Book Report: “The Quants” by Scott Patterson (video of him on the Daily Show), staff reporter for the Wall Street Journal. How the new breed of math whizzes conquered Wall Street and nearly destroyed it. I was given for Christmas this book to read and I took the time to read through it over the weekend on the way to Paris, via high speed rail. I thought I would give you my take aways from it.

First of all what is a Quant? A quantitative analyst is a person who works in finance using numerical or quantitative techniques. Similar work is done in most other modern industries, but the work is not always called quantitative analysis. In the investment industry, people who perform quantitative analysis are frequently called Quants. The book for me focused more on a biographical sketch of these math wizards, and their rise into Wall Street, but lacked a little on the actual Quant theories themselves.

This topic is very fascinating to me as I picture myself as a Quant wannabe. I have spent hundreds and hundreds of hours in search of the “Holy Grail,” in algorithmic trading strategies. Trying to make sense out of randomness with some success – but no where near these guys. These exercises have enable me to discern quickly when a trader presents his trade ideas, on whether they have merit or not. However, I am never quick to dismiss. Sometimes they may not have the good idea, but i am always willing to learn or even have their ideas trigger new thoughts of my own.

The book starts in 1967, with the famous mathematician Ed Thorp (see thumbnail), who revolutionized Wall Street with a method of using math and computers to predict the future of stock prices and then goes on to describe some of his followers; Guru Ken Griffin of Citadel Investment Group, Peter Muller of Morgan Stanley’s hedge fund PDT, Cliff Asness founder of AQR Capital Management, Jim Simons of Renaissance Technologies, and Boaz Weinstein who ran hedge funds at both Morgan Stanley and Deutsche Bank. Thorpe also was an avid gambler who beat the odds and was banned from casinos.

The book describes the Quants as nerds who could not get dates in High School, and spent their time conducting bizarre science and math experiments. They also were strong believers in Eugene Fama and the “efficient market theory.” Eugene Fama believes that the market is efficient and that it always reflecting all known data. When the market is not priced correctly knowledgeable investors will quickly come in and either buy or sell to the point where the market reaches equilibrium. This is where the Quants come in. They would use their complex formulas to find these small inefficiencies in the market and using rapid trading techniques profit off these inefficiencies.

As I was reading through the book I marked pages that jumped out to me on certain interesting points/comments and I share some of them with you here:

• The basis of many Quant theories have their origins in gambling odds making. Many of the Quants were avid poker, black jack and roulette players – that inspired them to beat the odds – and they did.
• Issac Newton, after loosing 20,000 pounds (a fortune in those days), in what was called the 1720 South Sea Bubble said; “I can calculate the motion of heavenly bodies but not the madness of people.”
• The 1987 market crash of 23% was a 27 standard deviation. It is like flipping a coin 100 times and it coming up heads 99 times in a row. If your strategy is to double down exponentially, you are all most 100% guaranteed to lose.
• Most Quant strategies loosely described seem to focus on arbitrage.
• Fat tailed distribution theory states that there are more exceptions to the rule than one would would logically believe. In other wards it is not a true bell curve, it has fat tails on either side of the bell curve. This seems to imply that there is a potential profit point between the top of the bell curve to the outer extremes (i.e. double down to a certain exponentiation stop point.).
• Renaissance’s secretive flagship Medallion Hedge Fund was the most successful Quant fund in the industry. Yielding 40% per year for nearly 3 decades. Why people think they can do this in one month consistently - are guaranteed to be losers.
• Renaissance hired many x-IBMers from their voice recognition unit to programme their Quant fund strategies. The theory is that many of the same look ahead speech recognition algorithms are used in predicting future stock price movements. The theory is buried somewhere in harmonic cycles.
• Efficient markets are over taken by wilder side of human behavior – but eventually time and logic take over.
• One reason the banks got so heavily into the mortgage securitization market, was because Quants thought they were diversified. Diversification does not always mean safety, if all the diversification is actually the same bet.
• The book goes into quite a long detailed explanation of the credit markets build up and its collapse. One thing that shouts out to me is that clearly it was simple corporate greed and a mistakes made by Quant assumptions of risk, was at the heart of the 2007 bubble. People and government regulators relied too much on these people because the were just far to impressed by their most recent past successes. They are making big money so they must be right – little me should not question the powerful.
• During the melt down – risk control got thrown out the window by the Quants (over betting). Sound familiar traders? Greed + Incompetence + a belief in “efficient markets theory” = Disaster. Some believe that Quants were at the heart of the near financial collapse. As the Quants move into high frequency trading, the next financial collapse will happen in 5 minuets not 5 months.

In the end the Quants started to collapse even a year before the real economic collapse in September 2008. The massive losses for the Quant funds started in August 2007 before the damage was really being felt in the rest of the financial sector. Suddenly, the models the Quants were using started not working. What happened was what Nissim Taleb described as a “a Black Swan event”. This refers to unexpected events that have a large and sudden impact. So the “efficient market theory” maybe true after all and the “Holy Grail” of Quants will remain allusive. Quitely though they are making a come back via high frequency trading algorithms – the story is not over. The Quants II?