and financial data modeling courses.
Autorenporträt
Daniel P. Palomar is a Professor at the Hong Kong University of Science and Technology. He is recognized as EURASIP Fellow, IEEE Fellow, and Fulbright Scholar, and recipient of numerous research awards. His current research focus is on convex optimization applications in signal processing, machine learning, and finance. He is the author of many research articles and books, including 'Convex Optimization in Signal Processing and Communications'.