FINANCE Corporate financial policy and R and D Management

and Ziemba (1992). The CTEF variable has statistically significant factor
loadings on earnings yield and growth, as was the case in the Russell 3000
universe. The CTEF variable produces statistically significant asset selec-
tion and significant factor exposures, primarily due to the earnings yield
exposure. Earnings forecasts and breadth generate greater asset selection in
small stock universes than in larger stock universes, as we reported in
Chapter 8. Moreover, as the firm size decreases, the CTEF variable is more
statistically associated with risk index returns, such as earnings yield. The
factor exposures increase as the sizes of firms decrease.
The additional R&D tilt increases the CTEF variable portfolio expo-
sures to size, trading activity, and earnings yield exposures. Larger firms
with greater trading activity are firms that engage in greater R&D expendi-
tures. Sector exposures, particularly in the technology and health care in-
dustries, result from the R&D variable (see Table 9.4). The R&D quadratic
term leads the portfolio manager to underinvest in financial companies.
The imposition of the CTEF tilt and R&D quadratic variable increases
total active returns in the Russell 1000 universe. One must ask if total active
portfolio returns and asset selection increase as the value of lambda is in-
creased. We find that as the lambda value is increased, total active returns
rise, the t-statistic on stock selection is increased, and the impact on risk in-
dexes and sector sensitivities is reduced. Total active returns increase from

Efficient Portfolio Optimization Results 241

TABLE 9.4 CTEF Variable Sector Exposures with R&D Tilt, Russell 1000
Universe. Attribution Report: Annualized Contributions to Sector Return

Average

Contribution (% Return) Total

Source Active Average Variation Total Risk Info
of Return Weight (%) [1] [2] [1+2] (% Std Dev) Ratio T-Stat

Basic Materials 6.76 –0.28 –0.02 –0.30 0.65 –0.36 –1.23
Energy –4.98 –0.09 0.23 0.14 0.94 0.13 0.44
Consumer –2.96 0.05 0.13 0.18 0.30 0.50 1.72
(Noncyclical)
Consumer 2.13 –0.54 –0.24 –0.79 0.82 –0.78 –2.69
(Cyclical)
Consumer Services –2.19 –0.10 0.02 –0.08 0.38 –0.18 –0.64
Industrials 3.77 –0.25 –0.09 –0.34 0.49 –0.57 –1.97
Utilities –5.19 0.12 0.02 0.14 0.57 0.21 0.73
Transportation –1.48 0.08 –0.01 0.07 0.14 0.37 1.27
Health Care 11.94 1.33 0.00 1.33 1.12 0.98 3.40
Technology 9.87 0.25 0.19 0.43 1.17 0.32 1.12
Telecommunications –4.96 –0.03 –0.02 –0.05 0.56 –0.07 –0.24
Commercial –0.67 0.01 0.04 0.05 0.09 0.44 1.52
Services
Financial –12.03 –0.14 0.02 –0.12 0.98 –0.12 –0.40
Total 0.65 2.95 0.20 0.70