Quantitative Hedge Funds: Discretionary, Systematic, Ai, Esg And Quantamental - Softcover

Bateson, Richard D

Softcover

ISBN 10: 1800612370 ISBN 13: 9781800612372

Publisher: WSPC (EUROPE), 2022

Synopsis

Welcome to the secretive club of modern hedge funds, where important players in the world of investing and capital markets have invested close to $4 trillion globally. If you're intrigued by the inner workings of hedge funds, investment techniques and technologies they use to source investment alpha, this book is for you. Focusing on the author's three decades of trading experience at leading banks and hedge funds, it covers both discretionary and computer-driven strategies and perspectives on AI-based and quantamental investing using new alternative data, which includes numerous examples and insights of real trades and investment strategies. No mathematical knowledge is required, with the relevant algorithms detailed in the appendices. Discretionary investing details equity and credit investing across the corporate capital structure. Through trading equities, bonds and loans, event-driven trades can target profitable special situations and relative value opportunities. Systematic trading involves computer-driven strategies derived from a scientific and statistical analysis of liquid markets. The investment strategies of both commodity trading advisors (CTAs) and long/short equity funds are detailed, from trend-following to factor-based approaches. AI investing is fashionable but does the reality for hedge funds correspond to the AI hype present in other non-financial domains? AI using neural nets and other machine learning techniques are outlined along with their practical application in regards to investing. Quantitative Hedge Funds also discusses environmental, social and governance (ESG) investing, which has rapidly evolved as the public and institutions demand solutions to global problems such as climate change, pollution and unethical labour practices. ESG investment strategies are migrating out of the long-only space and into hedge funds. Finally, the advent of big data has led to multiple alternative datasets available for hedge fund managers. The integration of alternative data into the investment process is discussed, together with the rise of so-called quantamental investing, a hybrid of the best of human skill and computer-based technologies.

About this title

About the Author

Richard D Bateson is the founder and CEO of Bateson Asset Management, an investment management company, based in London, specialising in quantitative strategies.

He has three decades of trading and investing experience across all major asset classes using a diverse range of discretionary and quantitative strategies at major fund managers, hedge funds and banks. Bateson worked at $120bn Man Group plc, one of the World's largest hedge funds and was head of Dimension, AHL's $5bn multi-strategy systematic fund, including the award-winning Evolution fund. He was also the senior quantitative research strategist for all discretionary macro, fixed income and emerging market funds at GLG Partners. In addition, he was the founder of MGIM, a quantitative corporate event-driven and relative value hedge fund manager and managing director at Royal Bank of Canada.

A former physicist at Cambridge, CERN and several other leading European research institutes, Bateson holds a first-class degree and a doctorate in physics from Cambridge University. He was a research committee member of the Oxford-Man Institute of quantitative finance at Oxford University. He is the author of Financial Derivative Investments (Imperial College Press 2011), an introduction to structured products and derivatives.

He is an industry expert in AI and alternative data in financial markets, hosts panels and is an invited speaker at major conferences in London and Europe on such matters. Dr Bateson has been engaged as an expert witness on major legal cases in the US and UK involving AI/systematic trading, hedge funds and financial markets.

Edition details

• Publisher: WSPC (EUROPE)
• Publication date: 2022
• ISBN 10: 1800612370
• ISBN 13: 9781800612372
• Binding: Paperback
• Language: English
• Number of pages: 288