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Wiley's Latest and Forthcoming Finance Titles

Wiley is pleased to announce the publication of two new finance titles.

Wednesday, April 25, 2018 11:39 am EDT

The first, A Guide to Financial Regulation for Fintech Entrepreneurs by Stefan Loesch, clearly explains the purpose and structure of the regulatory environment, and provides readers with frameworks that enable them to develop an effective regulatory strategy.

Fintech has been growing dramatically over the last few years, and it is now an important sector in its own right. This means that Fintech companies, who could so far often rely on a comparatively lenient regulatory regime, will now have to give serious thoughts on compliance with applicable regulatory rules. 

In the first part of the book, Loesch covers why financial services regulation exists, what its goals are and how Fintech executives can use this regulation to gain a strategic advantage for their companies.

The second part provides a more detailed map of the key regulations that Fintech companies have to follow – identifying the most relevant ones and then distilling down the thousands of pages of prose from regulatory texts to enable readers to quickly identify the areas which matter to them.

Operating in a highly regulated environment is not all bad - companies that can play the regulatory game well have a strategic advantage. Written for professionals, this easy-to-read introduction to financial services and its regulation is for anyone involved in formulating or executing a Fintech start-up strategy or whose job touches financial services regulation.

The second title is Marcos López De Prado’s Advances in Financial Machine Learning.

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

Readers of Advances in Financial Machine Learning will discover 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; and how to backtest discoveries while avoiding false positives.

Written by a recognised expert and portfolio manager, this guidebook offers authoritative insight into using advanced ML solutions to overcome real-world investment problems and will equip investment professionals and data scientists at the forefront of this evolution with the groundbreaking tools needed to succeed in modern finance.

Featuring code snippets and hands-on exercises that facilitate the quick absorption and application of best practices in the real world, Advances in Financial Machine Learning will help readers get ahead of tomorrow’s competition by:

  • Tackling today's most challenging aspects of applying ML algorithms to financial strategies, including backtest overfitting
  • Using improved tactics to structure financial data so it produces better outcomes with ML algorithms
  • Conducting superior research with ML algorithms as well as accurately validating the solutions they discover
  • Learning the tricks of the trade from one of the largest ML investment managers


About the Books:

  • A Guide to Financial Regulation for Fintech Entrepreneurs, by Stefan Loesch, will be published April 2018 in paperback, priced £29.99/ US$37.50/ €36.00, ISBN: 978-1-119-43670-6
  • Advances in Financial Machine Learning by Marcos López De Prado, will be published May 2018 in hardcover, priced £42.50/ US$50.00/ €45.50, ISBN: 978-1-119-48208-6

About the Authors:

A Guide to Financial Regulation for Fintech Entrepreneurs

STEFAN LOESCH is an experienced financial services executive, tech entrepreneur, and author. He is currently working on a number of ventures that use crypto and blockchain technology within the framework of traditional finance and regulation. His past ventures include an early stage peer-to-peer lending start-up and an edtech start-up. He is co-editor and one of the authors of PRMIA's Professional Risk Managers Handbook.

In the past, he was an Executive Director at J.P. Morgan, and a consultant in McKinsey's Corporate Finance practice. He holds a degree in Physics from the University of Bonn and an MBA from INSEAD.

Advances in Financial Machine Learning

DR. MARCOS LÓPEZ DE PRADO manages several multibillion-dollar funds for institutional investors using ML algorithms. Marcos is also a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). One of the top-10 most read authors in finance (SSRN's rankings), he has published dozens of scientific articles on ML in the leading academic journals, and he holds multiple international patent applications on algorithmic trading. 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 Financial ML course at the School of Engineering. Marcos has an Erdös #2 and an Einstein #4 according to the American Mathematical Society.

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