Quantitative analyst
From Wikipedia, the free encyclopedia
A quantitative analyst is a person who works in the investment industry as a research analyst applying numerical or quantitative techniques to investment issues. 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.
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[edit] History
Quantitative finance started in the U.S. in the 1930s as some astute investors began using mathematical formulas 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.
[edit] 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 quanatitative finance programs in Europe, with its MSc Quanatitive 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[1]. The University of California Berkeley's program in Financial Engineering through their Haas School of Business admits 60 students each year. Other well known programs are provided by the University of Chicago, Cornell University, Indiana University, Illinois Institute of Technology, Columbia University, Purdue University, and New York University. This surge in popularity has led other schools (Boston University, DePaul University, the University of Southern California, the University of California at Los Angeles, Rutgers University, Polytechnic University, the University of Michigan, the University of Minnesota, Florida State University), the National University of Singapore, and the Nanyang Technological University (Singapore) to add Masters level degrees. These Masters level programs are generally one year in length and more focused than the broader MBA degree.
[edit] 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.[2]"
A typical problem for a numerically oriented quantitative analyst would be to build or upgrade a model for arbitraging convertible bonds and the stocks the bonds can be converted into.
A typical convertible arbitrage model might imply, say, that convertible bond is objectively under priced compared to the stock given the price of the convertible bond, the price of the stock, the convertible bond can be converted into, interest rates and other factors.[clarify] An investment manager would implement this analysis by buying the convertible bond and selling the stock short.
Information on such techniques can be found on Paul Wilmott's popular numerical-quant website[3]. Mr. Wilmott is the author of many books on quantitative analysis and grants a Certificate in Quantitative Finance to anyone willing to pay a fee and pass certain tests. His books and certificate program, which are completely typical of this approach, stress probability theory, stochastic calculus, finite difference methods and other algebraic techniques. Neither his books nor the documentation for the certificate program makes any mention of statistical technique.
A typical problem for statistically oriented quantitative analyst would be to build or upgrade a model for deciding which stocks are relatively expensive and which stocks are relatively cheap. A typical quant 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.
The Chartered Financial Analysts Institute, which is the largest trade organization in the investment industry, and which grants the CFA certification, stresses the statistical approach to quantitative analysis in its certification program. The CFA's book Quantitative Investment Analysis, which makes no mention of numerical analysis, describes techniques such as hypothesis testing, regression analysis, and time series analysis.
[edit] Notable quants
Jim Mellancamp, formerly of Genie One Capital Management (retired), is one of the first active fund traders utilizing quantitative analysis, and also one of the first successful offshore fund managers.
