Capital Investment, Innovative Capacity, and Stock Returns

AuthorPRAVEEN KUMAR,DONGMEI LI
Date01 October 2016
Published date01 October 2016
DOIhttp://doi.org/10.1111/jofi.12419
THE JOURNAL OF FINANCE VOL. LXXI, NO. 5 OCTOBER 2016
Capital Investment, Innovative Capacity,
and Stock Returns
PRAVEEN KUMAR and DONGMEI LI
ABSTRACT
We study the dynamic implications of capital investment in innovative capacity (IC)
on future stock returns, investment, and profitability by modeling the unique effects of
IC investment on uncertain option generation/exercise and postexercise revenue. The
model highlights the diverse effects of IC investment on expected returns in different
postinvestment regimes and yields the novel prediction that, under the neoclassical
assumption of nonincreasing revenue returns, IC investment is positively related to
subsequent cumulative stock returns with a lag. The model also predicts a positive
effect of IC investment on future investment and profitability.We find strong empirical
support for these predictions.
WHAT ARE THE IMPLICATIONS OF capital investment for asset pricing? The tradi-
tional real options view is that firms undertake capital investment to convert
growth options into assets-in-place (AIP), with an attendant negative rela-
tion between capital investment and subsequent short-run expected returns
(e.g., Berk, Green, and Naik (BGN) (1999), Carlson, Fisher, and Giammarino
(CFG) (2006)). This view is an apt description of technologically mature in-
dustries. However, in many industries with rich possibilities for innovation,
firms undertake capital investment to develop innovative capacity (IC) to gen-
erate and commercialize potential future innovations (see Furman, Porter, and
Stern (2002)). For example, setting up long-range research facilities and ac-
quiring patents can help to generate growth options because innovation-related
Praveen Kumar is with the C.T. Bauer College of Business at the University of Houston and
Dongmei Li is with the Moore School of Business at the University of South Carolina. We thank two
anonymous referees, an Associate Editor,and Ken Singleton (the Editor) for very helpful comments.
We also thank Heitor Almeida; Jonathan Berk; Jeffrey Brown; Louis Chan; Jaewon Choi; Prachi
Deuskar; Phil Dybvig; Wayne Ferson; Slava Fos; Paolo Fulghieri; Joao Gomes; Andrew Grant; Eric
Ghysels; Richard Green; Dirk Hackbarth; David Hirshleifer; Gerard Hoberg; Elvis Jarnecic; Dirk
Jenter; Charles Kahn; Nisan Langberg; Michael Lemmon; Jun Liu; Mark Loewenstein; Graham
Partington; Neil Pearson; George Pennacchi; Gordon Phillips; Josh Pollet; Jeffrey Pontiff; Michael
Roberts; Laura Starks; Sheridan Titman; Selale Tuzel; Neng Wang; Joakim Westerholm; Toni
Whited; Jianfeng Yu; Lu Zhang; and Guofu Zhou; as well as seminar participants at University
of Illinois (Urbana-Champaign), the USC Conference on Financial Economics and Accounting,
University of Sydney, University of South Carolina, Texas A and M, Georgia Tech, University of
California Riverside, and Southwestern University of Finance and Economics for useful comments.
We hav e read the Journal of Finance disclosure policy and have no conflicts of interest to disclose.
DOI: 10.1111/jofi.12419
2059
2060 The Journal of Finance R
activities are often sources of new ideas and opportunities (Schumpeter (1942)
and Maclaurin (1953)).
In this paper, we model unique features of IC investment and empirically
test refutable predictions on the dynamic effects of IC investment on future
stock returns, investment, and profitability. Distinct from traditional option-
exercising investment, IC investment helps to develop innovations (or new
growth options), but with significant uncertainty in their generation and exer-
cise given the nature of the innovation discovery and commercialization pro-
cess. Moreover, IC investment enhances expected revenues by allowing the
firm to generate higher quality–based sales when innovations are generated
and exercised. These unique features are consistent with the innovation and
industrial organization literature, and we exploit them to derive dynamic im-
plications of IC investment.
An important implication of our model is that the effects of IC investment
on future expected returns depend on the resolution of the uncertainty
regarding the generation and exercise of options. Specifically, these effects
are generally ambiguous before innovation is generated and exercised, but
become unambiguously positive after the option is exercised as long as there
are nonincreasing revenue returns from IC investment. We also generate
implications of IC investment for future investment, profitability,and standard
risk factor loadings. Because IC investment facilitates the generation and
exercise of growth options (due to its positive revenue effect following exercise),
the prediction is that IC investment increases expected future investment (as-
sociated with exercising the potential options). Furthermore, combining these
effects on future expected returns and investment with the decomposition
of the market-to-book equity ratio with clean surplus accounting (see Fama
and French (2006)), we predict that, for firms with nonincreasing revenue
returns, IC investment increases expected profitability. These novel dynamic
implications of IC investment also have implications for the evolution of stan-
dard risk factor loadings (Fama and French (1993) and Carhart (1997)) after
IC investment. For example, we expect investing firms’ loading on the value
factor to be increasing and their loading on the size factor to be decreasing
over time as firms generate and exercise new options and become bigger.
To test the predictions of the model, we take IC firms to be R&D-active
firms because being R&D-active is widely viewed as being innovation-driven
(Rogers (1998)). We mainly use the total asset growth (AG) (Cooper,Gulen, and
Schill (2008)) of R&D-active firms to identify IC investment since AG is a gross
measure of capital investment. Building on a variety of empirical perspectives
(see Section II.B), we use large firm size in addition to R&D activities to capture
firms that are likely subject to nonincreasing revenue returns of IC investment.
We find strong empirical support for the implications of our conceptual frame-
work. For large IC firms, the effects of AG on subsequent cumulative returns
are insignificant over the first five years, but become significantly positive as
of the sixth year. In contrast, we observe no such patterns for small IC (and
R&D-inactive) firms. In addition, IC firms show significantly higher future
investment, and IC investment is positively related to future profitability for
Capital Investment, Innovative Capacity, and Stock Returns 2061
large IC firms. We also verify the predictions regarding the post-AG evolution of
standard risk factor loadings. Our results are robust to other measures of capi-
tal investment that have been used in the literature (Polk and Sapienza (2009)
and Lyandres, Sun, and Zhang (2008)) and alternative ways of identifying IC
firms.
By modeling the unique features of capital investment in IC, we uncover
both theoretically and empirically rich dynamic patterns following capital in-
vestment. Specifically,we identify the uncertainty of option generation/exercise
and the post-exercise operating leverage (OL) effect (under neoclassical restric-
tions on the revenue returns) as the key aspects of IC investment that drive
the dynamic effects of investment on subsequent returns. This qualitative in-
tertemporal heterogeneity in the relation of (IC) investment to future expected
returns is novel because extant literature has typically not considered the im-
plications of uncertain option generation/exercise on the effects of investment
on expected returns. In particular, as we mention at the outset, existing real
options literature views capital investment as exercising available growth op-
tions and typically predicts a negative relation between capital investment
and subsequent short-run expected returns. Furthermore, the key aspects of
IC investment above generate novel predictions on IC investment with respect
to future investment, profitability, and evolution of risk loadings, which we
empirically verify.
In a related vein, our results are also distinct from the literature that con-
siders the relation between capital investment and subsequent stock returns
using behavioral and agency-theoretic perspectives. For example, Titman, Wei,
and Xie (2004), among others, who find a negative relation between capital in-
vestment and subsequent abnormal stock returns—the so-called “investment
anomalies” literature—argue that investors underreact to empire building by
managers. However, since IC investments can be associated with empire build-
ing, this view also predicts a negative relation between IC investments and
subsequent stock returns, especially for firms with higher investment discre-
tion. Meanwhile, Cao, Simin, and Zhao (2008) use the Galai and Masulis (1976)
model to posit a positive association between growth options and idiosyncratic
volatility (IVOL), and suggest that more levered firms have greater incentive
to undertake projects with high idiosyncratic risk because these risks are borne
by debt holders. This perspective would also imply a negative relation between
investment and subsequent returns given the well-documented negative IVOL-
return relation. Notably, this literature does not generate the dynamic post-
investment patterns that we predict and find empirically for IC firms, which are
apparently masked by looking at the average responses of the universe of firms.
We organize the rest of the paper as follows. Section Ipresents the model and
develops empirical predictions. Section II describes the data and the empirical
framework. The empirical results are presented in Sections III,IV,andV.
Section VI concludes. All proofs and robustness checks are presented in the
Internet Appendix.1
1The Internet Appendix may be found in the online version of this article.

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