Advances in Financial Machine Learning - by Marcos Lopez de Prado (Hardcover)
Similar Products
Products of same category from the store
All
Product info
<p/><br></br><p><b> About the Book </b></p></br></br>"This book begins by structuring financial data in a way that is amenable to machine learning (ML) algorithms. Then, the author discusses how to conduct research with ML algorithms on that data and how to backtest your discoveries. Most of the problems and solutions are explained using math, supported by code. This makes the book very practical and hands-on. Readers become active users who can test the solutions proposed in their work. Readers will learn how to structure, label, weight, and backtest data. Machine learning is the future, and this book will equip investment professionals with the tools to utilize it moving forward"--<p/><br></br><p><b> Book Synopsis </b></p></br></br><p>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.</p><p/><br></br><p><b> From the Back Cover </b></p></br></br><p>Today's machine learning (ML) algorithms have conquered the major strategy games, and are routinely used to execute tasks once only possible by a limited group of experts. Over the next few years, ML algorithms will transform finance beyond anything we know today. <i>Advances in Financial Machine Learning</i> was written for the investment professionals and data scientists at the forefront of this evolution. <p>This one-of-a-kind, practical guidebook is your go-to resource of authoritative insight into using advanced ML solutions to overcome real-world investment problems. It demystifies the entire subject and unveils cutting-edge ML techniques specific to investing. With step-by-step clarity and purpose, it quickly brings you up to speed on fully proven approaches to data analysis, model research, and discovery evaluation. Then, it shines a light on the nuanced details behind innovative ways to extract informative features from financial data. To streamline implementation, it gives you valuable recipes for high-performance computing systems optimized to handle this type of financial data analysis. <p><i>Advances in Financial Machine Learning</i> crosses the proverbial divide that separates academia and the industry. It does not advocate a theory merely because of its mathematical beauty, and it does not propose a solution just because it appears to work. The author transmits the kind of knowledge that only comes from experience, formalized in a rigorous manner. <p>This turnkey guide is designed to be immediately useful to the practitioner by featuring code snippets and hands-on exercises that facilitate the quick absorption and application of best practices in the real world. <p>Stop guessing and profit off data by: <ul> <li>Tackling today's most challenging aspects of applying ML algorithms to financial strategies, including backtest overfitting</li> <li>Using improved tactics to structure financial data so it produces better outcomes with ML algorithms</li> <li>Conducting superior research with ML algorithms as well as accurately validating the solutions you discover</li> <li>Learning the tricks of the trade from one of the largest ML investment managers</li> </ul> <p>Put yourself ahead of tomorrow's competition today with <i>Advances in Financial Machine Learning.</i><p/><br></br><p><b> About the Author </b></p></br></br><p><b>DR. MARCOS LÓPEZ DE PRADO</b> 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.
Price History
Price Archive shows prices from various stores, lets you see history and find the cheapest. There is no actual sale on the website. For all support, inquiry and suggestion messagescommunication@pricearchive.us