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Quantitative Portfolio Optimization: Theory and Practice by Miquel Noguer

Quantitative Portfolio Optimization: Theory and Practice

by Miquel Noguer
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Book cover type: Hardcover
  • ISBN13: 9781394281312
  • Binding: Hardcover
  • Subject: N/A
  • Publisher: Wiley
  • Publisher Imprint: Wiley
  • Publication Date:
  • Pages: N/A
  • Original Price: USD 94.95
  • Language: English
  • Edition: N/A
  • Item Weight: 694 grams
  • BISAC Subject(s): Investments & Securities / Portfolio Management

From the Back Cover

PRAISE FOR
QUANTITATIVE PORTFOLIO OPTIMIZATIONOPTIMIZATION

"This book provides an excellent exposition on portfolio optimization, serving not only as a self-contained guide to this important topic, but also modernizing the field with the latest advances in battle-tested machine learning approaches. The book is well structured and application centric. This is a must read for every quantitative portfolio manager."
-- Matthew Dixon, FRM, Ph.D., Associate Professor of Applied Math at the Illinois Institute of Technology and an Affiliate Associate Professor of the Stuart School of Business

"Quantitative Portfolio Optimization: Advanced Techniques and Applications is an essential guide for anyone seeking to navigate the complex world of modern portfolio management. This book masterfully blends the foundational principles of portfolio theory with cutting-edge advancements in risk management, dynamic models, and control systems. Its integration of machine learning and deep learning offers readers a forward-looking perspective on leveraging AI-driven techniques for optimization. What truly sets this book apart is its comprehensive approach. From theoretical insights to practical backtesting applications, it equips professionals, researchers, and students with the tools to design and refine robust investment strategies. Whether you're delving into the nuances of risk modelling or exploring dynamic portfolio control with the latest AI methodologies, this text is an invaluable resource. This book isn't just about managing portfolios--it's about mastering the art and science behind it. Highly recommended for anyone aiming to achieve excellence in quantitative finance and portfolio optimization."
--Daniel Bloch, Director, Quant Finance Limited

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.

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