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Entry from December 20, 2008
Quant or Quant Jock (quantitative analyst)

A “quant” is a “quantitative analyst”—a person who applies mathematical models to the finance of Wall Street. Many college MBA programs trained “quants,” and these students were often called “quant jocks.” The term “quant” is cited in print from the 1970s; “quant jock” is cited in print from the 1980s. Many “quants” have physics degrees, but William Safire’s speculation (see the July 6. 1986 citation below) that “quant” is from “quantum” does not appear to have any factual support.

“Quants Do It With Models” became a popular T-shirt in the 2000s. In the recession of 2007-2008, quants were blamed for the excessive risks that some financial companies took in subprime mortgages and in related financial instruments.

Wikipedia: Quantitative analyst
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 called quantitative analysis. In the investment industry, people who perform quantitative analysis are frequently called quants.

Although the original quants were concerned with risk management and derivatives pricing, the meaning of the term has expanded over time to include those individuals involved in almost any application of mathematics in finance. An example is statistical arbitrage.

History
Quantitative finance started in the U.S. in the 1930s as some astute investors began using mathematical formulae to price stocks and bonds.

Harry Markowitz’s 1952 Ph.D thesis “Portfolio Selection” was one of the first papers to formally adapt mathematical concepts to finance. Markowitz formalized a notion of mean return and covariances for common stocks which allowed him to quantify the concept of “diversification” in a market. He showed how to compute the mean return and variance for a given portfolio and argued that investors should hold only those portfolios whose variance is minimal among all portfolios with a given mean return. Although the language of finance now involves Itō calculus, minimization of risk in a quantifiable manner underlies much of the modern theory.

In 1969 Robert Merton introduced stochastic calculus into the study of finance. Merton was motivated by the desire to understand how prices are set in financial markets, which is the classical economics question of “equilibrium,” and in later papers he used the machinery of stochastic calculus to begin investigation of this issue.

At the same time as Merton’s work and with Merton’s assistance, Fischer Black and Myron Scholes were developing their option pricing formula, which led to winning the 1997 Nobel Prize in Economics. It provided a solution for a practical problem, that of finding a fair price for a European call option, i.e., the right to buy one share of a given stock at a specified price and time. Such options are frequently purchased by investors as a risk-hedging device. In 1981, Harrison and Pliska used the general theory of continuous-time stochastic processes to put the Black-Scholes option pricing formula on a solid theoretical basis, and as a result, showed how to price numerous other “derivative” securities.

Education
Quants often come from physics, engineering or mathematics backgrounds rather than finance related fields, and quants are a major source of employment for people with physics, mathematics, and engineering Ph.D’s. Typically a quant will also need extensive skills in computer programming.

This demand for quants has led to the creation of specialized Masters and PhD courses in mathematical finance, computational finance, and/or financial reinsurance. In particular, Masters degrees in financial engineering and financial analysis are becoming more popular with students and with employers. London’s Cass Business School was the pioneer of quantitative finance programs in Europe, with its MSc Quantitative Finance as well as the MSc Financial Mathematics and MSc Mathematical Trading and Finance programs providing some leading global research. Carnegie Mellon’s Tepper School of Business, which created the Masters degree in financial engineering, reported a 21% increase in applicants to their MS in Computational Finance program, which is on top of a 48% increase in the year before. These Masters level programs are generally one year in length and more focused than the broader MBA degree.

Front Office Quant
Within Banking, quants are employed to support trading and sales functions. At the very simple level Banks buy and sell investment products known as Stocks (Equity) and Bonds (Debt). They can gain a good idea of a fair price to charge for these because they are liquid instruments (many people are buying and selling them) and thus they are governed by the market principles of supply and demand – the lower your price the more people will buy from you, the higher your price the more people will sell to you. Over the last 30 years a massive industry in derivative securities has developed as the risk preferences and profiles of customers have matured. The idiosyncratic, customised nature of many of these products can make them relatively illiquid and hence there are no handy market prices available. The products are managed, that is, actualised, priced and hedged, by means of financial models. The models are implemented as software and then embedded in front-office risk management systems. The role of the quant is to develop these models.

Mathematical and statistical approaches
According to Fund of Funds analyst Fred Gehm, “There are two types of quantitative analysis and, therefore, two types of quants. One type works primarily with mathematical models and the other primarily with statistical models. While there is no logical reason why one person can’t do both kinds of work, this doesn’t seem to happen, perhaps because these types demand different skill sets and, much more important, different psychologies.”

A typical problem for a numerically oriented quantitative analyst would be to develop a model for pricing and managing a complex derivative product.

A typical problem for statistically oriented quantitative analyst would be to develop a model for deciding which stocks are relatively expensive and which stocks are relatively cheap. The model might include a company’s book value to price ratio, its trailing earnings to price ratio and other accounting factors. An investment manager might implement this analysis by buying the underpriced stocks, selling the overpriced stocks or both.

One of the principal mathematical tools of quantitative finance is stochastic calculus.

According to a July 2008 Aite Group report, today quants often use alpha generation platforms to help them develop financial models. These software solutions enable quants to centralize and streamline the alpha generation process.

Zazzle.com
Quants do it with models
T-shirt
by tomyork

MSN Encarta Dictionary
quant [ kwont ] (plural quants)
noun
Definition:
expert in quantitative data: somebody skilled in computing and the analysis of quantitative data, employed by a company to make financial predictions ( slang )
[Late 20th century. Shortening of quantitative]

MSN Encarta Dictionary
quant jock
noun
Definition:
U.S. commerce ( slang )
Same as quant

(Oxford English Dictionary)
Finance and Econ. A quantitative analyst; a person who excels at or depends upon quantitative methods of analysis.
1979 Forbes 16 Apr. 120/2 Russell isn’t a ‘quant’, one of the young consultants who do much of their monitoring by questionnaire and most of their evaluating by quantitative analysis.
1989 Computers in Banking (Nexis) July 26 Quants, usually trained in mathematics, physics, or engineering disciplines, are being increasingly hired by Wall Street firms as analysts.
1993 Harper’s Mag. Oct. 64 A group of ‘policy wonks’ and quants disdainful of the sticky dilemmas inherent in moral reasoning.
2000 S. HÖRTER in L. Schuster Shareholder Value Managem. Banks ii. 31 The top management of financial firms has to be able to interpret figures… Otherwise, power will informally shift to ‘quants’ and risk managers.

quant jock n. Finance slang.
1985 Business Week (Nexis) 30 Dec. 150 Chamberlin and Stanley Levine, the brokerage’s vice-president,..have spent a good part of their careers as ‘*quant jocks’, relying on computers to outsmart the Wall Street herd.
2000 New Scientist 30 Sept. 56/1 Bankers have such a high regard for mathematical modelling and forecasting that they call people employed to do it ‘rocket scientists’ and ‘quant jocks’.

Securities and Federal Corporate Law
By Harold S. Bloomenthal and Samuel Wolff
1972
Pg. ?:
... a new generation of Wall Street geniuses have begun to market these products out across the country. By breaking down the price movement into individual deltas and gammas, betas, and vegas dancing across the computer screen, the quants, that is the mathematical geniuses who call themselves quants because they deal in quantitative mathematics, they deal as physicists, who have moved over from the nuclear physicist world into the world of creating these new products, have created the new world of…

The Dow Jones-Irwin Guide to Modern Portfolio Theory
By Robert Hagin
1980
Pg. 284:
Beyond the new words like quants (those who apply quantitative investment techniques), super-quants, pseudo-quants, and even turncoat-quants (those who purportedly understand…

Volume VII
1985
Pg. 29:
This is, however, a technically oriented course, although not one in which a student must be a certified “quant jock” to have any chance of survival.

6 July 1986, New York (NY) Times, “On Language: Quants Ain’t Quaint” by William Safire, pg. SM8:
Several professors, demanding anonymity because a confession of ignorance is career-threatening, have written to ask for the definition of quant.

At first, the answer seemed obvious: a shortening of quantum jump, which most people think means a huge leap, as in “from teaching courses in Corp Fin to cutting actual throats on Wall Street is a quantum jump.” Physicists grumble about this, holding that the phrase means the sudden emission or absorption of an atom’s energy, coming from quantum theory, which argues that energy is transmitted jerkily and only in multiples of indivisible units called quanta. Strict constructionists would say that a quantum is very small hence a quantum jump is no big deal; they are fighting the problem. The meaning is not what the Big Brains think, it is what all the Little Brains think, and a quantum jump is over a brook too broad for leaping.

On-site inspection offers a surprise: although a quant comes from the clipped quantum jump, its meaning is taken from the second word. A quant is a rocket scientist.

No, a rocket scientist in faculty slang is not a scientist who works on rockets. Werner von Braun was another kind of rocket scientist entirely. “A rocket scientist,” I am informed by Ray Healey Jr. of Forbes magazine, “is an academic superstar, especially in math or the physical sciences, who is lured away from the hallowed halls to work on Wall Street.” By putting their number-crunching genius to work on less-academic pursuits, these former theoreticians devise stratagems for making money in great bundles. “Apparently, zero-coupon bonds are an example of a new investment vehicle created by a rocket scientist,” Mr. Healey said.

Thus, quants, or rocket scientists, are great brains drained off campus by the business world.

By John A. Byrne
1990
Pg. 98:
But perhaps more than any other top B-school, Carnegie is something of a haven for the “quant-jocks” — the commonly used term for MBAs obsessed with mathematics and quantitative methods.

Robust Portfolio Optimization and Management
By Frank J. Fabozzi, Petter N. Kolm, Dessislava Pachamanova and Sergio M. Focardi
Hoboken, NJ: John Wiley and Sons
2007
Pg. 6:
The term “quant” which is short for quantitative analyst (someone who works in the financial markets developing mathematical models) was popularized, among other things, by Emanuel Derman in his book My Life as a Quant (Hoboken, NJ: John Wiley & Sons, 2004). On a lighter note, a T-shirt with the words “Quants Do It with Models” circulated among some quantitative analysts on Wall Street a few years ago.

WallStreetOasis.com
Quants Do It With Models
by alcman on 6/27/08 at 11:32pm
...from a T-Shirt distributed to interns of Goldman Sachs Quantitative Strategies last year.
(Just thought that was funny!)

Forbes.com
Commentary
Don’t Blame The Quants

Steven Shreve, 10.08.08, 12:01 AM EDT
It’s the executives who didn’t listen.
(...)
It is easy under these circumstances to point an accusing finger at the “quants” on Wall Street, that cadre of mathematics and physics Ph.D.s who crunch numbers in esoteric models. Without the quants, the complicated mortgage-backed securities that fueled the housing bubble and led to the freezing of credit might not have been created. The models used by the quants determine the prices of those securities and steer the traders who make markets in them. Without this guidance, the banks might not have touched them in the first place. To prevent a recurrence of financial crises, some call for a return to a simpler time, before derivative securities and the quants who analyze them—a time when investors bought stocks and bonds and little else.

Such complaints miss the point. When a bridge collapses, no one demands the abolition of civil engineering. One first determines if faulty engineering or shoddy construction caused the collapse. If engineering is to blame, the solution is better—not less—engineering. Furthermore, it would be preposterous to replace the bridge with a slower, less efficient ferry rather than to rebuild the bridge and overcome the obstacle.

The Associated Press
Layoffs expected to decimate Wall Street ranks
By STEVENSON JACOBS – Dec 7, 2008
NEW YORK (AP) — The U.S. financial services industry is witnessing the bursting of yet another bubble. This time, it’s the industry itself.
(...)
Another group whose ranks are being thinned are financial engineers. Those are the math whizzes, lured from top schools to build complex computer trading models at hedge funds and big Wall Street firms. The so-called “quants” have been blamed for underestimating the risks of mortgage-related securities, derivatives and other exotic assets that helped trigger the financial crisis.

Forbes.com
Commentary
Do Blame The Quants

Pablo Triana Portela, 12.09.08, 12:00 AM EST
Unlimited irreverence toward mathematical market models.
(...)
Derivatives are not theory or math, and they never needed the quantitative imprimatur before they could exist. Derivatives are a business, not a science. And they have, overwhelmingly, proved wildly useful. As such, they should be protected from those factors that may threaten their reputation and, perhaps, continued existence. Like, for example, deleteriously unworldly theoretical machinations with a habit of wreaking havoc.

One excruciatingly urgent lesson from this crisis is that we must develop unlimited skepticism and irreverence toward the application of mathematical models in the markets. We need to stop taking quantitative gadgets so seriously, and start to take the perilousness of quantitative gadgets more seriously. We can’t let this happen again.

Posted by Barry Popik
New York CityBanking/Finance/Insurance • (0) Comments • Saturday, December 20, 2008 • Permalink