If you want to understand how to succeed in the hedge fund world, read these two books
Happy holidays to all! I wanted to share brief thoughts on two excellent books that found their way to my book stack recently.
The first probably won't come as a shock, it's "The Man Who Solved the Markets" by Gregory Zuckerman. I have no idea if the title was meant with a wink, but after reading the book, I found myself thinking, a better title would be: "The man who assembled a team of engineers that spent 10 years grinding through data and code, searching for very slight probabilistic edges, and eventually building a system to exploit those edges." The book doesn't contain a single line of code but it's the best treatment I've seen for understanding the recipe for success in quant finance. Jim Simons was (maybe still is) excellent at recruiting brilliant mathematicians, physicians and coders and - crucially - creating an environment where those brilliant people could unleash their creativity. The result was not 'solving the market', as is pointed out several times by the author. The result was a very slight edge, a 51% probability of success in many instances.
I wish more people in quant finance would read this book before building data science teams and I think anyone who wants to get started in quant finance should read it. Data science and quant finance is still a human endeavor. Of course the humans need skills and intelligence, just as the players on a football team need speed and strength, but that's a necessary condition, not a sufficient condition. How will the quants work together as a team? Will they be allowed to flourish and think creatively? Will politics kill their productivity? To me it was eye-opening how times Simons had to make big decisions that had nothing to do with code and data, but had everything to do with leadership, talent, motivation, etc - the soft skills that you won't find listed in any data science job req.
I won't spoil too much except to say the hero of the book is a coder who finds a bug through obsessive poring over the code base. Another takeaway: hire people who are obsessed. Corollary: most hiring processes will filter out obsessive people who tend to be, well, obsessive and not polished interviewees.
The second book is "Red Notice" by Bill Browder. Browder founded Hermitage Capital to invest in Russia as it privatized ownership of large national enterprises. It's a great read and the last 1/3 focuses on the astounding corruption in Putin's Russia. The first 2/3 tell the story of how to succeed in the hedge fund world in the exact opposite way as Renaissance. Browder is a master at finding undervalued assets, figuring out why they're undervalued and whether they will eventually be properly priced by the market. He is a ninja of networking and human connections and is relentless in his pursuit of information that people would prefer he doesn't find. If you've ever wondered by private equity firms hire politicians and generals, this book will explain it.
These two books offer totally different yet viable paths to success in the hedge fund world. There's the pure quant path of Ren Tech. There's the connections and value seeking path of Hermitage.
If you have other recommendations in this area, leave them in a comment/reply. Thanks and enjoy!
Founder & CEO, Group 8 Security Solutions Inc. DBA Machine Learning Intelligence
9 个月Gratitude for your contribution!
Investing is competitive learning. Executive Director
4 年Don’t study finance, study mathematical topology, game theory and coding in C++, learn how tax on divi and capital gains work, make sure that none of the developers knows the full code/algorithms (in case of defection). Try to find academic literature on Henry’s signals. And don’t even think about benefiting from authoritarian regime.
CEO MacroXStudio | Measuring the world in real-time | DB exotics. BW research. MSFT PM and Senior Scientist|
4 年Great review Jonathan!
Researcher and Lecturer in AI
4 年Excactly, what you say is not only true for hedge funds but data science teams in general.