Machine Learning
A historical perspective on artificial intelligence is provided and a light, semi-technical overview of prevailing tools and techniques are given to help understand where real value ends and speculative hype begins.
Abstract
Machine learning is more fashionable than ever for problems in data science, predictive modeling, and quantitative asset management. Developments in the field have revolutionized many aspects of modern life. Nevertheless, it is sometimes difficult to understand where real value ends and speculative hype begins. Here we attempt to demystify the topic. We provide a historical perspective on artificial intelligence and give a light, semi-technical overview of prevailing tools and techniques. We conclude with a brief discussion of the implications for investment management.