I finally finished readingÂ Nerds on Wall Streetby David J. Leinweber the other day. It’s a book I actually started reading nearly a year ago when I was preparing for my visit to the ICMA Centre at the University of Reading to talk to some of the faculty there about the PhD program. I figured it wouldn’t hurt to bone up on some of the history of high quantitative methods employed by Wall Street since that was what I was about to be talking about. I didn’t end up getting overly far in the book because of other things coming up, and have been reading it slowly, in fits and starts since then. Not that this should be taken to indicate the quality of the book. It’s just not the type of thing I normally pick up when I’m looking to kick back and relax.
Nerds on Wall Street largely comprises ofÂ a collection of articles the author has published over the years, though I personally didn’t feel like I was reading a bunch of separate items. Leinweber did a pretty good job smoothing out the transitions. The result is a pretty expansive look at the history of computerized methods applied in the financial markets, the author having been involved in quite a bit of it himself. It covers subjects from fairly simple methods just about any trader or investor can use today (many of which are relatively recent developments) to highly complex systems employed primarily by institutional level operators.
For traders looking for something that goes beyond a history lesson,Â there are a couple of sections I really think have a lot of value. One is the chapter on data mining which does a good job of highlighting the pitfalls of trading system back-testing. Another is the chapter on stock market manipulation across the years, which ties in withÂ a chapter on collective intelligence, social media, etc.
My one disappointment with the book is toward the end where the author starts talking about ideas for resolving the banking crisis (the book was published in 2009)Â because it’s dated at this point (which comes after a rant about how financial engineering was taken to a ridiculous extreme). One can also question the last chapter which talks about how the brain power so recently applied to coming up with complex financial engineering could be shifted to the energy sector, though it does make some interesting points. All in all, though, I found the book a very interesting and potentially valuable read.
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