Tom J. Espel

Pr Shreeve is often credited as having created the first modern quantitative finance curriculum at Carnegie Mellon University. He published two books, the Stochastic Calculus for Finance series, from those lectures and the second volume dedicated to continuous-time models is one of the most known and most used books at the graduate level in quantitative finance.

Analysis of Financial Time Series is a practical catalogue of most of the common concepts and techniques in quantitative finance. I recommend this book to anyone interested in the field, it's an investment that will yield over and over again. I have found myself referring back to this book on multiple occasions, Tsay's style is clear and the book is well-organised for easy referencing.

Lehalle and Laruelle conduct a detailed analysis of the market microstructure properties of European equities. The book only has a few chapters and is better read from start to finish to capture the authors' perspective. This is one of my favourite books in the field of liquidity fragmentation, and the ideas from this book can be applied to any asset class.
Both first and second editions are good, the second includes updates for regulations, covers more modern topics and a foreword by Almgren.

In this book, Olivier Guéant introduces most of the mathematical tools needed in the day-to-day of algorithmic trading: Almgren-Chriss, alongside numerical methods; Avellaneda-Stoikov; and there is also one chapter about options. The proofs are clear, elegant and concise.

This book, part of Taleb's Incerto series, does not need an introduction. 😃
The other titles in the series are Fooled by Randomness, The Bed of Procrustes (closer to a philosophical essay) and Antifragile.

Michael Lewis is my favourite author on finance-related topics. His works are mostly nonfiction but they read like novels. Flash Boys is the true story of the birth of high-frequency stock trading in the US.

The authors are among the most famous experts in the field. Deep Learning is a comprehensive catalogue of models, with mathematical concepts. There is a free version of the book available online.

This book is the foundation of modern reinforcement learning and is still the reference in the field. Any of the two editions is an excellent introduction to that specific class of algorithms.

Murphy's book is a comprehensive study of machine learning models and is, in my humble opinion, a must-have for anyone who uses such models in high-stakes contexts. Its compelling probabilistic interpretation of models, alongside the broad range of algorithms, make it a perfect companion when choosing which implementation suits best a given problem. The book is very dense and I recommend a digital edition if possible.

Probably the podcast of quantitative finance. I think it's the best one out there, and most of the influential practitioners in the field end up being interviewed by Corey Hoffstein. Flirting With Models is a great podcast which balances the at times very technical content and makes it accessible. It airs about every other week.

Patrick Boyle's podcast On Finance is entertaining and informative. He's a professional fund manager and his perspective on a very broad range of events in the financial world is very informative. He has a YouTube channel but it can be listened to as a podcast with audio only.

Chat with Traders is one of the best-known and longest-running podcasts that relate to trading and finance. The episodes are in-depth interviews, most episodes stretch beyond one hour, of traders who share their journey, tips and techniques.

Jon's video essays are hands down some of the best-researched and most accurate in the fields of both the electronics industry and the broader Asian economies. The content is technical and of incredible quality.

Guy Raz interviews twice a week entrepreneurs who share their journey. It's a very inspirational podcast and the guests come from a broad range of industries and experiences.