After my last book review, a reader asked how I was able to read so many books, given my other responsibilities. My answer is this: I keep a book near me at all times. When I get a break, I read a few pages. Over a week, that means a book gets read. That’s how I read so many books.
I had a number of friends that liked "Nerds on Wall Street: Math, Machines and Wired Markets," by David Leinweber (Wiley, 2009), and I liked it as well. The book has a number of strengths. The author explains complex financial instruments in relatively simple terms, and the same goes for complex trading techniques.
The author offers a history and background of computerized finance as one who was sucked into the field from a technical background that might have had him in more of a pure technological role. As I read what he went through, I said to myself: “He was seven years ahead of me.” I did my own share of innovative things, but the things that happened in his era were bigger.
He gives reasonable explanations of how computerized trading works, and what factors programmers look for in designing trading systems. He talks about the common factors that dominate trading systems, including a few that he knows of but has not published. (He gives a taste, but does not serve up the full dish.)
Like me, he serves up a full plate of data mining disasters. There are a lot of losses to be taken by those who think they have discovered a statistical regularity in the financial markets. The few significant regularities make sense to seasoned observers, and are not consistent. They pay off 70% of the time, and kill you 15% of the time.
On Wall Street, if you are really, really smart, they will hand over to you exceptionally advanced tools that you can use to destroy yourself in a unique and memorable way. So it was for LTCM.
The book is badly edited. Many elements appear multiple times with little modification, and it sometimes reads like a bunch of articles that were strung together into a book. The editors should have tried to create something more cohesive.
The last several chapters feel like an afterthought, though many of the ideas presented there are ideas that I have suggested. I have talked about splitting mortgages into smaller mortgages plus equity appreciation rights. I have also suggested creating mutual banks, rather than what was done with the TARP.
All that said, the average reader will learn a lot here. I recommend the book to those that want to dig into how the equity markets became more computerized. For those that want to understand the same for the debt markets, that book remains to be written.
If you want to buy it, you can find it here: Nerds on Wall Street: Math, Machines and Wired Markets
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