Название: Quantitative Hedge Funds: Discretionary, Systematic, AI, ESG and Quantamental
Автор: Richard D Bateson
Издательство: World Scientific Publishing
Год: 2023
Страниц: 288
Язык: английский
Формат: pdf (true), epub
Размер: 30.4 MB

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.

Almost 30 years ago there was a flurry of interest in using artificial neural networks (ANNs) for predicting financial markets. Desktop computers, limited in processing power with DOS or buggy versions of Windows allowed people to experiment with neural nets. Although processing power was low and memories small, operating systems were less bloated. By using complied C++, surprisingly powerful neural nets could be built. One of my first bosses in a Japanese bank was a pioneer and had constructed, as a hobby, an ANN fx trading system in his garage.