McGraw-Hill

Life on the Leading Edge 9
. Quantifying Risk and Return for Profit
. Investment managers who use quantitative analysis, like managers
who use traditional analysis, seek to outperform the market, but
their search is engineered to combine human insight and intuition
with modem computing power, finance theory, and statistical
niques-instruments that have the potential to extend the reaches
(and discipline the vagaries) of the human mind. While human
brainpower continues to provide the creativity, computer model
of stock price behavior and quantitative portfolio construction
niques provide the discipline to ensure that return opportunitie
maximized at controlled levels of risk.
A quantitative stock selection process can deal with as wide
universe as passive management can. It can thus approach the investment
problem with an unbiased philosophy, unhampered, as is
traditional active management, by the need to reduce the equity
universe to a tractable subset of stocks. Analysis of a particular style
subset can take advantage of information gleaned from the whole
universe of securities, not just stocks of that particular style (or a
subset of that style, as in traditional management). The increased
breadth of inquiry should lead to improved insights vis-his traditional
style portfolios.
Quantitative management also delivers numerical estimates for
the expected returns and anticipated risks of the stocks in that universe.
Unlike the largely subjective judgments of traditional active
management, such numerical estimates are eminently suitable for
portfolio construction via optimization techniques.
The goal of optimization is to maximize the portfolio’s return
while controlling its risk level. Portfolio risk will typically reflect
risk of the underlying benchmark (systematic risk) and the risk incurred
in pursuing returns in excess of the benchmark return. This
incremental, or residual, risk should be no more than is justified by
the expected excess portfolio return.
The nature of quantitative stock selection and portfolio construction
processes imposes discipline on active portfolios. With individual
stocks defined by expected performance parameters, an
portfolios optimized along those parameters to provide desire
terns of expected risk and return, portfolios be can defined in terms
of preset performance goals. Adherence to stock selection models