This weekend I read David Leinweber’s book Nerds on Wall Street: Math, Machines and Wired Markets. While sitting at Radiance Tea, I read a book review in the Wall Street Journal. Since I had previously enjoyed David’s chapter in How I Became a Quant, I paid $24 and instantly downloaded it to my Kindle.
David’s has a clear, concise, and humorous writing style. Also, since I’m also a (significantly more junior) nerd on Wall Street, I’m in his target audience.
My big takeaway is the sense of pragmaticism and passion that oozes out of his stories. It’s clear that technology makes him tick, and that he’s always right on top of the newest techniques. And he’s been at it for years, so his stories all carry true gravitas.
Data mining while developing quantitative strategies is one principal theme that’s addressed in most of the book’s chapters. Personally, I wish he had addressed this in greater detail. It’s easy to dismiss eggregious data mining that links butter production to S&P returns. It’s also easy to say “withhold data from your training data.” I also felt that when he discussed a specific example of using genetic programming, he essentially admitted that the strategy was datamined, yet restrained by common sense.
I recommend this book. It’s a quick and enjoyable read about an interesting topic.
