European Financial Management, Vol. 17, No. 1, 2011, 100–119doi: 10.1111/j.1468-036X.2010.00548.x

The Impact of Corporate GovernancePress News on Stock Market Returns

Alessandro Carretta, Vincenzo Farina and Duccio MartelliUniversity of Rome Tor Vergata, Via Columbia 2, 00133, Rome, ItalyE-mail: carretta@uniroma2.it; vincenzo.farina@uniroma2.it; duccio.martelli@uniroma2.it

Franco FiordelisiUniversity of Rome III, Via D’Amico 77, 00145, Rome, ItalyE-mail: fiordelisi@uniroma3.it

Paola SchwizerUniversity of Parma, Via Kennedy 6, 43100, Parma, ItalyE-mail: paola.schwizer@unipr.it

Abstract

Stock market prices reflect information regarding firms’ business environments,operations and, in general, their fundamentals. Recently, various studies haveanalysed the link between news coverage and stock prices but no evidence existson how channels and ways of communication of information affect investors’behaviour. We analyses these aspects focussing on a large sample of corporategovernance news published between 2003 and 2007 in ‘Il Sole 24 Ore’, Italy’smajor financial newspaper. We show that before news is made public investorsare only able to assess the type of corporate governance event underlying it. Afterpublication, investors are influenced by the content (positive or negative) and thetone of communication (strong or weak) of the news.

Keywords: corporate governance, shareholder value, event study, text analysis

JEL classification: G14, G34

1. Introduction

Market efficiency is based on the principle that asset prices reflect all relevantinformation. Based on the type of information captured by stock prices, Fama (1970)distinguishes three forms of efficiency: the weak form (i.e. prices reflect all the

The authors wish to thank two anonymous referees, John Doukas (the editor), MarcusSchmidt, Stefano Caselli, the participants at the 2009 Annual Meeting of the EuropeanFinancial Management Association (EFMA) and the participants at the 2008 Annual Meetingof the Italian Academy of Management (AIDEA) for their very helpful comments. All errors,of course, rest with the authors. Correspondence: Franco Fiordelisi.

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The Impact of Corporate Governance Press News 101

information about historical prices), the semi-strong form (i.e. stock prices representall publicly available information) and the strong form (i.e. stock prices reflect allpublicly and privately available information).

Various studies show that information coverage has a significant impact on financialmarkets (Dell’Acqua et al., 2010; Tetlock et al., 2008; Tetlock, 2007; Doukas et al.,2005; Antweiler and Frank, 2004; Coval and Shumway, 2001). However, the literaturedoes not provide evidence of how channels and ways of communication of informationaffect investors’ behaviour.

This study analyses these aspects focussing on the impact of a large sample of corporategovernance news published between 2003 and 2007 in ‘Il Sole 24 Ore’, Italy’s majorfinancial newspaper, on abnormal stock returns. Corporate governance news is classifiedbased on the type of corporate governance event (i.e., changes in the board of directors,functioning of the board of directors, the firm’s ownership and other events).

We focus on corporate governance news since i) over the last decade several factors(such as corporate scandals, regulatory reforms, corporate crises, etc.) have contributedto raising the debate on corporate governance, in which the mass media have been givenincreasing importance and ii) the widespread belief that corporate governance affectsshareholder value (Fiordelisi and Molyneux, 2010; Bebchuk et al., 2009; El Mir andSeboui, 2008; Carretta et al., 2007; Lehn et al., 2007; Cremers and Nair, 2005; Drobetzet al., 2004; Klock et al., 2005; Gompers et al., 2003). Moreover, we analyse the Italianmarket since during this period important reforms regarding corporate governance havebeen implemented and this topic has been at the centre of the public debate in the massmedia.

Consistently with previous studies (Bulkley and Herrerias, 2006; Cai et al., 2006;Dimson and Mussavian, 1998) our results show that press news play an important role ininvestors’ expectation about future firm value. Our analysis also provides novel findingsshowing that, before news is made public, investors are only able to assess the type ofcorporate governance event underlying it. After publication, the behaviour of investorsis influenced by the content (positive or negative) and the tone of communication (strongor weak) of the news.

The contribution of this paper is manifold. First, the analysis accounts for thepossibility (hitherto neglected by other studies) that investors’ behaviour is influencedboth by the content and the tone of press news. Second, in order to allow the stability,the reproducibility and the accuracy of the measures of content and tone for a largenumber of news items, we apply text analysis techniques. Finally, the paper considerscorporate governance news and its interaction with the corporate economic and financialsituation, while previous studies assessing stock reaction to news focuses on a singlepiece of information such as the analysts’ stock recommendation (Schlumpf et al., 2008),governance characteristics (Cai et al., 2006), earnings announcements (Liu et al., 2003)without interacting these measures with company fundamentals.

This paper is structured as follows. Section 2 reviews the related literature, section 3outlines the methodology, section 4 describes the sample, section 5 presents the resultsand conclusions are drawn in section 6.

2. Literature Review

‘The role of the media is to collect, select, certify and repackage information’ (Dycket al., 2008, p. 1098). The mass media are an important source of information about the

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102 A. Carretta, V. Farina, D. Martelli, F. Fiordelisi and P. Schwizer

value of firms, since they fulfil two functions in financial markets (Deephouse, 2000).First, the media act as an information broker by simply spreading information passively,second, they represent an active participant, whose comments allow players operatingin the market to better assess their investment choices.

The literature provides evidence of a statistically significant relationship betweeninformation coverage and trading volumes, yield and price volatility (Dell’Acqua et al.,2010; Tetlock et al., 2008; Tetlock, 2007; Doukas et al., 2005; Antweiler and Frank,2004; Coval and Shumway, 2001).

Dell’Acqua et al. (2010) find evidence that voluntary disclosure following theintroduction of the Regulation Fair Disclosure, included in the Selective Disclosureand Insider Trading Act issued by the SEC, reduces price volatility of high tech firmslisted in the US market.

In addition, Tetlock et al. (2008) find that variations in the indicators of profitabilityand efficiency of market operations are a function of the percentage of negative wordsin the news. Moreover, some news exerts an effect in a relatively short period and othernews in the medium and long term (for example, news regarding core aspects of firmmanagement).

Tetlock (2007) finds that a high degree of media pessimism predicts downwardpressure on market prices, followed by a reversion to ‘fundamentals’, and an unusuallyhigh or low level of pessimism predicts a high market trading volume.

Doukas et al. (2005) find that positive excess analyst coverage, raising investorsoptimism, is associated with overvaluation and low future returns.

Antweiler and Frank (2004) do not find a statistically or economically significanteffect of positive messages on stock returns; however, they find evidence of a relationshipbetween message activity and both trading volume and return volatility. Similarly, Covaland Shumway (2001) establish that the ambient noise level created by traders in a futurespit is linked to volume and volatility, but not to returns.

Moreover, corporate governance news impacts on market reactions in two ways.First, based on agency theory, it contributes to mitigating the effects of informationasymmetry, helping to inform investors of the behaviour of managers and to discloseproblems within control mechanisms, with positive effects on control costs (Jensenand Meckling, 1976; Fama and Jensen, 1983). Second, based on the theory of socialconstructivism (Johnson et al., 2005; Pollock and Rindova, 2003; Deephouse, 2000),governance news can contribute to the legitimacy of firms following comments basedon comparison with standards commonly considered as ‘good governance’.

Dyck et al. (2008) show that news about governance abuses increase the pressure frominvestors and supervisory authorities. Johnson et al. (2005), using event study, analysethe impact of US firms’ board ratings published in ‘Business Week’ on stock returns. Inan observation period ranging from 6 days prior to 9 days following a news event, thepublication of a favourable rating is found to have a positive impact on the performanceof the shares (but, significantly, only within 2 days). The same authors also observea mildly positive impact of unfavourable ratings on returns before and after an event,considering this a finding worthy of further investigation.

However, while the literature provides important evidence that news can influenceinvestors’ behaviour, no evidence exists regarding ‘how’ the communication of the newsinfluences behaviour.

As shown by various cognitive studies (Baumeister et al., 2001; Rozin and Royzman,2001; Fiske and Taylor, 1991; Brief and Motowidlo, 1986), positive and negative news

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The Impact of Corporate Governance Press News 103

have different impacts on people’ perceptions, and negative news also exerts a strongerimpact than positive news.

Regarding ways of communication, the emotion aroused by news is likely toinfluence individuals’ behaviour (Reeve, 1992). Shoemaker and Reese (1996) arguethat newspapers generally tend to put certain emphasis in the news in order to make itmore engaging to the public. As a consequence, journalists may tend to dramatise newsevents in order to make their articles more interesting and to maximise impact by makingreaders more engaged by their writing style (Damton, 1975). This news dramatisationincreases readers’ involvement and lends more credibility to the content of items (Gibsonand Zillmann, 1994).

Overall, linguistic communication seems to be a potentially important source ofinformation about firms’ stockholder value. A relevant question is: what are the effectsof this dramatisation on investors’ behaviours? In other words, it is important to askwhether the tone of communication (strong or weak) should be investigated togetherwith content (positive or negative) to assess the effect of news on the behaviour ofinvestors. From this perspective, our hypothesis is: The effect of corporate governancenews on investors’ behaviour, measured by changes in the price of shares, depends onboth their content and tone.

3. Methods

This section describes the research methods used in the paper. First, the text analysismethodology used to examine the information content of corporate governance news isoutlined. Second the event study employed to assess the new impact on stock marketreturns is described, and, finally, the econometric model used to investigate the linkbetween corporate news and stock market returns is presented.

3.1. Text analysis

In order to allow the stability, the reproducibility and the accuracy of the measures ofcontent and tone of communication for a large number of corporate governance news,we apply text analysis (Stone et al., 1966) using the linguistic dictionary Harvard IVPsycho Social1 and the software Wordsmith 4 (Scott, 2004).

Content is defined as the degree to which news has a positive or negative meaning. Avalue of 1 means that corporate governance news has the highest positive content whilea value of −1 means that it has the highest negative content. Tone is defined as thedegree to which the news is expressed in a strong or weak manner. A value of 1 meansthat corporate governance news has the strongest tone of communication while a valueof −1 means that it has the weakest tone.

Operationally, Wordsmith 4 counts the number of words in each news item thatfalls within the four categories of the Harvard IV Psycho Social Dictionary: positive,negative, strong, and weak. In fact, each category contains a list of words and word senses.For example, the negative category is the largest, with 2,291 entries of words/phrasesdenoting a negative sense, while the positive category has 1,915 words with a positive

1 The spreadsheet format can be downloaded at: www.wjh.harvard.edu/∼inquirer/spreadsheet_guide.htm

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104 A. Carretta, V. Farina, D. Martelli, F. Fiordelisi and P. Schwizer

sense. The category strong has 1902 words implying strength and the category weak has755 words implying weakness.2

Employing scales (from −1 to 1) allows us to express the degree with which news ispositive or negative and the strength of the tone of communication of news.

The positive or negative sense of the news is determined by: (P − N)/(P + N), whereN and P are, respectively, the number of positive and negative words in news, accordingto the classification provided by the Harvard IV Psycho Social Dictionary. The valueobtained is between −1 (completely negative news) and 1 (completely positive news).Similarly, the strength of the tone of the news is given by: (S − W)/(S + W), where Sand W are, respectively, the number of words contained in the news that express strengthor weakness, according to the classification provided by the Harvard IV Psycho SocialDictionary. The value obtained in this way is between −1 (weakest) and 1 (strongest).

3.2. Event study

An event study approach (Campbell et al., 1997; MacKinlay, 1997) is used to assesswhether the stock returns of firms influenced by corporate governance news displayabnormal returns (AR) around the news date (t). Similar to previous studies (Tetlocket al., 2008; Tetlock, 2007; Antweiler and Frank, 2004; Coval and Shumway, 2001), thispaper posits that a small number of investors directly observe firms’ activities, whilemost investors collect second hand information. With this in mind, our analysis examineswhether abnormal returns occur at the time of release of news of the event in ‘Il Sole 24ore’, rather than when the company concerned makes an announcement.

The first step is the estimation of the AR, that is the forecast errors of a specificnormal return-generating mode. We estimated daily AR using market model regressionsby applying OLS-regression methodology for time series of one full trading year (252trading days) prior to the event window and regressing the daily returns for stock j onday t (rj,t) on a measure of the market return on day t (rm,t):

rj,t = αj + βj rm,t + εj,t (1)

where Rj,t = Ln[(Pt + Dt)/Pt−1], Pt and Dt are the market price and the daily flowdividend, respectively; RMt is the rate of return of the domestic market for that sectorwhich pertains to the target bank/bidder on day t, i.e. RMt = Ln[(It/It−1)], where It is thevalue of the market index at time t and εj,t is the error term. The residuals (εj,t), providethe estimates of ARs.

We defined various event windows of different sizes from 41 days (−20 to +20)to zero (i.e. a calculation carried out for a single day). The CARs estimates statisticalsignificance is assessed following the Standardised Cross Sectional Z test procedureproposed by Cummins and Weiss (2004).

2 We are grateful to one of the anonymous referees for drawing our attention to the factthat using lists of words of different size could influence the skew of the distributions fornews content and tone. This choice is due to the following reasons. First, using a standardtext analysis dictionary allows for the stability and the reproducibility of results. Second,the problem is limited by considering the number of times different words of each category(positive/negative or strong/weak) are repeated in the text of the news. Finally, the positiveskew of distribution for news tone could be explained by the fact that journalists generallyuse a strong tone in order to make news more engaging to the public (Shoemaker and Reese,1996; Damton, 1975).

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The Impact of Corporate Governance Press News 105

3.3. Econometric model

Linear models are specified to investigate the relationships between stock returns andvariables related to corporate governance news, following the established literature(Agrawal and Knoeber, 1996; Baliga et al., 1996; Core et al., 1999; Fiordelisi andMolyneux, 2006).

CARi,t = a0 + a1CONi,t + a2TCi,t + a3NCBi,t + a4NCFi,t + a5NOi,t + a6TAXi,t

+ a7EXTi,t + a8OPRi,t + a9OPCi,t + a10LEVi,t + a11Ri,t + a12OLDi,t

+ a13 ln(TAi,t) + a14(ROE ∗ VALi,t) + a15(ROE ∗ ETi,t)

+ a16(ROE ∗ NCBi,t) + a17(ROE ∗ NCFi,t) + a18(ROE ∗ NOi,t)

+ a19D1 + a20D2 + a21D3 + a22D4 + εi,t (2)

where subscript i denotes the cross-section dimension, t denotes the time dimension,CAR is the cumulative abnormal return, CON is the degree to which news has a positiveor negative meaning, TC is the degree to which the news is expressed in a strong orweak manner, NCB is a dummy variable (1 if the news is related to changes in the boardof directors, 0 otherwise), NBF is a dummy variable (1 if the news is related to thefunctioning of the board of directors, 0 otherwise), NO is a dummy variable (1 if thenews is related to the firm’s ownership, 0 otherwise), TAX is the ratio between firm netprofit and pre-tax profits, EXTR is the ratio between firm pre-tax profits and operatingprofits, OPR is the ratio between firm operating revenues and total assets, OPC is theratio between firm operating costs and total assets, LEV is the ratio between total assetsand total equity, ROE is the company Return of Equity publicly available at the newsdisclosure, OLD is the number of past corporate governance news items released overthe last 12 months, Di (i = 1, 2, 3, 4) are dummy variables for the year,3 and ei,t is therandom error term.

Three groups of variables are considered (Table 1). The first includes dummy variablescapturing the type of event (i.e., changes in the board of directors, functioning of theboard of directors, the firm’s ownership and other events).4 This group includes the twovariables relating to the content and tone of the news. These are estimated using the textanalysis techniques described above.

The second group of variables relates to the performance of firms, since this islikely to influence CARs. Rather than using a single performance indicator (e.g. Returnon Equity), various variables are included to account for possible managerial factorsinfluencing performance. These are obtained by the following Dupont’s five-part ROEdecomposition:5

ROEi,t = NPi,t

PTPi,t× PTPi,t

OPi,t×

(ORi,t

Ai,t− OCi,t

Ai,t

)× Ai,t

Ei,t(3)

3 Four dummy variables are assessed over a 5-year period (not including 2002) to avoidmulticollinearity problems.4 This latter dummy variable is not included to avoid multicollinearity problems.5 Since our sample comprises both financial and non-financial firms, the ROE decompositionused is slightly different from the original one, in order to maintain consistency in the analysisamong different firms.

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106 A. Carretta, V. Farina, D. Martelli, F. Fiordelisi and P. Schwizer

Table 1

Description of variables

This table describes the variables used to investigate the relationship between corporate governancenews and stock return reactions. Panel A displays cumulative abnormal stock returns over different eventwindows; panel B presents corporate governance variables; panel C displays corporate performancevariables.

Panel A: Stock market variables

Variable Symbol Description

CAR over the eventwindow (20;20)

CAR(20;20) CAR(20;20) is the cumulative abnormal returncalculated between 20 days before and 20 daysafter news publication

CAR over the eventwindow (10;10)

CAR(10;10) CAR(10;10) is the cumulative abnormal returncalculated between 10 days before and 10 daysafter news publication

CAR over the eventwindow (5;5)

CAR(5;5) CAR(5;5) is the cumulative abnormal returncalculated between 5 days before and 5 days afternews publication

CAR over the eventwindow (3;3)

CAR(3;3) CAR(3;3) is the cumulative abnormal returncalculated between 3 days before and 3 days afternews publication

CAR over the eventwindow (20;1)

CAR(20;1) CAR(20;1) is the cumulative abnormal returncalculated between 20 days before and 1 day afternews publication

CAR over the eventwindow (10;1)

CAR(10;1) CAR(10;1) is the cumulative abnormal returncalculated between 10 days before and 1 day afternews publication

CAR over the eventwindow (5;1)

CAR(5;1) CAR(5;1) is the cumulative abnormal returncalculated between 5 days before and 1 day afternews publication

CAR over the eventwindow (3;1)

CAR(3;1) CAR(3;1) is the cumulative abnormal returncalculated between 3 days before and 1 day afternews publication

CAR over the eventwindow (0;20)

CAR(0;20) CAR(0;20) is the cumulative abnormal returncalculated between the date of news publicationand 20 days later

CAR over the eventwindow (0;10)

CAR(0;10) CAR(0;10) is the cumulative abnormal returncalculated between the date of news publicationand 10 days later

CAR over the eventwindow (0;5)

CAR(0;5) CAR(0;5) is the cumulative abnormal returncalculated between the date of news publicationand 5 days later

CAR over the eventwindow (0;3)

CAR(0;3) CAR(0;3) is the cumulative abnormal returncalculated between the date of news publicationand 3 days later

CAR over the eventwindow (0;1)

CAR(0;1) CAR(0;1) is the cumulative abnormal returncalculated between the date of news publicationand 1 day later

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The Impact of Corporate Governance Press News 107

Table 1

Continued.

Panel B: Corporate governance variables

Variable Symbol Description

Content CON CON refers to the degree to which news has a positive ornegative meaning. A value of 1 means the corporategovernance new has the highest positive value and avalue of −1 refers to the highest negative value.

Tone ofcommunication

TC TC refers to the degree to which news is expressed in astrong or weak manner. A value of 1 means the newshas the strongest tone, while a value of −1 indicatesthe weakest tone.

News related tochanges in boardof directors

NCB NCB is a dummy variable, i.e. it has a value of 1 if thenews is related to changes in the board of directors, 0otherwise.

News related toboard of directorsfunctioning

NBF NBF is a dummy variable, i.e. it has a value of 1 if thenews is related to the functioning of the board ofdirectors, 0 otherwise.

News related to thefirm’s ownership

NO NO is a dummy variable, i.e. it has a value of 1 if thenews is related to the firm’s ownership, 0 otherwise.

Panel C: Corporate variables

Variable Symbol Description

Return on Equity ROE ROE is the ratio between firm net profit (NP) and totalequity capital. This ratio provides information aboutthe overall bank profitability.

Tax impact TAX TAX is the ratio between firm net profit (NP) andpre-tax profits(PTP), i.e. TAX = NP/PTP. This ratioprovides information about the tax influence oncorporate profits

Extraordinary items EXT EXT is the ratio between firm pre-tax profits (PTP) andoperating profits (OP), i.e. EXT = PTP/OP. This ratioprovides information about the extraordinary itemsthat influence corporate profits.

Revenue efficiency OPR OPR is the ratio between firm operating revenues (OR)and total assets (A), i.e. OPR = OR/A. This ratioprovides information about firms’ ability to generateoperating revenues.

Operating efficiency OPC OPC is the ratio between firm operating costs (OC) andtotal assets (A) , i.e. OPC = OC/A. This ratio providesinformation about firms’ operating efficiency.

Financial leverage LEV LEV is the ratio between total assets (A) and total equity(E), i.e. LEV = A/E. This ratio provides informationabout ‘firms’ operating efficiency.

Company size Ln(A) Ln(A) is the natural logarithm of the company assetsOld news OLD OLD is the number of corporate governance news items

published over the last 12 months.

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108 A. Carretta, V. Farina, D. Martelli, F. Fiordelisi and P. Schwizer

where NP is net profit, PTP is pre-tax profits, OP is operating profits, OR is the totaloperating revenues, OC is the total operating costs, A is total assets and E is the totalequity capital.

The third group comprises variables obtained by multiplying corporate governancevariables and performance variables. These cross-variables recognise that firms’ stockreturns are likely to be influenced by corporate soundness, by the news content and toneand also by the interaction of both groups of variables.

4. Data Description

Our sample includes corporate governance news topics of listed firms in the Italian StockExchange and published in ‘Il Sole 24 Ore’ between 2003 and 2007. ‘Il Sole 24 Ore’ is themost influential financial newspaper in Italy (managed by the Confederation of ItalianIndustry, Confindustria) and has the largest market share among financial newspapers.6

All the news published by ‘Il Sole 24 Ore’ is extracted from the database Factiva,which provides access to more than 10,000 sources, including newspapers, magazines,news agencies and information sites. In order to reduce the margins of subjectivity inchoosing the news and obtain replicable results, the classification of news in this studyfollows that of Factiva. ‘Governance news’, therefore, includes all releases falling inthe sub-categories of ‘Changes in Management’ and ‘Corporate Governance / InvestorRelations’, found within the broader category ‘Corporate and Industrial News’ in theFactiva database.

Regarding the event study analysis, for each news item, the daily return series ofthe firm involved is calculated, while stock market information was obtained fromthe Datastream database. In order to calculate a firm’s expected return, nine industrybenchmark indices are used: DJTM Italy, DJTM Italy Automobiles, DJTM Italy Banks,DJTM Italy Electricity, DJTM Italy Insurance, DJTM Italy Industrials, DJTM ItalyMedia, DJTM Italy Technology, DJTM Italy Telecom, DJTM Italy Utilities.

Regarding firms’ financial ratios, data is obtained from Aida and Bankscope databases.Since values come from various data sources, differences due to different accountingprinciples are taken into consideration for the period analysed.

Table 2 presents some descriptive statistics for variables considered in the analysis.ROE displays a negative mean value during the period analysed, ranging from 23.8%(Mediaset in 2007) and −179.5% (Alitalia in 2004). High standard deviation levels forTAX and EXT are consistent with the substantial accounting actions and extraordinaryoperations undertaken by Italian firms to smooth profits and losses. Revenues ability andoperating efficiency denote the ability of firms to generate value from their operatingactivities: in particular both ratios show similar values in term of mean (0.343 and 0.328respectively) and standard deviations (38.5% and 39.3%). Finally the mean of financialleverage is extremely high (more than 8.6). The highest level belongs to Generali, which,in 2007, had leverage equal to 20.26; by contrast, also in 2007, Fmr-Art’e shows thelowest level among all firms during that period. Corporate governance news usually hasa positive content and a strong tone of communication (i.e. the mean TC value is 0.82).

Table 3 summarises corporate governance news according to the type of underlyingevent, distinguishing news related to changes in the board of directors (NCB), news

6 Namely, 59% in terms of sold copies of Italian financial newspapers (source: DistribuzioneMedia Spa).

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The Impact of Corporate Governance Press News 109

Table 2

Sample: descriptive statistics

Table 2 displays descriptive statistics for the considered variables: CARs are the cumulative abnormalreturns calculated over different event periods; ROE is the ratio between firm net profit (NP) and totalequity capital. This ratio provides information about the overall bank profitability. CON refers to thedegree to which news has a positive or negative meaning; TC refers to the degree to which news isexpressed in a strong or weak manner. TAX is the ratio between firm net profit (NP) and pre-tax profits(PTP); EXT is the ratio between firm pre-tax profits (PTP) and operating profits (OP); OPR is the ratiobetween firm operating revenues (OR) and total assets (A); OPC is the ratio between firm operatingcosts (OC) and total assets (A); LEV is the ratio between total assets (A) and total equity (E); OLD isthe number of corporate governance news items published over the last 12 months.

Variable Obs. Mean Standard Deviation Minimum Maximum

CAR(20;20) 197 0.017 0.084 −0.230 0.377CAR(10;10) 197 0.015 0.066 −0.262 0.217CAR(5;5) 197 0.007 0.052 −0.319 0.219CAR(3;3) 197 0.007 0.048 −0.148 0.261CAR(20;1) 197 0.008 0.056 −0.189 0.251CAR(10;1) 197 0.008 0.045 −0.159 0.191CAR(5;1) 197 0.004 0.032 −0.153 0.193CAR(3;1) 197 0.003 0.027 −0.133 0.191CAR(0;20) 197 0.010 0.056 −0.174 0.253CAR(0;10) 197 0.007 0.053 −0.254 0.361CAR(0;5) 197 0.003 0.046 −0.270 0.295CAR(0;3) 197 0.005 0.045 −0.109 0.394CAR(0;1) 197 0.004 0.041 −0.142 0.408ROE 197 −0.052 0.387 −1,795 0,238CON 197 0.466 0.438 −1.000 1.000TC 197 0.824 0.198 0.000 1.000TAX 197 0.709 0.745 −4.051 5.434EXT 197 0.304 7.359 −71.682 3.638OPR 197 0.344 0.386 −0.011 1.349OPC 197 0.328 0.394 0.005 1.435LEV 197 8.682 5.488 1.306 20.266OLD 197 5.335 6.003 1.000 23.000

related to the board’s functioning (NBF), news related to the firm’s ownership (NO) andnews related to other corporate governance events (OCG). The number of news itemsrelated to corporate governance has shown a strong upward trend during the last fiveyears: the percentage increase is more than 400%, with the total number of news itemsin 2007 close to 90. During the same period, board changes represent the main topic,with more than half of the news items reporting on this. Starting from 2006, corporategovernance matters have become critical subjects in the Italian mass media; in fact,not only news related to board changes have been widely reported, but items regardingownership and board functioning have also appeared in newspapers.

5. Results

Table 4 displays the event study results obtained by analysing 197 corporate governancenews items for Italian listed firms published between 2003 and 2007. The percentage

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110 A. Carretta, V. Farina, D. Martelli, F. Fiordelisi and P. Schwizer

Table 3

Corporate governance news

This table displays the distribution of news according to the type of corporate governance event overthe period 2003–2007. NCB is the number of news items related to changes in the board of directors;NBF is the number of news items related to the functioning of the board of directors; NO is the numberof news releases related to the firm’s ownership; OCG is the number of news related to other corporategovernance events.

Year NCB NBF NO OCG Total

2003 15 1 1 0 172004 22 1 2 0 252005 19 5 2 0 262006 21 6 10 4 412007 32 11 19 26 88

Total 109 24 34 30 197

Table 4

Results: cumulative abnormal returns around publication dates of corporate governance news

for Italian listed firms between 2003 and 2007

The table displays the results of an event study analysing the data of 197 corporate governance newsitems between 2003 and 2007. Abnormal returns have been calculated following the market modelregression estimated using the OLS method. The OLS parameters have been estimated during a periodof 252 days in which the markets were open prior to the event window, maximum (−20, +20). Toestimate market returns, the market sector index was applied. The Standard Cross-Sectional procedurewas applied to CAR. The statistical significance test employed is the one suggested by Dodd andWarner (1983).

Event window Mean CAR(a) Standard deviation(a) Z-test(b) Positive CAR(a)

(−20;20) 1.519 8.543 1.609∗ 57.143(−10;10) 1.339 6.499 2.724∗∗ 56.682(−5;5) 0.547 5.194 1.810∗∗ 52.074(−3;3) 0.577 4.796 2.667∗∗∗ 52.535(−20;−1) 0.922 5.439 2.236∗∗ 56.221(−10;−1) 0.819 4.476 3.569∗∗∗ 52.074(−5;−1) 0.362 3.162 2.960∗∗∗ 51.152(−3;−1) 0.298 2.768 3.257∗∗∗ 54.839(0; 20) 1.105 5.471 2.463∗∗∗ 55.760(0; 10) 0.504 5.150 1.995∗∗ 51.152(0; 5) 0.175 4.441 1.014 42.857(0; 3) 0.280 4.437 2.564∗∗∗ 41.935(0; 1) 0.282 3.986 11.580∗∗∗ 45.161(a)Values are given as percentages.(b)The symbols ∗, ∗∗, and ∗∗∗ represent significance levels of 10%, 5% and 1% respectively.

of positive CARs ranges between 40% and 60%, showing substantial differences instock returns reaction to the news. The heterogeneity of the results is consistent withthe heterogeneity of corporate news included in the sample. Focussing on symmetricevent windows, mean CARs vary from 0.5% [for the event window (−3,3)] to 1.5% [for

C© 2010 Blackwell Publishing Ltd

The Impact of Corporate Governance Press News 111

the window (−20,20)], and all results are statistically significant at the 10% confidencelevel or less.

The percentage of positive CARs increases as the length of the event window increases,ranging from 52.1% [for the window (−3,3)] to 57.1% [for the window (−20,20)]. Inorder to assess whether investors are able to anticipate news, two sets of event windowsare also selected, one preceding and the other following the publishing date [respectively,(−20,−1), (−10,−1), (−5,−1), (−3,−1) and (0,20), (0,10), (0,5), (0,3), (0,1)]. Onaverage, positive CARs are found both before and after the publishing date and theresults obtained are statistically significant at the 10% confidence level or less.

The percentage of CARs immediately after the news publication date is lower than50%, but increases to more than 50% 10 days after publication. Despite all mean CARsestimates being positive (for all event windows analysed), it cannot be concluded thatcorporate governance news has a positive impact on firms’ stock returns. There is asubstantial heterogeneity of CAR estimates (e.g. in some event windows, the number ofpositive and negative CARs is exactly equal), so that it is not possible to make definiteconclusions about the impact of corporate governance news.

In order to assess the stock market reaction due to the semantic content of news,corporate performance and the interaction between these variables, Table 5 reports resultsof the analysis using the econometric model (1). First, the Ramsey Reset test shows that,in most cases, it is possible to reject the null hypothesis (at the 10% confidence level orless) that the models have no omitted variables. Although disappointing, this evidence islargely expected, since the study’s aim is to assess the link between corporate governancenews and stock returns rather than to use the relationship as a reliable forecasting method.

As a consequence, it is not surprising that the explanatory power of the models rangesbetween 10.4% and 32.2%. In addition, the White’s test and the Breusch-Pagan/Cook-Weisberg test results indicate that there are heteroskedasticity problems in a few models;reported standard errors and hypothesis tests are, therefore, based on White’s varianceestimator to account for these problems.

Focusing on symmetric event windows, CARs display a positive and statisticallysignificant (at the 10% confidence level or less) relationship with NO, OPC and TC ∗ROE, while, usually, there is a negative and statistically significant relationship withTAX, OPR, ROE, NCB ∗ ROE and NO ∗ ROE. These results are consistent withthe view that stock returns tend to increase around ownership news if the firm is notprofitable; otherwise, the overall effect on stock returns is substantially negative (i.e.investors dislike ownership related news for profitable firms so that they tend to selltheir stocks).

The results also suggest that the content and tone of corporate governance news arenot statistically significant in relation to CARs, but the strong tone for profitable firms(i.e. ROE ∗ TC) has a positive influence on CARs. This is consistent with the view thatinvestors are influenced by the tone of news related to profitable firms and tend to buytheir stocks.

The negative relationship between CARs and NCB ∗ ROE indicates that stock returnsare negatively linked to news related to change in the board of directors for profitablefirms, but not in the case of non-profitable firms.

Overall, results provide evidence that the type of corporate governance event hasa statistically significant effect on firms’ stock returns and that the strong tone forprofitable firms has a statistically significant relationship with CARs.

In order to further confirm the aforementioned findings, a number of robustnesschecks are conducted by considering different event windows before and after the

C© 2010 Blackwell Publishing Ltd

112 A. Carretta, V. Farina, D. Martelli, F. Fiordelisi and P. Schwizer

Tabl

e5

Res

ults

:rel

atio

nshi

pbe

twee

nco

rpor

ate

gove

rnan

cene

ws,

corp

orat

epe

rfor

man

cean

dcu

mul

ativ

eab

norm

alre

turn

sfo

rIt

alia

nli

sted

firm

sbe

twee

n

2003

and

2007

(197

obse

rvat

ions

)

Thi

sta

ble

show

sth

ere

lati

onsh

ipbe

twee

nco

rpor

ate

gove

rnan

cene

ws,

corp

orat

epe

rfor

man

cean

dcu

mul

ativ

eab

norm

alre

turn

sfo

rIt

alia

nli

sted

firm

sbe

twee

n20

03an

d20

07.S

tand

ard

erro

rs,r

epor

ted

inbr

acke

ts,a

rees

tim

ated

usin

gW

hite

’ses

tim

ator

toac

coun

tfor

hete

rosk

edas

tici

typr

oble

ms.

The

R-R

test

isth

eR

amse

yR

eset

test

and

the

null

hypo

thes

isis

that

the

mod

elha

sno

omit

ted

vari

able

s.T

heW

hite

’snu

llhy

poth

esis

test

isus

edto

asse

ssth

eho

mos

keda

stic

ity.

The

BS

/CW

test

isth

eB

reus

ch-P

agan

/Coo

k-W

eisb

erg

test

for

hete

rosk

edas

tici

tyan

dth

enu

llhy

poth

esis

isth

eC

onst

antv

aria

nce.

The

sym

bols

∗ ,∗∗

,and

∗∗∗

repr

esen

tsig

nifi

canc

ele

vels

of10

%,5

%an

d1%

resp

ectiv

ely.

Eve

ntw

indo

ws

arou

ndth

eE

vent

win

dow

sbe

fore

the

Eve

ntw

indo

ws

afte

rth

ene

ws

publ

icat

ion

date

new

spu

blic

atio

nda

tene

ws

publ

icat

ion

date

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

R(−

20,2

0)(−

10,1

0)(−

5,5)

(−3,

3)(−

20,1

)(−

10,1

)(−

5,1)

(−3,

1)(0

,20)

(0,1

0)(0

,5)

(0,3

)(0

,1)

Inte

rcpe

t−0

.046

5−0

.034

2−0

.057

2−0

.059

5−0

.040

6−0

.040

8−0

.052

3−0

.058

3∗∗−0

.058

80.

0063

−0.0

051

−0.0

012

−0.0

055

(0.0

941)

(0.0

666)

(0.0

495)

(0.0

513)

(0.0

585)

(0.0

490)

(0.0

343)

(0.0

280)

(0.0

537)

(0.0

637)

(0.0

540)

(0.0

614)

(0.0

617)

NC

B0.

0243

0.01

250.

0220

0.02

89∗∗

0.02

070.

0102

0.00

950.

0127

∗∗0.

0246

∗0.

0023

0.01

250.

0164

0.00

44(0

.021

6)(0

.017

2)(0

.013

6)(0

.011

4)(0

.012

9)(0

.012

3)(0

.006

5)(0

.005

6)(0

.013

0)(0

.014

1)(0

.012

4)(0

.010

7)(0

.009

5)N

BF

0.03

250.

0010

−0.0

080

−0.0

040

0.05

29∗∗

∗0.

0290

∗∗0.

0071

0.00

790.

0497

∗∗∗

−0.0

279

−0.0

152

−0.0

120

−0.0

038

(0.0

246)

(0.0

199)

(0.0

177)

(0.0

145)

(0.0

140)

(0.0

134)

(0.0

080)

(0.0

069)

(0.0

136)

(0.0

175)

(0.0

161)

(0.0

146)

(0.0

127)

NO

0.05

07∗∗

∗0.

0452

∗∗∗

0.02

54∗∗

0.02

26∗

0.04

32∗∗

∗0.

0311

∗∗∗

0.02

11∗∗

∗0.

0165

∗∗0.

0462

∗∗∗

0.01

400.

0044

0.00

620.

0069

(0.0

164)

(0.0

150)

(0.0

113)

(0.0

116)

(0.0

115)

(0.0

100)

(0.0

069)

(0.0

065)

(0.0

113)

(0.0

114)

(0.0

088)

(0.0

089)

(0.0

077)

CO

N0.

0119

0.00

04−0

.007

3−0

.005

50.

0154

−0.0

017

0.00

340.

0029

0.01

250.

0023

−0.0

109

−0.0

083

−0.0

058

(0.0

140)

(0.0

102)

(0.0

090)

(0.0

075)

(0.0

096)

(0.0

079)

(0.0

050)

(0.0

041)

(0.0

096)

(0.0

078)

(0.0

081)

(0.0

073)

(0. 0

074)

TC

−0.0

025

0.02

020.

0083

−0.0

032

0.00

010.

0210

0.01

440.

0136

0.00

13−0

.001

0−0

.005

9−0

.016

7−0

.003

9(0

.036

4)(0

.029

6)(0

.029

2)(0

.018

1)(0

.020

1)(0

.018

7)(0

.014

4)(0

.010

8)(0

.019

4)(0

.026

3)(0

.026

0)(0

.019

6)(0

.020

8)TA

X−0

.018

4∗∗−0

.017

9∗∗−0

.014

3∗∗−0

.012

0∗−0

.013

1−0

.011

2−0

.007

6−0

.008

0−0

.014

5∗−0

.006

7−0

.006

8∗−0

.003

9−0

.003

6(0

.008

6)(0

.008

0)(0

.007

2)(0

.006

5)(0

.008

4)(0

.008

8)(0

.008

6)(0

.007

8)(0

.007

9)(0

.005

1)(0

.003

6)(0

.003

6)(0

.003

1)E

XT

0.00

020.

0000

−0.0

004

−0.0

004

0.00

05∗∗

∗0.

0004

0.00

000.

0000

0.00

06∗∗

−0.0

004

−0.0

005∗

−0.0

004

−0.0

003

(0.0

004)

(0.0

004)

(0.0

003)

(0.0

003)

(0.0

003)

(0.0

003)

(0.0

002)

(0.0

001)

(0.0

003)

(0.0

003)

(0.0

003)

(0.0

003)

(0.0

002)

OP

R−0

.428

3∗∗−0

.358

1∗∗∗

−0.1

672∗

−0.2

087∗∗

−0.1

737

−0.1

150

−0.0

067

−0.0

171

−0.2

534∗∗

−0.2

412∗

−0.1

589

−0.1

904

−0.1

663

(0.2

079)

(0.1

360)

(0.0

967)

(0.1

025)

(0.1

189)

(0.0

952)

(0.0

765)

(0.0

631)

(0.1

160)

(0.1

252)

(0.1

058)

(0.1

245)

(0.1

248)

OP

C0.

4222

∗∗0.

3742

∗∗∗

0.18

32∗∗

0.21

59∗∗

0.18

270.

1289

0.01

910.

0211

0.26

20∗∗

0.24

32∗

0.16

270.

1935

0.16

60(0

.206

8)(0

.133

4)(0

.091

6)(0

.104

4)(0

.120

6)(0

.096

2)(0

.078

4)(0

.065

3)(0

.115

6)(0

.130

4)(0

.108

7)(0

.133

6)(0

.135

1)L

EV

−0.0

008

−0.0

002

−0.0

006

−0.0

013

0.00

010.

0004

0.00

00−0

.000

50.

0000

−0.0

006

−0.0

007

−0.0

008

−0.0

004

(0.0

017)

(0.0

011)

(0.0

010)

(0.0

008)

(0.0

011)

(0.0

007)

(0.0

005)

(0.0

004)

(0.0

011)

(0.0

009)

(0. 0

008)

(0.0

007)

(0.0

007)

Ln(

A)

0.00

210.

0012

0.00

200.

0029

∗0.

0007

0.00

040.

0010

0.00

130.

0014

0.00

080.

0011

0.00

160.

0013

(0.0

028)

(0.0

019)

(0.0

013)

(0.0

015)

(0.0

018)

(0.0

014)

(0.0

010)

(0.0

009)

(0.0

017)

(0.0

018)

(0.0

014)

(0.0

017)

(0.0

017)

C© 2010 Blackwell Publishing Ltd

The Impact of Corporate Governance Press News 113

Eve

ntw

indo

ws

arou

ndth

eE

vent

win

dow

sbe

fore

the

Eve

ntw

indo

ws

afte

rth

ene

ws

publ

icat

ion

date

new

spu

blic

atio

nda

tene

ws

publ

icat

ion

date

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

Ry

=C

AR

y=

CA

R(−

20,2

0)(−

10,1

0)(−

5,5)

(−3,

3)(−

20,1

)(−

10,1

)(−

5,1)

(−3,

1)(0

,20)

(0,1

0)(0

,5)

(0,3

)(0

,1)

RO

E−0

.290

2∗∗−0

.225

9∗∗−0

.096

7−0

.167

6−0

.094

2−0

.019

50.

0473

0.00

60−0

.158

0∗∗−0

.208

9∗∗−0

.143

7∗−0

.173

3∗∗−0

.139

3∗∗(0

.125

4)(0

.094

0)(0

.092

6)(0

.077

5)(0

.075

6)(0

.072

9)(0

.046

6v(0

.036

7)(0

.074

2)(0

.100

9)(0

.081

8)(0

.070

5)(0

.064

2)O

LD

0.00

22∗∗

0.00

150.

0006

0.00

040.

0023

∗∗∗

0.00

17∗∗

0.00

070.

0003

0.00

24∗∗

∗−0

.000

2−0

.000

10.

0001

−0.0

001

(0.0

010)

(0.0

009)

(0.0

007)

(0.0

007)

(0.0

007)

(0.0

007)

(0.0

005)

(0.0

004)

(0.0

007)

(0.0

008)

(0.0

006)

(0.0

007)

(0.0

006)

NC

B∗

RO

E−0

.135

0∗∗−0

.060

4−0

.124

7∗∗∗

−0.1

212∗∗

−0.0

274

−0.0

324

−0.0

591∗∗

∗−0

.071

3∗∗∗

−0.0

245

−0.0

277

−0.0

654

−0.0

500

0.01

59(0

.060

3)(0

.038

9)(0

.043

4)(0

.051

0)(0

.038

0)(0

.040

2)(0

.019

8)(0

.018

8)(0

.036

2)(0

.056

3)(0

.047

3)(0

.046

3)(0

.035

5)N

BF

∗R

OE

−0.2

456∗∗

∗−0

.081

0−0

.083

1−0

.076

7−0

.131

1∗∗−0

.069

5−0

.050

6∗∗−0

.063

5∗∗∗

−0.1

166∗∗

−0.0

114

−0.0

326

−0.0

128

−0.0

115

(0.0

796)

(0.0

707)

(0.0

558)

(0.0

634)

(0.0

521)

(0.0

565)

(0.0

246)

(0.0

213)

(0.0

551)

(0.0

655)

(0.0

528)

(0.0

572)

(0.0

452)

NO

∗R

OE

−0.3

634∗∗

∗−0

.263

3∗∗∗

−0.1

710∗∗

∗−0

.109

2−0

.173

8∗∗∗

−0.1

273∗∗

−0.1

025∗∗

−0.0

738

−0.1

772∗∗

∗−0

.135

0∗∗−0

.068

4−0

.036

0−0

.005

8(0

.087

2)(0

.073

0)(0

.074

3)(0

.070

3)(0

.066

1)(0

.059

3)(0

.046

3)(0

.042

9)(0

.065

0)(0

.063

3)(0

.055

1)(0

.050

4)(0

.040

6)C

ON

∗R

OE

−0.0

009

0.00

63−0

.013

7−0

.066

6∗∗−0

.003

10.

0508

0.02

730.

0031

−0.0

281

−0.0

446

−0.0

409

−0.0

696∗∗

−0.0

743∗∗

(0.0

705)

(0.0

634)

(0.0

409)

(0.0

336)

(0.0

484)

(0.0

509)

(0.0

245)

(0.0

182)

(0.0

494)

(0.0

484)

(0.0

368)

(0.0

344)

(0.0

368)

TC

∗R

OE

0.51

84∗∗

∗0.

3574

∗∗∗

0.25

43∗∗

∗0.

3551

∗∗∗

0.20

21∗

0.05

940.

0024

0.06

150.

2849

∗∗∗

0.30

04∗∗

∗0.

2512

∗∗∗

0.29

37∗∗

∗0.

2113

∗∗∗

(0.1

657)

(0.1

326)

(0.1

140)

(0.0

790)

(0.1

038)

(0.0

898)

(0.0

619)

(0.0

440)

(0.1

052)

(0.1

130)

(0.0

896)

(0.0

732)

(0.0

801)

D1

0.01

410.

0105

0.01

950.

0195

−0.0

079

0.00

150.

0093

0.01

97∗

0.00

330.

0091

0.01

04−0

.000

3−0

.001

9(0

.043

1)(0

.024

6)(0

.019

8)(0

.021

2)(0

.028

5)(0

.018

2)(0

.014

2)(0

.011

4)(0

.026

9)(0

.024

8)(0

.020

6)(0

.024

2)(0

.023

4)D

2−0

.024

1−0

.016

5−0

.003

8−0

.003

9−0

.028

5−0

.002

70.

0094

0.01

76∗∗

−0.0

231

−0.0

139

−0.0

131

−0.0

217

−0.0

165

(0.0

393)

(0.0

260)

(0.0

200)

(0.0

175)

(0.0

260)

(0.0

160)

(0.0

103)

(0.0

074)

(0.0

256)

(0.0

207)

(0.0

173)

(0.0

168)

(0.0

142)

D3

0.01

690.

0081

0.01

200.

0014

0.00

680.

0062

0.00

600.

0104

0.01

210.

0015

0.00

61−0

.009

1−0

.009

5(0

.038

5)(0

.023

4)(0

.019

1)(0

.017

9)(0

.026

0)(0

.015

1)(0

.010

5)(0

.007

5)(0

.025

6)(0

.018

4)(0

.016

9)(0

.016

6)(0

.015

7)D

40.

0044

−0.0

039

0.01

140.

0074

−0.0

075

−0.0

049

0.00

870.

0180

∗∗−0

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C© 2010 Blackwell Publishing Ltd

114 A. Carretta, V. Farina, D. Martelli, F. Fiordelisi and P. Schwizer

news publication. Focussing on events before the publication date, results are stronglyconsistent with the findings discussed above. In particular, stock returns tend to increasebefore news publication if this reports ownership news and the firm is not profitable.Otherwise, the overall effect on stock returns is substantially negative (i.e. investorsdislike rumours of ownership news for profitable firms, so that they tend to sell theirstocks).

As expected, text analysis does not generate variables with a statistically significantrelationship with CARs prior to the news publication. This suggests that, beforepublication, investors are simply able to assess the type of event underlying the news(e.g. related to the firm’s ownership). Focussing on the events after the news publicationdate, results are quite consistent with those presented above. CARs display a positiveand statistically significant relationship (at the 10% confidence level or less) with OPCand TC ∗ ROE, while there is usually a negative and statistically significant relationshipwith OPR, ROE and CON ∗ ROE.

In these models, text analysis enables us to generate variables with a statisticallysignificant relationship with CARs, while a naıve and subjective classification of newsdoes not achieve this result. This is consistent with the view that, after the newspublication, investors’ behaviour is influenced by the content and the tone of the news,while they are no longer influenced by the type of corporate governance event.

In order to further confirm the aforementioned findings, we conducted a robustnesscheck by estimating the AR (one for each event windows) using the Fama and French(1992) three factors model. This alternative approach enables us to assess whether ourfindings are sensitive to the AR calculation procedure. Following Fama and French(1992, 1993), AR is estimated by regressing the daily returns for stock j on day t (rj,t)on three stock market returns measures (rather than a single index) and applying OLS-regression methodology for the time series of one full trading year (252 trading days)prior to the event window as follows:

rj,t − rf ,t = α + β3 (rm,t − rf ,t) + βs rsmb,t + βv rhml,t + εj,t (4)

where rjt daily returns for stock j on day t (calculated using the same procedure used inthe equation 1); rf ,t is the rate of return of the risk free asset (measured by the Italy T-Bill12 months index); rm,t is the rate of return of the whole domestic stock market; rsmb,t isthe excess returns of small caps over big caps (measured by the difference between therates of return of the MSCI Italy Small and Large indices); rhml,t is the excess returns ofvalue stocks over growth stock (measured by the difference between the rates of return ofthe MSCI Italy Value and Growth indices) and the residuals (εj,t), provide the estimatesof ARs.

Table 6 reports results of the analysis by running the econometric model (1) usingthe new set of estimated CAR (one for each event window) as dependent variable.Our findings are strongly consistent with those discussed above: estimated regressioncoefficients display the same sign and a similar statistical significance to those reportedin Table 5. Overall, results reported in Table 6 confirm that the content and tone ofcorporate governance news are not statistically significant in relation to CARs, but thestrong tone for profitable firms has a positive influence on CARs. Similarly, stock returnsare negatively linked to news related to change in the board of directors for profitablefirms, but not in the case of non-profitable firms.

C© 2010 Blackwell Publishing Ltd

The Impact of Corporate Governance Press News 115Ta

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C© 2010 Blackwell Publishing Ltd

116 A. Carretta, V. Farina, D. Martelli, F. Fiordelisi and P. Schwizer

Tabl

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C© 2010 Blackwell Publishing Ltd

The Impact of Corporate Governance Press News 117

6. Conclusions

The mass media have a significant impact on financial markets since news reports cancontribute to the formation of investor expectations.

This paper analyses the interactions between the mass media and the stock market,focussing on the impact of a large sample of corporate governance news publishedbetween 2003 and 2007 in ‘Il Sole 24 Ore’, Italy’s major financial newspaper, onabnormal stock returns. The analysis accounts for the possibility that investor behaviouris influenced both by the content of the news and by the tone of communication.

Corporate governance news, corporate financial situation and their joint interactionhave been considered in the empirical analysis. This is also based on a naıve andsubjective classification of corporate governance news and on text analysis techniquesto assess both their content and tone.

Results provide the evidence that stock returns tend to increase after ownership news ifthe firm involved is not profitable at the time of the news release. Otherwise, the overalleffect on stock returns is substantially negative. This would indicate that investors dislikeownership related news for profitable firms, so that they tend to sell their stocks. Theresults also suggest that, in general, the content and tone of corporate governance newsare not statistically significant related to CARs. However, for profitable firms, the tonedoes appear to exert a positive influence on CARs. This is consistent with the view thatinvestors are influenced by the tone of news related to profitable firms and tend to buytheir stocks). The negative relationship between CARs and NCB ∗ ROE indicates thatstock returns are negatively affected by news related to changes in the board of directorsfor profitable firms, but not in the case of non-profitable firms.

The paper also finds evidence that investors are influenced by rumours about corporategovernance news and that, before publication, they are simply able to assess the typeof corporate governance event. However, after publication, investors’ behaviour isinfluenced by the content and tone of the news.

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