Quantitative Portfolio Optimization: Theory and Practice

＂*Quantitative Portfolio Optimization: Advanced Techniques and Applications* offers a comprehensive exploration of portfolio optimization, tracing its evolution from Harry Markowitz’s Modern Portfolio Theory to contemporary techniques. The book combines foundational models like CAPM and Black-Litterman with advanced methods including Bayesian statistics, machine learning, and quantum computing. It bridges theory and practice through detailed explanations, real-world data applications, and case studies. Aimed at finance professionals, researchers, and students, the book provides tools and insights to address future financial challenges and contributes to the field’s ongoing development＂--

MIQUEL NOGUER ALONSO is a financial markets practitioner with 25+ years of experience in asset management. He is the Founder of the Artificial Intelligence Finance Institute and serves as Head of Development at Global AI. He is also the co-editor of the Journal of Machine Learning in Finance.

JULIÁN ANTOLÍN CAMARENA holds a Bachelor’s, Master’s and a PhD in physics. For his Master’s he worked on the foundations of quantum mechanics examining alternative quantization schemes and their application to exotic atoms to discover new physics. His PhD dissertation work was on computational and theoretical optics, electromagnetic scattering from random surfaces, and nonlinear optimization. He then went on to a postdoctoral stint with the U.S. Army Research Laboratory working on inverse reinforcement learning for human-autonomy teaming.

ALBERTO BUENO GUERRERO has two Bachelor’s degrees in physics and economics, and a PhD in banking and finance. Since he got his doctorate, he has dedicated himself to research in mathematical finance. His work has been presented at various international conferences and published in journals such as Quantitative Finance, Journal of Derivatives, Journal of Mathematics, and Chaos, Solitons and Fractals. His article ＂Bond Market Completeness Under Stochastic Strings with Distribution-Valued Strategies＂ has been considered a feature article in Quantitative Finance.