McGraw-Hill

16 Introduction
model-defined value, calendar effects, and the size effect. The last
article in this section discusses some of the practical problems that
arise in building predictors to include in a stock selection model.
In Part 2, the emphasis shifts from security selection to portfolio
construction. The first two articles here investigate the benefits for
both stock selection and portfolio construction of a “holistic” ap
proach to the investment task, one that views the market from
unified perspective, rather than focusing more narrowly on individual
segments of the market. The third article discusses the limits of
portfolio risk, arguing that there be may such a thing as a portfolio that
is too safe. The fourth provides a casestudy example of a portfolio
construction process that aims to maximize the insights of our stock
selection system by allowing portfolio weights to change aggressively
as underlying economic and market conditions evolve.
The articles in Part3 explore some recent developments in quantitative
portfolio management. The first four articles concentrate on
long-short portfolios, which can enhance the implementation of investment
insights by enabling managers to sell short securities they
expect to perform poorly. In these articles, we debunk some of the
myths surrounding shorting and long-short portfolios, in particular,
including the perceptions that long-short portfolios are necessarily
riskier and costlier than long-only portfolios. We describe the mechanics
of constructing market-neutral and “equitized“ longshort portfolios,
and the trading required to maintain them. And we introduc
concept of ”integrated optimization” for maximizing the opportunities
available from long-short management.
The final article this in section looks at how derivatives can be
used in both long-only and long-short management to enhance
formance. Derivatives have the potential to revolutionize investment
management by allowing clients and managers to separate the
security selection decision from the asset allocation decision.
ENDNOTES
1. The plot reflects the relationship:
IR = IC&
where IC is the information coefficient, BR is the breadth, or the
number of independent insights, and IR (in this case assumed to be