CHAPTER
9The Optimization of Efficient
Portfolios: How the R&D
Quadratic Term Enhances
Stockholder Wealth
I
n this chapter, we produce mean-variance efficient portfolios for various
universes in the U.S. equity market, and show that the use of a composite
of analyst earnings forecasts and breadth variables, introduced in Chapter
8, as a portfolio tilt variable and an R&D quadratic term enhances stock-
holder wealth. The use of the R&D screen creates portfolios in which total
active returns generally rise relative to the use of the analyst variable. Stock
selection may not necessarily rise as risk index and sector index returns are
affected by the use of the R&D quadratic term. R&D expenditures of cor-
porations may be integrated into a mean-variance efficient portfolio cre-
ation system to enhance stockholder returns and wealth. The use of an
R&D variable enhances stockholder wealth relative to the use of capital ex-
penditures or dividends as the quadratic term. The stockholder return im-
plications of the R&D quadratic variable are particularly interesting given
that most corporations allocate more of their resources to capital expendi-
tures than to R&D.
Portfolio optimization is a tool that maximizes return for a given level
of risk, or minimizes the risk for a given level of return (Markowitz 1952,
1959). The purpose of this study is to test the effectiveness of a security val-
uation composite earnings forecast model composed of consensus analysts’
earnings per share forecasts, revisions, and breadth over various equity uni-
verses. We find that the composite earnings forecast model (CTEF) is statis-
tically significant in identifying undervalued stocks in the United States,
particularly in equity universes composed of smaller-capitalized securities.
We combine the composite earnings forecast variable with fundamental