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Robert C. Merton, a pioneer of quantitative analysis, introduced
stochastic calculus into the study of finance.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.
According to quantitative analysis Fred Gehm[1], "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 analysis
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. 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[2]. 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 companies book value to price ratio, it's
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[3], which is the largest
trade organization in the investment industry, and which grant's 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.
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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