Inside the Black Box explains how quantitative and algorithmic trading strategies work in non-mathematical terms supplemented by anecdotes and real-world stories. There is a large chasm in the understanding of what quants do with quants often perpetuating the darkness by cloaking even trivial facts about their strategies and operations in secrecy. Most of their strategies are understandable and with that understanding investment professionals can better assess a particular fund's value. The book also explains how quant strategies fit into a portfolio, why they are valuable, and how to evaluate a quant manager. How do quants capture alpha? What is the real level of discretion in quant trading? What is the difference between theory-driven systems vs. data-mining strategies? What are the typical structures of quant systems? How do quants model risk? How do you know if it works? What are execution algorithms?

Since the publication of ITBB's 2nd edition in 2013, a huge number of changes in the industry have occurred. The 3rd edition will address these and more:

• The explosion in the use of ML for alphas, signal mixing, data extraction and execution
• The proliferation of alt data (including guidelines on how to use it and considerations related to the research and modelling process)
• The evolution of quant and emergence of "quant 3.0"
• The overall growth in the space and its relationship to discretionary investing
• The emergence of platforms and pods as the predominant way talent is entering the space
• Changes to the dynamics of "big" vs "small" quant funds
• Newer and better approaches to portfolio optimization
• Changes to the "math" of HFT and even colocation for execution, as well as the approach to execution