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Advances in Financial Machine Learning

Autor Marcos Lopez de Prado
en Limba Engleză Hardback – 3 mai 2018
Praise for ADVANCES in FINANCIAL MACHINE LEARNING
"Dr. López de Prado has written the first comprehensive book describing the application of modern ML to financial modeling. The book blends the latest technological developments in ML with critical life lessons learned from the author's decades of financial experience in leading academic and industrial institutions. I highly recommend this exciting book to both prospective students of financial ML and the professors and supervisors who teach and guide them." --PROF. PETER CARR, Chair of the Finance and Risk Engineering Department, NYU Tandon School of Engineering
"Financial problems require very distinct machine learning solutions. Dr. López de Prado's book is the first one to characterize what makes standard machine learning tools fail when applied to the field of finance, and the first one to provide practical solutions to unique challenges faced by asset managers. Everyone who wants to understand the future of finance should read this book." --PROF. FRANK FABOZZI, EDHEC Business School; Editor of The Journal of Portfolio Management
"Marcos has assembled in one place an invaluable set of lessons and techniques for practitioners seeking to deploy machine learning methods in finance. Marcos's insightful book is laden with useful advice to help keep a curious practitioner from going down any number of blind alleys, or shooting oneself in the foot." --ROSS GARON, Head of Cubist Systematic Strategies; Managing Director, Point72 Asset Management
"The first wave of quantitative innovation in finance was led by Markowitz optimization. Machine learning is the second wave and it will touch every aspect of finance. López de Prado's Advances in Financial Machine Learning is essential for readers who want to be ahead of the technology rather than being replaced by it." --PROF. CAMPBELL HARVEY, Duke University; Former President of the American Finance Association
"The author's academic and professional first-rate credentials shine through the pages of this book-- indeed, I could think of few, if any, authors better suited to explaining both the theoretical and the practical aspects of this new and (for most)unfamiliar subject. Destined to become a classic in this rapidly burgeoning field." --PROF. RICCARDO REBONATO, EDHEC Business School; Former Global Head of Rates and FX Analytics at PIMCO
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Specificații

ISBN-13: 9781119482086
ISBN-10: 1119482089
Pagini: 400
Dimensiuni: 160 x 235 x 26 mm
Greutate: 0.66 kg
Editura: Wiley
Locul publicării:Hoboken, United States

Public țintă

Investment professionals, data scientists, and students.

Descriere

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations.

Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting.

Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
 


Notă biografică

DR. MARCOS LÓPEZ DE PRADO is a principal at AQR Capital Management, and its head of machine learning. Marcos is also a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). SSRN ranks him as one of the most-read authors in economics, and he has published dozens of scientific articles on machine learning and supercomputing in the leading academic journals. Marcos earned a PhD in financial economics (2003), a second PhD in mathematical finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a graduate course in financial machine learning at the School of Engineering. Marcos has an Erdös #2 and an Einstein #4 according to the American Mathematical Society.