CFE1 is a CEO Turnover Good or Bad News EFA2010

7/31/2019 CFE1 is a CEO Turnover Good or Bad News EFA2010

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Is a CEO Turnover Good or Bad News?

Axel Kind Yves Schlpfer

April 2010

Abstract

We investigate the information content of CEO turnovers by analyzing abnormal stockreturns and abnormal trading volumes in the surrounding of the announcement date. Thesample consists of 208 CEO turnovers between January 1998 and June 2009 for companiesbelonging to the Swiss Performance Index. The single most important variable in assessingthe value of a turnover news is found to be the quality of the departing CEO as proxied by theprior stock-price performance relative to the market. In line with economic intuition and inaccordance with previous studies, the departure of outperforming (underperforming) managersrepresents bad (good) news for shareholders. Outside successions and forced turnovers yieldsignificant positive abnormal returns. However, a forced turnover does not per se represent a

positive signal to shareholders. On the contrary, investors seem to critically assess the qualityof the boards firing decision by considering the quality of the departing manager. When atalented CEO is dismissed or forced to leave, shareholders appear to disesteem the boardsdecision. This finding is confirmed in multivariate cross-sectional regressions and is robustto time subperiods and alternative test statistics. Trading volume is found to consistentlyincrease for all types of CEO turnovers. However, the size of the reaction crucially depends onthe characteristics of the turnover event, with forced turnovers generating the largest impact onthe turnover announcement day (+196.37%). Finally, the operating performance significantlyincreases (decreases) in the years following (preceding) CEO turnovers and reflects on averagethe short-term stock-price reaction around the announcement date.

Keywords: Corporate governance; CEO turnover; Firm performance; Trading volumeJEL codes: G14; G30; G34; M51

Contact information: Email A. Kind: [email protected]; Email Y. Schlpfer: [email protected]. Aspecial thanks goes to Marco Poltera for his excellent research assistance.

Department of Finance, University of Basel and Swiss Institute of Banking and Finance, University of St. Gallen.Department of Finance, University of Basel.


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Is a CEO Turnover Good or Bad News?

Abstract

We investigate the information content of CEO turnovers by analyzing abnormal stockreturns and abnormal trading volumes in the surrounding of the announcement date. Thesample consists of 208 CEO turnovers between January 1998 and June 2009 for companiesbelonging to the Swiss Performance Index. The single most important variable in assessingthe value of a turnover news is found to be the quality of the departing CEO as proxied by theprior stock-price performance relative to the market. In line with economic intuition and inaccordance with previous studies, the departure of outperforming (underperforming) managersrepresents bad (good) news for shareholders. Outside successions and forced turnovers yieldsignificant positive abnormal returns. However, a forced turnover does not per se represent apositive signal to shareholders. On the contrary, investors seem to critically assess the qualityof the boards firing decision by considering the quality of the departing manager. When atalented CEO is dismissed or forced to leave, shareholders appear to disesteem the boardsdecision. This finding is confirmed in multivariate cross-sectional regressions and is robustto time subperiods and alternative test statistics. Trading volume is found to consistentlyincrease for all types of CEO turnovers. However, the size of the reaction crucially depends onthe characteristics of the turnover event, with forced turnovers generating the largest impact onthe turnover announcement day (+196.37%). Finally, the operating performance significantlyincreases (decreases) in the years following (preceding) CEO turnovers and reflects on averagethe short-term stock-price reaction around the announcement date.

1 Introduction

The duty of a Chief Executive Officer is to maximize shareholders wealth by tak-ing sensible management decisions. Given the scope and importance of this mission, it is evidentthat a CEO turnover represents a major event in the history of any corporation, with possibly farreaching consequences for the company and its shareholders. The aim of this paper is to assess the

information content of CEO turnovers from the stockholders perspective. In particular, we aim atexplaining the cross-sectional variation of abnormal returns by considering crucial characteristicsof the turnover, such as the departure type (forced or voluntary), the successor origin (insiders oroutsiders), the prior performance of the incumbent manager, and combinations thereof.

A real-world example should best illustrate how investors interpret the information related to aCEO turnover for determining the value of a stock. The example refers to Mr. Fred Kindle, formerCEO of ABB Ltd, a global leader in power and automation technologies.1 Under his leadership,

1Despite the fact that the story of Mr. Kindle motivates very well this study and is a prime example of aCEO turnover that achieved broad media attention and had a shocking impact on investors, we should remark that

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ABB recovered from financial distress and achieved a record result in 2007. In January 2005, thedate of Kindles appointment as CEO, ABBs stock price was around 6 Swiss francs. Under hisleadership the stock price rose to around 25 Swiss francs in February 2008. According to the Fi-

nancial Times, ABBs recovery qualifies as a prime case study of successful company restructuring.2

Nevertheless, on February 13, 2008, ABB surprisingly announced in an official statement that FredKindle would leave ABB due to irreconcilable differences about how to lead the company.3 TheCFO of ABB, Michel Demar, was appointed interim CEO, but at that time was also considered asa potential candidate for the position of permanent CEO. Several news agencies4 speculated thatthis decision was mainly caused by a power struggle with the president of the board, Hubertusvon Gruenberg, regarding ABBs acquisition strategy. The departure of Fred Kindle was a bigsurprise to the financial community as everybody agreed that he was doing an outstanding job atABB. Strikingly, the Financial Times referred to him as the wunderkind chief executive. Thefact that investors shared the same perception about Fred Kindles work performance is crucially

captured by the stock-price reaction on the announcement date of his departure. In spite of thesimultaneous announcements of a record result for the year 2007, a doubling of the dividend, andupcoming share repurchases, the stock price dropped sharply by 5.14% on that very same day.According to Bloomberg, ABBs stock price lost interim about 10%, which was the worst drop ofthe previous three years. This example highlightens two key insights that go along with this paper.First, investors may attribute a great importance to the information of a CEO departure. Second,the valuation consequences of a CEO turnover strongly depend on the characteristics and circum-stances of this event. While the academic literature has already stressed the beneficial effects offorced turnovers, the example of Mr. Kindle suggests that the prior performance of the departingmanager may convey equally important information. These insights motivate us in studying the

stock-price impact of CEO turnovers by considering a variety of characteristics associated withthese events.A large part of prior research on CEO turnovers focuses on the relation between the CEOs

performance and the turnover probability (Coughlan and Schmidt, 1985; Weisbach, 1988; Warner,Watts, and Wruck, 1988; Parrino, 1997; Suchard, Singh, and Barr, 2001). This strand of literaturecomes to the conclusion that there is a negative relation between performance and the probabilityof a (forced) turnover. However, while statistically significant, this negative relation is found to beeconomically weak.

A second strand of literature which is of immediate relevance for the hypotheses studied in thispaper investigates the impact of CEO turnovers on the companys performance. Contributionsdiffer with respect to the performance measures employed (stock price reactions vs. accountingperformance measures) and the characteristics of the turnovers considered: (i) outside vs. insidesuccessions, (ii) forced vs. voluntary turnovers, (iii) governance differences, (iv) gender differences,

this event could not be included in the empirical analysis due to a no-confounding-event criterion applied in theconstruction of the sample. More precisely, the release of other valuation-relevant news (dividends and earningsannouncement) on the date of the dismissal of Mr. Kindle prevents us from using this data point.

2http://www.ft.com/cms/s/0/5a5db304-da69-11dc-9bb9-0000779fd2ac.html3ABB Press Release: ABB CEO Fred Kindle leaves company, available at http://www.abb.com.4Amongst others Reuters, Bloomberg, Timesonline, Financial Times, Financial Times Deutschland, Handelsblatt

and Handelszeitung covered the news regarding the departure of Fred Kindle at ABB.

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etc.. Table 1 presents an overview of the most important contributions in this field together with asummary of the main empirical findings.

The majority of studies (Reinganum, 1985; Furtado and Rozeff, 1987; Warner, Watts, and Wruck,

1988; Bonnier and Bruner, 1989; Borokhovich, Parrino, and Trapani, 1996; Dherment-Ferere andRenneboog, 2002; Huson, Parrino, and Starks, 2001; Dahya and McConnell, 2005; Adams and Mansi,2009) detect significant positive abnormal returns following turnovers with company-outsiders assuccessors. Notable exceptions are Worrell, Davidson, and Glascock (1993) and Khanna and Poulsen(1995). The former find mixed results and the latter do not report significant abnormal returnsby examining companies eventually filing for Chapter 11 protection, neither for outside nor insidesuccessions.

The majority of studies that also investigate the subsample of forced turnovers find that ab-normal returns following firings are higher than those following voluntary turnovers (Furtado andRozeff, 1987; Denis and Denis, 1995; Huson, Parrino, and Starks, 2001; Dherment-Ferere and Ren-

neboog, 2002; Adams and Mansi, 2009). Borokhovich, Parrino, and Trapani (1996) report significantpositive abnormal performance for forced turnovers in combination with outside successions. OnlyDedman and Lin (2002) detect significant negative abnormal returns on average after a CEOsdismissal.

Weisbach (1988) investigates the relation between the composition of the board of directors(insider- vs. outsider-dominated boards) and CEO turnovers. He reports positive announcementeffects but no difference in the impact between the firing decision of outsider- and insider-dominatedboards. Similarly, Fisman, Khurana, and Rhodes-Kropf (2005) examine the role of managerial en-trenchment for the boards firing decision and its consequence on the stock-price, finding a weaklysignificant relation between entrenchment and abnormal returns.

Lee and James (2007) and Coxbill, Sanning, and Shaffer (2009) study gender effects by compar-ing the price impact of male vs. female CEO appointments. While the former detect significantlylower (and negative) abnormal returns for women CEOs, the latter report a negative but insignif-icant impact on the stock price. Finally, Johnson, Magee, Nagarajan, and Newman (1985) andWorrell, Davidson, Chandy, and Garrison (1986) measure the stock-price reaction in the aftermathof key-executives deaths. The latter report negative and significant effects in association with sud-den deaths and the former significantly positive (negative) reactions following the death of companyfounders (non-founders).

As mentioned, accounting performance measures can be used as an alternative way to assessthe value of a CEO turnover. Several papers (e.g. Denis and Denis, 1995; Khurana, 2001; Dedmanand Lin, 2002; Huson, Malatesta, and Parrino, 2004; Fisman, Khurana, and Rhodes-Kropf, 2005;Hillier and McColgan, 2005; Dezso, 2007) investigate the impact of CEO changes on key account-ing performance measures. Typically, the papers evidence that a CEO-turnover is preceded bydeteriorating accounting figures, which improve after the new CEO takes up his/her position. Thedescribed pattern is generally more pronounced for forced than for voluntary turnovers.

CEO turnover in relation to manager quality (proxied by prior company or stock performance)is investigated in Weisbach (1988) and Bonnier and Bruner (1989). Weisbach (1988) finds a strongand negative relation between the intersection of prior stock performance with outside boards andabnormal returns around the CEO turnover. Bonnier and Bruner (1989) investigate underperform-

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ing firms jointly identified by the criteria of negative earnings and dividend omission prior to themanagement turnover. The reason to select this particular sample of management turnover is thatthe abnormal return at the announcement of a (forced) management turnover comprises two effects

as described by Warner, Watts, and Wruck (1988). First, if the turnover signals managerial qualitythat is worse than anticipated then the information effect is negative. Second, the real effect ispositive if the (board-initiated) turnover is appreciated by the shareholders. Therefore, positiveabnormal returns are observed only if the real effect outweighs the information effect. By using asample of companies for which the bad performance has already recognized they try to reduce thenegative information effect and estimate a more accurate real effect.

In this paper, we investigate stock returns, operating return on assets, as well as trading volumesin the surrounding of CEO turnover events. The sample consists of CEO turnovers at companiesin the Swiss Performance Index during the period between January 1998 and June 2009. The fi-nal sample comprises 208 CEO turnovers. It is survivorship-bias free since it also includes CEO

turnovers at companies that exited the index. The CEO-turnover variables considered in the inves-tigation are the successor origin, the departure type, and the prior stock performance.

This paper contributes in three ways to the existing literature. First, it corroborates the findingsof the existing literature on CEO turnovers by employing a new hand-collected data sample. Inparticular, we are able to show that the most important results reported for the US also apply tothe Swiss market. This is interesting because - as shown in LaPorta, de Silanes, and Shleifer (1999)and Faccio and Lang (2002) - the Swiss market is characterized by a less atomistic ownership struc-ture with more family-controlled companies and fewer active investors. Second, the paper classifiesturnovers with respect to (i) the departure type of the CEO (voluntary vs. forced), (ii) the successororigin (internal or external), (iii) the prior performance (outperformance or underperformance), and

all the interactions of those variables. Most importantly, in contrast to previous research, the paperemphasizes that forced turnovers do not always constitute a positive signal to shareholders: Forcedturnovers of underperforming managers trigger significantly positive abnormal returns, while forcedturnovers of overperforming managers are associated with negative abnormal returns. This suggeststhat shareholders assess the quality of the boards firing decision by considering the performanceof the departing CEO. Third, instead of solely focusing on abnormal returns, the paper analyzesthe impact of CEO turnover announcements on trading volumes5 and long-term accounting perfor-mance measures.

The results obtained in this paper indicate that outside successors, forced turnovers, and priorunderperformance of the company under the departing manager lead to significant positive abnor-mal returns: +1.85%, +2.74%, and +1.94% on average for the [-2 0] event window. The largestaverage abnormal returns are detected for the following two categories of CEO turnovers: (i) forceddepartures in conjunction with an outside successor (+6.71%)6 and (ii) forced departures of under-performing managers (+5.73%). Interestingly, while forced turnovers of underperforming managerstrigger positive and significant abnormal returns (+5.73%), forced turnovers of outperforming CEOsare associated with negative abnormal returns (2.24%). This suggests that shareholders assess

5To the best of our knowledge, the only study that investigates abnormal returns and trading volumes aroundmanagement-turnover announcement is Cools and van Praag (2007).

6When not otherwise stated, the abnormal returns reported in parethesis refer to [-3 0] event windows

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the quality of the firing decision by the board of directors by considering the prior performance ofthe company under the departing CEO. The results are robust with respect to time subperiods anda wide range of parametric and non-parametric test specifications.

The trading volume of the average company affected by a CEO turnover is found to increase byalmost 130% on the announcement day. Particularly large increases in trading volume are observedfor forced-turnover announcements (mean: +196.37%) and forced turnovers of underperformingCEOs (mean: +259.64%). In accordance with theoretical papers on the release of public informa-tion, absolute abnormal stock returns are found to be positively correlated with abnormal tradingvolumes.

The long-term relation between CEO turnovers and operating performance, which is measuredas the ratio of operating income and book value of total assets, shows that a CEO turnover istypically preceded by deteriorating operating performance and followed by a steady increase inoperating performance. Besides for the total sample, this pattern is particularly evident for the

subsamples of outside successions, forced departures, departures of underperforming CEOs, andthe intersection of forced departures with underperforming CEOs.

The remainder of this paper is structured as follows. Section 2 develops hypotheses regardingthe expected stock-price reaction following different types of CEO turnovers. Section 3 deals withthe sample construction and describes the final sample of CEO turnovers. Section 4 presents theempirical analysis of this paper. After addressing the setup of the event-study and presenting gen-eral results related to the impact of CEO turnovers on abnormal stock returns (Subsection 4.1),we perform a cross-sectional analysis of the results by regressing abnormal returns against selectedCEO-turnover variables (Subsection 4.2) and provide extensive robustness checks (Subsection 4.3).Subsection 4.4 focuses on the impact of CEO turnovers on the trading volume and Subsection 4.5

investigates the long-term impact of turnovers on the companies operating performance. Section 5provides a summary of the paper and concludes.

2 Theory, Prior Empirical Results, and Hypotheses

In this section we formulate hypotheses regarding the impact of CEO turnovers on the corre-sponding stock prices. In particular, we are interested in differentiating between various charac-teristics of the turnover, such as (i) the successor origin (inside vs. outside successions), (ii) thedeparture type (forced vs. voluntary departures) and, (iii) the relative performance of the company

under the departing CEO. Such hypotheses are meant to reflect explicit theories proposed in theCEO-turnover literature, plausible extensions thereof, and empirical results from previous studies.

2.1 Outside Succession

It is a well established empirical fact that in the majority of CEO turnovers the successor is acompany insider. The corporate-finance literature has proposed a number of plausible reasons for

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the Boards preference for inside over outside CEOs. These are (i) the company-specific human cap-ital accumulation theory of Dherment-Ferere and Renneboog (2002), (ii) the quality-measurementtheory, (iii) the tournament theory of Chan (1996).

Dherment-Ferere and Renneboog (2002) argues that inside candidates have two main advantagesover outsiders. First, over the years they have the opportunity to accumulate valuable company-specific knowledge about processes and technologies. Second, they can exploit an already existingsocial network to acquire specific internal information. Thus, the accumulation of company-specifichuman capital naturally makes insiders more attractive than outsiders for a CEO position.

Another explanation for the reluctance to appoint outside candidates to the CEO position arisesfrom the less accurate estimation of their quality. The history of an insider in the company auto-matically generates a performance track record that can be easily used by the Board of Directors toassess the insiders quality. Conversely, the information basis to estimate the quality of an outsideris much smaller, which makes this choice intrinsically more risky.

Finally, Chan (1996) argues that considering outsiders for the CEO position can reduce theincentives and hence the motivation of lower-level executives. Clearly, if outsiders are includedinto the circle of potential successors the chance for insiders to become CEOs diminishes. Thus,Chan (1996) suggests that the preference for inside successors may represent a natural attempt tomotivate employees by strengthening the link between performance and reward. By considering thegeneral preference for insiders as CEO successors, we argue that the board of directors will appointan outsider as CEO only if his/her quality exceeds by far that of the best available insider. Inthis light, we might expect the stock price to react positively once the information about a CEOturnover with an outside succession is released, which leads us to the formulation of the followinghypothesis.

Hypothesis 1: The announcement of an outside succession yields positive abnormalreturns.

By considering the empirical evidence reported in Table 1, column 6, the above hypothesis seemsto be backed by the majority of previous studies.

2.2 Forced Turnovers

The board of directors has the non-transferable and indefeasible duty of nomination and dis-missal of the management of the company. Ideally, we would expect the board to act in the bestinterest of shareholders when deciding about a CEOs dismissal.

The improved management hypothesis presented by Huson, Malatesta, and Parrino (2004) statesthat forced management turnovers induce a higher expected company performance through in-creased managerial quality. Since the quality of the CEO is not directly observable, companydirectors will infer the quality of a CEO from his/her past performance. A CEO will be replaced

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if the realized performance is sufficiently low and the expected benefit of a turnover exceeds theexpected cost. More precisely, the resulting costs from the turnover have to be more than offsetby the quality differential separating the new and the incumbent CEO. Following this argument,

investors should interpret the firing decision by the board as a positive signal about the quality ofthe appointed CEO and the value of the firm.

Under the scapegoat hypothesis based on Holmstrm (1979), Shavell (1979), and Mirrlees (1976)firings of CEOs occur even though all managers are assumed to be identical in terms of quality.The threat of a dismissal merely serves to ensure adequate effort by the incumbent CEO. In equilib-rium, all CEOs provide the same effort and low performance arises just by chance. In case of poorperformance, the board of directors will fire a CEO just to maintain the threat of dismissal therebycreating the incentive to supply the optimal level of effort. Since in this model the poor performanceleading to the dismissal of a CEO is simply the result of luck and not poor managerial quality orlack of effort, the fired CEO can be viewed as a scapegoat. Also in this case, it is conceivable that

investors will interpret the dismissal of the CEO as a positive signal that testifies the responsibilityof the board in providing adequate effort incentives for CEOs.

Since the majority of empirical studies (cf. Table 1, column 9) associates a positive stock-pricereaction with the announcement of a CEO dismissal, thus providing supportive evidence for thetheoretical predictions, we formulate our second hypothesis as follows.

Hypothesis 2: The announcement of a forced CEO turnover yields positive abnormalreturns.

In case of a voluntary retirement, a responsible board of directors should appoint the manager

with the highest quality as CEO successor. However, this does not imply a specific quality differ-ential of the new CEO over the departing one. Further, voluntary departures due to the age ofthe CEO can be anticipated, which should suggest small price reactions. Negative returns couldoccur if the departure of the incumbent CEO is associated with a loss of valuable company-specifichuman capital or if the voluntary decision to leave the company is motivated by superior (negative)information of the departing CEO about the future development of the company. The empirical lit-erature offers a very mixed picture concerning the impact of voluntary CEO turnovers on abnormalreturns. While the majority of papers do not find significant abnormal returns (cf. Table 1, column10), Adams and Mansi (2009) and Hillier and McColgan (2005) report positive and significant ARsand (Neumann and Voetmann, 2005) negative and significant ARs. While in view of the theory

and previous empirical evidence, we expect voluntary retirements to cause smaller stock-price reac-tions than forced departures, we do not see compelling theoretical arguments to formulate a specifichypothesis.

2.3 Performance

Previous studies show an inverse relation between the stock performance and the probability ofa CEO turnover (e.g. Warner, Watts, and Wruck, 1988; Weisbach, 1988, among others). In this

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paper, we investigate the impact of the companys prior performance under the departing CEO(which can be seen as a proxy for his/her skills) on the abnormal stock returns in the surroundingsof the announcement of the CEO departure. When an underperforming CEO leaves the company,

we expect shareholders to benefit from the turnover.

Hypothesis 3: In case of prior underperformance of the stock relative to the marketindex, the announcement of a CEO turnover yields positive abnormal returns.

In case of prior overperformance, the turnover announcement is expected to cause negativeabnormal returns because the value of all future projects should be reduced to take into accountthe departure of a talented and successful CEO.

Hypothesis 4: In case of prior overperformance of the stock relative to the market index,the announcement of a CEO turnover yields negative abnormal returns.

2.4 Combinations of Turnover Characteristics

In this paper, we consider the three above variables (successor type, departure type, and com-panys prior relative stock performance) not only as stand-alone characteristics but also in con-nection with each other. More precisely, we investigate whether the interaction of those variables

conveys additional valuation-relevant information. While we refrain from discussing all possiblecombinations to be constructed by pairs and triples of those variables, some considerations regard-ing specific intersections are useful.

First, based on the previously mentioned theoretical considerations and the available empiricalfindings, the combination of forced turnovers with outside successions - the two characteristics thatin previous studies are found to deliver the highest abnormal returns - is expected to yield positiveabnormal returns.

Hypothesis 5: The announcement of a forced turnover with an outside successor yieldspositive abnormal returns.

Second, we challenge the notion that forced turnovers per se represent positive news to share-holders on average. We believe that forced turnovers have to be examined in connection with theskills of the departing CEO (proxied by the companys relative stock performance). In particular,we expect to observe positive abnormal returns for forced turnovers of underperforming managersand negative abnormal returns for forced departures of overperforming managers. While the firstevent reflects a wise decision by the companys board of directors, the latter does not.

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Hypothesis 6: The announcement of a forced turnover of an underperforming manageryields positive abnormal returns.

Hypothesis 7: The announcement of a forced turnover of an overperforming manageryields negative abnormal returns.

2.5 Trading Volume

Analyzing trading volumes in addition to abnormal returns can likely add an important dimen-sion to the analysis of CEO turnovers. As noted by Beaver (1968), trading volume of a given securityindicates a lack of consensus among investors regarding the price of that security. Along these lines

Holthausen and Verrecchia (1990) conclude: If one defines information content as the ability of aninformation signal to alter investors beliefs, evidence on volume reactions is as relevant for assess-ing information content as evidence on unexpected price changes. To derive testable hypothesesrelated to the trading volume, we follow Kim and Verrecchia (1991b). In their theoretical study7

on the relation between abnormal returns and abnormal trading volumes after the release of publicinformation, they argue as follows: Volume reflects the sum of differences in traders reaction; thechange in price measures only the average reaction. As a result, volume is proportional to both theabsolute price change and the measure of differential precision. The first part of their conclusionmotivates us to state the following hypothesis:

Hypothesis 8: The higher the absolute abnormal returns caused by the announcementof a CEO turnover, the higher the abnormal trading volume.

Further, we conjecture that out of the different subsamples of CEO turnovers, the one thatconveys the highest degree of surprise will likely relate to forced turnovers of overperforming CEOs.

Hypothesis 9: The announcement of a forced turnover of an overperforming managertriggers the highest abnormal trading volume.

2.6 Operating Performance

If we assume markets to be efficient, the abnormal returns in the surrounding of a CEO-turnoverannouncement date reflect investors perceptions about fundamental changes in the value of thecompany. From finance 101, we know that the fundamental value of a company results from thesum of all the expected future free-cash flows discounted by the appropriate risk-adjusted interest

7Other papers that address in a theoretical framework the trading volume around news releases include Holthausenand Verrecchia (1990), Kim and Verrecchia (1991a, 1994), and Demski and Feltham (1994).

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rate. Thus, changes in the value of a company either reflect changes in the relevant discount rateor changes in the expected future cash flows (or both). If we rule out that a CEO turnover has animpact on the relevant discount rate,8 the different company valuation before and after the CEO-

turnover announcement will solely reflect changes in the expected cash flows and thus in the futureoperating performance of a company. Based on this line of reasoning, we formulate the followinghypothesis.

Hypothesis 10: The higher the abnormal returns caused by the announcement of a CEOturnover, the greater the increase in the future operating performance.

3 Data

3.1 Sample Construction

The data investigated in this paper comprises CEO turnovers of companies in the Swiss Perfor-mance Index (SPI) between 1998 and June 2009. The sample is hand-collected and initially consistsof 347 turnovers at 184 companies.

To cover all CEO turnovers, we apply the following procedure. First, the complete list of CEOchanges is obtained by collecting the annual reports of all companies included in the SPI sinceJanuary 1998. Second, to verify the event and obtain the exact CEO-turnover announcement date,the following sources are screened: (i) ad-hoc disclosures at the SIX Swiss Exchange, (ii) articles inleading Swiss financial and business newspapers (in particular, NZZ, Finanz und Wirtschaft,and Handelszeitung), (iii) company-specific news provided by Bloomberg, (iv) company Internetsites, and (v) selected Internet news sites.9

To be included in the final sample, we require CEO-turnover events to cumulatively satisfy thefollowing criteria: (i) The date of the announcement, i.e. the first day investors can trade on theCEO-turnover information, has to be identifiable (this also includes the information on whetherthe announcement was made before or after the closing of the market); (ii) The relevant detailsregarding the departing and the incoming CEO (age, succession type, and successor origin) have tobe known; (iii) There must be no confounding events, such as earnings or dividend announcementsor mergers and acquisitions, in a three-day time period around the turnover announcement; (iv)

The CEO turnover may not be directly related to the takeover of the company; (v) Furthermore,there has to be a sufficiently long stock-price history before the CEO-turnover announcement dateand the stock must be traded at least at 100 days (40%) in the estimation period to guarantee areasonably accurate estimation of the market model.

8This would be the case if the average successor reduces the systematic risk of a company or has an impact on themarket premium. An analysis of betas before and after the event date rules out the first hypothesis and the latterappears highly implausible.

9Internet sites include www.news.ch, www.swissinfo.ch, and http://moneycab.presscab.com.

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The number of events that had to be excluded due to the criteria (i) to (v) are reported in Table 2.

[Table 2 about here]

3.2 Explanatory Variables

For all CEO-turnover events, we gather detailed information regarding the company, the de-parting CEO, the new CEO, and the turnover characteristics. The main explanatory variables inthis study are the successor origin (inside vs. outside successions), the departure type (forced vs.voluntary departures), and the prior performance relative to a broad stock-market index.

In the related literature, the classification of the successor origin is measured by applying twoalternative rules. According to the first rule, the new CEO is classified as an outsider if the ap-pointment as CEO occurs on the same date as he/she joined the company; All other successors areclassified as insiders. According to the second rule, the new CEO is considered as an outsider ifhe/she has a working history in the relevant company of less than a year (see e.g. Parrino, 1997). Inthis paper, successors are classified as insiders or outsiders according to the former rule. However,applying the latter method does not qualitatively alter the major findings of the paper. In oursample, 75 CEO turnovers (36% of the total sample) are classified as outside successions and 133turnovers (64% of the total sample) are classified as inside successions.

The division into forced and voluntary departures is carried out following the methodology of De-nis and Denis (1995). Based on the information provided by diverse media reports, such as leadingSwiss financial and business newspapers, ad-hoc news, and company statements, a CEO turnoveris classified as forced if it is accompanied by an internal conflict with the Board. In those cases inwhich the turnover cannot be directly assigned to the sample of forced or voluntary turnovers onthe basis of the available data, we apply the following decision scheme: If the departing CEO is notover 64 years old and the new appointed CEO is an outsider, the CEO turnover is assigned to thesubsample of forced turnovers. By applying this procedure, the sample of forced turnovers consistsof 60 events (29%) and the sample of voluntary turnovers includes 148 events (71%).

The companies relative stock performance is calculated against the Swiss Performance Indexover the same time period that is used to estimate the market model, i.e. over a 250 trading-dayperiod from day

260 to day

11 prior to the CEO-turnover announcement. Depending on the sign

of the prior relative performance, the event is assigned either to the over- or the underperformingsubsample: 118 turnovers (57%) are preceded by prior underperformance and 90 turnovers (43%)prior overperformance.

Table 3 provides a breakdown of the final sample by year and turnover characteristics. Whilethere seem to be an overall increase in the total number of CEO turnovers over the years, thisdevelopment is far from being steady and smooth.


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Figure 1 is a Venn diagram that splits the sample according to the main CEO-turnover char-acteristics (together with their intersections): outside successions, forced departures, and turnoversof underperforming managers. It is worth noting that the percentages of outside successions and

forced departures are, with 36% and 29% of the sample respectively, higher than those reported inearlier studies. For instance, Adams and Mansi (2009) report for the period between 1990 and 200029.4% of outside replacements and 19.6% of forced turnovers; Parrino (1997) classifies only 15%of all turnovers in his sample as outside successions and only 13% as forced departures; Finally,Clayton, Hartzell, and Rosenberg (2005), examining the impact of CEO turnovers on stock-pricevolatility, classify 20.6% as outside successions and 17.4% as forced departures.

[Figure 1 about here]

3.3 Control Variables

Abnormal stock returns induced by a turnover announcement might be influenced by a numberof variables besides the origin of the new CEO, the performance of the departing CEO, and theturnover type. For instance, a blue-chip stock might react stronger to a CEO-turnover announce-ment because investors follow the company news more attentively or the media offer a strongercoverage. Conversely, small companies might get less attention because they are often owned byfamilies, weaker media and analysts coverage or are simply too risky for investors to take actionafter a turnover announcement. To account for the existence of such effects related to the size of acompany, we include as a control variable in our regressions the logarithm of companys total assets(SIZE) which we obtain from Datastream.

Other variables that will likely play an important role in determining the magnitude of thestock-price impact are the age of the departing and the appointed CEO. If the incumbent CEOis close to retirement age, his/her departure might be anticipated and thus lack a strong surpriseeffect. In this case, the age of the departing CEO will have a dampening effect on the news impact.The appointment of a young CEO which is relatively unknown and potentially less experiencedcould also have a material effect on the stock-price reaction. To control for age-related effects, weinclude in the cross-sectional regressions the variables AGEDEP and AGEINC, i.e. the logarithmof age of the departing and incoming CEO, respectively.

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4 Empirical Analysis

4.1 Abnormal Returns

In order to investigate the impact of CEO-turnover announcements on stock prices, we applystandard event-study methodology. As usual, the tests rely on the assumption of market efficiency,i.e. that stock prices reflects all relevant information and thus quickly incorporate the effect relatedto CEO-turnover news. Consequently, we choose a short-term event window to measure the impacton stock prices. Following Brown and Warner (1985) and McWilliams and Siegel (1997) this eventwindow should be long enough to capture the impact of the event, but short enough to minimize theinfluence of confounding effects unrelated to the event. Consequently, we choose to employ differentevent windows ranging from one to five days. To account for potential information leakage, we let

some event windows start before the CEO-turnover announcement date.In accordance with the bulk of the literature on short-term event studies, we calculate abnormal

stock returns in the event window by subtracting from realized stock returns the normal returnsobtained by the market model. The parameters of the market model are estimated over a 250trading-day period ending 11 days before the CEO-turnover announcement date. To make surethat the findings of the paper are not driven by inaccurate parameter estimates, the estimation ofthe market model is performed both by simple OLS and robust linear regressions (Huber, 1973).The latter approach is an iteratively re-weighted least squares algorithm (Holland and Welsch,1977). In particular, in each iteration the weights are calculated by applying the bisquare functionto the residuals from the previous iteration. Since the results of the two estimation procedures donot lead to qualitatively different results, for the sake of brevity, only the robust regression resultsare reported in the paper. In addition to measuring the magnitude of mean and median abnormalreturns, it is critical to determine their statistical significance. For this purpose we employ theStandardized Cross-Sectional test by Boehmer, Musumeci, and Poulsen (1991) (henceforth simplydenoted by Boehmer test). In addition, we also consider the Wilcoxon Signed Rank test by Wilcoxon(1945) (henceforth simply denoted by Wilcoxon test) which is a non-parametric test and thus doesnot rely on specific assumptions about the distribution of stock returns.

We start the empirical investigation of this paper by measuring abnormal returns (ARs) forthe whole sample and for selected subsamples defined by the key turnover characteristics: successororigin (insider or outsider), departure type (forced or voluntary), and CEOs prior performance (un-derperformance or overperformance). Table 4 reports both average and median abnormal returns

together with test statistics obtained by the Boehmer, Musumeci, and Poulsen (1991) test and thenon-parametric Wilcoxon Signed Rank test by Wilcoxon (1945).10

When considering the results related to the whole sample (Panel A), we observe that for allevent windows considered, the average and median abnormal returns are positive (the only excep-tion is the median AR two days before the event). In the period [-2 0] both the Boehmer and the

10While standardized residuals from the market model - and not abnormal returns - are used in the calculationof the test statistics of Boehmer, Musumeci, and Poulsen (1991), in Table 4 we still report mean abnormal returnsbecause of their easier interpretation.

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Wilcoxon test detect significant ARs at the 10% level with a mean ARs of +0.74% and a medianARs of +0.32%. The period [-1 1] is significant at the 5% level for the Boehmer test with a mean(median) AR of 0.65% (+0.35%). The mean AR of +0.42% on the announcement day is significant

at the 10% level for the Boehmer test. Overall, CEO turnovers seem to convey good news forinvestors on average. This result finds grafical support in the development of the cumulative ARsdisplayed in Figure 2 (a).

If we consider the subsample of turnovers with outside successors (cf. Table 4, Panel B), abnor-mal returns become larger and more significant. For instance, mean ARs for the periods [-2 0], [-10], and [-1 1] are all significant at the 5% level with values of +1.85%, +1.41% and +1.58%, respec-tively. By comparing in Figure 2 (b) the ARs of outside successions to the ARs of inside successionsit becomes evident that the former convey positive news about the value of the company whereasthe latter do not.11 Furthermore, the difference in the cumulated AR of 1.96% for the two samplesover the window [-3 0] is significant at the 10% level (see Table 5). The findings validate Hypothesis

1 of this paper and conform to the theory that an outside candidate for the CEO position mustoffer distinguishable better qualities than an inside candidate to be appointed CEO.

According to Hypothesis 2, we expect the stock price to rise following the decision to fire aCEO. Also this hypothesis finds support in the event-study results reported in Table 4, Panel Cand depicted in the ARs evolution in Figure 2 (c). The mean AR for the subsample of forcedturnovers are significant at the announcement day and for all event windows longer than one day.We observe that the mean abnormal return is largest for the window [-2 0] with a value of +2.74%.By comparing in Figure 2 (c) the development of ARs for forced vs. voluntary turnovers one canvisually capture the striking difference in the pattern of the two lines: increasing in correspondenceof forced turnovers and very close to zero for unforced turnovers. For all tested event windows,

ARs following unforced turnovers are found to be insignificant at all conventional confidence levels(results reported in Table B.1 in the Appendix). Table 5 shows that the difference in means of3.12% between forced and voluntary turnover over the event window [-3 0] is significant at the 5%level.

The impact of the departure of underperforming CEOs is shown in Table 4, Panel D. Strikingly,all the mean ARs for the event windows [-2 0], [-1 0], [-1 1], and 0 are statistically significant atthe 1% level with values as high as +1.94%, +1.56%, +1.62%, and +1.25%, respectively. A verysimilar picture arises when focusing on median ARs and considering the Wilcoxon test. Accordingly,Hypothesis 3 stating that the information of the departure of underperforming CEOs will triggersignificantly positive abnormal returns finds strong empirical support in our sample. Conversely,ARs related to departing CEOs with positive prior performance are found to be negative but in-significant (results reported in Table B.1 in the Appendix). Furthermore, we observe in Table 5 thatthe difference in means of 2.96% over the window [-3 0] is significant at the 1% level. Consequently,also Hypothesis 4 is confirmed in our sample. A direct comparison of the impact of the turnoverof under- and overperforming CEOs is depicted in Figure 2 (d) with a clear upward trend for theformer and a downward trend for the latter.

The results obtained for outside successions and forced turnovers are in line with the findingsreported by other authors in in the related literature (cf. Table 1). For both subsamples, positive

11As reported in Table B.1 in the Appendix, ARs of inside successions are very close to zero and insignificant.

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and significant abnormal returns could be detected. Conversely, voluntary turnovers and insidesuccessions induce minor and insignificant stock-price reactions. Not reported in previous work,the impact of a CEO turnover on stock returns depends on the performance of the departing CEO.

When underpeforming (overperforming) CEOs leave the company, the stock experiences a signifi-cantly positive (negative) price shock.

The results for the samples restricted to one turnover characteristic are displayed in a compactform in Panel A of Table 7, where the ranking of ARs are based on the return period [-3 0]. Weobserve that forced turnovers, underperforming CEOs, and outside successors generate the largestand most significant ARs with respective values of +2.94%, +2.00%, and +1.98%. Conversely, thesmallest AR is associated with overperforming CEOs. It amounts to 0.96% but is not statisticallysignificant.

At this point, it is natural to extend the current analysis and define further subsamples bycombining different turnover characteristics. The goal of this exercise is to identify certain CEO-

turnover constellations that convey either particularly positive or negative news to shareholders. Ina first step we calculate ARs for all 12

32

(2 2)

possible subsamples (by using a [-3 0] event

window) that can be constructed by pairwise interrelating the three selection criteria (turnover type,successor origin, and prior CEO performance) and rank them accordingly (cf. Panel B of Table7). Some results deserve our attention. First, the subsamples obtained by the pairwise intersectionof Outsider, Forced, and Underperformance generate the largest ARs: +6.71% (t-value = 2.68),+5.73% (t-value = 3.74), and +3.84% (t-value = 2.90) for Outsider & Forced; Forced & Under-performance; and Outsider & Underperformance, respectively. Even when considering alternativeevent windows (cf. Table 4, Panels E and H) those pairs of characteristics generate the strongest(and most significant) price reactions. According to Hypothesis 5 of this paper, the combination

Outsider & Forced should generate positive ARs. Since this subsample is associated with the largestand most significant ARs, the data support Hypothesis 5. Second, it is of special interest to observethat forced turnovers rank both 2nd and 12th (last) in this list. In particular, when consideringforced turnovers of underperforming CEOs a mean AR as large as +5.73% is achieved (associatedwith a t-value of 3.74). Conversely, when forced turnovers of overperforming CEOs are considered,ARs become negative! This finding is depicted in Figure 2 (f) and confirmed by alternative eventwindows in Table 4, Panels G and H (although the negative ARs associated with forced turnoversof overperforming CEOs are not statistically significant at low confidence levels). However, the re-ported results are further supported by the large and at the 1% level significant difference of 7 .97%in the mean AR over the window [-3 0] reported in Table 6. This finding suggests that shareholders

assess the quality of the firing decision by the board of directors by considering the quality andskills of the departing CEO. If the relative stock performance under the departing CEO is positive,shareholders seem to disfavour the decision and adjust downward their estimates about the valueof the company. The double edged impact of forced turnovers is also apparent in Table 6, wherewe observe on the one hand mostly significant (9 out of 11 comparisons) negative differences inmeans of the other subsamples against the sample of forced turnovers of underperforming managers(FOR*UND) and, on the other hand exclusively positive differences against the sample of forcedturnovers of overperforming managers (FOR*OVE), whereof four are significant at least at the 10%level. The sole exception of a larger cumulated AR than the one calculated for forced turnovers

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of underperforming managers is the sample of outside successors combined with a forced turnover.The just described empirical results seem to support Hypothesis 6 and Hypothesis 7 of this paper.Finally, it is interesting to note that outside CEOs trigger positive abnormal returns only if the

previous CEO was fired (Figure 2 (e)), not if he/she voluntary left the company.If we define subsamples based on the interaction of all three turnover characteristics, we obtain

a total of eight subsamples (23). Table 7, Panel C ranks those subsamples by their ARs in the eventwindow [-3 0]. Not all too surprisingly, the subsample with the most significant ARs (Boehmert-value = 4.29, Wilcoxon z-value = 3.05) is characterized by forced departures of underperformingCEOs substituted by firm outsiders. The mean (median) ARs over the window [-3 0] of the 14events falling in this category amounts to +10.61% (+9.41%). The most negative AR (2.82%)corresponds to the intersection of forced departures with inside successions at overperforming com-panies. The columns R1, R2, and R3 in Table 7, Panel C evidence an interesting pattern which canbe interpreted as follows. First, the prior performance (R1) is the single most important variable in

deciding whether a turnover represents good or bad news. Turnovers at underperforming compa-nies are always associated with positive ARs, while turnovers at overperforming companies triggernegative ARs. Second, column R2 impressively shows the amplifying effect of forced turnovers incombination with under-, and overperforming companies. Third, in column R3 subsamples withoutside successors rank above the corresponding subsamples with inside successors. Thus, whileoutside successors are ceteris paribus viewed more positively than inside successors, the other vari-ables (departure type and prior performance) seem to be more relevant in judging the value of aCEO-turnover event.




4.2 Cross-Sectional Regressions

In this subsection we evaluate the cross-sectional information content of CEO turnovers by

regressing ARs against a set of explanatory variables. More precisely, we regress ARs in the eventwindow [-2 0] on an outside-succession dummy (OUT) a forced-turnover dummy (FOR), priorperformance under the departing CEO (OVE)12, size of the company measured as the logarithm oftotal assets (SIZE), the age of the departing CEO (AGEDEP), as well as the age of the incomingCEO (AGEINC). The regressions results are reported in Table 8. Regressions 1 to 3 are univariateregressions of ARs against a single turnover characteristic and thus simply replicate some of theresults obtained by analyzing ARs of selected subsamples. For instance, the sum of the constant,

12The variable PERF denotes both a continuous variable and a dummy variable, taking on the value of one if thecompany experienced prior relative overperformance and zero otherwise.

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0.0011, and the coefficient of the variable OUT, 0.0173, in Table 8 is equivalent (except for roundingerrors) to the mean [0 2]-AR for the subsample of turnovers with outside successors, 0.0185, in Table4, Panel B. Nonetheless, performing cross-sectional regressions offers two decisive advantages: First,

it allows to measure the impact of continuous variables (and not only dummy variables); Second,it allows to combine the effect of multiple variables on ARs and to isolate the impact of each them.Not surprisingly, the coefficients related to outside successions (OUT), forced departure (FOR), andoverperformance (OVE) are all found to be significant in the univariate regressions. The size ofthe company has a slightly negative but insignificant effect on ARs. The coefficient related to theage of the departing manager (AGEDEP) is negative and weakly significant and the one relatedto the age of the incoming CEO (AGEINC) is positive but not significant. Importantly, in themultivariate regression with all six explanatory variables (Table 8, Regression 7) the coefficientsand significances of the variables OUT, FOR, and PERF experience remarkably small changes. Inthe multivariate regression, almost six percent of the cross-sectional variance can be traced back to

the six explanatory variables.


In a next step, we investigate whether these results are consistent over different return periods.For that purpose, we regress in Table 9 ARs of six event windows against all variables found to besignificant in Regression 7 of Table 8. By looking at the results, it stands out that the signs of thecoefficients remain unchanged and the significances are reasonably consistent across the performedregressions. The variables OUT, FOR, and OVE are always significant, except for OUT in theperiods [-1 1] and [-2 1]. The coefficient of SIZE is always negative but in solely two cases ([-3 1]and [-1 1]) a weak significance at the 10% level is detected. The results from Table 9 reinforce ourview that the successor origin, the turnover type, and the prior CEO performances are key variablesin explaining cross-sectional variations in abnormal returns and determining whether a turnover isgood news or bad news to shareholders.


Motivated by the previous results about the impact of forced turnovers in dependence of theCEOs prior performance, we add an additional dummy variable, FOROVE, to capture thisinteraction. As can be seen in Panel A of Table 10, for both event windows considered FOR OVEis significant at the 1% level and the adj. R2 rise to 0.1363 for the [-3 0] event window and 0.0959for the [-2 0] event window. The results reported in Panel B of Table 10 are obtained by definingOVE as the realized relative performance during the estimation period (and avoid to transform itinto a dummy variable). Also under this specification FOROVE remains significantly negative atthe 1% level and the adj. R2 increases to 0.2184 for the period [-3 0] and 0.2114 for the period [-20].


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It is of particular interest to examine the impact on shareholder value of those turnovers inwhich the CEOs is forced to leave the company by a deliberate decision of the board of directors.Table 11 presents the results of cross-sectional regressions on the subsample of forced turnovers.

In all regressions, the coefficients of the variables OUT and OVE have the expected sign and arehighly significant. In particular, knowing that the performance of a fired CEO was positive inthe year preceding the dismissal induces an average drop in shareholder value of approximately0.8%. The results of Table 11 emphasize once more the importance of the prior performance ofthe departing CEO in assesing the news of a firing. Conversely, they challenge the oversimplifyingview that the dismissal of a CEO represents per se good news. Similarly, the results suggest thatshareholders systematically mistrust the board of directors to act in their best interest when theyfire an outperforming CEO.


4.3 Robustness

In this subsection we intend to check the robustness of our results with respect to (i) econometrictest specifications and (ii) time subperiods. To further ensure the robustness of the findings, we re-examine the event-study results by implementing, in addition to the already employed StandardizedCross-Sectional test by Boehmer, Musumeci, and Poulsen (1991) and Wilcoxon Signed Rank testby Wilcoxon (1945), an additional battery of parametric and non-parametric event-study tests.The parametric methods include the Traditional test by Brown and Warner (1980), the Portfolio

test by Brown and Warner (1980), a test that accounts for first-order autocorrelation in abnormalstock returns by Ruback (1982), and the Standardized-Residual test by Patell (1976). The non-parametric test statistics have the advantage of avoiding to assume a specific distribution for theabnormal returns. The non-parametric test employed in this study include a Bootstrap test, theCorrado Rank test by Corrado (1989), and the Generalized Rank test by Kolari and Pynnonen(2008). Table 12 provide an overview on all test used in this paper and Table 13 illustrates thecomputation of the corresponding test statistics.



One major worry in event studies concerns the risk of detecting spurious abnormal returns. Ineconometrics, the risk of erroneously rejecting the null hypothesis is called error of type I. Theprobability of incurring into this error should be determined by the confidence level, . However,misspecified test statistics may lead to higher or lower rejection rates of true null hypotheses. To shedlight on this issue and gain insights about the reliability of the statistical inferences in this paper,we perform empirical experiments that evaluate the performance of three very different event-study

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tests: the Bootstrap method, the Standardized Cross-Sectional test by Boehmer, Musumeci, andPoulsen (1991), and the Wilcoxon Signed Rank test by Wilcoxon (1945). The historical-simulationexperiment uses the daily stock-price histories of 160 SPI companies in the time period from January

1990 to June 2009. It consists of two steps. In the first one, we generate 250 random samplesofN pseudo or fake CEO turnovers, each one representing a possible empirical sample of CEOturnovers. Clearly, since the turnovers did not actually take place, we know that the null hypothesisof zero abnormal returns is indeed true. Consequently, we expect the event-study tests to rejectthe null hypothesis with frequency . Each of the 250 samples is constructed as follows: First, werandomly draw with replacement N (N {10;20;50;100;200}) securities from the overall sampleof 160 securities. Second, each sampled security gets a randomly drawn pseudo-event day which alsodefines both the estimation and event windows. In particular, in accordance with the event-studydesign employed in the paper, the days 260 till day 11 refer to the estimation window with dayzero referring to the event date.13 In a second step, we conduct for each of the 250 pseudo-turnover

samples a complete event-study test, i.e. we (i) estimate the market model by OLS, (ii) calculateabnormal returns in the event window, and (iii) determine the rejection of the null hypothesis basedon a particular test and confidence level, . The rejection rates reported in Table 16 represent theaverage number of samples for which abnormal returns are found to be significantly different fromzero divided by the sample size (N). Since for all three models the test statistics reject the nullhypothesis at approximately the significance levels, the Type I error rate is acceptable and the testsdo not seem prone to detect spurious abnormal returns. Interestingly, the rather involved Bootstrapevent-study test does not seem to deliver better results than the other two test statistics.


To asses the power of the tests, i.e. the capability of rejecting falls null hypotheses, we repeatthe above simulation experiment by artificially introducing in the event window of each pseudoCEO turnover abnormal returns in the range of 3% to +3%. In Figure 3 the empirical rejectionrates are plotted against the level of abnormal returns used to contaminate the stock-price returnsin the event window. As expected, the larger the absolute value of the contamination, the higherthe rejection rates. For sufficiently large abnormal returns the probability of rejecting the null ofzero abnormal returns reaches 100%. Figures 3 (a)-(d) differ with respect to the size of the CEO-turnover sample and highlight the fact that the sample size is critical for obtaining a high testpower. By comparing the shapes of the rejection curves, the bootstrap test appears to be slightlyoutperformed by the other two test statistics.


13To estimate the market model for the event study, we require the companies to be a member of the SwissPerformance Index during all 261 days prior to the randomly drawn event date. If this condition is not fulfilled anew pseudo event day is randomly drawn for this security. This cycle continues until a complete history of securityreturns is generated.

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It is now interesting to investigate the robustness of the basic results on CEO-turnover subsam-ples by employing all event-study tests previously introduced. Table 14 reports t-values associatedwith the different tests, event windows, and CEO-turnover subsamples. It is reassuring to observe

that the significant results obtained earlier for outside successions, forced departures, and priorunderperformance are strongly supported by the additional test methods. Furthermore, we obtainsignificant negative ARs for the subsample of overperforming companies for five out of six parametrictest methods (Table 14, Panel E). Similar conclusions can be drawn for the subsample constructedby combining outside successions with forced and voluntary departures as well as forced departureswith the performance of the departing CEO. In particular, we emphasize that the finding of signif-icant negative abnormal returns for forced turnovers at overperforming companies (Hypothesis 7)and significant positive returns at underperforming companies (Hypothesis 6) is robust with respectto alternative test specifications.


Finally, for testing robustness over time, we divide the sample into two subperiods of equallength (1998-2003 and 2004-2009) and perform cross-sectional regressions on both set of abnormalreturns. It is reassuring to observe that regardless of the time subsamples and event windows allthe coefficients in Table 15 have the expected sign. Having said that, the results related to the sub-period 1998-2003 show a higher number of significant coefficients and are characterized by higherR2 and thus a better fit. However, for the event window [-3 0], even in the latter period the dummy

variables FOR and FOROVE are statistically significant at the 5% confidence level. Therefore,the dependency of the announcement impact of forced turnovers on prior performance is a featurethat is present in both subperiods.


4.4 Trading Volume

As mentioned earlier in the paper, trading volume could convey even more information aboutthe relevance of a CEO turnover to investors than abnormal returns. For this reason, we conductanother event-study based on the stock trading volume (TV), i.e. the number of traded shares(data item Turnover by Volume in Datastream). To provide an immediate interpretation of theimpact of CEO-turnover news on the trading volume, we first consider the following standardizedmeasure of abnormal trading volume:

ST VAit =TVitTVNit

1, (1)

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where TVit is the realized trading volume of company i at time t and TVN

i is the normal, i.e.the expected, trading volume which is measured in accordance with a constant-mean model asthe average trading volume between day

60 and day

11: TVNi = 1/50

11t=60 TVit. ST V is

particularly easy to interpret because it simply represents the percentage increase in trading volumerelative to a 50-day benchmark period before the event date.

Figure 4 and Figure 5 depict the daily average and cumulative average standardized abnormaltrading volumes. All graphs show a distinct increase of the average ST VA on the day of theCEO turnover announcement and the following one. In Figure 4 (a), we see that for the totalsample the average trading volume on the event day is +129.97% larger than the average tradingvolume in the estimation period. By examining Figures 4 (b)-(f), it is apparent that the changes intrading volumes strongly depend on the characteristics of the turnover event. For instance, forceddepartures (graph (c)) have a much larger impact on trading volume than voluntary departures(+196.37% vs. +103.04%). Surprisingly, the largest average ST VA is caused by forced turnovers

at underperforming companies (+259.64%) and not - as conjectured in Hypothesis 9 of this paper- by forced turnovers of overperforming CEOs (+78.87%).



By following the previous literature on trading-volumes in correspondence of news releases(Ajinkya and Jain, 1989; Cready and Ramanan, 1991; Campbell and Wasley, 1996), we perform

an event study based on a constant-mean model applied to the logarithm of the trading volume(LTV = ln(TV)). As mentioned in the above articles, working with log-transformed trading vol-umes is preferable because its empirical distribution is closer to the normal and allows for moreaccurate statistical inferences.14 Similar to abnormal stock returns, abnormal trading volumes ofcompany i on day t, LTVAit , must be calculated as the difference between realized and normalLTV.In accordance with the constant-mean model, the normal daily LTV in the event window is cal-culated as the average LTV from day 60 to day 11 prior to the turnover announcement date:LTVNi = 1/50

11t=60 LTVit.

15 Finally, abnormal LTV for each event are obtained by subtractingnormal LTVs from the realized ones: LTVAit = LTVit LTVNit .

Table 17 presents the test statistics of the event study. In the total sample (Panel A) the increase

in trading volume before the CEO-turnover announcement indicates the existence of informationleakage. Significant abnormal trading volumes are detected for the periods [-2 2], [1 3], as wellas day 0 and day +1. The trading-volume effect is particularly pronounced for the subsamples of

14As an alternative trading-volume metrics, we also employ the relative trading volume (RTV), defined as the ratioof the logarithm of traded shares and shares outstanding (data item Number of Shares in Issue in Datastream). Ina formula: RTV = ln ((100 V/NOSH) + c), where TV denotes the number of traded shares, NOSH is the numberof outstanding shares, and c = 0.000255 denotes a constant which precludes taking a logarithm of zero when noshares are traded (Cready and Ramanan, 1991). In general, the results obtained with this alternative methodologydo not materially differ from those described and reported in the paper.

15Days in which no trading was reported are not considered when calculating this average.

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forced departures in Table 17, Panel C (similar to Cools and van Praag (2007)), outside successorswith forced departures (Panel E), and forced turnovers of underperforming managers (Panel H).


In Table B.2 of the Appendix we show that an increase in trading volume is also observed forinside successions, voluntary departures, and departures of overperforming managers. The resultsof those subsamples show how trading volume can capture the trading relevance of news in cases inwhich we do not observe significant abnormal returns (cf. Table B.1 in the Appendix).

By regressing in Table 18 the abnormal trading volume on turnover characteristics only thedeparture type (forced vs. voluntary) is found to be significant.


To address Hypothesis 8 of this paper, we regress absolute abnormal returns against abnormaltrading volumes, LTVA. For all event windows considered, we find a highly significant slope coef-ficients (cf. Table 19). The strongest relation refers to the event day with a t-value of 6.4273 andan adj. R2 of 0.1589. These results support the hypothesis that belief updates by investors, asmeasured by absolute price changes, generate trading.


4.5 Operating Performance

To round off the analysis on CEO turnovers we test whether they have a longer-term impacton the operating performance of a company. This longer-term effect is measured by the operatingreturn on asset (OROA). We calculate the operating return on total assets in period t, OROAt, asthe ratio of operating income (Datastream item 137) and book value of total assets (Datastreamitem 392). We do not consider the return on assets in the financial year of the CEO turnover becauseit is affected by both the old and the new CEO.16 Therefore, OROA0 indicates the operating return

on assets of the financial year ending before the CEO turnover and OROA+1 denotes the returncorresponding to the first full-time year under the lead of the new CEO. We follow the methodologyproposed by Barber and Lyon (1996) and calculate normal, or expected, operating performance,

16It is often argued that the departing CEO has incentives to artificially increase the reported earnings in a lastattempt to keep his/her position and that the newly appointed CEO has incentives to reduce reported earnings tocredit poor performance to the predecessors and augments the chance that subsequent good performance will beattributed to him/her. The second mentioned discretionary behavior that a new CEO has the incentive to decreaseearnings in the year of his appointment is known as taking a so-called earnings bath (Elliott and Shaw, 1988;DeAngelo, 1988; Murphy and Zimmerman, 1993; Pourciau, 1993; Wells, 2002).

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OROANit , as the sum of the lagged companys OROA, OROAi,t1, and the change in the median

industry OROA from year t 1 to year t, OROAIit (without considering company i). Thus, theabnormal operating performance, OROAA

it, accounts for industry effects and is calculated as

OROAAit = OROAit OROANit , with (2)OROANit = OROAi,t1 + OROA

Iit. (3)

The sample used in this analysis (N = 136) is smaller than the one used for the event studies onabnormal returns and trading volumes (N = 208) because we need three (two) years of accountingdata before (after) the financial year of the CEO turnover to perform the analysis and the lack ofdata for some companies restricts our sample. Again, year 0 and year +1 refer to the last full yearunder the departing CEO and the first full year under the new CEO, respectively.

Median OROAs for an industry are calculated starting from a sample of 246 companies in theSPI index (both present and past constituencies of the index). First, we consider all companiesin the same Sector 4 industry code of Datastream reporting in the same calendar year as thecompany of interest. If less than three companies with available data belong to the same Sector 4,we consider all companies which belong to the larger Sector 3 industry code of Datastream. Ifeven with this broader industry definition we cannot find at least three companies with availableOROAs, we employ the median change over all companies which report OROAs for the years t 1and t.

Figure 6 (a) depicts the abnormal OROAs in the financial years around the CEO-turnover an-

nouncement date. The inverted tent shape of the graph indicates that CEO turnovers are generallypreceded by deteriorating operating performance and followed by a steady increase in profitability.Hence, CEO turnovers seem to have an overall positive impact on the real operating performanceof a company. This pattern is more pronounced than in the earlier studies conducted by Denis andDenis (1995), Dedman and Lin (2002), and Huson, Malatesta, and Parrino (2004).17 The graphs inFigure 6 tend to mirror the results of the analysis on abnormal stock returns: The subsamples withthe more pronounced changes in OROAA coincide with the subsamples with the largest abnormalstock returns. Particularly large changes in abnormal operating performance are associated withoutside successions (Figure (b)), forced departures (Figure (c)), prior underperformance (Figure(d)), outside successions in connection with forced departures (Figure (e)), and the intersection

of forced turnovers with prior underperformance (Figure (f)). On the contrary, the subsamples ofvoluntary turnovers (Figure (c)), prior overperformance (Figure (d)), outside successions in com-bination with voluntary turnovers (Figure (e)), and forced turnovers with prior overperformance(Figure (f)) do not trigger large changes of the abnormal operating performance.


17Other studies (Dezso, 2007; Fisman, Khurana, and Rhodes-Kropf, 2005; Hillier and McColgan, 2005; Khurana,2001) that examine the impact of CEO turnovers on companies operating performance arrive to similar conclusions.

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Table 20 provides formal econometric tests about the significances of the abnormal OROA overspecified periods.18 Panel A of this table confirms that OROAA significantly worsen in the run-upto the CEO turnover. In the year following the CEO change, OROAAs tend to rise but are not

statistically different from zero. Only over a two-year period following the turnover, the positiveimpact on the operating performance kicks in and leads to high levels of statistical significance.Surprisingly, this operating-performance pattern holds for the majority of subsamples yielding de-creasing OROAAs prior the CEO-turnover year and increasing OROAAs after the turnover. Whenconsidering median changes, the subsamples in which CEO turnovers have a particularly strong andsignificant impact on OROAs are those related to outside successors (Panel B), forced departures(Panel D), prior stock underperformance (Panel F), and the intersection of forced departures withunderperformance (Panel K). For example, the subsample of forced departures yield a mean changein OROAA of +2.92% (t-value = 2.4106) and a median change in OROAA of +1.98% (z-value= 2.6375). In the subsample of forced departures with underperforming companies we measure a

mean change of +3.56% (t-value = 2.1730) and a median change of +2.61% (z-value = 2.2824).


To test whether different CEO-turnover characteristics have a significantly different impact onthe operating performance, we regress cross-sectional OROAA changes over the time period [1 2]on a set of explanatory variables. While most of the coefficients have the same sign as in thecross-sectional regressions based on abnormal returns (cf. Table 8), only the coefficients related tothe outsiders dummy (OUT) and the companys relative overperformance (OVE) are statistically

different from zero at the 10% confidence level.19


Finally, we are interested in finding out whether the stock price reaction in the surrounding of theannouncement date correlates with the future development of the companys operating performance(Hypothesis 10). For this purpose, we regress using robust linear regressions20 OROAA changes overthe period [0 2] (financial years) on the ARs from the period [-3 0] (trading days). Table 22, PanelA reports for the total sample a significant relation between ARs and OROAA changes with acoefficient of 0.1112 (t-value = 2.4758). This positive relation also holds for most subsamples (cf.

18The same analysis was repeated by employing OROA changes as a measure of abnormal operating performance,which implies that the normal OROA for the next year is proxied by the OROA from the previous year, hence wecalculate OROAAit = OROAit OROAi,t1. This alternative model specification did not qualitatively alter theresults reported in Table 20.

19When performing the same cross-sectional regressions based on a [0 2] event window, the significances of OVEand OUT vanish and SIZE becomes weakly significant. The latter result could reflect the higher degree of sluggishnessin the restructuring of larger companies.

20For the robust regression we apply the bisquare weighting function as before in Section 4.1 for estimating themarket model for the expected security returns.

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Table 22, Panel B). A particularly strong connection between ARs and OROAs can be observedfor the subsample of outside successors (= 0.3991, t-value = 3.88). Overall, it is reassuring (fromthe view point of market efficiency) that the information content of CEO turnovers appears to be

reflected both in the short-term stock-market reaction and in the long-term operating performanceof the company.


5 Summary and Conclusions

In this paper we investigate the information content of CEO turnovers in the Swiss stock mar-

ket by analyzing abnormal stock returns and trading volumes around the turnover announcementdate. The sample consists of 208 CEO turnovers between January 1998 and June 2009 in compa-nies belonging to the Swiss Performance Index. The results provide strong evidence that selectedcharacteristics of CEO turnovers are determinant in explaining the stock-market reaction.

The relative stock-price performance under the departing manager is found to be the singlemost important variable in assessing the shareholder-value content of a CEO-turnover. In line witheconomic intuition, the departure of outperforming (underperforming) managers represents bad(good) news. Outside successions and forced turnovers yield, in accordance with previous studies,significant positive abnormal returns. Most interestingly, while forced turnovers of managers withpoor prior performance trigger positive and significant abnormal returns, forced turnovers of out-

performing managers are associated with negative abnormal returns. Therefore, a forced turnoverdoes not - as often argued in the literature - per se constitute a positive signal to shareholders.On the contrary, shareholders seem to critically assess the quality of the boards firing decision byconsidering the skills of the departing manager as proxied by the prior relative stock performance.When an outperforming CEO is dismissed or forced to leave, shareholders seem to disesteem theboards decision. This finding is confirmed in multivariate cross-sectional regressions and is robustto time subperiods and alternative test statistics.

Trading volume is found to consistently increase for all types of CEO-turnovers. However, thesize of the impact crucially depends on the characteristics of the turnover event, with forced depar-tures causing the largest effect on trading-volume (+196.37%). Furthermore, in line with theoretical

models on news releases (e.g. Kim and Verrecchia, 1991b), we observe a statistically significant re-lation between absolute abnormal returns and abnormal trading volumes.By examining the long-term relation of CEO-turnovers and companies operating performance,

we report a significant deterioration of the operating performance in the forefront of the turnoverand a significant improvement afterward. The relation between abnormal stock returns aroundthe announcement day and subsequent changes in operating performance is positive and statisti-cally significant. This result indicates that the short-term investors reaction to a CEO-turnoverannouncement reflects on average the new long-term operating prospects of that company.

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