ia ≠ ai: Investment analytics in the dawn of artificial intelligence

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Credit: World Scientific

What do we mean by “ia ? ai”? Simply put, the ‘formula’ symbolizes how investment analytics (ia) is not a simplistic reapplication of artificial intelligence (ai) techniques, as the popular press likes to suggest.

Written for investment professionals keen to learn about the latest investment analytics techniques in the dawn of artificial intelligence, Investment Analytics in the Dawn of Artificial Intelligence aims to set the methodological gold standard for artificial intelligence-driven analytics for institutional investing. The book presents sophisticated best-of-class techniques to solve high dimensional problems in investment analytics with properties that go deeper than what is required to solve customary problems in engineering today.

This book focuses on solving problems for professional and institutional asset managers, whose typical portfolios may contain hundreds if not thousands of assets. These portfolios face different mathematical and practical constraints as compared to retail ones. For example, the latter may face liquidity issues when an institutional investor seeks to rebalance more than 50 assets in each monthly rebalancing cycle.

This book does not claim to have the answers to every investment problem. It presents a holistic and consistent framework to solve the full chain of problems commonly found in institutional multi-asset investing, ranging from asset selection to portfolio rebalancing to decisions to reporting. For example, the book provides an analytically rigorous derivation of a multi-scenario approach to institutional investing, unlike the traditional strategy of optimizing against a single scenario, which tends to give excessively rosy upside estimates while ignoring the potential downside. Other leading-edge topics include machine learning-based asset selection, tail-risk enhanced portfolio construction, as well as AI and big-data techniques to crawl on-line data to analyze investments.

The methodology as described by this book has its roots in a class of highly mathematical algorithms that works with three-dimensional (3D) data known as “graphs”, which can be applied to optimization and machine learning. The research efforts behind this book focuses on applying these algorithms to solve more complex problems with financial data, which tend to be in higher dimensions (easily over 100), based on probability distributions, with time subscripts and jumps. The 3D research analogy is to train a navigation algorithm when the way-finding coordinates and obstacles such as buildings change dynamically and are expressed in higher dimensions with jumps.

Dr Bernard lee will be presenting one use case of the methodologies described by the book as applied to the US-China Trade War at the Fintech and Regtech Summit https://finsum.jp/ to be held in Tokyo, Japan, from 3 to 6 September 2019. He welcomes the opportunity to be interviewed by the financial press about this book.

Investment Analytics in the Dawn of Artificial Intelligence retails for US$48 / &40 (paperback) and US$98 / £81 (hardback). To order or know more about the book, visit http://www.worldscientific.com/worldscibooks/10.1142/9823.

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About the Author

Dr. Bernard Lee is the Founder and CEO of HedgeSPA, USA. ‘HedgeSPA’ stands for ‘Sophisticated Predictive Analytics for Hedge Funds and Institutions’. Previously, he was a managing director in the Portfolio Management Group of BlackRock in New York City as well as a finance professor who has taught and guest-lectured at a number of top universities globally, including Columbia University, NYU Courant, Stanford Business School and MIT-Tsinghua.

About World Scientific Publishing Co.

World Scientific Publishing is a leading international independent publisher of books and journals for the scholarly, research and professional communities. World Scientific collaborates with prestigious organisations like the Nobel Foundation and US National Academies Press to bring high quality academic and professional content to researchers and academics worldwide. The company publishes about 600 books and over 140 journals in various fields annually. To find out more about World Scientific, please visit http://www.worldscientific.com.

For more information, contact Amanda at [email protected]

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Amanda Yun
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Original Source

https://www.worldscientific.com/page/pressroom/2019-08-23-01

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