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Stock market reactions to adverse ESG disclosure via media channels
Jin Boon Wong1* and Qin Zhang1
1 Macquarie University, Sydney, NSW 2109, Australia
Abstract
This study examines the value relevance of corporate reputation risks (CRR) from adverse
media coverage of environmental, social and governance (ESG) issues on stock performance
at the firm level. Empirical results advance signalling theory and resource-based view by
providing evidence that corporate reputation is considered a valuable intangible asset by
investors and adverse ESG disclosure via media channels have a significant and negative
impact on firm valuation. The research is extended using various factors and indicates that
heightened CRR have a substantially negative corollary effect on stock price of smaller and
less liquid firms that are typically not S&P500 constituents. Further analysis using industry
classifications reveals that stock performance of companies in the ‘sin’ triumvirate (i.e.,
alcohol, tobacco, and gaming) is not significantly affected by negative ESG media coverage.
Instead, firms in candy & soda, steel works, banking, and insurance industries are the most
susceptible to investors’ repercussion from undesirable media spotlight. These findings provide
new insights and indicate that beyond the type and delivery method of ESG disclosures, firm
characteristics, corporate reputation status and industry explain differences in investors’
reaction to ‘bad’ news.
JEL classification: G14, G30, G32, G40
Keywords: Corporate reputation; ESG; CSR; signalling; information asymmetry; market
behaviour
* Corresponding author. Jin Boon Wong. Tel: +61 (2) 9850 6815. Email: jeffrey.wong@mq.edu.au Macquarie
University, Sydney, NSW 2109, Australia.
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1. Introduction
Internationally, there are increasing societal demands for corporate social responsibility (CSR)
initiatives and environmental, social and governance (ESG) accountability beyond that of
mandated requirements (Brooks and Oikonomou, 2018; Gillian, Koch, and Starks, 2021).1 This
has drawn significant practitioner and academic attention to the information content of firms’
CSR reputation on their corporate financial performance (e.g., Chen, 2020; Hsu et al., 2020;
Harjoto et al., 2021). Prior studies examining the value relevance of corporate reputation on
stock market performance and firm valuation have focused predominately on the incremental
effects from positive CSR ratings (e.g., Ingram, 1978; Jaggi and Freedman, 1992; Murray et
al., 2006; Moneva and Cuellar, 2009 and Hussainey and Salama, 2010; Minor and Morgan,
2011; Servaes and Tamayo, 2013; Lourenco et al., 2014; Harjoto and Jo, 2015; Mishra, 2017;
Lenz et al., 2017; Buchanan et al. 2018; Aouadi and Marsat, 2018; Jeong et al, 2018). To-date,
there is a paucity of research that examines the consequences arising from corporate reputation
risks (CRR) on negative ESG issues. This paper contributes to the literature by investigating
how increased CRR from adverse media coverage of ESG activities affects investors’ stock
valuation of affected companies.
This study draws on signalling theory and resource-based view to explain why investors may
revise their stock valuation based on heightened CRR from information shocks involving
adverse media coverage on ESG issues. The release of value-relevant materials to investors
about how firm’s organisational effectiveness compares with competing firms (Hussainey and
Salama 2010) and information on corporate social performance can help reduce information
asymmetry for investors, lessen uncertainty and hence influences the share price response
(Ramchander et al. 2012). Positive resource-based theory suggests that good CSR reputation
is an intangible resource that can increase the value of a firm's expected cash flows, reduce the
variability of its cash flows, have higher market valuation of net income (Hussainey and Salama
2010; Robinson et al. 2011; Lourenco et al., 2014) and lower implicit and explicit cost of
contracts with governments, suppliers, community representatives and other stakeholders
(Liston-Heyes and Ceton 2009). Other studies provide evidence that corporate reputation can
offer sustainable competitive advantages and benefit a firm by improving financial, investment
and economic performance, higher employee productivity, and easy access to financial
1 The focus of this study is on ESG which is generally a more updated and expansive terminology relative to CSR
(for more details, see Gillan, Koch and Starks, 2021).
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resources (Beatty and Ritter, 1986; Turban and Cable, 2003; Sarstedt et al., 2013; Gatzert, 2015;
Deephouse et al., 2016).
Conversely, it is plausible that negative ESG media coverage which adversely impacts firm
reputational capital, is likely to introduce new information and provide signals to investors
about increased future contracts costs, leading to negative adjustments on firm valuation. This
issue is increasingly of concern as companies seek to continually manage threats arising from
changes in perceptions by key stakeholders which is a growing challenge as traditional media
expansion, along with a surge in social media, increasing awareness of corporate pursuits,
mounting demands for corporate transparency, high expectations from various stakeholders
and customer loyalty deterioration have contributed to the momentum of firm risks from
heightened CRR (Sarstedt et al., 2013; Deephouse et al., 2016; Kolbel et al., 2017; Chen, 2020;
Hsu et al., 2020; Glossner, 2021; Harjoto et al., 2021). Despite the emergence of this body of
literature, the extent to which CRR from adverse media coverage of ESG issues can negatively
impact stock market performance is largely unexplored.2
This study attempts to fill the gap by concentrating first on the impact of heightened CRR,
through undesirable ESG activities highlighted in media reports on the stock valuation of
perpetrating companies. For this purpose, the US stock market is ideally suited for evaluation
the impact of non-financial information related to ESG issues,3 as it focuses on the reaction of
2 Prior studies examining the positive effects of CSR on stock market participants provide evidence that these
disclosures can lower information asymmetry as proxied by stock market volatility and bid-ask spreads (Cormier
et al., 2009, Cormier et al., 2011) and improve analyst forecast precision (Cormier and Magnan, 2014). In terms
of general corporate reputation, Pfister et al. (2020) provide evidence that it can help to lower the cost of equity,
and Ota et al. (2019) observes that investors are more likely to react positively to share repurchase announcements
for companies with better reputation from historical behaviour. It is noteworthy that this research differs from the
above-mentioned studies as it focuses on investors’ stock market reactions to heighten corporate reputation risks
from adverse media coverage on negative ESG issues. Similar to Kolbel et al. (2017), this study utilizes the
RepRisk data, however it is important to highlight that their paper investigates how media coverage of corporate
social irresponsibility (CSI) generates financial risk (as proxied by credit risk using credit default swaps) by
providing conditions that increase the potential for stakeholder sanctions. This research builds on Kolbel et al.
(2017) but differs significantly as the emphasis is on stock returns, relevant firm characteristics, and the inherent
nature of some industries. The authors gratefully thank an anonymous reviewer for making this important point.
3 There are several reasons for the choice of US equity market. First, the US stock market is the world’s largest
by market capitalization and is highly liquid. Second, US equity market is perceived to be among the most
sophisticated in the world (e.g., Levitt, 1999). Third, socially responsible investing is significant in the US. For
example, according to the Social Investment Forum (2018), from 1995 to 2018, assets in socially responsible
investment grew from $639 billion to $12.0 trillion, an 18-fold increase at a compound annual growth rate of 13.6
percent and accounted for 26 percent of the total assets managed by professional managers. Finally, in addition to
stock market size and liquidity considerations, the literature provides substantial evidence (e.g. Cormier et al.
1993; Barth and McNichols 1994; Cormier and Magnan 1997, 2007; Hughes 2000; Al-Tuwaijri et al. 2004;
Clarkson et al. 2004; Hassel et al. 2005; Johnston et al. 2008; Sinkin et al. 2008; Moneva and Cuellar 2009;
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investors (an essential stakeholder group) to undesirable ESG behaviours that can directly
affect their valuation of the underlying firms. The link between ESG-related reputation risks
and investors’ reaction is particularly important since the dissatisfaction and withdrawal of this
key stakeholder class, can increase the cost of capital, or seriously damage a corporation ability
to raise equity and continue as a going concern (Clarkson, 1995). Empirical results from this
analysis are likely to be beneficial for practitioners and academics as it provides evidence on
the value relevance placed by a key category of stakeholder on CRR caused by detrimental
media coverage on ESG issues. Further, if unfavourable media reporting provides a
demonstratable impact on firms’ market valuation, it may provide avenues for stakeholders to
guide companies away from unwanted ESG behaviours and avert costly attention (Fombrun
and Shanley, 1990; Chen and Meindl, 1991; Berman et al., 1999; Henriques and Sadorsky,
1999; Farrell and Whidbee, 2002; Siegel and Vitaliano, 2007). From a regulatory perspective,
this may arguably be a more effective incentive to motivate firm behaviour, when compared to
voluntary CSR disclosures which can be selective in nature (Owen et al., 2001; Hodder-Webb
et al., 2009; Schaltegger and Burritt, 2010).
The second part of this paper focuses on identifying value-relevant factors that may help
explain differences in stock market reactions at the firm level to adverse ESG media reporting.
Given the diverse firm characteristics and inherent nature of some industries, it is unlikely that
all companies are affected equally from negative media coverage on ESG issues. Extant
literature provides substantial evidence suggesting that firms with larger market capitalization
(Chiang and Venkatesh, 1988; Eleswarapu et al. 2004), high stock turnover (Bartov and Bodnar,
1996; Leuz, 2003; Chae, 2005; Mohd, 2005) and S&P500 constituents (Baran and King, 2012
and 2014) have lower information asymmetry. Therefore, they may be less likely to experience
significant negative price movements from adverse media coverage on ESG activities since
these issues may already be known and factored into stock prices. In contrast, for smaller and
less-liquid firms, the cost of acquiring information is high and media reports may be a critical
source of information asymmetry reduction (McWilliams and Siegel, 2001, Chan, 2003 and
Frankel and Li, 2004, Siegel and Vitaliano, 2007; Charitou et al., 2019) for market participants,
since they lack direct interaction with the corporation (Deephouse, 2000). Consequently,
negative media coverage may cause greater price shocks in these companies. Further, Hong
Lourenco et al., 2014) that non-financial information related to CSR issues is value relevant in a predominantly
North American context or a European context similar to the North American (such as the UK).
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and Kacperczyk (2009) also suggest that industries associated with ‘sin’ (e.g., alcohol, tobacco,
and gaming) will likely receive a disproportionate levels of stakeholder attention, regulatory
scrutiny, and litigation risk. Hence, by focusing on cross-sectional heterogeneity, this research
can provide firm specific information to corporate executives, portfolio managers and
stakeholders on the importance of ESG reputation management to help minimize risks.
This paper contributes to the literature on ESG reputation and firm valuation in several
important ways. First, prior studies establish that good corporate CSR reputation brings
positive benefits to firms (e.g., Servaes and Tamayo, 2013; Lins, Servaes and Tamayo, 2017).
However, there is limited research on the potential consequences of negative ESG behaviour
on firm performance and no prior study investigates how investors react in the financial
markets to heighten CRR from negative ESG media coverage. The empirical findings from this
research significantly extend the relevant literature on signalling theory (e.g., Lys et. al., 2015)
and resource-based view (e.g., Russo and Fouts, 1997; McWilliams and Siegel, 2001) by
providing evidence that similar to the concept of a positive relationship between CSR
behaviour and firm performance, media disclosures relating to negative corporate behaviour
on ESG matters can have an equally detrimental impact on firm valuation. This finding is
important as it provides companies with financial incentives to prudently manage their
corporate reputation, which is increasingly viewed as a valuable intangible asset by investors
(Kolbel et al., 2017).
The second contribution in this study relates to the identification of key firm characteristics
that may influence investors’ reactions in the stock market when there is increased ESG
reputational risks. One key observation is that not all firms are affected equally by media
disclosures pertaining to negative ESG activities. Generally, results suggest that smaller, less
liquid firms that are typically not S&P500 constituents are more significantly impacted by these
adverse ESG media disclosures, compared to their counterparts. In addition, there is evidence
indicating that companies with good reputation status are more adversely impacted by negative
media coverage on ESG matters, which further supports the resource-based view that corporate
reputation plays an important role in investors’ firm valuation. To the best of authors’
knowledge, this is the first study to explore and provide empirical evidence that firm
characteristics affect shareholders’ response in the stock market to heighten CRR from negative
ESG media coverage.
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Finally, using cross-sectional diagnosis, this paper provides empirical evidence that industry
also plays an important role in the analysis of increased CRR on stock performance. Contrary
to expectations, negative press coverage of ESG issues does not significantly affect stocks in
the ‘sin’ triumvirate of (i.e., alcohol, tobacco, and gaming), which is consistent with prior
findings that these stocks are shunned to such an extent that they are inherently underpriced
(Hong and Kacperczyk, 2009). In contrast, firms in the candy & soda, steel works, banking,
and insurance sectors, are significantly affected by heightened reputation risks from
undesirable media coverage on ESG issues. These results extend Hong and Kacperczyk (2009)
and suggest that investors may not initially associate these companies with negative ESG
activities and intense media coverage may uncover new information that are value relevant and
provide adverse signals to investors on the potential depreciation of a valuable intangible asset,
corporate reputation. This provides new insights extending signalling theory and resource-
based view by highlighting that ESG disclosure is value relevant but the impact on firm
valuation differs across industries.
The remainder of this paper is organized as follows. The next section provides a review of the
literature and hypotheses developments. The third section presents descriptions of the data and
research methodologies used for this study. The fourth section presents the empirical results
and conclusions are provided in the final section.
2. Related literature and hypotheses development
2.1 Value relevance
Generally, a variable of interest is considered value-relevant if it is significantly related to the
dependent variable. This area of research has a long history (Beaver, 2002) and most
applications of value relevance have focused on accounting variables (Carnevale et al. 2012).
However, the existence of a reported gap between book value and company stock market
valuation is increasingly leading to the view that accounting information alone has a limited
ability to explain a company’s market valuation and its movements, resulting in exploration on
the value-relevance of non-financial information (Lourenco et al., 2014).
Several studies provide empirical evidence documenting the value relevance of CSR
information, observing a significant link between positive firm performance on CSR measures
(either disclosed by the firm itself or by an external party) and increased market valuation of
equity (Cormier et al. 1993; Barth and McNichols 1994; Cormier and Magnan 1997, 2007;
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Hughes 2000; Al-Tuwaijri et al. 2004; Clarkson et al. 2004; Hassel et al. 2005; Johnston et al.
2008; Sinkin et al. 2008; Moneva and Cuellar 2009; Lourenco et al., 2014). With regards to the
value relevance of corporate reputation based on CSR behaviour, Hussainey and Salama (2010)
observe that good corporate environmental reputation has positive effects on current annual
stock returns and current and future annual earnings,4 and Lourenco et al. (2014) documents
that book value of equity and net income, is higher for firms with reputation for sustainability
leadership, when compared to a control group.
2.2 Signalling theory
The value relevance of corporate reputation from CSR activities can be linked to signalling
theory that originate from Akerlof (1970) and is based on the concept of information
asymmetries between insiders (managers) and outsiders (e.g., investors, suppliers, financers).
Since corporate insiders usually have better access to information compared to other
stakeholders, outsiders are likely to interpret any additional information beyond the required
pro forma financial reporting as signals to financial markets. This theory is particularly useful
in the context of CSR information and stock returns, as individuals utilize this information
provided by corporates to analyse and formulate impressions about the company, its core
values and future direction (Jones and Murrell, 2001). These type of company evaluations are
valuable in various settings and circumstances, as individuals need information to make
relevant decisions such as whether they will purchase a firm’s goods and services and whether
they want to invest in a firm (Akerlof, 1970; Spence, 1973).
Dhaliwal et al. (2011) highlights the importance of CSR related information in reducing
information asymmetry and uncertainty related to factors affecting firm value, and the literature
provides several reasons to support the principle that companies with good CSR will
outperform their competitors financially (Branco and Rodrigues 2006; Chatterji et al. 2009;
Fairchild 2008; Lyon and Maxwell 2008). Generally, it is proposed that positive CSR
behaviour can (i) benefit firms by attracting socially conscious customers who care about
environmental, social and governance issues, (ii) contribute towards minimizing the risk of
government regulations, (iii) address concerns from activists and non-governmental
organisations, (iv) appeal to socially responsible investors who may be willing to pay a
premium for the securities of firms engaging in CSR, and (v) potentially lead to energy and
4 See also Hussainey et al., 2003; Schleicher et al., 2007; Hussainey and Walker, 2009.
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waste minimisation, along with material efficiency. Conversely, the onset of negative ESG
media coverage is likely to provide adverse signalling effects about corporate reputation to
investors (as it indicates non-conformity with societal expectations) which may imply
additional implicit or explicit contract costs, such as restrictions on business operations,
financial penalties or communal backlash that decrease demands for company’s underlying
products.
2.3 Resource-based view
The focus of this research is to examine investors’ reactions to increased CRR from adverse
ESG media coverage and analyse the value relevance of this information on investors’ firm
valuation. Extant literature contends the resource-based view which emphasize imperfect
information as the predominant cause of stock market directional movement provides a
meaningful framework that is suitable to analyse firms’ engagement in CSR activities (Branco
and Rodrigues 2006; Clarkson et al. 2011; Hussainey and Salama 2010; McWilliams et al.
2006; Siegel 2009; Surroca et al. 2010; Ramchander et al., 2012; Lourenco et al., 2014). To
summarize, the resource-based theory suggests variations in a firm’s endowment of resources,
especially intangibles, can create sustainable competitive advantages which lead to
outperformance, given that such resources are difficult to accumulate or replicate, develop, or
acquire, or be perfectly imitated by competitors (Surroca et al. 2010; Barney et al. 2011).
Corporate reputation has been particularly identified as one of the most valuable intangible
resources that can provide companies with sustainable competitive advantage (Roberts and
Dowling 2002; Branco and Rodrigues 2006; Hussainey, and Salama 2010; Orlitzky et al. 2003;
Orlitzky 2008). The intangible benefits provided by CSR reputation can be viewed as a
resource to facilitate complex, long-term stakeholder engagement that is likely to enhance a
company’s ability to outperform against its counterparts, either by reducing costs or increasing
revenues (Schnietz and Epstein, 2005). This enables signalling to stakeholders with imperfect
information about a firm’s product or CSR commitment to assess the corporate’s ability to
generate value and serves as signalling of the barriers to replicate the company’s prior
engagements with stakeholders, which can enhance performance in the form of attracting,
recruiting, motivating, and retaining core stakeholders, such as investors, financers, employees,
customers, and suppliers (e.g., Brooks and Oikonomou, 2018).
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From a stakeholder’s perspective, the potential benefit of ESG reputation is dependent on how
it affects value. In the literature, there is growing recognition that traditional financial
information lacks timeliness, has limited ability to convey firm risks (Garcia-Meca and
Martinez, 2007) and may exclude intangible resources that is critical in the value creation
process (Lourenco et al., 2014). Consequently, investors (Eccles et al. 2011) and financial
analysts (Ioannou and Serafeim 2015; Dhaliwal et al. 2012) are increasingly aware of the
importance of intangibles such as CSR information which is not directly reflected in financial
statements. Hence, it is plausible that investors are likely to perceive increased CRR from
negative ESG activities as a signal of reduced capacity to capture revenue-generating
opportunities, obtain cost savings, and heightened the detrimental effects of failures, fines, and
lawsuits, which is likely to precede higher economic uncertainty, more unpredictable earnings,
and higher risk, thereby making affected companies less attractive to investors (e.g., Brooks
and Oikonomou, 2018). Consequently, it is expected that stock price will be lower for firms
with increased CRR, when compared to firms without such adverse reputation. This leads to
the first hypothesis,
H1: Stock returns and CRR are negatively related, ceteris paribus.
2.4 Information asymmetry and firm characteristics
Extant literature provides substantial evidence that financial disclosures can reduce information
asymmetry and thus decrease the cost of capital (Botosan, 1997; Clarkson et al., 1996;
Diamond & Verrecchia, 1991; Core 2001; Healy and Palepu 2001; Leuz and Wysocki 2008).
The same principle applies to non-financial disclosure such as value-relevant CSR information
(Dhaliwal et al. 2011; Margolis and Walsh 2001; Orlitzky et al. 2003; Al-Tuwaijri et al. 2004)
which can also affect firms' financial performance and value through channels other than those
related to financial disclosure (Anderson and Frankel 1980; Lev et al. 2010; Richardson and
Welker 2001). These arguments highlight the importance of CSR disclosure in reducing
information asymmetry and uncertainty related to factors affecting firm value (Rodriguez et al.
2006), which in turn reduces the cost of equity capital (Chelley-Steeley and Lambertides, 2016)
In addition, Kothari et al. (2009) argues that disclosure content and delivery methods are
equally important and observes that favourable disclosures reduce various firm risk measures,
including the costs of capital and vice versa for unfavourable disclosures. More importantly,
they emphasize that disclosures from business press sources (see also Bushee et al. 2010) are
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viewed with more credibility by investors and observe that the stock market provides heavy
weighting to negative news disclosures and tends to discount positive news as firms and
investment analysts have incentive to skew disclosures. This underscores the significance of
understanding the implications of negative media coverage on ESG issues for investors.
Aside from the importance of news disclosure to investors, numerous studies in market
microstructure provide substantial evidence that firm characteristics play a significant
explanatory role on the impact of reducing information asymmetry on costs of capital. For
example, Eleswarapu et al. (2004) provides empirical evidence that smaller and less liquid
stocks experience greater information asymmetry reduction after the Securities and Exchange
Commission passed Regulation Fair Disclosure to reduce selective disclosure of material
information by firms to analysts and other investment professionals. Overall, the market
microstructure literature provides substantial evidence that firm size (Chiang and Venkatesh,
1988; Eleswarapu et al. 2004) and stock turnover (Bartov and Bodnar, 1996; Chae, 2005; Leuz,
2003; Mohd, 2005) are value relevant for analysis of information asymmetry. Further, studies
such as Baran and King (2012 and 2014) examine S&P500 index revisions and observe that
inclusion (deletion) as constituent stocks significantly reduce (heighten) information
asymmetry, lower (increase) costs of equity and increase (decrease) stock liquidity.
Based on these discussions, it is plausible that investors weigh news coverage of negative ESG
issues strongly, particularly for companies with inherently higher levels of information
asymmetry such as smaller, less liquid firms which are typically non-S&P500 constituents,
since these non-financial disclosures are likely to provide new information (Chan, 2003 and
Frankel and Li, 2004). Hence, this research segregates the study’s sample size based on firm
characteristics such as (i) firm size by market capitalization, (ii) stock liquidity by share
turnover value, and (iii) S&P constituents, to analyse if these factors explain variations in
investors’ reaction to adverse ESG media coverage. These lead to the following hypotheses,
H2: Smaller firms are more likely to experience negative stock returns from increases in CRR,
ceteris paribus.
H3: Firms with lower trading turnover are more likely to experience negative stock returns
from increases in CRR, ceteris paribus.
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H4: Firms that are non-S&P500 constituents are more likely to experience negative stock
returns from increases in CRR, ceteris paribus.
2.5 Corporate reputation status and industry classifications
The primary focus of this paper is to examine the value relevance of CRR in explaining stock
performance. To further this objective, two additional analyses are conducted based on the
following rationale. First, information shocks can play a significant role in stock price
movements (e.g., Savor, 2012; Jiang and Zhu, 2017; Andreou et al., 2020). Hence, it is
anticipated that firms with good reputation status (e.g., limited or no negative media coverage
previously) are more likely to experience a greater price reaction from adverse ESG media
reporting, since intense media coverage may reveal unexpected information on the affected
company or focus market participants’ attention on CSR activities that would otherwise go
undetected or be considered negligible (Miller 2006; Bednar et al., 2013; Rogers et al., 2016).
This is consistent with the resource-based view that corporate reputation is a valuable
intangible asset which needs to be managed carefully.
Second, Hong and Kacperczyk (2009) observe that companies involved in the business of
alcohol, tobacco, and gaming (i.e., ‘sin’ stocks) receive less coverage from analysts than do
stocks of otherwise comparable characteristics and face greater litigation risk and regulatory
scrutiny heightened by social norms (see also Kim and Venkatachalam, 2011). Further, studies
examining the portfolio returns of ‘sin’ stocks observe the existence of abnormal returns (e.g.
Fabozzi et al. 2008; Fauver and McDonald, 2014; Blitz and Fabozzi; 2017) which suggest
different industries are confronted with distinct levels of stakeholder attention, regulatory
scrutiny, and litigation risk which will lead to varying investors reaction. Hence, this study
considers (iv) corporate reputation status, and (v) industry classifications as additional factors
that may be value relevant for explaining investors’ reaction to increased CRR from negative
media coverage on ESG issues, which lead to the final two hypotheses,
H5: Firms that have good reputation status are more likely to experience negative stock returns
from increases in CRR, ceteris paribus.
H6: Firms in specific industries are more likely to experience negative stock returns from
increases in CRR, ceteris paribus.
3. Data and research design
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3.1 Data and sample
This study covers US publicly traded companies from January 2007 to December 2018. Stock
price data is obtained from the Center for Research in Security Prices (CRSP), the 4 factors
from Fama, French and Carhart model are extracted from Wharton Research Data Services
(WRDS), S&P500 constituents are extracted from Compustat, and the reputation risk data is
obtained from the RepRisk database.5
The sample processing for this research starts with the intersection of available monthly data
from RepRisk, CRSP, WRDS and Compustat databases. In the first stage, the study removes
all non-US listed companies from the RepRisk database and removes observations with
missing data, which results in 804,432 monthly firm observations. The RepRisk database for
US based companies is then combined with market data from CRSP. The next step involves
removing firms with RepRisk information but missing CRSP data, and firms possessing CRSP
market data but without RepRisk ratings, which leads to an elimination of approximately
472,915 firm observations. Subsequently, the remaining sample is subsequently combined with
Fama, French and Carthoche factors database from WRDS. No observations were removed
due to missing data in this step, leaving a final sample of 331,517 which is used for this research.
The remaining firms in the study’s sample is then classified as either S&P500 index stocks or
non-constituents based on Compustat database. Table 1 (Panel A) provides details of this
sample selection, Table 1 (Panel B) presents descriptive statistics of the variables used in this
study and Table 1 (Panel C) tabulates the tolerance and variance inflation factor for
multicollinearity analysis between variables.
INSERT TABLE 1 (Panel A) HERE
INSERT TABLE 1 (Panel B) HERE
INSERT TABLE 1 (Panel C) HERE
3.2 CRR and reputation status variables
To measure the impact of negative ESG media coverage on CRR, this study utilized the ESG
reputation risk index (RRI) from RepRisk AG, 6 a data provider that integrates human
5 This study’s sample frequency is monthly and commence from January 2007, as this coincides with the data
availability for RepRisk database.
6 See Hasan et al. (2021) for details on the advantages of RepRisk database over CSR data from MSCI (formerly
KLD).
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intelligence with technology to detect ESG incidents. Starting from January 2007, the extensive
research process to build RRI and track the ESG performance of over 130,000 listed and non-
listed companies, begins with the daily collection of information from over 90,000 media,
stakeholder, and other public sources for news items that criticize companies for ESG issues
(in 20 different languages). Upon the identification of an incident, further screening is
performed by RepRisk analysts to verify that the issue is ESG-related, remove possible
duplicates and characterize the nature of the event. Then each incident is evaluated and given
proprietary scores for severity (the harshness of the perceived impact of the incident) and reach
(the influence or the readership of the source).
Based on these factors, RepRisk computes the monthly current RRI which denotes the current
level of a firms’ media and stakeholder exposure to ESG-related issues. The current RRI
indexes typically range from zero (lowest exposure) to 100 (highest exposure). More
importantly, there is a RepRisk Rating (RRR), consisting of a letter rating from (AAA to D)
that facilitates benchmarking and integrating of ESG and business conduct risks, as well as
other metrics such as the UN global Compact Violator Flag. The RRR methodology combines
two factors, (i) company specific ESG risk exposure (represented by RRI), and (ii) the country-
sector ESG risk exposure (which is calculated by the headquarters ESG risk exposure value
and the international ESG risk exposure value, both equally weighted). Table 2 presents
RepRisk descriptions that are utilized to create the RRR Scores and Reputation Status Band for
the purpose of this study.
INSERT TABLE 2 HERE
The use of third-party data is important in evaluating whether firm intentions translate into real
actions (RepRisk, 2016) and several recent studies have started to use RepRisk data to proxy
for CRR from adverse media coverage (e.g., Schembera and Scherer, 2017; Kolbel et al., 2017;
Cui et al., 2018; Burke et al., 2019; Asante-Appiah, 2020; Dai et al., 2020; Hasan et al., 2021).7
7 Numerous high-profile global firms and institutions, including some of the Big Four accounting firms, use
RepRisk data to assess ESG reputation risk. Global companies that subscribe to RepRisk ESG data include Bank
of America, Barclays Bank, Citi Bank, Deloitte, KPMG, PricewaterhouseCoopers, Société Générale, UBS, and
World Bank Group (https://www.reprisk.com/our-clients).
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3.3 Firm characteristics and industry variables
To analyse if various firm and industry characteristics can help explain differences in investors’
reaction to changes in CRR from adverse media on ESG issues, this study adopts the following
measures,8
Market Capitalization = Total Outstanding Shares * Stock Price (1)
where total outstanding share is the number of shares issued by the company, and stock price
is the daily closing price of the company.
Trading Turnover Value = Total Traded Volume * Stock Price (2)
where total traded volume is the sum of the daily trading volume for the company, and stock
price is the daily closing price of the company.
For S&P500 constituents, the index components are extracted from Compustat for the entire
duration of the study’s sample (i.e., January 2007 to December 2018). Firms in this study are
denoted with a dummy variable of 1 during the period where it is a component of the S&P500
index, and 0 otherwise. S&P500 constituents are updated constantly throughout the sample
period to account for additions and deletions of companies.
To analyse the impact of CRR from adverse ESG media coverage, this research adopts the
Fama and French 48 (FF48) industry classifications (Fama and French, 1997). In addition,
since the ‘sin’ triumvirate of alcohol, tobacco, and gaming receive particular stakeholder
attention, regulatory scrutiny, and litigation risk, this research implements the methodology
outlined by Hong and Kacperczyk (2009) to create an additional ‘gaming’ industry which
includes companies in the following North American Industry Classification System (NAICS)
codes, 7132, 71312, 713210, 71329, 713290, 72112, and 721120. This is separate and distinct
from the FF48 industry groups.
8 Relevant corporate action adjustment factors are applied to both shares and stock prices.
15
3.4 Methodologies
The primary interest of this research is to determine whether changes in RRR scores9 (which
denotes changes to CRR arising from adverse media coverage) provide incremental
information, beyond the generally accepted return generating factors such as the Fama, French
and Carhart four-factors, in describing stock returns of listed US companies. To achieve this,
the research characterizes excess US stock returns as a function of the Fama, French and
Carhart four-factors model and the monthly RRR changes.
(, ,) = + + (, ,) + + +
+ + + (3)
The study extends the analysis further by grouping the sample based on firm size, S&P500
constituents, reputation status and FF48 (and gaming) industry classifications.
(, ,) = + + (, ,) + + +
+ + + (4)
(, ,) = + + (, ,) + + +
+ + + (5)
(&, ,) = + + (, ,) + + +
+ + + (6)
(, ,) = + + (, ,) + + +
+ + + (7)
(, ,) = + + (, ,) + + +
+ + + (8)
9 This study measures RRRC (RepRisk Ratings change) as which implies a negative
RRRC value (e.g., -1) is indicative of a deterioration in RRR score (i.e., increase in corporate reputation risk by 1
category). For example, if a firm with a RepRisk Ratings of AAA (represented as RRR of 1 in Table 3) experience
a decline (i.e., increased risks) in corporate reputation to AA (i.e., RRR of 2), the RRRC numeric value will be -
1.
16
where ( ) is the monthly excess group stock returns for full sample of US listed
companies, where ( ) is the monthly excess stock returns grouped by firm size (into
deciles based on market capitalization), where ( ) is the monthly excess stock
returns grouped by trading turnover value (into deciles), (& ) is the monthly excess
stock returns grouped by S&P500 constituents (with dummy variable of 1 denoting S&P500
constituents and 0 otherwise), ( ) is the monthly excess stock returns grouped by
reputation status, ( ) is the monthly excess stock returns grouped by FF48 (and
‘gaming’) industry classifications, RRRC is the numeric change in RRR monthly scores, (
) is the monthly market premium, representing the excess returns of the market over the risk-
free interest rate. SMB is the monthly equally weighted average of the stock returns on the
small stock portfolios (portfolios with small market cap stocks) minus the stock returns on the
big stock portfolios (portfolios with big market cap stocks) and represents the size premium.
HML is the monthly equally weighted average of the stock returns on the high book-to-market
ratio stock portfolios minus the stock returns on the low book-to-market ratio stock portfolios
and represents the value premium. WML is the monthly equally weighted average of the stock
returns on winner portfolios (portfolio of stocks with highest prior stock returns) minus the
stock returns on the loser portfolios (portfolio of stocks with lowest prior stock returns) and
represents the momentum factor. In all regressions, dummy variables are included to control
for firm and year fixed effects. Stock returns are adjusted for corporate actions and all variables
are windsorized at 1% and 99% level. Robust standard errors are clustered by firm.
4. Results
4.1 Investors’ reaction to heightened CRR from media coverage
One of the key objectives of this paper is to examine if increases in CRR from adverse media
coverage on ESG issues impact the stock performance of listed companies. Table 3 presents
regression results detailing how changes to RRR scores (which correspond to an RRR grade
change) affect stock performance of the entire sample of US listed companies. The variable of
interest is RRRC (which represents the numeric change in RRR scores) and a positive
coefficient indicates that each unit decline in RRR scores (signifying increase in reputation
risks from ESG related issues) is associated with negative stock returns performance of -0.39%
after controlling for Fama, French and Carhart four-factors. This is consistent with expectation
for H1 that company stock performance is negatively affected by increasing reputation risks
arising from adverse ESG related media reporting. The finding from Table 3 extends signalling
17
theory and resource-based view by providing empirical evidence that firms should be
concerned about negative CSR disclosures as they provide value relevant information to
investors regarding firm valuation.
INSERT TABLE 3 HERE
4.2 Impact of various firm characteristics on increased CRR
This study extends the analysis of CRR on various firm characteristics and industry
classification10 to identify if they explain differences in stock performance of affected firms.
Extant literature on costs of capital and information asymmetry predicts that smaller, less liquid
firms which are typically not S&P500 constituents, are more likely to experience changes in
stock prices with the public release of information that is deemed value relevant (e.g., Chiang
and Venkatesh, 1988; Bartov and Bodnar, 1996; Leuz, 2003; Eleswarapu et al. 2004; Chae,
2005; Mohd, 2005; Baran and King, 2012 and 2014).
Table 4 provides regression results for the impact of RRRC on companies of varying market
capitalization (proxy for firm size) by deciles. Consistent with expectation for H2, only stock
performance of firms in the smallest deciles (i.e., 7, 8, 9 and 10) are significantly affected by
heightened CRR from adverse media reporting. Further, the stock returns of the smallest firms
appear to experience the most severe negative investors’ response to adverse media reporting,
i.e., for each unit increase in RRR score, investors penalize the stock prices of affected firms
by -0.8% in Decile 7, -1.03% in Decile 8, -1.17% in Decile 9, and -1.62% in Decile 10.
INSERT TABLE 4 HERE
Similar with firm size, this research segregates companies into deciles based on their average
monthly trading turnover value to analyse if market activity affects investors’ reaction to
changes in corporate reputation risks. Findings are reported in Table 5 and consistent with
expectation for H3, it is observed that only stock performance of the least actively traded
companies (i.e., 6, 7, 8, 9 and 10) are significantly impacted by increased reputation risks from
adverse media reporting on ESG issues. The top half of companies by trading turnover value
10 See also Wong and Zhang (2020), Wong (2021), Wong and Hasan (2021) on the importance of firm
characteristics and industry classification.
18
do not appear to be significantly affected. Regression results indicate that every unit increase
in RRR score for companies in the lower half of the trading activity spectrum, will impact their
stock performance by -0.76%, -0.74%, -1.48%, -1.21 % and -0.99% in Decile 6, 7, 8, 9 and 10,
respectively. It is noteworthy that companies in the lower half of the trading activity spectrum
are usually also the smallest by market capitalization.
INSERT TABLE 5 HERE
Table 6 presents regression analysis for the impact of CRR change from negative media
reporting on S&P500 component stocks and non-constituents. Results are consistent with
expectation for H4 and suggest that only non-S&P500 constituents experience significant
negative stock price reactions from heightened unfavourable media coverage. Generally, the
stock performance of affected companies declines by -0.48% per unit increase in RRR score.
Consistent with findings in Table 4 and 5, S&P500 constituents are usually highly visible firms
that are larger by market capitalization and are also amongst the most actively traded.
INSERT TABLE 6 HERE
Table 7 presents regression results for increase CRR from adverse media reporting by
reputation status. Results are consistent with expectation for H5 and suggest that companies
with higher reputation status (i.e., lower ESG risk exposures) experience statistically
significant stock price reactions from spikes in undesirable media coverage. It is observed that
only firms in reputation status band 1 (low ESG risk exposure) and 2 (moderate ESG risk
exposure) experience deteriorations in stock performance of -0.5% and -0.3% for each unit
increase in RRR score, respectively.
INSERT TABLE 7 HERE
Overall, the results from Table 4 to 7 reinforce that CSR information signals value relevant
information to investors. However, an extended analysis based on firm characteristics shows
that not all companies are affected equally. The disclosure of CSR information relating to
negative media coverage of ESG issues plays a more significant role for smaller, less liquid
firms that are typically not S&P500 constituents. Moreover, negative press on ESG issues
appears to provide more of an information shock to firms with good reputation status,
19
suggesting that corporate reputation is viewed as an important intangible asset that affects
investors’ firm valuation. Overall, these findings extend our understanding of signalling and
resource-based theory by providing empirical evidence that in addition to positive theory,
companies should be concerned about negative CSR disclosure, as it can negatively impact
firm’s valuation. Further, beyond the type of public CSR disclosures, firm characteristics such
as firm size, trading turnover and S&P500 constituents play an important part on
informativeness of CSR disclosures.
4.3 Industry effects on CRR from negative media coverage
As observed by Hong and Kacperczyk (2009), different industries are confronted with varying
levels of stakeholder attention, regulatory scrutiny, and litigation risk. Table 8 presents
regression results focusing on cross-industries heterogeneity. Table 8a provides analysis on
firm stock returns grouped by FF48 industry classifications and Table 8b provides additional
analysis on the gaming industry. It is noteworthy that contrary to expectation, stock
performance of companies in the ‘sin’ triumvirate does not experience negative investors’
reaction to adverse ESG-related media coverage. These findings provide some evidence to
suggest that ESG related CRR for companies associated with ‘sin’ industries may already be
factored into their stock prices (Blitz and Fabozzi; 2017), and is consistent with prior findings
that ‘sin’ stocks are avoided to such an extent that they become systematically underpriced,
and investors who are willing to bear the reputation risk involved with investing in these stocks
earn abnormal returns (e.g. Fabozzi et al. 2008; Kim and Venkatachalam, 2011; Fauver and
McDonald, 2014). Hence, the additional media coverage of adverse ESG activities is unlikely
to affect investors who have already invested in ‘sin’ stocks.
INSERT TABLE 8 (Panel A) HERE
INSERT TABLE 8 (Panel B) HERE
In contrast, results indicate that firms in the (i) candy & soda, (ii) steel works, (iii) banking,
and (iv) insurance sectors, are significantly affected by heightened reputation risks from
undesirable media coverage on ESG issues. The candy & soda industry appears to be most
affected with a significant deterioration in adjusted stock performance of -1.9% for each unit
increase in RRR score. Similarly, companies in steel works, banking, and insurance, experience
adverse share price movements of -1.4%, -1.0%, -0.9%, for every uptick in RRR score,
respectively. This result may suggest that investors have not previously factored negative ESG
20
issues into these companies and any adverse media coverage containing new information that
provides undesirable signals on corporate reputation would significantly impact shareholders’
valuation of affected firms in these industries.11 These results provide support for H6 that some
industries are more likely to experience negative stock returns from increases in CRR.
4.3 Additional robustness tests
To control for other firm characteristics and corporate governance mechanisms which may
affect the observed results, this research adopts two proxies (i) firm age, and (ii) board size12
to control for some broad attributes.13
(, ,) = + + (, ,) + + +
+ + + + + (9)
where ( ) is the monthly excess group stock returns for full sample of US listed
companies, RRRC is the numeric change in RRR monthly scores, ( ) is the monthly
market premium, representing the excess returns of the market over the risk-free interest rate.
SMB is the monthly equally weighted average of the stock returns on the small stock portfolios
(portfolios with small market cap stocks) minus the stock returns on the big stock portfolios
(portfolios with big market cap stocks) and represents the size premium. HML is the monthly
equally weighted average of the stock returns on the high book-to-market ratio stock portfolios
minus the stock returns on the low book-to-market ratio stock portfolios and represents the
value premium. WML is the monthly equally weighted average of the stock returns on winner
portfolios (portfolio of stocks with highest prior stock returns) minus the stock returns on the
loser portfolios (portfolio of stocks with lowest prior stock returns) and represents the
momentum factor. FirmAge is the natural log of firm age and is measured as the number of
months since the firm was first covered by the CRSP (i.e., from December 1925). BoardSize is
the natural log of number of directors on the board. In the regression, dummy variables are
11 For robustness checks, this research controls for industry effects using dummy variables and also applies the
Capital Asset Pricing Model (CAPM), Fama-French three-factor and five-factor models for all reported tables.
Results are broadly consistent with findings reported in this paper and are available upon request from the authors.
12 Additional board related data is extracted from BoardEx.
13 This study adopts the natural log of firm age as it can be generated monthly and serves as a broad proxy for
firm maturity which is indicative of free cash flow, dividends, firm risk, growth, etc. (e.g., Zou and Xiao, 2006;
Dickinson, 2011; DeAngelo, et al. 2006). The research also utilizes the natural log of board size (i.e., number of
company directors on the board) as a general proxy for corporate governance mechanisms, since this variable is
considered to be negatively correlated with the strength of board monitoring of management in a number of
corporate governance studies (see review by Hermalin and Weisbach, 2003).
21
included to control for firm and year fixed effects. Stock returns are adjusted for corporate
actions and all variables are windsorized at 1% and 99% level. Robust standard errors are
clustered by firm.
INSERT TABLE 9 HERE
Table 9 presents the results and reaffirms that CRR is value relevant after controlling for firm
age and board size.14 The additional control variables may suggest avenues for future research
which are covered in the conclusion.
5. Conclusion
There is increasing global emphasis and pressure by stakeholders for companies to engage in
positive CSR15 and ESG activities to maintain good corporate reputations. Despite numerous
studies examining CSR and corporate financial performance, most research focused on the
positive aspects of CSR disclosures on stock returns and firm valuations16 (e.g., Ingram, 1978;
Jaggi and Freedman, 1992; Murray et al., 2006; Moneva and Cuellar, 2009 and Hussainey and
Salama, 2010; Minor and Morgan, 2011; Servaes and Tamayo, 2013; Lourenco et al., 2014;
Harjoto and Jo, 2015; Mishra, 2017; Lenz et al., 2017; Buchanan et al. 2018; Aouadi and
Marsat, 2018; Jeong et al, 2018). In particular, with regard to signalling theory and the
resource-based view of CSR reputation, Hussainey and Salama (2010) identify a critical link
between positive corporate reputation for environmental leadership performance and improved
forecasting ability of future earnings by investors. Their finding demonstrates the value
relevance of positive CSR reputation, as it signals important information about long-term
prospects to investors, which enable firms to distinguish themselves from their peers.
Consistent with this, Lourenco et al (2014) provides empirical support that favourable CSR
reputation is considered a valuable intangible resource which provides a long-term advantage
to companies, as it can help shareholders better evaluate firm value.
This paper differs from the aforementioned literature which focus on the positive relationship
between CSR and firm performance by empirically establishing that undesirable (‘bad')
14 This study also utilizes these two additional variables for all reported tables. Results for RRRC are observed to
be broadly consistent with findings reported in this paper. For brevity, these additional tables are available upon
request from the authors.
15 See for example, Cumming et al. (2016) and Wu et al. (2021).
16 See also Malik (2015) for relevant literature review.
22
corporate behaviour relating to ESG matters can also have a detrimental impact on the stock
performance of the infringing firms. The research further contributes to the literature by
providing clear evidence that firm characteristics such as firm size, stock liquidity, S&P500
constituents, corporate reputation status and industry classifications are highly value relevant
and explain significant differences in investors’ stock market reactions to heightened CRR
from adverse ESG media coverage. These findings provide several important implications for
corporate executives (managers, directors, etc.), portfolio managers (e.g., mutual funds, hedge
funds, etc.) and stakeholders (investors, suppliers, employees, customers, etc.) on the
importance of ESG reputation management.
First, corporate executives may wish to pay more attention to their firm’s ESG reputational
branding, as investors place a substantial tangible value on this aspect. Hence, there are
financial incentives for companies to carefully monitor and preserve a good corporate
reputational standing on ESG matters. Second, from a risk management perspective, the
observation of a significant adverse stock market reaction to negative ESG media coverage
may indicate a potential need to incorporate these factors into modern portfolio management
models. In addition, the findings that non-S&P500, smaller and less liquid firms are more
susceptible to investors’ repercussion from ESG reputational risks, may require especial
consideration and awareness regarding the heightened threats of ESG reputational risks from
these types of companies. Third, it is noteworthy that industry matters for ESG reputational
risks. The empirical results from this study show that some industries are more sensitive to
adverse stock market reaction from increased CRR due to negative ESG media coverage.
Contrary to expectations, the ‘sin’ troika of alcohol, tobacco, and gaming are not significantly
affected by heightened ESG reputational risks. Rather, firms in the candy & soda, steel works,
banking, and insurance sectors are significantly affected by escalating reputation risks from
undesirable media coverage on ESG issues. This provides new insights and may suggest new
areas of concerns beyond the traditional triumvirate which may have important economic
implications in the future.
Overall, this paper provides empirical results to support the signalling theory and resource-
based view of ESG corporate reputation by highlighting that adverse media disclosure on ESG
related issues is value relevant for investors. More importantly, beyond the type and method of
disclosures on ESG matters, this study observes significant differentiations by shareholders
based on firm characteristics, corporate reputation status and industry.
23
To conclude, it is worth highlighting that the scope of this study signifies both limitations and
fertile ground for future research. For instance, there may be potentially numerous other factors
that can inherently influence investors’ firm valuation which are beyond the scope of this study
(e.g., dividends, firm risk, cash-holdings, board characteristics, audit committee characteristics
and ownership structure, etc.). With the growing importance of corporate reputation
management, the extension of analysis based on these additional variables would present an
important field of empirical inquiry which provides new and exciting opportunities for
researchers.
INSERT APPENDIX HERE
Acknowledgements
We gratefully thank the Editors, Associate Editor and two anonymous reviewers for helpful
comments and suggestions on the earlier drafts of this paper.
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Filtering Process Observations
U.S. firms observations covered in RepRisk from fiscal year January 2007 to December 2018 804,432
Less observations with missing data in CRSP files (472,915)
Less observations with missing data in Fama, French and Carhart factors files (0)
Final Sample 331,517
Table 1 (Panel A): Sample Selection Methodology
Table 1 (Panel A) provides a summary of the filtering process to obtain the final sample utilized for this research.
Mean Std. Dev 25 percentile Median 75 percentile
ER 0.0080 0.1401 -0.0520 0.0056 0.0616
(RM-RF) 0.0064 0.0433 -0.0175 0.0109 0.0324
SMB 0.0006 0.0230 -0.0186 0.0017 0.0128
HML -0.0021 0.0264 -0.0170 -0.0031 0.0095
WML 0.0024 0.0380 -0.0165 0.0029 0.0266
RRRC -0.0062 0.2593 0.0000 0.0000 0.0000
FirmAge 5.0704 1.0906 4.4773 5.2364 5.8201
BoardSize 2.9207 0.4804 2.6391 2.9444 3.2581
Table 1 (Panel B) provides descriptive statistics for variables utilized in this study.
Table 1 (Panel B): Descriptive Statistics
ER Tolerance Variance Inflation Factors
(RM-RF) 0.79 1.27
SMB 0.88 1.14
HML 0.75 1.32
WML 0.74 1.35
RRRC 1.00 1.00
FirmAge 0.90 1.11
BoardSize 0.90 1.11
Table 1 (Panel C): Multicollinearity Statistics
Table 1 (Panel C) provides variance intolerance factors for variables utilized in this study.
RepRisk Ratings (RRR) RRR Scores ESG Related Risk Representations Reputation Status Band
AAA 1
AA 2
A 3
BBB 4
BB 5
B 6
CCC 7
CC 8
C 9
D 10 Very high ESG risk exposure 4
2
High ESG risk exposure 3
Table 2: Grouping Methodologies
Low ESG risk exposure 1
Moderate ESG risk exposure
Table 2 provides the RepRisk Ratings (RRR) and the ESG risk exposures related to each band. For the purpose of this study, the highest RRR of
‘AAA’ is associated with a RRR score of 1, RRR of ‘AA’ is associated with a RRR score of 2, RRR of ‘A’ is associated with a RRR score of 3,
etc. and the lowest RRR score of 10 is given to RRR of ‘D’. Reputation status band 1 represents firms with low ESG risk exposures (i.e. RRR of
'AAA', 'AA' or 'A'), reputation status band 2 represents firms with moderate ESG risk exposures (i.e. RRR of 'BBB', 'BB' or 'B', reputation status
band 3 represents firms with high ESG risk exposures (i.e. RRR of 'CCC', 'CC' or 'C'), and reputation status band 4 represents firms with very high
ESG risk exposures (i.e. RRR of 'D').
US listed companies Observations RRRC (RM-RF) SMB HML WML Year Effect Firm Effect Adj. R-squared
Full sample 331,517 0.0039** 1.0638** 0.4984** 0.0825** -0.2065** Yes Yes 0.24
[0.001] [0.006] [0.011] [0.01] [0.007]
Table 3: Impact of increase CRR from adverse media coverage on stock performance of US listed companies (full sample)
Table 3 provides regression results for (Rfull – Rf
) the monthly excess group stock returns for the full sample of US listed companies, on RRRC which represents numeric change in RRR scores,
(Rm – Rf) the market premium which represents the excess returns of the market over the risk-free interest rate, SMB the monthly equally weighted average of the stock returns on the small
stock portfolios minus the stock returns on the big stock portfolios which represents the size premium, HML the equally weighted average of the stock returns on the high book-to-market ratio
stock portfolios minus the stock returns on the low book-to-market ratio stock portfolios which represents the value premium, WML the equally weighted average of the stock returns on winner
portfolios minus the stock returns on the loser portfolios which represents the momentum factor. In all regressions, dummy variables are included to control for firm and year fixed effects.
Stock returns are adjusted for corporate actions and all variables are windsorized at 1% and 99% level. Robust standard errors clustered at firm level are reported in the brackets.
*Denotes significance at the 5% level and ** denotes significance at the 1% level.
Deciles Avg. Market Capitalization ('000s) Observations RRRC (RM-RF) SMB HML WML Firm Effect Year Effect Adj. R-squared
1 $160,002,002 39,588 0.000 0.9895** -0.028 -0.017 -0.0934** Yes Yes 0.32
[0.001] [0.011] [0.018] [0.018] [0.013]
2 $11,214,638 38,561 0.002 1.0462** 0.2156** 0.0572** -0.1298** Yes Yes 0.32
[0.001] [0.012] [0.021] [0.02] [0.014]
3 $5,510,385 34,450 0.004 1.083** 0.3261** 0.022 -0.1406** Yes Yes 0.32
[0.002] [0.014] [0.023] [0.022] [0.016]
4 $3,102,854 32,158 0.002 1.0847** 0.5402** 0.038 -0.1922** Yes Yes 0.29
[0.003] [0.017] [0.029] [0.027] [0.02]
5 $2,000,947 31,936 0.002 1.1388** 0.5968** 0.1505** -0.2219** Yes Yes 0.29
[0.003] [0.018] [0.031] [0.029] [0.021]
6 $1,256,704 35,797 -0.002 1.0581** 0.6775** 0.1802** -0.1899** Yes Yes 0.27
[0.002] [0.018] [0.03] [0.029] [0.02]
7 $740,624 36,732 0.008** 1.0855** 0.678** 0.1894** -0.2431** Yes Yes 0.25
[0.003] [0.018] [0.031] [0.03] [0.022]
8 $422,223 29,378 0.0103* 1.0932** 0.7975** 0.1983** -0.2879** Yes Yes 0.21
[0.005] [0.027] [0.047] [0.045] [0.032]
9 $199,549 27,549 0.0117** 1.0249** 0.843** 0.063 -0.2926** Yes Yes 0.21
[0.004] [0.027] [0.048] [0.045] [0.032]
10 $53,783 25,368 0.0162* 1.0322** 0.6315** -0.089 -0.3798** Yes Yes 0.16
[0.007] [0.04] [0.07] [0.065] [0.046]
Table 4: Impact of increase CRR from adverse media coverage on stock performance of US listed companies (by firm size)
Table 4 provides regression results for (Rsize – Rf) the monthly excess stock returns grouped by firm size (into deciles based on market capitalization), on RRRC which represents numeric change in RRR scores,
(Rm – Rf
) the market premium which represents the excess returns of the market over the risk-free interest rate, SMB the monthly equally weighted average of the stock returns on the small stock portfolios minus
the stock returns on the big stock portfolios which represents the size premium, HML the equally weighted average of the stock returns on the high book-to-market ratio stock portfolios minus the stock returns on
the low book-to-market ratio stock portfolios which represents the value premium, WML the equally weighted average of the stock returns on winner portfolios minus the stock returns on the loser portfolios
which represents the momentum factor. In all regressions, dummy variables are included to control for firm and year fixed effects. Stock returns are adjusted for corporate actions and all variables are windsorized
at 1% and 99% level. Robust standard errors clustered at firm level are reported in the brackets.
*Denotes significance at the 5% level and ** denotes significance at the 1% level.
Decile Avg Turnover (Monthly) Observations RRRC (RM-RF) SMB HML WML Firm Effect Year Effect Adj. R-squared
18,017,496,965 37,132 0.002 1.0734** 0.027 0.007 -0.133** Yes Yes 0.30
[0.002] [0.013] [0.022] [0.021] [0.015]
22,093,121,474 37,392 0.001 1.068** 0.3061** 0.029 -0.1657** Yes Yes 0.30
[0.002] [0.014] [0.023] [0.022] [0.016]
31,125,405,136 33,440 0.003 1.1436** 0.4076** -0.006 -0.2397** Yes Yes 0.28
[0.003] [0.017] [0.03] [0.028] [0.02]
4677,846,871 39,412 -0.001 1.1179** 0.393** 0.0615* -0.2203** Yes Yes 0.30
[0.002] [0.015] [0.025] [0.024] [0.017]
5420,370,739 38,144 -0.002 1.0029** 0.5054** 0.1259** -0.1562** Yes Yes 0.26
[0.002] [0.016] [0.027] [0.026] [0.018]
6256,107,210 30,737 0.0076* 1.1214** 0.5975** 0.1117** -0.2162** Yes Yes 0.25
[0.003] [0.021] [0.035] [0.033] [0.024]
7146,105,537 33,046 0.0074* 1.1093** 0.7197** 0.1394** -0.243** Yes Yes 0.22
[0.004] [0.023] [0.039] [0.037] [0.026]
879,701,536 28,430 0.0148** 1.1236** 0.9158** 0.1624** -0.2239** Yes Yes 0.23
[0.004] [0.027] [0.045] [0.043] [0.031]
934,173,596 27,138 0.0121* 1.083** 0.7568** 0.1849** -0.2686** Yes Yes 0.20
[0.005] [0.029] [0.05] [0.047] [0.033]
10 7,688,151 26,646 0.0099* 0.7452** 0.6116** 0.060 -0.2404** Yes Yes 0.16
[0.005] [0.03] [0.053] [0.049] [0.035]
Table 5: Impact of increase CRR from adverse media coverage on stock performance of US listed companies (by trading turnover value)
Table 5 provides regression results for (RTurnover – Rf) the monthly excess stock returns grouped by trading turnover value (into deciles), on RRRC which represents numeric change in RRR scores, (Rm
– Rf) the market premium which represents the excess returns of the market over the risk-free interest rate, SMB the monthly equally weighted average of the stock returns on the small stock portfolios
minus the stock returns on the big stock portfolios which represents the size premium, HML the equally weighted average of the stock returns on the high book-to-market ratio stock portfolios minus the
stock returns on the low book-to-market ratio stock portfolios which represents the value premium, WML the equally weighted average of the stock returns on winner portfolios minus the stock returns
on the loser portfolios which represents the momentum factor. In all regressions, dummy variables are included to control for firm and year fixed effects. Stock returns are adjusted for corporate actions
and all variables are windsorized at 1% and 99% level. Robust standard errors clustered at firm level are reported in the brackets.
*Denotes significance at the 5% level and ** denotes significance at the 1% level.
ER Observations RRRC (RM-RF) SMB HML WML S&P500 (Dummy) Year Effect Firm Effect Adj. R-squared
Full sample 331,517 0.0039** 1.0638** 0.4984** 0.0827** -0.2064** -0.0137** Yes Yes 0.24
[0.001] [0.006] [0.011] [0.01] [0.007] [0.004]
*Denotes significance at the 5% level and ** denotes significance at the 1% level.
Table 6: Impact of increase CRR from adverse media coverage on stock performance of US listed companies (by S&P500 constituents)
Table 6 provides regression results for (RS&P500 – Rf) the monthly excess stock returns grouped by S&P500 constituents (with dummy variable of 1 denoting S&P500 constituents and 0 otherwise), on RRRC
which represents numeric change in RRR scores, (Rm – Rf) the market premium which represents the excess returns of the market over the risk-free interest rate, SMB the monthly equally weighted average of the
stock returns on the small stock portfolios minus the stock returns on the big stock portfolios which represents the size premium, HML the equally weighted average of the stock returns on the high book-to-market
ratio stock portfolios minus the stock returns on the low book-to-market ratio stock portfolios which represents the value premium, WML the equally weighted average of the stock returns on winner portfolios
minus the stock returns on the loser portfolios which represents the momentum factor. In all regressions, dummy variables are included to control for firm and year fixed effects. Stock returns are adjusted for
corporate actions and all variables are windsorized at 1% and 99% level. Robust standard errors clustered at firm level are reported in the brackets.
Reputation Status Band Observations RRRC (RM-RF) SMB HML WML Firm Effect Year Effect Adj. R-squared
1266,311 0.005** 1.053** 0.613** 0.115** -0.194** Yes Yes 0.24
[0.001] [0.007] [0.013] [0.012] [0.008]
253,159 0.003* 1.078** 0.193** -0.07** -0.244** Yes Yes 0.27
[0.001] [0.014] [0.023] [0.023] [0.016]
311,606 0.002 1.169** -0.364** -0.040 -0.343** Yes Yes 0.32
[0.003] [0.027] [0.044] [0.044] [0.031]
4441 -0.005 1.321** -1.156** -0.413 -0.337 Yes Yes 0.28
[0.021] [0.166] [0.275] [0.247] [0.183]
Table 7: Impact of increase CRR from adverse media coverage on stock performance of US listed companies (by reputation status band)
Table 7 provides regression results for (Rstatus – Rf) the monthly excess stock returns grouped by reputation status [where band 1 consists of firms with low ESG risk exposures (i.e. RRR of 'AAA',
'AA' or 'A'), band 2 consists of firms with moderate ESG risk exposures (i.e. RRR of 'BBB', 'BB' or 'B', reputation status band 3 consists of firms with high ESG risk exposures (i.e. RRR of 'CCC',
'CC' or 'C'), and reputation status band 4 consists of firms with very high ESG risk exposures (i.e. RRR of 'D'], on RRRC which represents numeric change in RRR scores, (Rm – Rf) the market
premium which represents the excess returns of the market over the risk-free interest rate, SMB the monthly equally weighted average of the stock returns on the small stock portfolios minus the
stock returns on the big stock portfolios which represents the size premium, HML the equally weighted average of the stock returns on the high book-to-market ratio stock portfolios minus the stock
returns on the low book-to-market ratio stock portfolios which represents the value premium, WML the equally weighted average of the stock returns on winner portfolios minus the stock returns on
the loser portfolios which represents the momentum factor. In all regressions, dummy variables are included to control for firm and year fixed effects. Stock returns are adjusted for corporate actions
and all variables are windsorized at 1% and 99% level. segregated into quartiles by reputation status. Robust standard errors clustered at firm level are reported in the brackets.
*Denotes significance at the 5% level and ** denotes significance at the 1% level.
FF48 Industry Classifications Observations RRRC (R M-RF) SMB HML WML Firm Effect Year Effect Adj. R-squared
Agriculture 1,018 0.000 1.064** 0.128 -0.146 -0.134 Yes Yes 0.21
[0.014] [0.101] [0.175] [0.163] [0.117]
Food Products 6,523 0.010 0.7191** 0.2418** -0.022 -0.1388** Yes Yes 0.17
[0.005] [0.038] [0.067] [0.062] [0.044]
Candy & Soda 2,264 0.0189** 0.6737** 0.172 -0.052 -0.1248* Yes Yes 0.21
[0.007] [0.051] [0.091] [0.083] [0.059]
Beer & Liq uor 2,037 -0.001 0.8032** 0.070 0.057 0.016 Yes Yes 0.27
[0.008] [0.054] [0.093] [0.089] [0.064]
Tobacco Products 1,100 -0.007 0.6702** 0.036 0.070 -0.141 Yes Y es 0.15
[0.013] [0.111] [0.191] [0.177] [0.128]
Recreation 1,548 -0.002 1.0579** 0.6038** 0.158 -0.221 Yes Yes 0.23
[0.013] [0.109] [0.196] [0.179] [0.125]
Entertainment 3,142 0.000 1.1559** 0.8127** 0.160 -0.4099** Yes Y es 0.26
[0.012] [0.068] [0.117] [0.111] [0.079]
Printing and Publis hing 2,138 -0.001 1.0701** 0.5581** 0.6283** 0.033 Yes Yes 0.33
[0.009] [0.06] [0.102] [0.098] [0.07]
Consumer Goods 4,075 0.010 1.019** 0.3928** 0.4686** -0.1502* Yes Yes 0.29
[0.006] [0.051] [0.089] [0.083] [0.059]
Apparel 3,084 -0.005 0.9957** 0.8504** 0.4759** -0.2131** Y es Y es 0.30
[0.007] [0.063] [0.111] [0.102] [0.072]
Healthcar e 3,908 -0.004 0.9175** 0.8799** -0.009 -0.102 Yes Yes 0.25
[0.008] [0.053] [0.092] [0.086] [0.061]
Medical Eq uipment 6,464 0.007 0.8734** 0.6838** -0.1431* -0.1214** Yes Yes 0.26
[0.005] [0.035] [0.062] [0.058] [0.041]
Pharmaceutical Products 12,839 0.016 1.0254** 0.7074** -0.4544** -0.3281** Yes Yes 0.15
[0.009] [0.055] [0.097] [0.089] [0.063]
Chemicals 6,489 0.003 1.3222** 0.6224** 0.114 -0.2732** Yes Yes 0.36
[0.006] [0.04] [0.069] [0.065] [0.046]
Rubber and Plasti c Products 1,406 -0.001 1.1007** 0.7235** 0.4403** -0.2993** Yes Y es 0.40
[0.014] [0.069] [0.118] [0.113] [0.08]
Textiles 721 -0.022 1.1569** 0.6122** 0.5816** -0.202 Yes Yes 0.33
[0.021] [0.121] [0.207] [0.197] [0.141]
Construction Materials 3,578 0.004 1.2697** 0.8696** 0.4532** -0.1842** Yes Yes 0.38
[0.007] [0.048] [0.082] [0.079] [0.056]
Construction 3,638 0.003 1.2035** 1.1375** 0.5253** -0.2544** Yes Yes 0.37
[0.008] [0.052] [0.088] [0.083] [0.06]
Steel Works Etc 4,541 0.0136* 1.544** 0.3783** -0.152 -0.3764** Yes Yes 0.37
[0.007] [0.049] [0.086] [0.081] [0.057]
Fabricated Products 753 -0.006 1.325** 0.9077** 0.286 -0.2505* Yes Yes 0.39
[0.013] [0.108] [0.177] [0.174] [0.126]
Machinery 6,903 0.006 1.312** 0.6043** 0.091 -0.1424** Yes Y es 0.38
[0.005] [0.033] [0.057] [0.053] [0.038]
Electrical Equipment 2,536 -0.002 1.0339** 0.7394** 0.128 -0.040 Yes Yes 0.24
[0.01] [0.07] [0.124] [0.114] [0.081]
Automobiles and Trucks 4,907 0.006 1.4781** 0.8371** 0.5476** -0.3711** Yes Y es 0.43
[0.007] [0.047] [0.081] [0.076] [0.055]
Aircraft 1,612 -0.009 1.004** 0.2705** -0.006 -0.224** Yes Yes 0.31
[0.008] [0.058] [0.099] [0.094] [0.067]
Shipbuilding, R ailroad Equipment 432 0.020 1.3229** 0.9568** 0.6545** 0.129 Yes Y es 0.33
[0.026] [0.154] [0.262] [0.249] [0.178]
Defense 1,018 0.011 0.6729** 0.5185** -0.4534** -0.3319** Y es Y es 0.16
[0.013] [0.102] [0.177] [0.165] [0.117]
Precious M etals 1,674 -0.002 0.4424** -0.278 -1.0821** -0.803** Yes Yes 0.14
[0.012] [0.108] [0.181] [0.176] [0.125]
Non-Metallic and Industrial Metal Mining 3,826 0.012 1.3614** 0.211 -0.5798** -0.6546** Y es Yes 0.24
[0.012] [0.077] [0.131] [0.126] [0.09]
Coal 1,805 0.014 1.2999** 0.7088** -0.245 -0.3634* Yes Y es 0.19
[0.02] [0.127] [0.225] [0.208] [0.147]
Petroleum and Natural Gas 17,934 0.003 1.3108** 0.6469** 0.035 -0.3547** Yes Y es 0.24
[0.005] [0.032] [0.055] [0.052] [0.037]
Utilities 14,851 0.002 0.6671** -0.0875** -0.1542** 0.022 Yes Yes 0.18
[0.003] [0.019] [0.033] [0.031] [0.022]
Communication 11,678 0.005 1.0457** 0.030 -0.099 -0.2291** Yes Yes 0.23
[0.004] [0.032] [0.055] [0.051] [0.036]
Personal Services 4,219 -0.019 1.0552** 0.8157** -0.011 -0.125 Yes Yes 0.22
[0.011] [0.066] [0.115] [0.108] [0.077]
Busines s Services 29,854 0.007 1.1573** 0.5857** -0.1981** -0.0916** Yes Yes 0.20
[0.004] [0.025] [0.042] [0.04] [0.029]
Computers 6,140 0.002 1.2187** 0.7725** -0.3697** -0.229** Yes Yes 0.29
[0.006] [0.043] [0.075] [0.07] [0.05]
Electronic E quipment 12,491 0.001 1.3482** 0.5982** -0.2072** -0.1933** Yes Yes 0.30
[0.004] [0.032] [0.057] [0.053] [0.037]
Measuring and Control Equip ment 3,245 0.014 1.0625** 0.6257** -0.2122** 0.095 Yes Yes 0.27
[0.008] [0.05] [0.086] [0.081] [0.057]
Business Suppl ies 3,194 0.002 1.2068** 0.62** 0.7536** -0.3049** Yes Yes 0.32
[0.011] [0.068] [0.121] [0.112] [0.079]
Shipping Containers 1,153 -0.002 1.1341** 0.4057** -0.138 -0.3736** Yes Yes 0.42
[0.011] [0.061] [0.105] [0.098] [0.07]
Transportation 9,674 -0.007 0.9545** 0.512** 0.3007** -0.1723** Yes Yes 0.23
[0.005] [0.037] [0.064] [0.061] [0.043]
Wholesale 9,718 0.007 1.0781** 0.6496** 0.2514** -0.1679** Y es Y es 0.27
[0.005] [0.033] [0.057] [0.054] [0.039]
Retail 17,625 0.002 1.0016** 0.7863** 0.3609** -0.1511** Yes Yes 0.25
[0.004] [0.028] [0.048] [0.045] [0.032]
Restaurants, Hotels, Motels 6,824 0.002 1.0453** 0.6528** 0.1597* -0.3007** Yes Y es 0.28
[0.006] [0.039] [0.068] [0.064] [0.045]
Banking 19,935 0.0096** 0.9641** 0.3091** 0.8163** -0.2493** Yes Y es 0.28
[0.003] [0.023] [0.04] [0.037] [0.027]
Insurance 10,471 0.0094* 1.114** 0.239** 0.5091** -0.2653** Yes Yes 0.29
[0.005] [0.03] [0.052] [0.049] [0.035]
Real Estate 2,546 -0.003 1.3632** 0.475** 0.328** -0.3189** Y es Yes 0.32
[0.011] [0.074] [0.125] [0.12] [0.086]
Trading 38,081 -0.001 0.9156** 0.2188** 0.098** -0.2092** Yes Yes 0.30
[0.001] [0.012] [0.02] [0.019] [0.014]
Almost Nothing 2,049 0.001 1.0144** 0.288** -0.2036* -0.1639* Yes Yes 0.24
[0.01] [0.062] [0.109] [0.102] [0.072]
Non-classifiable Establishments 13,856 0.009 1.0226** 0.8775** -0.1918** -0.2296** Yes Yes 0.18
[0.007] [0.044] [0.062] [0.073] [0.053]
*Denotes significance at the 5% level and ** denotes significance at the 1 % level.
Table 8 (Panel A): Impact of increase CRR from adverse media coverage on stock performance of US listed companies (by FF48 industry classi fications)
Table 8 (Panel A) provides regress ion results for (RIndustry – Rf) the monthly excess stock returns grouped by FF48 i ndustry classifications, on RRRC which represents numeric change in RRR scores, (Rm – Rf)
the market premium which represents the excess returns of the market over the risk-free interest rate, SMB the monthly equally weighted average of the stock returns on the small stock por tfolios minus the stock
returns on the big stock portfolios which represents the size premium, HML the equally weighted average of the stock returns on the high book-to-market ratio stock portfolios minus the stock returns on the low
book-to-market ratio stock portfolios which represents the value premium, WML the equally weighted average of the stock returns on winner portfolios minus the stock returns on the loser p ortfolios which
represents the momentum factor. In all regressions, dummy variables are included to control for firm and year fixed effects. Stock returns are adjusted for corporate actions a nd all variables are windsorized at 1%
and 99% level. Robus t standard errors clustered at firm level are reported in the brackets.
Industry Observations RRRC (RM-RF) SMB HML WML Firm Effect Year Effect Adj. R-squared
Gaming 354 0.037 1.5809** 1.5541** 0.604 -1.0166** Yes Yes 0.30
[0.031] [0.284] [0.499] [0.473] [0.334]
Table 8 (Panel B): Impact of increase CRR from adverse media coverage on stock performance of US listed companies (by 'gaming' industry classification)
Table 8 (Panel A) provides regression results for (RIndustry – Rf)
the monthly excess stock returns grouped by the ‘gaming’ industry classification, on RRRC which represents numeric change
in RRR scores, (Rm – Rf) the market premium which represents the excess returns of the market over the risk-free interest rate, SMB the monthly equally weighted average of the stock
returns on the small stock portfolios minus the stock returns on the big stock portfolios which represents the size premium, HML the equally weighted average of the stock returns on the high
book-to-market ratio stock portfolios minus the stock returns on the low book-to-market ratio stock portfolios which represents the value premium, WML the equally weighted average of the
stock returns on winner portfolios minus the stock returns on the loser portfolios which represents the momentum factor. In all regressions, dummy variables are included to control for firm
and year fixed effects. Stock returns are adjusted for corporate actions and all variables are windsorized at 1% and 99% level. Consistent with Hong and Kacperczyk (2009), this study adopts
the NAICS classification and identifies gaming stocks as those displaying the following NAICS codes, 7132, 71312, 713210, 71329, 713290, 72112, and 721120. This is separate and
distinct from the Fama and French (1997) 48 industry groups. Robust standard errors clustered at firm level are reported in the brackets.
*Denotes significance at the 5% level and ** denotes significance at the 1% level.
US listed companies Observations RRRC (RM-RF) SMB HML WML FirmAge BoardSize Year Effect Firm Effect Adj. R-squared
Full sample 331,517 0.0048** 1.0595** 0.6254** 0.1555** -0.1837** -0.0036** 0.003 Yes Yes 0.24
[0.001] [0.007] [0.012] [0.012] [0.008] [0.001] [0.003]
Table 9: Impact of increase CRR from adverse media coverage on stock performance of US listed companies (full sample)
Table 9 provides regression results for (Rfu ll – Rf) the monthly excess group stock returns for the full sample of US listed companies, on RRRC which represents numeric change in RRR scores, (Rm – Rf) the market premium
which represents the excess returns of the market over the risk-free interest rate, SMB the monthly equally weighted average of the stock returns on the small stock portfolios minus the stock returns on the big stock portfolios
which represents the size premium, HML the equally weighted average of the stock returns on the high book-to-market ratio stock portfolios minus the stock returns on the low book-to-market ratio stock portfolios which
represents the value premium, WML the equally weighted average of the stock returns on winner portfolios minus the stock returns on the loser portfolios which represents the momentum factor. FirmAge is the natural log of firm
age and is measured as the number of months since the firm was first covered by the CRSP (i.e. from December 1925). BoardSize is the natural log of number of directors on the board. In the regression, dummy variables are
included to control for firm and year fixed effects. Stock returns are adjusted for corporate actions and all variables are windsorized at 1% and 99% level. Robust standard errors clustered at firm level are reported in the brackets.
*Denotes significance at the 5% level and ** denotes significance at the 1% level.
Variable Definition
ER ER [or R(t)-RF(t)] is the excess return on the stock portfolio, where R(t) is the return on a stock portfolio,
RF(t) is the risk-free return rate (e.g., one month treasury bill rate).
(RM-RF)
(RM-RF) or MKTRF is the excess return on the market. It is calculated as the value-weight return on all
NYSE, AMEX, and NASDAQ stocks (from CRSP) minus the one-month Treasury bill rate (from Ibbotson
Associates).
SMB
SMB (Small Minus Big) is the average return on the three small portfolios minus the average return on the
three big portfolios,
SMB = 1/3 (Small Value + Small Neutral + Small Growth) - 1/3 (Big Value + Big Neutral + Big Growth).
SMB for July of year t to June of t+1 include all NYSE, AMEX, and NASDAQ stocks for which market
equity data for December of t-1 and June of t, and (positive) book equity data for t-1, exists.
HML
HML (High Minus Low) is the average return on the two value portfolios (that is, with high BE/ME ratios)
minus the average return on the twogrowth portfolios (low BE/ME ratios),
HML = 1/2 (Small Value + Big Value) - 1/2 (Small Growth + Big Growth).
HML for July of year t to June of t+1 include all NYSE, AMEX, and NASDAQ stocks for which market
equity data for December of t-1 and June of t, and (positive) book equity data for t-1, exist.
ME (Market Equity): Market equity (size) is price times shares outstanding. Price is from CRSP, shares
outstanding are from Compustat (if available) or CRSP.
BE (Book Equity): Book equity is constructed from Compustat data or collected from the Moody's Industrial,
Financial, and Utilities manuals. BE is the book value of stockholders' equity, plus balance sheet deferred
taxes and investment tax credit (if available), minus the book value of preferred stock. Depending on
availability, redemption, liquidation, or par value (in that order) were used to estimate the book value of
preferred stock. Stockholders' equity is the value reported by Moody's or Compustat, if it is available. If not,
stockholders' equity was measured by the book value of common equity plus the par value of preferred stock,
or the book value of assets minus total liabilities (in that order). See Davis, Fama, and French, 2000,
"Characteristics, Covariances, and Average Returns: 1929-1997," Journal of Finance, for more details.
BE/ME (Book-to-Market): The book-to-market ratio used to form portfolios in June of year t is book equity
for the fiscal year ending in calendar year t-1, divided by market equity at the end of December of t-1.
WML
WML (or Mom) is the average return on the two high prior return portfolios minus the average return on the
two low prior return portfolios,
Mom =1/2 (Small High + Big High)
- 1/2(Small Low + Big Low).
Six value-weight portfolios formed on size and prior (2-12) returns are used to construct Mom. The
portfolios, which are formed monthly, are the intersections of 2 portfolios formed on size (market equity,
ME) and 3 portfolios formed on prior (2-12) return. The monthly size breakpoint is the median NYSE market
equity. The monthly prior (2-12) return breakpoints are the 30th and 70th NYSE percentiles.
The six portfolios used to construct Mom each month include NYSE, AMEX, and NASDAQ stocks with
prior return data. To be included in a portfolio for month t (formed at the end of month t-1), a stock must
have a price for the end of month t-13 and a good return for t-2. In addition, any missing returns from t-12 to
t-3 must be -99.0, CRSP's code for a missing price. Each included stock also must have ME for the end of
month t-1.
RRRC
RRRC (RepRisk Ratings change) is the numeric change in RepRisk Ratings (RRR) monthly scores. For the
purpose of this study, the highest RRR of ‘AAA’ is associated with a RRR score of 1, RRR of ‘AA’ is
associated with a RRR score of 2, RRR of ‘A’ is associated with a RRR score of 3, etc. and the lowest RRR
score of 10 is given to RRR of ‘D’.
RRRC is calculated as RRRscore(t-1) - RRRscore(t) which implies a negative RRRC value (e.g., -1) is
indicative of a deterioration in RRR score (i.e., increase in corporate reputation risk by 1 category). For
example, if a firm with a RepRisk Ratings of AAA (represented as RRR of 1 in Table 3) experience a decline
(i.e., increased risks) in corporate reputation to AA (i.e., RRR of 2), the RRRC numeric value will be -1.
FirmAge Firm age, measured as the number of months since the firm was first covered by the Center for Research in
Securities Prices (CRSP). FirmAge is calculated as the natural log of (1+ age of the firm).
BoardSize Number of board members as captured by BoardEx database. BoardSize is calculated as the natural log of
total directors (i.e., sum of all directors).
Appendix: Variable definitions.
*Descriptions for Fama, French and Carhart 4 factors are extracted from WRDS and Ken French’s web site
(https://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html).
