So Sue Me!
The Value Implication of Patent Litigation‡
Fred Bereskin*, Po-Hsuan Hsu**, William Latham***, Huijun Wang†
July 23, 2018
Abstract: Using comprehensive patent lawsuit data from 2000 to 2014, we find that firms with
litigated patents and their adversaries experience positive stock returns ranging between 0.25%
and 1.18% in the 10 or 24 days following litigation announcements. In addition, portfolios
consisting of firms involved in patent lawsuits generate risk-adjusted alphas between 0.56% to
0.75% per month in the following year. Further analysis on firms’ future profitability and their
competition suggests that our finding of positive, yet undervalued, effects of patent litigation on
stock prices could be explained by investors’ underreaction.
Keywords: Patent litigation; stock returns; information delay; underpricing
JEL classification: G11, G14, O34
‡ We thank Dan Bereskin, Jim Bessen, Lauren Cohen, Edwin Lai, Haitian Lu, Don MacOdrum, Michael Meurer,
Zhenjiang Qin, Ghon Rhee, Ryan Whalen, and Angela Zhang, as well as seminar participants at the University of
Hong Kong (School of Law), University of Massachusetts Lowell, and the Taiwan Finance Association Annual
Meeting for their valuable comments. We also thank Brian Howard from Lex Machina for preparing and organizing
data for us.
* Trulaske College of Business, University of Missouri, Columbia MO 65211. Email: [email protected].
** Faculty of Business and Economics, University of Hong Kong, Pokfulam Road, Hong Kong. Email:
[email protected]. Phone: +852-2859-1049.
*** Lerner College of Business & Economics, University of Delaware, Newark, DE 19716.
Email: [email protected]. Phone: (302) 831-6846.
† Lerner College of Business & Economics, University of Delaware, Newark, DE 19716. Email: [email protected].
Phone: (302) 831-7087.
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1. Introduction
Patent litigation is an important issue for firms, managers, and shareholders in today’s
business environment where intellectual property plays a critical role. Compared to the 1980s and
earlier, firms are now more likely to be involved in patent litigation, either as plaintiffs or
defendants (Bessen and Meurer, 2013; United States Government Accountability Office, 2013;
Cohen, Gurun, and Kominers, 2016a,b, 2018). It is commonly perceived that the more litigious
environment has increased firms’ risk of being exposed to significant direct and indirect litigation
costs, which may retard their exploitation of intellectual property and reduce their long-term
growth.1 Recent research in patent litigation focuses on both the role and impact of non-practicing
entities (NPEs, sometimes referred to as “patent trolls”) in today’s legal environment (Bessen,
Ford, and Meurer, 2011; Cohen, Gurun, and Kominers, 2016b, 2018), as lawsuits initiated by NPEs
have increased faster than those initiated by practicing entities (PEs) in recent decades. Unlike
NPEs, which mainly target cash-rich firms and value out- of-court settlements, PEs are generally
more motivated by product competition (Cohen, Gurun, and Kominers, 2018). Moreover, while
NPEs primarily aim to share the profits of targeted defendants, PEs seek to eliminate (potential)
competitors, regardless of their profits. In this paper, we focus on stock market reactions to the
announcements of patent lawsuits that do not involve NPEs; these events offer asset pricing
implications of patent-related industry competition.
We first collect patent lawsuits involving public firms from the Lex Machina database,
which covers patent litigation cases filed since 2000. The Lex Machina database is regarded as the
most comprehensive database of U.S. patent lawsuits and has been used in many recent studies
(Akcigit, Celik, and Greenwood, 2016; Allison, Lemley, and Schwartz, 2015, 2018; Cohen, Gurun,
and Kominers, 2016b, 2018). We then combine the patent litigation data with the CRSP/Compustat
database to examine the stock market’s daily and monthly reactions to announcements that firms
1 For example, the American Intellectual Property Law Association (2015) reports that patent litigation tends to be
costly and time-intensive. Specifically, the median patent infringement suit experiences litigation costs ranging from
$100,000 (when less than $1 million is at risk) to $5 million (when more than $25 million is at risk); additionally,
amounts at risk are associated with greater hours required to litigate. Aside from these direct costs, we also note
potential indirect costs including reduced pledgeability (Chava, Nanda, and Xiao, 2017; Mann, 2017) or the reduced
selling price of intellectual property (Lev, 2001). Akcigit, Celik, and Greenwood (2016) note that 20% of domestic
patents are sold. Other indirect costs include distractions to management, difficulties in ensuring long-run
commitments with suppliers and customers (Tucker, 2013), difficulties in attracting financing (Feldman, 2014), and
delays in implementing innovation and marketing strategies.
2
are litigants (either plaintiffs or defendants) in patent lawsuits between 2000 and 2014. We find
that patent litigation leads to positive announcement returns, both for plaintiffs and defendants. On
announcement of patent litigation, litigants experience cumulative abnormal returns (CAR)
ranging from 25 to 118 basis points in various short-term announcement windows, various models,
and different samples.2 For example, plaintiffs provide average returns in excess of the CRSP
value-weighted market index of 52, 114, 55, and 118 basis points in the [-1, 10], [-1, 24], [-3, 10],
and [-3, 24] windows, respectively, around litigation announcement dates (denoted by 0).
Defendants provide average returns in excess of the CRSP value-weighted market index of 33,
109, 34, and 110 basis points in the [-1, 10], [-1, 24], [-3, 10], and [-3, 24] windows, respectively.
Although this phenomenon is slightly larger for plaintiffs, it is significantly positive for both
plaintiffs and defendants. This finding might appear puzzling at first glance, as it challenges the
general impression that patent litigation harms firm value. More interestingly, we find significantly
positive correlations in the cumulative abnormal returns of plaintiff-defendant pairs, which
challenges the belief that patent litigation is a zero-sum game for plaintiffs and defendants.
Our investigation based on comprehensive post-2000 patent litigation cases provides up-
to-date empirical evidence and offers new insights with respect to the effects of patent litigation
on stock prices, which differs from prior event studies based on pre-2000 press data that show
negative announcement effects of approximately 2-3% of firm value (e.g., Bhagat, Brickley, and
Coles, 1994; Lerner, 1995; Bhagat, Bizjak, and Coles, 1998). Moreover, using a sample of patent
lawsuits from 1984-1999 with a 25-day window around the filing dates of cases, Bessen and
Meurer (2012) estimate average losses of 0.5% for defendants.
The following example illustrates how patent litigation can enhance stock prices for
defendants. In April 2008, Seagate sued STEC for patent-infringement; the suit pertained to patents
relating to solid-state drives (SSDs). Although one might expect litigation to be value-destroying
in this case, the lawsuit provided an opportunity for STEC to establish the value and strength of
2 We consider the following four short-term announcement windows: [-1, 10], [-1, 24], [-3, 10], and [-3, 24], around
litigation announcement dates (denoted by 0). We also consider the following three CAR types: CAR1 is defined as
the cumulative daily returns in excess of the CRSP value-weighted market index in the period; CAR2 is defined using
the CAPM model with market beta estimated during the window of trading days -171 through -22 with a minimum of
100 non-missing observations (as in Bhagat, Brickley, and Coles, 1994); and CAR3 replaces the CAPM model in
CAR2 with the Fama-French four-factor model (including the market factor, SMB factor, HML factor, and MOM
factor). In addition, we consider two samples: the first one includes all patent litigation cases, and the second one
includes patent litigation cases with both a public plaintiff and a public defendant.
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its SSD patents. In particular, its CEO indicated that “STEC will take appropriate action to protect
its interests, including seeking the invalidation of Seagate’s patents” (Cheung, 2008). Consistent
with the positive effects of the litigation, the [-1, 1], and [-1, 10] cumulative abnormal returns for
STEC around the lawsuit filing were 4.04% and 27.6%, respectively. The lawsuit was dropped in
the following year, with no licensing agreement or financial exchange. Around this time, STEC’s
CEO expressed how the events around this agreement helped establish the validity of its SSD
patents: “We have always contended that SSD does not borrow from existing hard-drive
technology but rather offers an all-together new approach to storage. We view the dismissal as a
vindication of our technology” (Mearian, 2009).
It is also worth noting that a plaintiff in patent litigation is not necessarily the party that
challenges others’ infringements. In cases of declaratory judgments (DJ), the alleged infringer is
the plaintiff, and the patent owner claiming to own patent rights is the defendant. When claiming
for a declaratory judgment, the plaintiff asks the courts to provide clarity (e.g., ruling that there is
no infringement, ruling that the patent owner’s claim is invalid or unenforceable). Thus, we study
both parties—plaintiffs and defendants—due to the unique role that declaratory judgments play in
patent litigation.3
To further understand the value implication of patent litigation, we create a monthly-
rebalanced stock portfolio consisting of firms experiencing patent litigation in the past 12 months
(“litigation portfolio” henceforth), and find that this portfolio generates excess returns as high as
1.02% per month with a t-statistic of 2.1.4 We then consider various risk factor models and find
that the litigation portfolio generates alphas (i.e., risk-adjusted returns) of 56-75 basis points per
month (with t-statistics above 3.0) after we control for relevant risk factors (e.g., size, value,
momentum, profitability, investment factors), for factors related to R&D and patents, and for
mispricing factors. When we focus on the portfolio consisting of defendants only, we obtain
3 9.9% of our cases are declaratory judgments, and our results are robust to excluding these cases from our analysis. 4 This approach is often known as a “calendar-time portfolio” and differs from an “event-time portfolio.” We do so
because stocks typically are involved in multiple patent litigations in the same period. The latter approach treats each
stock involved in each litigation case as an event, and forms a portfolio based on all events. Thus, statistical inferences
based on event-time portfolios will be subject to issues including cross-correlation of event returns and overweighing
stocks with multiple cases.
4
consistent results. Therefore, the significantly positive returns on the litigation portfolio cannot be
attributed to conventional risks and factors.
It is also possible that our findings are driven by particular industries. That is, certain fast-
growing, high-tech industries might experience both high stock returns and more patent lawsuits.
To examine this possibility, we implement the following matched-samples analysis: for every
treated firm involved in patent litigation, we find a matched firm that is in the same industry and
has similar firm characteristics, but has not been involved in patent litigation in the prior year; we
then form a control portfolio consisting of those matched firms, so we may examine the difference
in the returns generated by both the litigation portfolio and our control portfolio. The returns of
the litigation portfolio consistently outperform those of the control portfolio, suggesting that our
baseline finding cannot be attributed to industry-specific causes.
To further examine if the predictive power of patent litigation on future stock returns is
distinct from that of existing return predictors, we implement monthly Fama-MacBeth regressions
for all CRSP/Compustat firms by controlling for various firm characteristics, including size, book-
to-market ratio, lagged stock returns, momentum, R&D expenditure, patents, operating profit, cash
flow, financial constraints, leverage, profit margin, and industry concentration, as well as industry
fixed effects. We find a significantly positive coefficient of 0.2%-0.3% on the indicator variable
associated with a firm that experiences at least one patent lawsuit over the past 12 months. This
result, which suggests that the litigation-return relation we document is different from other
documented patterns with respect to return predictability, calls for a deeper analysis.
We propose four possible explanations for the intriguing pattern that firms involved in
patent litigation experience significantly positive stock returns. First, these firms share a common
exposure to an unknown or unspecified systematic risk associated with patent competition and/or
litigation, and thus provide higher expected stock returns as compensation for bearing higher risk
exposure. Second, systematic risk related to financial constraints (Li, 2011) could exist, such that
more financially constrained litigants are then associated with higher expected returns. Third, firms
that are rich in cash or appear promising in future cash flows are more likely to be sued; thus, our
findings simply capture the pattern that cash-rich litigants provide higher subsequent stock returns.
Lastly, these firms may, on average, benefit from being involved in patent litigation, and this
5
benefit may be consistently undervalued by the stock market due to the complexity of patent
lawsuits, investors’ limited attention or ambiguity aversion to litigation, and/or systematic
underpricing.5
Our evidence is not consistent with our first explanation (i.e., firms share a common
exposure to an unknown or unspecified systematic risk associated with patent competition and/or
litigation). Whereas a risk-based explanation suggests a price drop following the announcement of
patent litigation (as investors discover new risk exposure and start to discount future cash flows to
a greater degree), we find positive abnormal stock returns in the [-1, 1] and [-3, 3] windows around
the announcements. Moreover, if the risk-based explanation holds, then the return on the litigation
portfolio is driven by heterogeneous exposure to the new risk, and can thus serve as a mimicking
factor for the risk. We implement Fama-MacBeth two-pass regressions to test if the return on our
litigation portfolio is priced in the returns of individual stocks (see Cochrane, 2001). However, we
do not find that the sensitivity of individual stocks’ returns to the litigation portfolio return (i.e.,
the beta to the hypothetical litigation risk) is associated with significantly positive slopes in the
cross-section (i.e., the price of risk for the hypothetical litigation risk).
Further tests show that our baseline finding cannot be explained by systematic risk related
to financial constraints or by litigants pursuing cash-rich firms. We do not find a stronger litigation-
return relation in financially constrained firms that are more subject to systematic risk.6 Nor are
our results concentrated in cash-rich firms, suggesting that firms’ cash balances are unlikely to be
driving our results.
5 The literature shows that investors consistently undervalue R&D-intensive firms owing to concerns about technical
uncertainty associated with R&D activities, which leads to underpricing and return predictability (see, e.g., Lev and
Sougiannis 1996; Aboody and Lev, 2000; Chan, Lakonishok, and Sougiannis 2001; Lev, Sarath, and Sougiannis 2005).
Eberhart, Maxwell, and Siddique (2004) present evidence consistent with investor underreaction to R&D increases.
Cohen, Diether, and Malloy (2013) and Hirshleifer, Hsu, and Li (2013) both argue that investors have limited
processing power for complex innovations in patents and thus undervalue innovative efficient firms. Moreover,
theoretical models show that investors are more skeptical of investment opportunities when they perceive greater
uncertainty (see, Dow and Werlang 1992; Chen and Epstein 2002; Cao, Wang, and Zhang 2005; and Bossaerts et al.
2010). Moreover, the psychology literature finds that individuals tend to interpret signals more skeptically and with
greater risk when they have less processing fluency with those signals (e.g., Alter and Oppenheimer 2006; Song and
Schwarz 2008, 2009). 6 Mezzanotti (2017) finds that patent litigation’s reduction in a firm’s innovation patterns is driven by exacerbated
financial constraints.
6
We then turn to our fourth explanation and investigate the potential benefits of patent
lawsuits for both defendants and plaintiffs. First, for both parties, an allegation of infringement
signals the value of patents and provides the public with a gauge of the potential value at stake.
For example, more valuable patents tend to experience more litigation and attract additional
citations following litigation (Lanjouw and Schankerman, 2001). Indeed, previous evidence shows
that the number of patent citations received is associated with greater patent value (Harhoff, Narin,
Sherer, and Vopel, 1999; Sampat and Ziedonis, 2005; Kogan et al., 2017); as a result, the publicity
associated with patent litigation delivers more information to investors (albeit with a potential
delayed reaction). It is difficult for investors to effectively value or ascertain the validity of patents,
and the litigation process helps clarify patent value (Marco and Vishnubhakat, 2013).7 Using
patent lawsuits, investors obtain more information about litigated and other associated patents and
assess their value more accurately. For example, Kiebzak, Rafert, and Tucker (2016) note that
venture capital investment typically increases with patent litigation (before eventually declining),
consistent with the net positive benefit of patent litigation in certain situations.
Moreover, patent lawsuits attract media attention and thus highlight barriers to entry by
discouraging future competitors, such as smaller firms with less extensive patent portfolios (Choi,
1998; Shapiro, 2000; Hall and Ziedonis, 2001; Bessen and Meurer, 2013; Cohen, Gurun, and
Kominers, 2018); indeed, prior research (e.g., Cohen, Gurun, and Kominers, 2016a,b, 2018;
Caskurlu, 2017) has highlighted how patent litigation changes firms’ behaviors. The filing of
patent litigation also informs investors of corporate managers’ determination to enforce intellectual
property rights against infringement or to confront groundless charges, which benefits
shareholders (Agarwal, Ganco, and Ziedonis, 2009). For example, in writing about Eastman
Kodak’s efforts to protect and monetize its patent portfolio, Mattioli (2010) notes that “aggressive
litigation has become an increasingly important part of Kodak’s corporate strategy.” Consequently,
there are certain positive aspects to litigation exposure that can potentially increase firm value,
7 The litigation process helps clarify (over the course of the legal proceedings) a firm’s patent enforcement ability and
rights. Litigation can thus help initially signal patent value and resolve associated uncertainties, albeit with a delay.
Related to this point, Marco and Vishnubhakat (2013) find that stock market reactions associated with the resolution
of patent uncertainty are comparable to those of initial patent grants: each are approximately 1.0%-1.5% excess returns.
Their findings imply that the uncertainty of patent validity is economically important, and can affect litigation behavior.
Moreover, Graham and Vishnubhakat (2013) note that the effects of legal uncertainty regarding patent validity are
particularly severe in emerging technologies and in areas with rapid growth in patenting activities.
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even for defendants.8 We recognize, of course, that patent infringement does not always result in
litigation; in particular (especially regarding how our results relate to defendants’ returns), an
infringing defendant might find it optimal to settle prior to a lawsuit. This observation helps explain
why there are positive returns associated with defendants who choose to defend themselves against
alleged infringements.9
To empirically test our explanation of the market’s underreaction to the potential benefits
of patent litigation, we implement further analyses on the subsequent profitability, competition,
and information delay (i.e., the price of a stock is adjusted more slowly). First, we find that firms
experiencing patent litigation tend to be more profitable in the long run: firms involved in patent
litigation are associated with a 3.0% increase in average return on equity (ROE) over the
subsequent five years. This finding indicates that the benefits associated with patent lawsuits, on
average, exceed the associated costs. Similarly, and reflecting increased barriers to entry associated
with patent litigation, we find that litigants experience lower industry competition (measured by
the Similarity and HHI of Hoberg and Phillips (2016)) following litigation.
Consistent with our findings being driven by investors’ delayed reactions to the benefits
from litigation announcements, we find a stronger litigation-return relation among the types of
firms with greater information delay. Specifically, we provide double-sorts using both stock return
R2 (Hou, Peng, and Xiong, 2013) and Hou and Moskowitz’s (2005) price-delay measure. Across
all models, we find that abnormal returns are significantly larger among firms with greater
information delay (lower stock return R2 or higher price delay): specifically, firms with greater
information delay experience monthly excess returns and alphas that are 65 to 107 basis points
higher than those of firms with less information delay.
Consequently, to the extent that it takes time for investors to fully appreciate patent-related
news, our findings offer new evidence on patent litigation to the asset pricing literature. In
8 To the extent that the litigation will result in a trial (as opposed to a settlement), the market values the ability to better
evaluate management with information revealed over the course of a trial and its judgment. For example, Haslem
(2005) notes that litigation resolution by court decisions dominates out-of-court settlements (from shareholders’
perspectives), and attributes his results to the valuable information associated with court judgments. 9 In evaluating patent disputes, it is important to be aware of their endogenous nature (Bessen and Meurer, 2006; 2013).
For example, Bessen and Meurer (2013) note that “the rate of lawsuit filing depends as much on the frequency of
disputes as the frequency of bargaining breakdown.” Also, Lemley, Richardson, and Oliver (2017) use survey data to
show that about one-third of alleged infringement results in litigation. This indicates that litigation is not an infrequent
result of negotiations between litigants to address potential infringement.
8
particular, we demonstrate the presence of the market’s delay in reacting to benefits associated
with patent litigation; indeed, litigation is an important event that helps the market understand or
re-evaluate the value of a firm’s patent portfolio.10 We also provide intriguing evidence and new
insights into the effects of patent litigation on shareholder value. Although prior studies highlight
the pernicious effects of patent litigation, we show that the net effect of patent litigation is positive:
by increasing the market value (or simply the awareness) of firms’ intellectual property and by
deterring potential competition, litigation’s net effect is positive, despite the direct and indirect
costs of addressing a lawsuit. Our evidence does not negate the significant direct and indirect costs
associated with patent litigation, as discussed in Footnote 1. Rather, we present evidence showing
that the effect of litigation is positive, despite these considerable costs. Our investigation based on
post-2000 cases based on court records provides up-to-date empirical evidence and offers new
insights on patent litigation’s effect on firm value, which is different from prior event studies based
on pre-2000 data that are based on news articles rather than court records (e.g., Bhagat, Brickley,
and Coles, 1994; Lerner, 1995; Bhagat, Bizjak, and Coles, 1998). More recent papers have
suggested a smaller magnitude in value loss associated with patent litigation. 11
Other recent studies have also explored how the patent system affects firms. Many recent
studies have focused on the negatives associated with the current patent system, especially
associated litigation costs and effects on innovation (Heller and Eisenberg, 1998; Jaffe and Lerner,
2004; Lemley and Shapiro, 2007; Ewing, 2011; Cohen, Gurun, and Kominers, 2018). Indeed,
citing a recent letter to Congress by 51 prominent economics and legal scholars in innovation and
intellectual property law, Asay et al. (2015) assert the harmful effects of patent litigation not only
on innovation, but also on R&D and venture capital investment as well.12 By examining the
10 Our study is related to the broader literature on mispriced intangibles. Aside from the innovation and R&D literature,
other examples of mispriced intangibles include corporate governance (Gompers, Ishii, and Metrick, 2003), executive
perks (Yermack, 2006), social norms (Hong and Kacperczyk, 2009), and employee satisfaction (Edmans, 2011). 11 For example, Bessen, Meurer, and Ford (2011) estimate average losses of 0.37% associated with lawsuits by non-
practicing entities. Similarly, using a sample of lawsuits from 1984-1999 with a 25-day window around the filing
dates of cases, Bessen and Meurer (2012) estimate average losses of 0.5% for defendants. In contrast, our sample
begins in 2000. Additionally, Feldman (2014) describes the extent to which the increased rate of patent assertion
claims is very different from earlier periods: previously, litigation served as a last resort and was harmful to both firms
(since a defendant would use its patent portfolio to retaliate against the plaintiff). 12 In contrast, Farre-Mensa, Hegde, and Ljungqvist (2017) present causal evidence that patent approvals are associated
with start-up success. They note that patents help start-up firms address information asymmetries in four ways: (1) by
providing evidence that a firm can monetize its invention; (2) by increasing a firm’s ability to disclose details of its
invention; (3) by allowing those details to be conveyed with improved certification; and (4) by helping firms to signal
their quality. We recognize that the effects and determinants of patent litigation depend on the unique circumstances
9
frequency of litigation, one of the most controversial aspects of the current patent system, we use
this paper to offer new insights into the appropriateness of future reforms. Recognizing that policy
makers may wish to consider reforming the patent approval system in ways that address frequent
litigation, we argue that our study’s findings suggest that lawsuits may indeed have a positive
effect with respect to promoting intellectual property protection; in turn, this positive effect
benefits firm value.
We organize our paper as follows. In Section 2, we present our sample construction and
summary statistics. In Section 3, we describe our main results for stock market reactions to patent
litigation. In Section 4, we examine possible explanations for our empirical results. We conclude
this paper with Section 5.
2. Sample and summary statistics
To construct our data, we collect patent lawsuits related to public firms’ patents by
combining the patent database of public firms (available until 2014) and the Lex Machina database
for patent litigations (available since 2000). We begin by constructing a list of 1,609,059 patents
that were granted to public firms from 1983 to 2014 by combining the NBER patent dataset
(originally developed by Hall, Jaffe, and Trajtenberg (2001)), the patent dataset of Kogan et al.
(2017), and the Google Patent database. The updated NBER patent dataset contains the patent
number, application date, grant date, and Compustat firm identifier GVKEY of the patent assignee
(i.e., the firm that owns the patent) of all utility patents granted to public firms from 1976 to 2006.
Kogan et al.’s patent database includes the patent number, application date, grant date, and Center
for Research in Security Prices (CRSP) firm identifier (PERMNO) of the patent assignee of each
utility patent granted to public firms in 1926–2010. Lastly, we use the Google Patent database to
extend the patent data to all patents granted by 2014.13
of the litigants. For example, Chien (2009) describes litigation by two large firms as a “sport of kings,” litigation by
an independent inventor against a large firm as “David v. Goliath,” and litigation to exploit a defendant’s financial
distress as “patent predation.” 13 To find the GVKEY and/or PERMNO for assignees that own patents granted in 2011–2014, we first collect the
company names and locations of the patent assignees that are public firms and that receive at least one patent in the
period 1976-2010. The company names are from the CRSP and Compustat databases. We then develop a matching
10
We start our patent list with the 1983 grant year because patents were valid for 17 years
from the grant date at that time, and the Lex Machina database is available from 2000 (since June
8, 1995, patents are valid for 20 years from their application date). Then, we use this list of
1,609,059 patents in our search in the Lex Machina database, which includes patent litigations
announced since 2000. In establishing its database, Lex Machina cleaned and verified daily
updates from the United States federal court system, all United States district courts, the United
States International Trade Commission database (EDIS), and the USPTO. Lex Machina is
regarded as the most comprehensive database of U.S. patent litigation since 2000. Other recent
studies have used data from Lex Machina (Akcigit, Celik, and Greenwood, 2016; Allison, Lemley,
and Schwartz, 2015, 2018; Cohen, Gurun, and Kominers, 2016b, 2018). We derive a list of 9,343
patent litigations (“Case_IDs”) in which the involved patents were granted to at least one public
firm, which includes those without court decisions or out-of- court settlements.
When evaluating the effects of patent litigation, it is important to recognize the differences
between practicing entities (PEs) and non-practicing entities (NPEs, or “patent trolls”).14 Evidence
suggests that PEs’ patent litigation has not increased at the same rate as that of NPEs. A great deal
of litigation with PEs involves inadvertent infringement (Bessen and Meurer, 2013) and, more
generally, is driven by the actual infringement itself, as opposed to being driven by exploiting the
profitability of potential lawsuits (Cohen, Gurun and Kominers, 2016b, 2018). Since our study
focuses on litigation between PEs, we exclude all lawsuits related to patent trolls. We manually
identify litigants that are not manufacturers, universities, government entities, or non-profit firms,
and also identify those whose firms’ activities are classified as intellectual property consulting
according to Google search websites. By merging this list with the sample of public patent trolls
used by Bessen, Ford, and Meurer (2011), we construct a list of NPEs that we use to filter out
NPE-related cases.15 For brevity’s sake, we use the term “patent litigation” to describe a firm
involved in a litigation case that is related to a public firm’s patents, but that is unrelated to NPEs.
algorithm that matches the name and location of each patent assignee that appears in 2011–2014 to the name and
location in the list of assignees in 1976-2010. As a result, we construct a database of patents granted to U.S. public
firms from 1976 to 2014. 14 Nevertheless, Bessen, Neuhausler, Turner, and Williams (2015) find no differences in announcement effects for
PEs and NPEs (after they include their control variables). 15 An alternative approach, to which our results are robust, is to omit cases filed in the Eastern District of Texas (a
venue that is often preferred by patent trolls).
11
For each patent litigation case unrelated to NPEs, we manually match the plaintiff and
defendant names to the corresponding GVKEY and PERMNO in the CRSP and Compustat
databases. Doing so yields 1,216 unique public firms involved in a total of 4,721 patent litigation
cases in our sample period. We then collect the financial data of these firms from CRSP and their
accounting data from Compustat. We exclude financial firms with SIC codes between 6000 and
6999 and utility firms with SIC codes beginning with 49.
To show how litigation intensity varies over time in our sample, the upper panel of Figure
1 provides the number of patent litigation cases with publicly-traded plaintiffs in each year
(Plaintiff), the number of cases with publicly-traded defendants in each year (Defendant), and the
number of cases with any publicly-traded litigants in each year (Both).16 We observe continuous
growth in patent litigation for most of our sample period: the number of patent litigation cases
gradually increases to 2007 and then dips in 2008 (perhaps consistent with the effects of the
financial crisis). The number peaks in 2012 with 535 observations in the Both group, and then
gradually declines. The decline in recent years may be attributed partly to the Leahy-Smith
America Invents Act, which reduces patent litigation (e.g., Cohen, Gurun, and Kominers, 2018).
Since a case may involve multiple public firms and their stocks, we also plot the number of stocks
involved in patent litigation (i.e., stock-case observations).17 The lower panel of Figure 1 provides
the annual number of all stock-case observations in each group (Plaintiff, Defendant, and Both); it
shows a mostly similar pattern, and peaks in 2012 (with a value of 2,027 in the Both group).
Since we also have patent numbers of each litigation case, we find that, in 82.3% of sample
cases, all litigated patents belong to plaintiffs. In addition, in 16.5% of sample cases, all litigated
patents belong to defendants. Lastly, both plaintiffs and defendants own parts of litigated patents
in 1.1% of sample cases. Moreover, as we note in the introduction, our sample includes declaratory
judgments (9.9% of our sample cases), where the alleged infringer is the plaintiff and asks the
court to provide clarity regarding whether infringement is occurring.
16 When both the plaintiff and defendant of a litigation case are public firms, this case is counted in all three groups. 17 A firm involved in multiple cases will be counted as having multiple stock-case observations.
12
3. Empirical Results
3.1. Announcement returns around disclosure
We first examine the stock market’s reaction to the disclosure of patent litigation in our
sample, based on Lex Machina from 2000 through 2014. In Table 1, we provide the cumulative
abnormal returns (CAR) of a stock in an event window [-n, m] starting from n days before the
disclosure day (day 0) to m days after the disclosure day. We consider three ways to calculate CAR.
Specifically, CAR1 is defined as the cumulative daily returns in excess of the CRSP value-
weighted market index in the period; CAR2 is defined using the CAPM model with market beta
estimated during the window of trading days -171 through -22 with a minimum of 100 non-missing
observations (as in Bhagat, Brickley, and Coles, 1994); CAR3 replaces the CAPM model in CAR2
with the Fama-French four-factor model including the market factor, SMB factor, HML factor,
and MOM factor to account for market beta, the beta to the size premium, the beta to the value
premium, and the beta to momentum premium.
In Panels A1 and A2, we focus on the following four event windows: [-1, 10], [-1, 24], [-
3, 10], and [-3, 24]. We select these windows to more effectively capture the effect of announced
litigations, since Bessen and Meurer (2012) point out the delayed announcement and reporting of
patent litigation, and express the concern of lawsuits not being disclosed (either widely or at all)
around smaller event windows.18 For example, -3 indicates that the period starts three days before
disclosure and 10 indicates that the period ends ten days after disclosure. For each disclosure, we
categorize each stock into either the plaintiff or defendant group, and report the mean and median
of cumulative abnormal returns and the number of stocks (NSTOCK) in Table 1. For each litigant
type (Plaintiff, Defendant, and Both), we also provide the number of patent litigation cases
(NCASE). It is noteworthy that one case may involve multiple public firms on both sides, so
NSTOCK is larger than NCASE.
We provide the mean, median, and statistical significance for CAR in different samples in
Table 1: Panel A1 includes all litigation cases, and Panel A2 includes the litigation cases with both
18 Bessen and Meurer (2012) focus their analysis on the [-1, 24] window, and Bessen, Neuhäusler, Turner, and
Williams (2015) consider the [-1, 3] and [-1, 23] windows.
13
a public plaintiff and a public defendant.19 We find that both plaintiffs and defendants consistently
experience significant positive cumulative abnormal returns around the disclosure dates of patent
litigation. Examining CAR1 in Panel A1, we note that the plaintiff group provides cumulative
abnormal returns of 52 basis points in the [-1, 10] window, 114 basis points in the [-1, 24] window,
55 basis points in the [-3, 10] window, and 118 basis points in the [-3, 24] window. The magnitudes
are comparable when we use CAR2 (with values of 52, 111, 55, and 114 basis points over the [-1,
10], [-1, 24], [-3, 10] and [-3, 24] windows, respectively) and CAR3 (with values of 43, 95, 43, and
95 basis points over the [-1, 10], [-1, 24], [-3, 10] and [-3, 24] windows, respectively). These values
are all significantly positive, suggesting that the stock market evaluates the initiation of patent
litigation as positive news.
The defendant group also experiences significantly positive cumulative abnormal returns.
Specifically, this group experiences cumulative abnormal returns (CAR1, CAR2, or CAR3) of 25-
33 basis points in the [-1, 10] window, 83-109 basis points in the [-1, 24] window, 25-35 basis
points in the [-3, 10] window, and 83-110 basis points in the [-3, 24] window. All of these values
are significantly positive (with the exception of the first and third windows for CAR3), suggesting
that the stock market reacts positively to the event of being sued.
We combine all defendant and plaintiff stocks in each event window in the column labelled
“Both”, and we find that this group provides cumulative abnormal returns (CAR1, CAR2, or CAR3)
of 33-42 basis points in the [-1, 10] window, 90-113 basis points in the [-1, 24] window, 33-45
basis points in the [-3, 10] window, and 90-115 basis points in the [-3, 24] window. All of these
estimates are significantly positive.
One possible concern with the results reported in Panel A1 is if public firms
disproportionately benefit from patent litigation by opportunistically suing smaller, private firms,
or have financial or other advantages when they are sued by smaller, private ones. We examine
this concern in Panel A2, where we restrict our sample to cases with both a public plaintiff and a
public defendant. After imposing this filter, we still find significantly positive CARs in most cases.
In fact, we find that the abnormal returns become even higher: for each of the 36 CARs calculated
19 When there is more than one plaintiff (defendant), we require at least one plaintiff (defendant) to be publicly listed,
in forming the sample used in Panel A2.
14
in the panel, the value exceeds the corresponding value in Panel A1. These results do not support
the argument that public firms have advantages in patent litigation against smaller, private firms,
and suggest that the significantly positive announcement returns are a general pattern existing in
different samples.
At first glance, the significantly positive announcement returns experienced by both
plaintiff and defendant groups might appear to be surprising for two reasons. First, the direct and
indirect costs associated with patent litigation are non-trivial and would potentially lead one to
expect negative announcement returns. Second, patent litigation is frequently treated by financial
analysts and media as a zero-sum (or even negative-sum) game for plaintiffs and defendants.
Consequently, the arguably intriguing pattern that we identify—both sides’ stock prices reacting
positively to the initiation of patent litigation—calls for further explanation.
Some might argue that disclosure of patent litigation might make investors aware of
specific systematic risk associated with the litigants and that such risk is resolved quickly within
10 or 24 days. These stocks might thus be expected to provide higher returns during that narrow
event window as compensation for the short-term risk. However, if the announcements make
investors aware of some risk exposure, those investors should discount the stock price immediately
on announcement dates. To examine this possible explanation, we examine the average returns in
the short windows [-1, 1] and [-3, 3], which we show in Panels B1 and B2 of Table 1. Panel B1
includes all litigation cases, and Panel B2 includes the litigation cases with both a public plaintiff
and a public defendant. Our finding of no significant price drops in either of these windows does
not support the explanation of newly discovered (and soon resolved) risk exposure. In contrast, it
support Bessen and Meurer’s (2012) finding of limited disclosure/reporting immediately around
litigation filing dates.
In Panel C, we examine the relation between the CARs of the plaintiffs and defendants to
evaluate whether a positive market reaction for a defendant (i.e., news that it intends to challenge
the lawsuit) is associated with offsetting reactions to the plaintiff. The sample in Panel C includes
all cases with both a public plaintiff and a public defendant, and shows that the correlation between
plaintiffs’ and defendants’ CARs is, in fact, positive. The correlation coefficients (CAR1, CAR2,
or CAR3) are 2.99%-3.47% for the [-1, 10] window, 6.48%-8.27% for the [-1, 24] window, 4.67%-
15
5.70% for the [-3, 10] window, and 7.62%-8.32% for the [-3, 24] window, all statistically
significant except for the first window. These significantly positive correlations indicate that the
positive CARs do not generally come at the expense of the opposing party in patent litigation;
rather, they indicate that the market reacts positively to both plaintiffs and defendants, even though
the lawsuit places them on opposing sides.
3.2. Portfolio analysis for the returns in the subsequent 12 months
Having documented a pattern of positive daily stock returns, we now examine monthly
stock returns using a calendar-time portfolio approach. At the end of every month, t, from January
of 2000 to November of 2014, we create a portfolio for firms that were involved in patent litigation
within the most recent 12 months (t-11 to t) and for their opponents. We use such a calendar-time
portfolio instead of an event-time portfolio, as the latter treats each stock involved in each litigation
case as an event and forms a portfolio based on all events. Since a stock can often be involved in
multiple patent litigations in the same period, an event-time portfolio will be subject to issues that
include a cross-correlation of event returns and overweighting stocks with multiple cases. We hold
this portfolio for the next month t+1, calculate its equal-weighted portfolio return at the end of the
month, and then adjust/rebalance the portfolio in a similar way, based on patent lawsuits
announced from t-10 to t+1 at the end of month t+1.20 Similar to Table 1, we report the portfolio
results in two panels: Panel A includes all litigation cases, and Panel B includes the litigation cases
with both a public plaintiff and a public defendant.
In Panel A of Table 2, we present the average monthly excess returns (i.e., monthly returns
in excess of the one-month T-bill rate) of the constructed portfolio (“litigation portfolio”
henceforth) and the alphas based on various linear factor models to control for various systematic
20 Because the number of stocks involved in the portfolio is small (212, on average), we focus on equal-weighted
portfolio returns to ensure that the effects of patent litigation on all stocks are presented, following Loughran and
Ritter (2000), Chan, Lakonishok, and Sougiannis (2001), Eberhart, Maxwell, and Siddique (2004), and Lyandres,
Sun, and Zhang (2007). If a firm is involved in two cases as a plaintiff and in one case as a defendant, then it is weighed
by three in the litigation portfolio. The results based on the value-weighted portfolios are robust, albeit with weaker
statistical significance.
16
risk or other potential explanatory factors.21 In Model 1, we present the average monthly excess
return, which is as high as 102 basis points per month with a t-statistic of 2.07. Such an estimate
is of reasonable statistical significance, especially given that our sample period is only 179 months
long (February 2000 to December 2014).
In order to consider various systematic risk or other potential explanatory factors in Models
2 to 8, we conduct time-series regressions by regressing the monthly excess returns of the portfolio
on various combinations of return factors, and then report the estimate and statistical significance
of the intercept term (“alpha”) in Panel A. In the Fama-French four-factor model (Model 2), the
alpha is 60 basis points per month with a t-statistic of 3.99. The six-factor model of Fama and
French (2015) that includes the profitability factor RMW and the investment factor CMA (Model
3) generates an alpha of 57 basis points per month with a t-statistic of 3.47. These findings suggest
that the return of the litigation portfolio cannot be explained by the size effect, value effect,
momentum effect, profitability effect, or the investment effect.
In Models 4 to 6, we add each of the following innovation-related factors to Model 2: an
R&D factor, a patent factor, and an innovative efficiency factor. The R&D factor is the difference
between the monthly returns of the high R&D portfolio and that of the low R&D portfolio. The
high (low) R&D portfolio consists of firms with R&D capital (the R&D expenditure over the
rolling five-year period, with 20% annual depreciation) divided by the market value of equity in
the top 20% (bottom 20%), following Chan, Lakonishok, and Sougiannis (2001) and Lev, Sarath,
and Sougiannis (2005).22 The patent factor is the difference between the monthly returns of the
high patent portfolio and those of the low patent portfolio. The high (low) patent portfolio consists
of firms with the number of patents granted over a rolling five-year period (with 20% annual
depreciation) divided by total assets in the top 20% (bottom 20%).23 The innovative efficiency
factor is the difference between the monthly returns of the high efficiency portfolio and those of
the low efficiency portfolio. The high (low) efficiency portfolio consists of firms with the log of
21 Our one-month T-bill rate and Fama and French factors—MKT, SMB, HML, UMD, RMW, and CMA—are from
the Kenneth French data library. The Hou, Xue, and Zhang q-factors—IA and ROE—are from Lu Zhang. The
Stambaugh and Yuan mispricing factors—MGMT and PERF—are from Yu Yuan's website. We thank Kenneth
French and Yu Yuan for making the data publicly available, and thank Lu Zhang for sharing the data with us. 22 R&D capital in year t is defined as the sum of [1- 0.2τ] times R&D expense in years t-τ (with τ ranging from 0 to
4), following Chan, Lakonishok, and Sougiannis (2001). 23 We scale the number of granted patents by total assets following Hall, Jaffe, and Trajtenberg (2005) and Noel and
Schankerman (2013).
17
the number of patents granted over a rolling five-year period (with 20% annual depreciation) minus
the log of one plus the industry-adjusted R&D expenditure over a rolling five-year period (with
20% annual depreciation) in the top 20% (bottom 20%).24 We find positive coefficients on the
R&D factor and the patent factor. Nevertheless, the alphas from the models that include
innovation-related factors range between 56 and 58 basis points per month and remain statistically
significant (with t-statistics above 3), suggesting that the return of the litigation portfolio cannot
be explained by R&D- or patent-based factors.
In Models 7 and 8, we consider two new factor models and find even higher alphas: the q-
theory factor model of Hou, Xue, and Zhang (2015) and the mispricing factor model of Stambaugh
and Yuan (2017). The q-theory factor model includes a market factor, a size factor, an investment
intensity factor, and a profitability factor that are derived from a q-theory model; the mispricing
factor model includes a market factor, a size factor, a management factor, and a performance factor.
The former and the latter generate alphas of 75 and 72 basis points per month with t-statistics of
3.74 and 3.33, respectively. These results suggest that the return of the litigation portfolio cannot
be attributed to investment-based risk or common mispricing factors.
Our results remain similar in Panel B of Table 2, in which we restrict our sample to lawsuits
where both the plaintiff and defendant are public. The excess returns and alphas of the litigation
portfolio are comparable to (and slightly larger than) the counterparts in Panel A, which confirms
an intriguing finding in Table 1: market reactions seem to be even more positive when the opposing
party in the litigation is another public firm. This panel thus confirms that our results are not driven
by large public firms’ advantages in patent litigation against smaller, private firms. As we observe
consistent results across different case samples in both Tables 1 and 2, we will only report the
results based on all litigation cases for the rest of our analyses for brevity.
An important implication of Table 2 is that the positive short-term stock returns that we
report in Section 3.1 are persistent and do not revert in the future. In fact, firms involved in patent
litigation not only experience short-term stock price appreciation, but also provide significantly
24 The construction of the innovative efficiency factor is motivated by Cohen, Diether, and Malloy (2013) and
Hirshleifer, Hsu, and Li (2013).
18
greater stock returns in the following year. Consequently, a positive litigation-return relation
receives further support and calls for further explanation.
We further examine the robustness of Table 2 by using alternative definitions for our
sample of relevant firms. In Panel A of Table 3, we include firms that were involved in any patent
litigation in month t-11 to t but were not involved in any patent litigation in months t-23 to t-12
(the prior year). We consider this alternative approach in constructing our sample in order to
mitigate the concern that some firms may be involved in patent litigation for many years and are
always present in our portfolio. That said, we find that our results are robust when we exclude such
firms: in Panel A, the mean excess returns and alphas of the portfolio range between 56 and 108
basis points per month, with t-statistics ranging from 2.08 to 3.57.
In Panel B of Table 3, we restrict treated firms to only defendants and find that our results
are robust when we focus on such firms: the mean excess returns and alphas of the defendant
portfolio are commensurate to (albeit slightly weaker than) their counterparts in Table 2. This
finding further supports our earlier argument that defendants in patent litigation cases may also
benefit from the announcement of patent lawsuits.
As discussed earlier, it may be inappropriate to separate our sample into the plaintiff and
defendant groups because, with Declaratory Judgments, the plaintiffs are alleged infringers and
the defendants are patent owners claiming to own patent rights. In addition, our analyses thus far
suggest that both parties experience significantly positive price increases in most scenarios. Thus,
in subsequent analyses, we include all plaintiffs and defendants in our test sample.
Another possible concern is if the findings from our portfolio analysis in Table 2 are subject
to industry effects, for some industries may be subject to greater patent litigation risk and also
provide greater stock returns at the same time. To address this concern, we construct portfolios
that include only industry-matched firms. In this approach, we define “treated” firms as those that
experienced patent litigation within the previous 12 months. For each treated firm in each month,
we match it with another firm (i.e., control firm) with the same SIC 2-digit industry code and with
the closest distance in size, book-to-market ratio, momentum, profitability, and investment. At the
end of every month from December of 2000 to December of 2014, we create an equal-weighted
portfolio (“Control”) for these control firms in each month and then track its equal-weighted return
19
in the next month. Similarly, we create an equal-weighted portfolio (“Treated”) for these treated
firms, so we can find matched control firms in each month and then track their equal-weighted
returns in the next month. We also construct a difference portfolio by taking a long position in the
treated portfolio and taking a short position in the control portfolio. We then report the mean excess
returns and alphas of the treated portfolio, the control portfolio, and the difference portfolio. The
difference portfolio generates monthly returns of 30-45 basis points per month, which are
statistically significant at the 5% level in all models.
Consequently, we use Tables 3 and 4 to confirm the robustness of a positive litigation-
return relation by excluding firms that frequently experience patent litigation, by focusing on
defendants, and by controlling for industry-specific issues.
3.3. Fama-MacBeth cross-sectional regressions for returns
In this section, we continue our analysis by using monthly Fama-MacBeth (1973) cross-
sectional regressions for all public firms (except financial and utility firms) in the
CRSP/Compustat database, which enables us to control more directly for characteristics
potentially associated with returns, so we may examine whether the effect of patent litigation on
stock valuation is distinct from that of other firm or industry characteristics. In these regressions,
our focal variable is an indicator variable, DUMMY_CASE, for whether a firm experiences patent
litigation in the prior 12 months, either as a plaintiff or a defendant. The other control variables
include returns over the previous month (RET), the log of the book-to-market ratio (LOGBM), the
log of the market value of equity (LOGME), the log of one plus the R&D expense over the past
five years using an annual discount rate of 0.2, divided by total assets (LOGXRD), the log of one
plus the number of patents granted in the past five years divided by the book value of total assets
(LOGNPATENT), cumulative returns over the past twelve months with a one-month gap (MOM11),
cumulative returns over the past three years with a one-year gap (MOM36), the growth rate of the
book value of total assets (INV), stock operating profit defined by revenue minus the costs of goods
sold, interest expense, selling, general and administrative expense, divided by book value of equity
(OP), cash flow scaled by total assets (CF), the Kaplan-Zingales index (KZ), long-term debt plus
current liabilities scaled by the book value of equity (LEVERAGE), gross profit scaled by sales
20
(PM), and the Herfindahl-Hirschman Index (HHI), based on the sales of shares in industries
defined by 2-digit SIC codes.
In Table 5, we report the summary statistics (mean, median, and standard deviation) of the
related variables for the following four litigation groups: (1) Plaintiff: those in which the firm was
a plaintiff in at least one patent lawsuit and was not a defendant in any litigation in the prior year;
(2) Defendant: those in which the firm was a defendant in at least one patent lawsuit and was not
a plaintiff in any litigation in the prior year; (3) Mixed: those in which the firm played both roles
(i.e., it was a plaintiff in at least one patent lawsuit and was a defendant in at least one patent-
related litigation in the prior year); and (4) No case: those in which the firm was neither a plaintiff
nor a defendant in any patent lawsuit in the prior year. Distinguishing our results in this manner
enables us to evaluate the differences between firms based on their status as litigants.
The median Plaintiff firm experiences two lawsuits per year, the median Defendant firm
also experiences two lawsuits per year, and firms that experience both types of litigation (Mixed)
experience eight lawsuits per year. Consistent with the intuition that larger firms experience
significantly more litigation, the number of cases per year are skewed; for example, Mixed firms
experience a mean of 13 lawsuits per year. We find that median book-to-market (BM) ratio is
larger for firms that do not experience any litigation compared to those that do experience litigation,
and R&D capital stock (XRD) is smallest for firms that do not experience litigation. Firm size (ME)
is consistent with larger firms experiencing more litigation: firms without any litigation are
smallest, plaintiffs are slightly smaller than defendants, and firms that are both plaintiffs and
defendants are the largest. Plaintiffs have more patents (NPATENT) than defendants, consistent
with the former group’s desire to enforce their intellectual property rights. Median returns over the
prior three years (MOM11 and MOM36) and operating performance (OP) are smallest for firms
that do not experience litigation, perhaps consistent with these firms being less likely to be targeted
for litigation (or behaving more conservatively to avoid litigation). Consistent with litigation
targeting relatively cash-rich firms, firms that do not experience any litigation have the lowest
level of cash flow (CF) and the highest measure of financial constraints (KZ) of all the groups.
Similarly, litigation intensity increases with profit margins (PM): firms not experiencing litigation
have the lowest profit margins, and those that are both plaintiffs and defendants have the highest
profit margins. Finally, litigation intensity declines with industry concentration (HHI), since firms
21
that do not experience any litigation have the highest value of HHI, and those that acted as both
plaintiffs and defendants have the lowest value of HHI.
In Table 6, we provide the means and t-statistics based on the times series of the
coefficients on all explanatory variables from our Fama-MacBeth cross-sectional regressions. Our
focal variable is DUMMY_CASE, which is an indicator variable equal to one for a firm in month t
if the firm is involved in any patent litigation over the past 12 months (t-11 to t) as either a plaintiff
or defendant, and zero otherwise. In each month t from December 2000 to December 2014, we
conduct a cross-sectional regression by regressing the monthly excess returns of all firms in month
t+1 on DUMMY_CASE of all firms in month t, all control variables known in month t, and industry
fixed effects based on 2-digit SIC codes. These cross-sectional regressions let us estimate the
coefficient on DUMMY_CASE in every month. We then test if the average of monthly coefficients
on DUMMY_CASE is statistically significant by using the time-series of monthly coefficients, and
report the average and t-statistics in Table 6. We apply the same procedure for the coefficients on
control variables. The first four specifications (Models (1) through (4)) do not use industry fixed
effects; the final four specifications (Models (5) through (8)) include industry fixed effects.
We find that the litigation-related variable (DUMMY_CASE) is positive in all specifications,
with a magnitude of 23-33 basis points per month; the t-statistics range between 2.50 and 3.65.
The signs and magnitudes of the coefficients of other control variables are largely consistent with
the literature. Consequently, our baseline findings that firms involved in patent litigation are
associated with significantly higher subsequent stock returns remain robust when we control for
relevant firm- and industry-specific variables. Therefore, firm and industry characteristics cannot
(fully) explain our baseline results.
4. Possible Explanations
We now examine four possible explanations for our baseline finding that patent litigation
positively predicts stock returns. First, systematic risk related to patent litigation might exist, and
firms involved in patent litigation carry higher exposure to such risk, which provides greater
expected returns. Second, systematic risk related to financial constraints might exist, such that
22
financially constrained litigants may be subject to risk to a greater extent. Third, only firms that
are rich in cash are sued and provide higher future stock returns. Finally, substantial benefits
related to patent lawsuits might exist that exceed the associated costs, and these benefits might be
undervalued by the market.
4.1. Systematic risk related to patent litigation
In this section, we provide additional analyses to examine if the return predictability
associated with patent litigation can be explained by systematic risk. Firms involved in patent
litigation are subject to discounts in their stock prices due to greater systematic risk exposure, and
are thus expected to provide higher expected stock returns to investors as risk premia. In Section
3.1, we argue that this explanation is not supported by the observation that the average return of
firms in the three-day window around the disclosure of patent litigation is positive. Nevertheless,
to further examine the risk explanation, we employ a two-pass procedure to test if the return on
the litigation portfolio serves as a risk factor. If the litigation portfolio we construct in Section 3.2
creates significantly positive monthly excess returns and alphas (as reported in Table 2), that
portfolio may be considered as a mimicking portfolio that reflects the risk compensation for
bearing one unit of risk exposure to a systematic risk associated with patent litigation (see Fama
and French (1993)).
In this section, we refer to the monthly returns on the portfolios formed by firms that are
involved in patent litigation (litigation portfolio) as the “litigation factor.” Then, we test if this
factor exists in a linear stochastic discount factor model by implementing a two-pass procedure
(see Cochrane (2001)). First, we conduct a rolling window estimation to estimate the beta
associated with the litigation risk, βi,Litigation, for stock i using its stock returns in the most recent 60
or 12 months. For example, for stock i in month t, we estimate its βi,Litigation,t by regressing its
monthly excess returns on the litigation factor and other factors (MKT, SMB, and HML) from
month t-59 (or t-11) to month t. Then, we conduct a cross-sectional regression for each month; for
each month in our sample period, we regress the monthly excess returns of all stocks on the
litigation betas of all stocks (and other betas, such as market betas) to calculate the coefficient on
the litigation betas for the month. The coefficient on the litigation beta (βLitigation) serves as an
23
estimate of litigation risk premium (known as “lambda”) in the month. Finally, we test the
significance of the litigation risk premium by the time series mean and standard deviation of the
coefficients on litigation betas across all months and report our results in Table 7: a significantly
positive coefficient associated with βLitigation indicates that the litigation factor is positively priced
in testing assets. On the other hand, an insignificant coefficient associated with βLitigation indicates
a lack of evidence that the litigation-return relation is driven by risk.
The results across all panels in Table 7 indicate that the coefficient on βLitigation is
consistently insignificant across various models and specifications.25 In Panel A, we present our
results using 60 months to estimate beta, and we use Panel B to present our results using 12 months
to estimate beta. As we cannot find any significant coefficient on βLitigation that reflects litigation
risk premium in the various models in Table 7, we note that the litigation factor is not priced in the
stock market, which casts doubt on the likelihood that our results are driven by any systematic risk
associated with patent litigation.
4.2. Systematic risk related to financial constraints
Another potential risk-based explanation for our results is that costly patent litigation
affects financially constrained firms in particular, as R&D-intensive firms incur greater systematic
risk when they are under financial constraints (Li, 2011). Costly patent litigation makes these
R&D-intensive firms subject to such risk (Lanjouw and Schankerman, 2004), and this explanation
would predict excess returns to be concentrated in those financially constrained firms. In Panel A
of Table 8, we examine this possibility by creating portfolios sorted by financial constraints, based
on the Kaplan-Zingales index (1997). In particular, we classify all firms experiencing patent
litigation by their financial constraints into three groups: the low group includes firms with
financial constraints below the 30th percentile, the high group includes firms with financial
constraints above the 70th percentile, and the middle group includes firms with financial constraints
between the 30th percentile and the 70th percentile. We then calculate the equal-weighted excess
returns for each group in each month, and report the mean excess returns and alphas (similar to
25 These results use all individual stocks as test assets; however, our results are also robust when we use industries or
portfolios as test assets.
24
Table 4). At the bottom of each panel, we report the mean excess returns and alphas (and the
corresponding t-statistics) of a high-minus-low (High-Low) portfolio that takes a long position in
the high group and a short position in the low group. If the litigation-return relation is caused by
financial constraints, we would expect a stronger predictive ability in the high group (i.e., the high
group will outperform the low group in excess returns and alphas).
We find that the mean excess returns and alphas of the High-Low portfolio range between
2 and 27 basis points per month, although these values are not statistically significant. This finding
indicates that the effect of patent litigation on stock returns does not concentrate on financially
constrained firms. Thus, it is difficult for us to attribute the litigation-return relation to the
systematic risk associated with financial constraints. In Panel B, we show that this pattern holds
when we only consider defendants (since this issue is particularly acute among financially
constrained defendants). Our results remain similar to those provided in Panel A.
Panels A and B of Table 8 thus suggest that the higher stock returns associated with firms
involved in patent litigation cannot simply be attributed to systematic risk associated with financial
constraints.
4.3. Cash holdings
In Panel C of Table 8, we consider an important driver of litigation—cash—that may
explain our baseline finding. Firms with larger cash balances are known to attract patent litigation
since they are able and/or are more willing to settle lawsuits. It is possible that our excess returns
are driven by cash-rich firms that both attract litigation and outperform in stock returns in
subsequent periods.
To evaluate this explanation, we implement one-way sorts based on our proxies for cash
holdings, which is defined as cash and marketable securities scaled by lagged total assets. In each
month, we divide firms that had experienced litigation in the prior 12 months into three groups,
based on their cash holdings. As in Panel A, the three groups are defined by the 30th and 70th
percentiles of cash holding: the low group includes firms below the 30th percentile, the high group
includes firms above the 70th percentile, and the middle group includes firms between the 30th
25
percentile and the 70th percentile, similar to Panels A and B. We present the mean excess return,
the difference in excess return between the low and high groups, and the t-statistic of the difference
in Panel C of Table 8.
We do not find that the positive returns are significantly larger among cash-rich firms,
which indicates that the excess returns are not driven by cash-rich firms being more likely to attract
patent litigation. In Panel D, we provide the results among defendants only, as the impact of cash
on litigation could be more severe among defendants. Our results remain broadly comparable to
those that we provide in Panel C, albeit with statistical significance in Models 3 and 7.
4.4. Potential benefits from patent litigation
Our last explanation is that the benefits associated with patent litigation outweigh the
associated costs, but these benefits are generally undervalued by investors. The benefits should be
particularly intuitive for plaintiffs: they ought to only litigate when doing so increases value, and
the firm is likely to win its lawsuit. In addition, the initiation of patent lawsuits may illustrate to
investors the economic value or unique applications of plaintiffs’ patents. The announcement of a
patent lawsuit also informs the stock market of managerial determination and aggressiveness in
monetizing and protecting its intellectual property (Agarwal, Ganco, and Ziedonis, 2009), which
also positively contributes to firm value.
For defendants, being sued may increase their stock prices for the following reasons. First,
defendants who feel confident that they will win their lawsuits do not choose to settle their issues
out of court. Second, a lawsuit highlights the profits earned (or potentially being earned) from the
defendants’ use of certain intellectual property. In other words, defendants would generally not be
sued if they were not generating (or are not expected to generate) substantial profits from the
alleged patent infringement. Thus, patent litigation provides more information about the (expected)
value of the defendant to the market. Third, more generally, a lawsuit reduces the information
asymmetry associated with the defendant’s profits and/or innovations for investors (because more
information about each firm’s intellectual property is revealed over the course of the lawsuit),
which may also improve stock valuation. Fourth, patent litigation highlights the substantial barriers
26
to entry associated with a defendant’s operations and products, which may deter potential
competitors.
To test the explanation based on net benefits associated with patent litigation, we first
examine how patent litigation is associated with future profitability in Table 9. In particular, we
examine firms’ subsequent three-year and five-year average ROE, and perform annual Fama-
MacBeth cross-sectional regressions against DUMMY_CASE (the indicator variable for a firm
being a party in patent litigation within the prior 12 months) and other explanatory variables,
similar to our approach in Table 6, except that we use annual regressions instead of monthly
regressions. We examine the average ROE over the subsequent three-year and five-year periods
since the benefits associated with the patent litigation are likely to be recognized over time, albeit
with a delay. As we do in Table 6, we control for investment (INV), the log book-to-market
(LOGBM), the log market value of equity (LOGME), the log patent output (LOGNPATENT), and
the log R&D investment (LOGXRD). Additionally, to control for persistence in profitability, we
include the prior year’s ROE (ROE). Also, to control for mean reversion in profitability (Fama and
French, 2000), we include the prior one-year change in ROE (ΔROE). We also include industry
fixed effects.
Consistent with our proposition of litigation benefits, we find that the coefficient on
DUMMY_CASE is significantly positive: firms involved in any patent litigation (DUMMY_CASE
=1) are associated with an increase in the mean five-year ROE of 3.0% and an increase in the mean
three-year ROE of 2.4%. The slopes of the other explanatory variables are also as expected, and
experience little change with respect to the two different windows of future profitability. These
results support our argument that patent litigation may be, on average, beneficial to patent litigants
by both signaling the value of patents and the potential of associated profits to the public and
highlighting barriers to potential new competitors.
Another way to assess the increased barriers to entry associated with patent litigation is to
examine future competition at the industry levels. In Table 10, we examine the effects of patent
litigation on future five-year and three-year averages of Similarity and HHI as defined in Hoberg
and Phillips (2016), since both are important measures of competition in an industry (these
measures are based on textual analysis from firms’ 10-K annual filings of their business
27
descriptions). Consistently, our results point to the effects of increased barriers to entry following
patent litigation. Firms’ products become more differentiated as Similarity in the following five
years (three years) declines by 0.28 (0.29) around this time. Industries also become less
competitive as defined with the sales-based HHI, with average future HHI increasing by 1.5% in
the subsequent five-year and three-year periods. Consequently, using a range of industry-level
proxies of competition, we find that patent litigation leads to increased barriers to entry.
Tables 9 and 10 thus collectively help identify the mechanisms of our results by providing
evidence of higher future profits for patent litigants, as well as of increased barriers to entry in
their industries.
4.5. Undervaluation due to information delay
After presenting the positive relation between patent litigation and subsequent profitability
and the negative relation between patent litigation and future competition, we argue that investors
are unaware of and thus underreact to the positive value associated with firms’ involvement in
patent litigation. Such underreaction leads to our baseline finding that litigation predicts stock
returns. The details of patents and lawsuits are often complicated in ways that challenge investors,
even institutional ones, to readily analyze and comprehend these details (Hirshleifer, Hsu, and Li,
2013, 2018).26 In Table 11, we examine the information delay argument by using a one-way sorted
portfolio, similar to our approach in Table 8.
To do so, we rely on two information delay measures: stock return R2 as in Hou, Peng, and
Xiong (2013) and the delay in stock-price reactions to new information as in Hou and Moskowitz
(2005). In Panel A, we use the stock return R2 to measure information delay. Following Hou, Peng,
and Xiong (2013), stock return R2 is calculated as the R2 from regressing the stock’s monthly
returns on the contemporaneous returns of the CRSP value-weighted index portfolio and industry
portfolio, based on Fama and French 48 industries. We require a minimum of 24 observations to
estimate R2. Hou, Peng, and Xiong (2013) argue that a low R2 is associated with price inefficiency,
26 See Footnote 3 for a review of prior studies that have provided empirical evidence and explanations for the market’s
undervaluation of innovation-related information.
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in part by showing that a lower R2 is associated with greater medium-term momentum, and also
associated with stronger long-term price reversal.
In Panel B, we use Hou and Moskowitz’s (2005) price delay measure, which reflects the
delay in stock-price reaction to new information and is mostly driven by frictions in investor
recognition. Following Hou and Moskowitz (2005), we estimate price delay by the following two
steps. In the first step, at the end of June in each calendar year, we calculate the “first-stage
individual stock delay” measure. This measure is defined as one minus the R2 from the regression
of an individual stock’s weekly returns on the market portfolio and four weeks of lagged returns
on the market portfolio over the prior year. In the second step, we derive “second-stage portfolio
delay” measures to mitigate the errors-in-variables problem in individual stock regressions.
Specifically, at the end of June of each calendar year, we sort stocks into deciles based on their
market capitalization. Within each size decile, we then sort stocks into deciles based on their first-
stage individual delay measures. We then compute the equal-weighted weekly returns of the 100
size-delay portfolios over the following year from July to June, and we re-estimate the regression
in step one by using the entire past sample of weekly returns for each of the 100 portfolios in the
second stage. We then assign the computed delay measures for each portfolio to each stock within
the portfolio, and defined them as stock-level price delay.
In each month from January 2000 to November 2014, we classify firms that had
experienced litigation in the prior 12 months into three groups based on each of the information
delay proxies: the group consisting of firms with information delay proxies below the 30th
percentile is defined as the “low” group, the group consisting of firms with information delay
proxies above the 70th percentile is defined as the “high” group, and the group consisting of firms
with information delay proxies between the 30th and 70th percentiles is defined as the “middle”
group.27 We present the mean excess return, the difference in excess return between the high and
low groups (High-Low), and the t-statistic of the difference in Table 11. In both panels, we show
that the litigation-return effect is larger among firms with greater information delay; this difference
27 Specifically, when we use stock return R2 as the proxy for information delay, the high group includes firms with the
lowest 30% R2, the low group includes firms with the highest 30% R2, and the middle group includes the remaining
firms. When we use price delay as the proxy for information delay, the high group includes firms with the highest 30%
price delay, the low group includes firms with the lowest 30% price delay, and the middle group includes the remaining
firms.
29
is statistically significant across models in Panels A and B based on R2 and price delay,
respectively.
In Panel A, litigants with low return R2 are associated with significantly higher excess
returns than those with high return R2, as shown by the significantly negative differences in the
High-Low row. In particular, the differences range from 81 to 107 basis points per month
(depending on the model used); all differences are statistically significant at the 5% level. In Panel
B, based on the price delay measure of Hou and Moskowitz (2005), we again find that litigants
with high information delay are associated with significantly higher excess returns. The differences
in excess returns between the high and low groups range from 63 to 84 basis points per month, and
are statistically significant in all but two models.
Table 11 thus provides support for our fourth explanation of our results based on
underraction: the benefits of firms experiencing patent litigation are not immediately observed
and/or understood by investors, which results in positive return drifts in both daily and monthly
frequencies.
5. Conclusion
Patent litigation has important and wide-ranging effects on firms, and firms are
experiencing patent litigation with increased frequency. Although there are significant direct and
indirect costs associated with this type of litigation, there are also well-documented benefits,
including increases in patent citations and patent value following litigation, signaling managers’
determination and confidence to the market, increased barriers to entry for more litigation-
intensive industries, reduced information asymmetries for investors, and increased prominence of
firms’ intellectual property.
In this paper, we examine the effects of patent litigation on firms’ stock prices, focusing on
the role of practicing entities. Our empirical results suggest that the positive effects associated with
patent litigation outweigh the associated costs. Consistent with these effects, we show that both
plaintiffs and defendants experience positive stock returns following the announcements of patent
30
litigation. We then show that these firms experience significantly positive returns over the longer
term as well.
Further analyses indicate that firms involved in patent litigation provide higher future
profits and experience less future competit