INNOVATIONS, REAL OPTIONS, RISK AND RETURN: EVIDENCE FROM
THE PHARMACEUTICAL AND BIOTECHNOLOGY INDUSTRIES

by
AZIZJON ALIMOV

A DISSERTATION
Presented to the Department of Finance
and the Graduate School of the University of Oregon
in partial fulfillment of the requirements
for the degree of
Doctor of Philosophy
September 2007

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“Innovations, Real Options, Risk and Return: Evidence from the Pharmaceutical
and Biotechnology Industries,” a dissertation prepared by Azizjon Alimov in partial
fulfillment of the requirements for the Doctor of Philosophy degree in the Department of
Finance. This dissertation has been approved and accepted by:

Dr. Wayne Mikkelson, Chair of the Examining Committee

Date

Committee in Charge:

Dr.
Dr.
Dr.
Dr.


Wayne Mikkelson, Chair
Bruce Blonigen
John Chalmers
Megan Partch

Accepted by:

Dean of the Graduate School

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An Abstract o f the Dissertation of
Azizjon Alimov
in the Department o f Finance

for the degree o f

Doctor o f Philosophy

to be taken

September 2007

Title: INNOVATIONS, REAL OPTIONS, RISK AND RETURN: EVIDENCE FROM
THE PHARMACEUTICAL AND BIOTECHNOLOGY INDUSTRIES

Approved: ___________________________________________________
Dr. Wayne Mikkelson


Based on recently developed real options models, such as in Berk, Green and
Naik (1999, 2004), I develop and test hypotheses about the impact o f growth options
embedded in innovative investment on the risk and the expected return o f a firm’s equity.
I test my hypotheses using a hand-collected dataset on the major innovation activities
undertaken by pharmaceutical and biotech firms over the period 1985-2004. The dataset
contains detailed information on 112 innovation-targeted acquisitions, 273 highlyinnovative drug introductions and 211 key patent grants underlying these drugs.
I find significantly positive abnormal stock returns around the announcements of
patent and new drug applications and approvals, and negative abnormal stock returns
around acquisition announcements. These results suggest that innovative events provide
value-relevant information to the stock market. To examine whether changes in firm
value around the events are in part due to predicted revisions in expected return on

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equity, or cost o f equity capital, I study medium-term post-announcement returns. The
results are mixed. I find that patent-related events are followed by positive abnormal
returns, which is consistent with the prediction that investors require higher return
following the discovery of a relatively risky growth option. However, I find that new
drug applications are also followed by positive abnormal returns, which contradicts the
prediction that expected returns decline following the conversion o f a growth option into
relatively safe assets in place.
I then examine the central prediction of the real options models that the new
information about growth options affects expected returns by changing a firm’s equity risk.
I do not find that the events significantly affect the systematic risk o f innovating firms.
Furthermore, changes in the systematic risk do not explain abnormal returns around the
event announcements. Taken together, these results do not support the main prediction of
real options theory that the systematic risk and hence the expected return o f individual
firms change in a predictable manner in response to information about growth options
embedded in innovative investment.


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V

CURRICULUM VITAE
NAME OF AUTHOR: Azizjon Alimov

GRADUATE AND UNDERGRADUATE SCHOOLS ATTENDED:
University of Oregon
Central Michigan University
Banking and Finance Academy, Uzbekistan
Samarkand Cooperative Institute, Uzbekistan

DEGREES AWARDED:
Doctor of Philosophy, Finance, 2007, University of Oregon
Master of Business Administration, 2001, Central Michigan University
Master of Science, Economics, 1998, Banking and Finance Academy, Uzbekistan
Diploma of Economist, Samarkand Cooperative Institute, Uzbekistan

AREAS OF SPECIAL INTEREST:
Corporate Finance
Investments
Corporate Investment Decisions and Asset Prices

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ACKNOWLEDGMENTS

I gratefully acknowledge the advice and support of my dissertation committee,
Bruce Blonigen, John Chalmers, Megan Partch, and especially Wayne Mikkelson (chair).
Their guidance and encouragement are ultimately responsible for this dissertation. I also
wish to thank Jonathan Berk, Ro Gutierrez, Ilan Guedj, Ron Giammarino, and seminar
participants at the University of Oregon, the 2006 FMA Doctoral Seminar in Salt Lake
City, and California State University, Fullerton for their helpful comments. I thank the
University of Oregon and the Hopewell/Racette Scholarship for financial support.

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V ll

TABLE OF CONTENTS
Chapter

Page

I. INTRODUCTION ......................................................................................................

1

II. THEORETICAL PERSPECTIVES .........................................................................
Real Options Models and Innovative Investment ............................................

12
12

Empirical Implications.......................................................................................


17

The Effect of Competition and Business Cycle................................................

23

III. THE PHARMACEUTICAL AND BIOTECHNOLOGY INDUSTRIES ..........
Background .........................................................................................................

27
27

Patent Applications and A pprovals...................................................................

32

New Drug Applications......................................................................................

33

Innovation-Targeted Acquisitions.....................................................................

34

IV. SAMPLE SELECTION AND VARIABLE CONSTRUCTION ........................
Sample Selection................................................................................................

35
35


Dataset Construction..........................................................................................

39

Information on New Drug Innovations .......................................................

39

Information on Patents ..................................................................................

44

Information on Innovation-Targeted Acquisitions......................................

46

Independent Variables: Equity Risk and R eturn..............................................

49

Control Variables ...............................................................................................

53

V. EMPIRICAL ANALYSIS........................................................................................
Descriptive Statistics of Innovative Investment E vents...................................

58
58


Abnormal Announcement Returns....................................................................

64

Medium-Horizon Post-Event Abnormal Returns..............................................

70

Changes in Risk Around Innovative Investment Events..................................

78

Returns and Changes in Risk .............................................................................

86

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viii

Chapter

Page

Returns, Risk Changes and Growth O ptions.................................................

93

Discussion ...........................


100

VI. CONCLUSIONS..................................................................................................

103

APPENDICES.............................................................................................................

106

A. VALUE AND RISK OF THE INNOVATIVE PROJECT OVER TIME

106

B. SAMPLE NEWS REPORTS............................................................................

107

BIBLIOGRAPHY.......................................................................................................

109

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ix

LIST OF FIGURES
Figure


Page

1. Timeline of Events and Predicted Changes in Risk and Returns.....................

19

2. Estimates of Time and Cost of Innovative Drug Development .....................

30

3. Average Raw and Risk-Adjusted Returns for the Three Categories of
Firms in Event T im e...........................................................................................

74

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X

LIST OF TABLES
Table

Page

1. List of Sample F irm s.......................................................................................

36


2. Temporal Distribution of Innovative Investment Events.............................

59

3. Descriptive Statistics.......................................................................................

60

4. Announcement Period Abnormal Returns ....................................................

67

5. Medium-Horizon Post-Event Abnormal Returns..........................................

73

6. Changes in Systematic and Idiosyncratic Equity R isk ..................................

81

7. Regression of Returns on Changes in Risk Controlling for Firm
Characteristics: Patent Applications...............................................................
8. Regression of Returns on Changes in Risk Controlling for Firm
Characteristics: Drug Applications ................................................................
9. Regression of Returns on Changes in Risk Controlling for Firm
Characteristics: Innovation-Targeted Acquisitions.......................................
10. Regressions of Returns and Risk Changes on Growth Options
and Firm Characteristics: Patent Applications.............................................
11. Regressions of Returns and Risk Changes on Growth Options
and Firm Characteristics: Drug Applications...............................................

12. Regressions of Returns and Risk Changes on Growth Options
and Firm Characteristics: Innovation-Targeted Acquisitions .....................

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89
90
91
97
98
99


1

CHAPTER I
INTRODUCTION
I investigate whether information about real options embedded in a firm’s
innovative investment affects the risk and expected return of a firm’s equity. An
increasingly important component of many firms’ portfolio of projects is technological
innovations, which can potentially generate new products and markets. Innovations in
turn are the result of deliberate multi-stage research and development activities, which
are usually characterized by multiple sources of uncertainty about the potential benefits
and costs of the investment. Because an innovative project involves a sequence of
contingent investment decisions, the project can be viewed as a compound real option
on the variables underlying the project value, such as the expected time and costs to
completion and the stream of cash flows after completion. These options can have
substantial economic value by generating future decision rights for a firm. As reviewed
below, real options theory claims that information about the growth options embedded
in a firm’s innovative investment plays an important role in determining the required

return of a firm’s equity.
One area to which my study contributes is a relatively recent but rapidly
growing literature that applies real options methods to corporate finance and asset
pricing problems. The theory of real options recognizes that firms represent
continuously evolving portfolios of ongoing projects and growth options to invest in
new projects. Berk, Green and Naik (1999, 2004), Gomes, Kogan, and Zhang (2003),

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2

and Carlson, Fisher, and Giammarino (2004, 2006) theoretically demonstrate that a
firm's systematic risk, and hence its expected return, reflect the firm’s exposure to the
systematic risks of assets in place and growth options. The relative distribution of assets
in place and growth options changes with the external acquisition and internal
development of new growth options, the exercise of growth options as well as with
other investment decisions. Therefore, a critical implication of the real options models
is that important investment events will have a direct impact on the risk and required
return for a firm’s equity.
Despite the theoretical development of real options theory, little empirical
evidence documents the impact of real options on firms’ equity risk and expected
return. Existing studies, which have examined some of the implications of real options
theory, lack necessary firm-level data and are able to provide only indirect evidence.
For example, Anderson and Garcia-Feijoo (2006) and Xing (2006) document an
association between the capital investment rate, a proxy for the exercise of growth
options, and the information contained in the Fama and French (1993) size and book-tomarket portfolios. Carlson et al. (2005) document an increase in firms’ beta prior to
seasoned equity offerings and a decrease thereafter, and argue that this result is
generally consistent with a real options explanation of stock underperformance
following seasoned equity offerings. In contrast, my paper directly tests the empirical

implications of real options theory by identifying discrete instances of the discovery and
exercise of growth options and relating the economic characteristics of these options to
changes in the measures of firms' equity risk and return around the event. In addition, I

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focus on investment (not financing) events related to a discovery and exercise of growth
options that could be financed from multiple sources.
My paper also contributes to the literature that studies the stock return
implications of firms’ innovative activities. While real options models argue that
movements in the market valuation of such firms reflect the time-varying exposure of
firms to risks of growth options, there has been popular support for the notion that the
market participants often misreact to innovation news with uncertain economic value.
Most of the studies in this area examine the association between accounting data on
firms’ research activities and subsequent stock returns. For example, Chan, Lakonishok,
and Sougiannis (2001) and Eberhart, Maxwell, and Siddique (2004) report a positive
association between the level of and changes in R&D investment and subsequent
abnormal stock returns. These studies conclude that the market underreacts to the
potential benefits from the firms’ research activity. Daniel and Titman (2006) find that a
stock’s future return is unrelated to the firm’s past accounting-based performance and
negatively related to the firm’s past non-accounting based performance. They argue that
this is evidence that investors overreact to intangible information, such as information
about the firm’s growth options. In contrast, my goal is to deepen our understanding of
how firms’ innovative activities affect the expected return on their equity in two ways.
First, building on real options theory I propose and examine the hypothesis that
innovative events are associated with significant changes in firms’ cost of equity
capital, and that these changes can explain the pattern of abnormal returns around the
event. Real options theory implies that ignoring growth options embedded in most


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investment projects will tend to understate the risk and value of the projects. As a result,
I test whether changes in risk and return around the innovative investment events are
related to the properties of growth options embedded in these investments. These results
should help distinguish between the risk and investor misreaction stories. Second, I
examine a wider class of innovation events than has been examined and measure
information about innovation events directly from its source. Therefore, my tests are
arguably more direct and should provide meaningful additional evidence.
Rather than studying the implications of real options theory in a variety of
industries, however, I focus on innovative investments of firms in the pharmaceutical
and biotechnology industries. While my focus on firms within the same industry
restricts the generality of results, it has four advantages. First, the pharmaceutical and
biotechnology industries are one of the most research-intensive industries in the U.S.
and real options represent a significant portion of pharmaceutical and biotech firms’
value. The real options of these firms are clearly demarked and come in the form of new
patents and drugs created by substantial investment in research and development.
Second, the theoretical literature makes specific predictions as to the effects of a
pharmaceutical firm’s drug research and development activity on the expected return on
its equity. In particular, Cornell (1999) and Berk, Green and Naik (2004) demonstrate
how a pharmaceutical firm’s progress towards completion of a drug development
project drives the required return for a firm’s equity. Third, due to the Federal Drug and
Food Administration regulation, a great deal of data is available on the activities related
to the discovery and development of growth options by biotech and pharmaceutical

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firms. These activities result in highly visible events describing progress towards

completion of the project, such as new patent and drug applications. A researcher can
also obtain important value-relevant information to compute proxies for the value and
risk of real options embedded in innovative investment events. Other critical variables
can also be identified and controlled for. Finally, this approach allows me to limit the
possibility of contamination of results due to mis-measurement of key variables or the
effects of other variables not included in the analysis. For example, it is extraordinarily
difficult to obtain comparable project level data across firms. As a result, the properties
of real options for a large sample of firms in different industries are likely to be
measured with much error. For these reasons, I believe that my sample provides the
most promising setting for conducting an investigation of how a firm’s decisions related
to the development and exercise of growth options affect the risk and expected return of
a firm’s equity.
I develop and analyze a unique hand-collected dataset that focuses on two
distinct categories of innovative activities that should have particularly important effects
on the risk-retum o f characteristics of firms, namely, the discovery and exercise of
growth options. Specifically, I explore my research questions using the data on three
different innovation events: (i) announcements of a highly-innovative new drug
application and approval; (ii) announcements of an application and approval of a patent
underlying these drugs; and (iii) announcements of innovation-targeted acquisitions.
The patenting and introduction of highly-innovative new drugs are one of the most
important innovative investments of biotech and pharmaceutical firms. Before a

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potentially profitable drug can be marketed, it must be approved by the Federal Drug
Administration. A patent grant provides monopoly rights to sell the drug until the patent
expires and, therefore, gives the firms exclusive access to a growth option. Innovationtargeted acquisitions are important means through which established pharmaceutical
firms obtain new technologies and associated skills as well as promising products. In
sum, I argue that these events are important events in the life-cycle of the sample firms

and result in significant changes in the composition and risk of firms’ assets. As a
result, I expect these events to affect investors’ perception of innovator firms’ riskretum characteristics.
I use the real option model of Berk, Green and Naik (2004) to formalize
hypotheses about how these innovation events should impact the systematic and
idiosyncratic equity risk and thus the expected return. Their model captures different
sources of risk embedded in the multi-stage innovative investment project, and the
authors analyze their interaction in determining the risk premium and value of the
project over its life-cycle. Specifically, there is systematic risk associated with future
cash flows the project can potentially produce after completion. There is also
idiosyncratic risk pertaining to the uncertainty about the successful completion of the
project. The project involves several separate stages of development, and at each stage,
the managerial decision of whether to continue the investment depends on the resolution
of systematic and idiosyncratic uncertainty. Therefore, an investment project is viewed
as a compound real option on systematic uncertainty. The models shows that the
systematic risk, and thus the expected return, of the project are likely greatest at the

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7

onset, and decrease as the project approaches completion and idiosyncratic and
systematic uncertainty gets resolved. The intuition behind this result is that growth
options, because of the implicit leverage they impart, have higher systematic risk and
therefore expected returns than the asset on which it is written. As a result, the model
implies that important events in the project’s life-cycle that impact its value and risk
premium, will also influence a firm’s systematic risk and the expected return for its
stock.
In the context of my study, I expect both the patent and acquisition events to
result in an increase in a firm’s equity risk and thus the expected return because these

events signal to the market that a firm expands its portfolio of growth options.
Conversely, I expect the drug application and approval events to decrease a firm’s
equity risk and expected stock return because a firm is exercising its growth options and
converting them into less risky assets in place. Both predictions reflect the assumption
that growth options have higher required risk premium and, hence, expected return than
the assets in place when the underlying asset of the option closely mimics assets in
place. Finally, I hypothesize that the impact of the events on the equity risk and return
of firms depends on the intensity of product-market competition and the business cycle.
I start my analysis by examining the short and medium window stock price
reaction to the event announcements. I conduct tests with stock returns for three
reasons. First, such tests permit me to directly examine the pricing effects of news about
growth options. Second, by studying post-event patterns of stock returns I can measure
the economic compensation for the event-induced change in the systematic risk of the

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firm required by investors. In efficient markets, events that change the equity risk a firm
should also change expected stock returns in the same direction. Therefore, I expect that
firms with a predicted event-induced increase in their equity risk will exhibit an
increase in their expected returns. In contrast, I expect that firms with a predicted
decrease in their equity risk will exhibit a decrease in their expected returns. Third, by
examining whether return movements following the events are explained by changes in
equity risk, I can measure the violations of real options theory in economic terms.
The results show that that all three innovative events have significant stock price
effects and thus appear to possess substantial information content. I find positive
abnormal returns to the announcements of patent grants as well as applications and
approvals of new drugs. For example, the average firm announcing a patent grant and a
new drug approval experiences the cumulative abnormal returns of 1.45% and 2.2%
over the five-day window around the event. In contrast, the average firm announcing an

innovation-motivated acquisition realizes a negative abnormal return of 1.9%. In the
medium-window tests, I find that patent-related events and applications of new drugs
are followed by positive abnormal returns that last for at least nine months after the
events. The positive abnormal return pattern after the patent-related events is consistent
with the prediction that investors require higher rate of return in response to new
information about the discovery of a risky growth option. However, I do not find a
corresponding pattern of increasing stock returns following innovation-driven
acquisitions. I also do not find a pattern of stock returns moving downward following
the drug applications and approvals, or the exercise of growth options, as would be the

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9

case if the exercise of growth option were to reduce the equity risk and expected returns
of innovator firms.
In order for these abnormal returns to be consistent with an efficient price
formation, the level of equity risk measures in the post-event period must be different
from that before the event. To measure changes in the systematic risk and idiosyncratic
equity risks of innovator firms, I estimate the Fama and French (1993) three-factor
model at the firm-level. The Fama and French model suits the purpose of my study
particularly well because, according to Berk, Green and Naik (1999) and Gomes, Kogan
and Zhang (2003), the size and book-to-market factors in the model capture the
components of a firm’s systematic risk attributable to its growth options and assets in
place. Therefore, the analysis in this paper should help us understand whether the real
options story is a good description of behavior of asset prices around innovative events.
The results show that, in general, firms do not experience changes in their
systematic equity risk, measured as both changes in individual loadings on the FamaFrench three factors and change in the overall risk premia. However, I document an
increase in idiosyncratic equity risk following the patent events and a decrease in

idiosyncratic equity risk after the announcement of drug approval and innovationmotivated acquisitions. While the observed reductions in idiosyncratic risk are
economically significant, it is not clear how the changes in non-compensated risk can
explain the stock return movements following the event. To test the proposition that
seemingly abnormal returns that follow the test events are induced by risk shifts, I
estimate multivariate regressions of the post-event abnormal stock returns on the

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10

changes in the systematic and idiosyncratic risk. The results show that, in general,
changes in both measures of equity risk do not explain the post-event patterns of
abnormal stock returns.
My final analysis then directly examines the central prediction of real options
theory that the economic properties of growth options embedded in innovative
investment are the main determinants of changes in equity risk and expected stock
returns around the innovation news. I find that cross-sectional differences in the
announcement abnormal stock returns are positively related to the relative value of
growth options embedded in these events. However, I do not find that economic
properties of growth options are systematically related to changes in the firms’
systematic and idiosyncratic risks that follow the events.
Taken together, my results are both interesting and puzzling, in particular, for
the current generation of real options models. The results do suggest that announcement
of innovation news provide value-relevant information to investors, who rationally
revise firms’ stock prices in response to new information about the value of the
underlying growth option. However, I do not find support for the central prediction of
the real option theory that the new information affects expected stock returns by
influencing firms’ cost of equity capital. O f course, the interpretation of the tests is
certainly limited by my need to use a proxy for the unobservable model of expected

returns. As a result, my tests are joint tests of the changes in the pricing of assets in
place and growth options around the event and the Fama and French factors as priced
risk factors. Nevertheless, at a minimum, my results cast doubts on arguments in Berk,

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Green and Naik (1999) and Gomes, Kogan and Zhang (2003) who argue that changes to
the firm’s portfolio of growth options are able to explain the abnormal returns estimated
using the Fama and French three-factor model. Perhaps, a new asset pricing model is
needed to explain the excess returns following changes in the composition of firms’
portfolios of assets.

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12

CHAPTER II
THEORETICAL PERSPECTIVES
In this section, I present the theoretical arguments for the impact of innovative
investment events on firms’ equity risk, and thus the expected return on their equity.
The goal is to make the intuition as clear as possible by synthesizing the main
arguments of this literature and my research questions. Section 2.1 presents and
discusses a simplified version of the real options model of Berk, Green and Naik (2004)
and discuses its implications regarding the impact of growth options embedded in the
innovative project on the required risk premium and expected returns of firms. Section
2.2 gives an interpretation of the model in the context of biotech and pharmaceutical
innovative activities and develops the empirical implications. In Section 2 .3 ,1 discuss
how product-market competition and the business cycle, not considered in the real

options models, may affect empirical results.

Real Options Models and Innovative Investment
The theory of real options provides a model of investment decisions involving
upfront irreversible cost commitments in the face of uncertainty and the choice of
incurring additional costs in the future. Under these conditions, a firm’s investment
policy includes rights or options, but not the obligation, to make further investments or
delay such investments. These investment options therefore create value for the firm by
generating future decision rights. Once uncertainty is reduced, a firm can then choose to

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exercise only those options that are ‘in the money’ and allow the other options to expire.
A good survey of the real options literature can be found in Dixit and Pindyck (1994).
Recently, a new strand of research has emerged that uses real options theory to relate
stock return dynamics to firms’ optimal investment decisions. This literature, pioneered
by Berk, Green, and Naik (1999), includes Carlson, Fisher, and Giammarino (2004,
2006), Gomes, Kogan, and Zhang (2003), Berk, Green, and Naik (2004), Cooper
(2006), Kogan (2004), and Zhang (2005). In this paper, I use the Berk, Green, and Naik
(2004) model to develop hypotheses on the impact of real options embedded in
innovative projects on the firms’ cost of equity capital and expected returns. I
summarize here a simplified version of this model and its implications.
The model begins when a firm starts a new project to develop a new product at
time 0. The new project will generate a stream of stochastic cash flows after the firm
successfully completes a number of discrete stages of research. The value and risk
premium of the project is determined by its idiosyncratic and systematic risk. These two
sources of risk allows the model to embed the capital budgeting problem in an asset
pricing framework, which is suitable to address the main question of my paper. The
source of systematic risk of the project is uncertainty about the future cash flows after

the project is completed. Although the firm does not receive cash flows prior to the
completion of the project, it is assumed that the firm and investors knows what the cash
flows would be if the project were complete today. These cash flow change as more
information is obtained through investment and learning about the demand for the
product. The source of idiosyncratic risk is technical uncertainty regarding the

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14

successful completion of the project, as well as the competitive threat. Technical
uncertainty can be resolved only through investment.
At each stage of the investment process, the decision of whether it should
continue to the next stage depends on the resolution of systematic and unsystematic
uncertainty. This gives to the project the characteristics of a series of compound options
to invest, where the strike price of the option is the expected investment cost to
complete the project and the underlying asset is the value of future cash flow. Thus, the
value of real options embedded in the innovative project comes from systematic and
idiosyncratic uncertainty regarding future cash flows and fixed investment costs.
In the model, the market value of a firm at any time is given by
VALUE=A+G(X, I)

(1)

Where
VALUE=the firm’s market value
A=fhe present value of the expected cash flows generated by the assets-inplace(ongoing projects)
G=operator representing an American call option
A=the present value of the expected cash flows generated by the project

7=the expected investment cost required to complete the project

Consequently, the firm’s overall cost of capital or risk premium at any time
reflects the firm’s exposure to risks of the assets in place and growth options, as
described by

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