intra-industry effects of shareholder activism in … · 300-day period, the mean bhars are 16.68%...

Electronic copy available at: http://ssrn.com/abstract=1879170

BIDDING STRATEGIESSHAREHOLDER ACTIVISM

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Mark Mietzner/Denis Schweizer/Marcel Tyrell*

INTRA-INDUSTRY EFFECTS OF SHAREHOLDER ACTIVISM IN GERMANY – IS THERE A DIFFERENCE BETWEEN HEDGE FUND AND PRIVATE EQUITY INVESTMENTS?**

ABSTRACT

We investigate the valuation effects of industry rivals on German firms targeted by hedge funds and private equity investors. We argue that both types of investors differ from other blockholders due to their strong motivation and ability to actively engage and monitor. We find that the announcement of a change in ownership structure gen-erates statistically significant short- and long-term intra-industry effects for rivals to the respective private equity and hedge fund targets. However, these effects differ mark-edly between hedge fund investments and private equity investments. We conclude that hedge funds are more aggressive than private equity investors in implementing a shareholder orientation.

JEL-Classification: G14, G32, G34.

Keywords: Corporate Governance; Hedge Fund; Information Signaling; Intra-Industry Effects; Private Equity; Rivals; Shareholder Activism.

* Mark Mietzner, Assistant Professor of Alternative Investments and Corporate Governance, Zeppelin Universi-ty, Am Seemoser Horn 20, D-88045 Friedrichshafen, Germany, e-mail: [email protected]; Tech University Darmstadt, Hochschulstraße 1, D- 64289 Darmstadt, Germany, e-mail: [email protected] stadt.de. Denis Schweizer, Assistant Professor of Alternative Investments, WHU – Otto Beisheim School of Management, Burgplatz 2, D-56179 Vallendar, Germany, e-mail: [email protected]. Marcel Tyrell, Buchanan Institute for Entrepreneurship & Finance, Zeppelin University, Am Seemoser Horn 20, D-88045 Friedrichshafen, Germany, e-mail: [email protected]; Goethe University Frankfurt, Finance Department, House of Finance, Grüneburgplatz 1, D-60323 Frankfurt am Main, Germany, e-mail: [email protected].

** We are indebted to two anonymous referees for their efforts to improve the paper. We would like to thank Frank-lin Allen, Yakov Amihud, Steve Ferris, Roland Füss, Juliane Proelss, Markus Glaser, Andreas Hackethal, Lutz Jo-hanning, Christian Koziol, Steffen Meyer, Clay Moffett, Isaac Otchere, Jörg Rocholl, Dirk Schiereck, Reinhard H. Schmidt as well as the participants of the Eastern Finance Association (45th Annual Meeting), Academy of Economics and Finance (36th Annual Meeting), Midwest Finance Association (58th Annual Meeting), German Finance Association (DGF) (16th Annual Meeting), Campus for Finance 2009, and German Economic Associ-ation of Business Administration e. V. (GEABA) (X. Annual Meeting) for helpful comments and excellent sug-gestions. Furthermore, we would like to thank Dieter G. Kaiser for sharing his excellent industry knowledge and for his outstanding help in constructing the data sample. All remaining errors are our own.

Electronic copy available at: http://ssrn.com/abstract=1879170

M. MIETZNER/D. SCHWEIZER/M. TYRELL

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1 INTRODUCTION

Hedge funds and private equity funds, both of which are often lumped under the heading “new institutional investors”, apparently pursue di!erent strategies in their e!ort to make money from funds’ investments. Even though both try to gain influence on the firms’ management and interfere with important financial and corporate issues, these di!er-ences in strategies might be due to di!erent organizational set-ups and the various busi-ness models the fund managers are following. However, these investors’ own governance structure is particularly relevant in a typical Continental European financial and corporate governance system like Germany’s, which is characterized by a high degree of ownership concentration, banks’ strong role in financing and monitoring firms, weak protection of minority shareholders, and a distinctive stakeholder orientation with co-determination and other stakeholder groups represented on the supervisory board. Stemming from and typically being embedded in a shareholder-oriented society, it is important to understand in more detail how these new institutional investors perform in a stakeholder-oriented economy. Previous empirical studies such as those by Achleitner, Betzer, and Gider (2010) and Mietzner and Schweizer (2007) show us that to influence and restructure their compa-nies in Germany, hedge funds and private equity funds act quite di!erently, but we know nothing similar about the broader industrial impact that these investors have.

In this paper we empirically investigate this question by analyzing the valuation e!ects on rivals from the information associated with an engagement of hedge funds or private equity investors in target firms in Germany. We provide empirical evidence on the valua-tion e!ects of a change in ownership structure by activist blockholders on directly a!ected rival firms. If market valuation e!ects are observable, we ask if these e!ects are consistent with the di!ering abilities of private equity funds and hedge funds in mitigating agency conflicts in its target companies, which, in turn, are also reflected in di!erent intra-industry e!ects. And we ask how we might be able to explain these di!erences in valuation e!ects in dependence on private equity respectively hedge fund investments. By answering these questions, we gain a deeper understanding of how capital markets incorporate the information contained in ownership structure or corporate governance changes into stock prices. Moreover, our results may have far-reaching implications in terms of corporate governance systems and its resistance to changes. In particular, the answers indicate the impact of a strong shareholder orientation on firms that are embedded in a more stake-holder friendly environment.

It is widely believed that large shareholders’ (which we define as any entity that owns at least 5% of a firm’s outstanding shares) monitoring activities can be very e!ective in solving agency problems that arise from the separation of ownership and control (see, e.g., Shleifer and Vishny (1986)). However, more recent research argues that large shareholders di!er from each other along many dimensions, and that changes in investment, finan-cial policy and operations are greater in the presence of certain specific groups of active blockholders (Bertrand and Mullainathan (2003); Cronqvist and Fahlenbrach (2009)). In this sense, private equity funds and hedge fund investors comprise two main groups of shareholders that acquire large blocks of voting rights that wish to actively influence and monitor a firm. In addition, both, hedge fund and private equity managers may spend

SHAREHOLDER ACTIVISM

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considerable resources gathering information about the target, but only if the transaction increases expected wealth. "us, the investment should reflect investors’ private informa-tion about the target firm, but it may also convey valuable information about the industry to a larger public. For that reason, following Jensen (1986) and Shleifer and Vishny (1988), we expect that problems arising from the separation of ownership and control will a!ect not only a single target firm, but also, due to, e.g., information spillover, impact the entire industry. "e market may then expect rival firms to experience parallel gains. "is wealth e!ect might be due to an increased takeover probability for the rival firms, but it could also result from positive spillover e!ects arising from corporate governance improve-ments in the target firms. We label this assumption the information signalling hypothesis, which we define as the expectation of positive valuation e!ects when a fund announces a block purchase in the target. We expect these considerations to be particularly relevant for private equity funds, since these active investors have a su#ciently long investment horizon and typically follow an investment strategy whose objective is to change the stra-tegic agenda of its portfolio companies.

However, there is a second hypothesis, the competition hypothesis, which might explain rival e!ects. "e new blockholder changes the firm’s objective functions toward a stronger short-term shareholder value orientation. "is change in turn a!ects the way firms compete (Allen, Carletti, and Marquez (2009); Boyson and Mooradian (2007)), which might lead to ambiguous consequences for rival firms. Increased competition can force industry peers toward economic e#ciency (see, e.g., Shleifer and Vishny (1997)), thereby negatively a!ecting their profit margins. Since hedge funds typically use a specific short-term outlook in their investment strategies, they quite often invest in companies they perceive as undervalued, and believe that they can at least partially mitigate the undervalu-ation. We expect such a strategy to increase the competitive pressure in an industry; thus, the competition hypothesis is strongly interlinked with hedge fund activism.

Although hedge fund and private equity investors both wish to increase a target’s value, their level of activism might di!er in sustainability. As we noted above, private equity investors usually focus on longer investment horizons, while hedge funds are more inter-ested in short-term and trading-induced profits (Dai (2007); Klein and Zur (2009)). Hence, in accordance with our competition hypothesis, we would expect not only a distinct rival e!ect in dependence on a private equity or hedge fund investment, but also that di!erent competitive e!ects would appear over the longer term. "erefore, we need to determine whether rivals to hedge fund targets experience other long-term valuation e!ects than do rivals to private equity targets. To the best of our knowledge, until now these issues have not been examined in empirical studies.

Our analysis is based on a unique hand-collected data set of 249 German companies that were targeted by hedge funds and private equity investors between 1993 and 2009. We grouped these firms into 171 private equity and 78 hedge fund events. Using a matching procedure based on industry classification codes, size, and market-to-book matches, we identify 367 industry rivals. We then apply a standard event study method to analyze whether the activities of these specific active investors are associated with di!erent short-term valuation e!ects for industry rivals. In addition, we analyze whether there are di!er-


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ences in target and rival firm characteristics that can be linked to the type of institutional investor. To determine whether market reactions can be explained by information signal-ling or competition e!ects, we also relate stock returns to several corporate characteristics and market variables. Because we expect the acquisition of a significant ownership claim by new institutional investors to a!ect an entire industry, we also examine long-term rival stock performance by calculating benchmark-adjusted buy-and-hold returns (BHARs).

We find that the cumulative abnormal returns (CARs) for the target companies around the announcement of an investment by private equity or hedge funds are significantly positive, but the CARs of around 8% for a private equity engagement are remarkably higher than are the CARs for a hedge fund investment, which are around 4.5%.

Second, we find that the announcement of a change in ownership structure generates statistically significant positive short-term intra-industry e!ects of between 1.78% and 3.9%, depending on the event window for rival firms to private equity targets, and signifi-cantly negative e!ects that are between –1.85% and –4.65% for competitors of hedge fund targets.

"ird, by comparing the characteristics of target and rival firms, we find that since the dividend payout ratio increases significantly the first two to three years after acquiring a stake, hedge funds typically extract the cash holdings of the companies they invest in. Furthermore, target firms’ investment activity decreases. We do not observe the same pattern when private equity funds take a stake. "is result leads us to the conclusion that in particular hedge fund investments are driven by shareholder value maximization.

Fourth, we find that the long-lasting return drift to hedge fund rivals and private equity rivals is positive even when we correct for the Fama and French (1993) factors. Over a 300-day period, the mean BHARs are 16.68% for private equity target firm rivals and 22.71% for hedge fund target firm industry rivals. Because we have a very small number of extreme outliers in our sample, in our opinion the medians are a more reliable measure. We find that the medians are lower, and positive on a significant level, only for the hedge fund rival firms.

"ese findings provide a challenge for us. It could be that because of their strong share-holder orientation, hedge fund target firms encounter greater resistance from the existing stakeholder-friendly firms and from government policies that are geared towards protecting their stakeholder-oriented corporate governance system. In line with arguments given by Gompers, Ishii, and Metrick (2003), we could interpret the positive long-term perform-ance of hedge fund target firm rivals as rival firms’ shareholders learning over time that the threat of shareholder activism does not have the perceived negative consequences for their firms, since in the long-run hedge funds do not succeed in implementing a shareholder-orientation where managers must act only in the interest of shareholders. In Germany, firms’ objectives encompass a broad set of stakeholders, including employees, banks, suppliers, and customers. Further, the corporate governance system is enforced by the regulatory framework. Such a governance system creates major obstacles for firms with a strong shareholder orientation. In comparison, private equity managers take a longer-


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term perspective and are better at adapting themselves to the local governance system. "erefore, they succeed more often in raising the e#ciency of the resource allocation.

"e paper proceeds as follows. In Section 2, we review related empirical studies. We discuss in detail the impact of hedge funds and private equity funds on their target firms and the reasons for possible intra-industry spillover e!ects, and we give an institutional background of the hedge fund and private equity industry. In Section 3 we describe our data set and method. In Section 4 we report our empirical results and introduce a frame-work for explaining the results. Section 5 concludes.

2 BACKGROUND

2.1 HEDGE FUNDS AND PRIVATE EQUITY FUNDS AS BLOCKHOLDERS: THE POTENTIAL FOR INTRA-INDUSTRY EFFECTS

Previous evidence on the engagement of new institutional investors as blockholders indi-cates that target-firm shareholders receive substantial positive stock returns in response to the announcement. Brav et al. (2008), Klein and Zur (2009), Cli!ord (2008), Boyson and Moora-dian (2007), and Greenwood and Schor (2009) report average excess returns to target firms of about 5% when a hedge fund becomes a blockholder in U.S. firms. Mietzner and Schweizer (2007) and Bessler, Drobetz, and Holler (2010), find comparable positive announcement returns for German hedge-fund targets. Klein and Zur (2009) note similar announcement returns when the acquirer of voting rights is a private equity fund in the U.S., as do Mietzner and Schweizer (2007) and Achleitner, Betzer, and Gider (2010) for Germany.

"e sources of these gains are widely discussed in the corporate governance literature (see, e.g., Cronqvist and Fahlenbrach (2009) or Shleifer and Vishny (1997)). As we noted above, aligning interests between managers and shareholders and increasing the monitoring activities of blockholders can serve as mechanisms for solving the agency problem (Grossman and Hart (1980); Shleifer and Vishny (1986)). "erefore, private equity targets typically experience an increase in research and development expenditures, a sell-o! of assets, a reduction in working capital, optimization of cash flows or a decrease in capital expenditures (Muscarella and Vetsuypens (1990)). "is monitoring leads to improved operating profits during the engagement period (Kaplan (1989); Muscarella and Vetsuypens (1990); Kaplan and Stein (1993); Hogan, Kish, and Olson (2001)).

In comparison, recent studies on hedge fund activism report an ambiguous impact on targets’ corporate performance. Cli!ord (2008) documents an increase in operational e#ciency after a hedge fund manager has become a blockholder, but finds that this change may be the result of a reduction in assets. In contrast, Klein and Zur (2009) find no increase in operating performance, but they do find a decline in profitability ratios and an extraction of cash due to an increase in payouts. Boyson and Mooradian (2007) find that a change in a target firm’s corporate governance improves performance and reduces agency costs. "ese results already point into a direction that it is meaningful to distin-guish between hedge fund and private equity investors.


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In any event, increasing a target firm’s value becomes essential for new institutional inves-tors. Against this background, our central hypothesis is that an engagement of a new insti-tutional investor not only a!ects the target company, but also, at least to a certain extent, impacts rival firms of the respective target company. On the one hand, the engagement may signal new information about the future prospects of the industry (the information signalling hypothesis). On the other hand, changes implemented by the new institu-tional investor may a!ect firm competition on an industry-wide basis (the competition hypothesis). "us, announcements of this particular change in ownership structure should generate market valuation e!ects for industry rivals.

But we should not expect the new institutional investors to act homogeneously, as many models assume; rather, they di!er in their capabilities and incentives to become active and to influence the companies in question (see Cronqvist and Fahlenbrach (2009) for a detailed discussion). "erefore, a recent strand in the corporate governance literature argues that even though these two types of new institutional investors have the highest incentives and capabilities to become active, the researcher should distinguish between them1.

However, when analyzing the valuation e!ects of private equity and hedge fund invest-ments, we must consider the degree of intra-industry competition as intervening factor. Giroud and Mueller (2010; 2011) find support for the argument that highly competitive industries do not have room for managerial ine#ciency, thus minimizing the poten-tial for agency cost reduction. Consequently, the level of competition in an industry is negatively correlated with the expected e!ects on its rivals, because product competition acts to discourage managers from wasting corporate resources (Masulis, Wang, and Xie (2007)).

2.2 SIMILARITIES AND DIFFERENCES BETWEEN PRIVATE EQUITY AND HEDGE FUNDS

An important reason for an active engagement by hedge funds and private equity managers might be that both have negotiated attractive performance-based compensation schemata with their investors: on average, these agreements carry an annual fixed management fee of about 2% plus a performance fee of around 20% (see, e.g., Hennessee (2007); Metrick and Yasuda (2010)). "ese compensation structures align the interests of the fund manage-ment with the interests of their investors and ensure that a fund’s management is highly motivated to pursue shareholder interests.

Furthermore, hedge fund and private equity funds are generally not a#liated with banks or insurance companies. "e latter might wish to retain the potential for future business with the firms in question so they might restrict the fund management in their activism e!orts. For that reason we can conclude that conflicts of interest are much lower compared to, e.g., mutual funds (Kahan and Rock (2007); Davis and Kim (2007)).

1 For more insights on hedge funds and private equity funds, see, for example, Fung and Hsieh (1999); Gompers and Lerner (2006). A detailed comparison between both types of investors can be found in Achleitner and Kaser-er (2005); Amess et al. (2007); Mietzner and Schweizer (2007).


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Both types of new institutional investors are less restricted in their investment behavior, e.g. portfolio weight constraints, leverage, short-selling etc. compared to mutual funds or insurance companies. "us, they can obtain large blocks of voting rights more easily than traditional investors. Private equity funds and hedge funds exhibit similar advantages in this respect, except for the ability of private equity funds to use derivatives (Black and Hu (2007); Christo!ersen et al. (2007)).

Hedge funds and private equity funds also di!er from each other due to several points. Both investment vehicles have a di!erent funding structure and therefore a di!erent life cycle – hedge funds are typically structured as open ended funds whereas private equity funds have a specified lifetime. During the funds’ lifetime private equity mangers are not a!ected by short-term share redemptions which empower them to focus on longer investment horizons and a wide range of investment strategies. In addition, since private equity funds are focused on one activity, namely investments of equity capital in certain companies, their management does not only encompass managers with substantial finan-cial expertise but also personnel with strong business skills and abilities. Of course, these abilities are important in order to develop a deep knowledge of the business model of a target company, which, in turn, is a prerequisite for improving the company’s value. Keep in mind, such a long-term strategy can also imply that a private equity dominated company in a certain sense accepts the “consensus” with the other stakeholder in the company because they know that in the long-run they profit from this cooperation. "is is in particular relevant in countries like Germany with stakeholder-friendly corporate governance.

In contrast, hedge fund managers may face significant capital withdrawals and higher probability of losing the best employees after reporting negative performance for several subsequent months and low or no new cash inflows (Getmansky (2005)). "erefore, hedge fund managers have to act more short-term orientated compared to private equity managers to avoid a reduction in funds capital and to preserve liquidity (Agarwal, Daniel, and Naik (2009)). "ey have to face the threat of illiquidity when they acquire a large share position in a target company which they cannot sell within a short time period. Hence, hedge funds prefer investments where they can achieve a fast turnaround.

"erefore, they try to identify firms which are undervalued and, even more important, where they have the means of establishing a strong shareholder-orientation in the short-run. Only such a strategy allows them to liquidate their holding positions on the short-term at low cost. However, this also requires investment professionals with substantial financial expertise. For that reason, hedge funds are mainly recruiting employees with a strong background in financial markets. Given their business model and their organi-zational set-up, the financial expertise of its management is a precondition of success. And this should be reflected in the type of activism vis-a-vis their portfolio companies: Strong shareholder-orientation and aggressive behavior on the product markets to achieve quick gains.


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3 DATA AND METHOD

We collected data from four primary sources for our analysis. We obtained time series data, i.e., daily closing prices and consolidated trading volumes for all firms in our sample and the CDAX® index, from "omson Financial DataStream. For accounting data, we used the "omson Financial Worldscope database to obtain information from the two fiscal years prior to the announcement until three years after, when available. In accord-ance with prior research based on Fama and French (1992), we assign all accounting variables for the fiscal year-end in year t – 1 to announcements between July and June of year t + 1. We used the "omson Financial Mergers and Acquisition database to identify M&A transactions. Further, we gathered information from the database of the Federal Financial Supervisory Authority (Bundesanstalt für Finanzdienstleistungsaufsicht (BaFin)) to identify disclosures of shareholders who owned 5% (in January 2007, the minimum threshold was lowered to 3%) or more of a company’s voting rights from 2001 through August 2009. Investors are required by the German Securities Trading Act (§§ 21!.) to disclose an acquisition of at least 5% (3% after January 2007) of the voting rights of any German publicly traded company no later than nine days after the transaction. "ese requirements ensure that the database is a complete collection of transactions.

3.1 PRIVATE EQUITY SUBSAMPLE CONSTRUCTION

Our major challenge for the private equity subsample construction is to identify the private equity related transactions in the BaFin database, since private equity fund managers often structure their transactions via so called Special Purpose Acquisition Companies (SPVs) or by using complex holding structures. Hence, it is possible that a private equity fund acquisition might be filed by, for example, a SPV that is ultimately owned by the fund, but because of a di!erent name of the SPV it is di#cult to trace it back to the fund.

To overcome this problem we scrutinize the "omson Financial Mergers and Acqui-sition database and collect a raw sample of 31,496 M&A transactions for which the target is located in Germany. Next, we apply a two-step approach to identify the trans-actions in which the acquirer is a private equity fund. First, we compile a complete list of private equity funds from di!erent data sources such as member lists of investment associations (BVI and BVK), public rankings of private equity funds, and the "omson One Banker “Private Equity Flag”. We remove the legal form identifier from the names, thus reducing them to their distinctive body, i.e., “"e Blackstone Group” was reduced to “Blackstone”, and we delete non-distinctive terms such as “Group”. Second, we use a text-matching program procedure to match this list with the acquirer’s name, its imme-diate parent’s name, its ultimate parent’s name, and the deal description (deal synopsis). We add deal-descriptive terms like “leveraged buy out” (LBO) to our search criteria for the deal synopsis. "e initial sample we create by using this two-step approach comprises 891 transactions.

We reduce the sample further by deleting double entries and target companies that are not publicly listed. To avoid confounding events, we exclude all private equity disclosures


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that happen within three months after a prior announcement of a 5% shareholding in that company by any other investor. Doing so reduces our sample to 171 transactions (see Figure 1). "en we visually inspect every transaction to ensure accuracy and conduct an individual judgment verified with practitioners. Further, to avoid potential biases from illiquid stocks, we also exclude 46 companies with no turnover data on more than 30% of the trading days within the 200 days prior to the announcement.

We validate our sample by repeating the text-matching program procedure for the complete list with the disclosures provided by the BaFin database, and research news articles on LexisNexis® for publicly listed companies in Germany, but do not find further events. Our final sample totals 125 private equity target firms listed in Germany between 1993 and 20092.

Figure 1: Distribution of Hedge Fund and Private Equity Target Events from 1993 through 2009

10

1 1

43

8

16

7

9

11

19

27

38

11 11

4

0 0 0 0 0 0 0 01 1

34

17

36

15

10

0

5

10

15

20

25

30

35

40

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Number of Private EquityTargets

Number of Hedge Fund Targets

The entire sample covers 249 events. We subclassify these events into 171 private equity events and 78 hedge fund events.

Table 1 gives the industry classification for the target companies. Table 2 shows the percentage of the shares in the target company.

2 None of the target companies were taken private within a period of 300 days after the block purchase.


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Table 1: Industry Classification of Private Equity and Hedge Fund Targets

Panel I: Private Equity Transactions Panel II: Hedge Fund Transactions

No. of Transactions

Percent of Panel No. of Transactions

Percent of Panel

Agriculture, Forestry, and Fishing 0 0% 1 1%

Construction 2 1% 0 0%

Manufacturing 84 49% 24 31%

Transportation, Communications, Electric, Gas, and Sanitary Services

16 9% 6 8%

Wholesale Trade 7 4% 5 6%

Retail Trade 1 1% 3 4%

Finance, Insurance, and Real Estate 28 16% 10 13%

Services 33 19% 29 37%

Total 171 100% 78 100%

This table summarizes the industries of the private equity fund (Panel I) and hedge fund (Panel II) target "rms. We classify each "rm according to its primary four-digit SIC.

Table 2: Descriptive Statistics of Private Equity and Hedge Fund Transactions

Percentage of Shares Acquired.

Percentage of Shares Owned After Transaction

Panel I: Private Equity Transactions

Mean 46.87% 52.36%

Median 34.17% 46.55%

Panel II: Hedge Fund Transactions

Mean 12.11% 12.21%

Median 7.89% 7.89%

This table shows the percentages of shares acquired and percentages of shares owned after transaction in the target "rms of private equity fund (Panel I) and hedge fund (Panel II).

3.2 HEDGE FUND SUBSAMPLE CONSTRUCTION

"e creation of our hedge fund subsample comprises of two steps. We gather a complete list of hedge funds from di!erent hedge fund databases such as Eureka Hedge and Credit Suisse Tremont. We remove the legal form identifier from the names, reduce them to their distinctive body, and omit non-distinctive terms such as “Fund”. To extend the list


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we search LexisNexis® for all news articles that use terms such as “hedge fund” or “share-holder activism” for publicly listed companies in Germany. Again, we use a text-matching program procedure to match this list with the acquirer’s name stated in BaFin database.

Our initial sample contains 251 transactions filed by 81 hedge funds. Since hedge fund managers follow heterogeneous investment strategies, such as merger arbitrage, long-short equity investments, activism etc., we must ensure that we include only hedge funds that apply pure activism strategies3. Otherwise, there would be a high risk of biased results when we compare events in which the blocks of voting rights are acquired for, e.g., invest-ment purpose (e.g. long-short equity investments) or in case of distress (e.g. debt-equity swaps transactions). "us, we check the hedge fund databases (Eureka Hedge and Credit Suisse Tremont) for their self-classifications. With the help of industry participants we contact the hedge funds for final verification that they apply activism strategies. "is procedure gives us a sample of 78 events (see Figure 1).

"ereafter, we exclude all events that are disclosed within three months after a prior announcement of a 5% shareholding in the same company by any other hedge fund investor. Doing so ensures that the results of the subsequent analysis are not biased by clustering of single events due to the well-known problem of hedge fund herding behav-iour. We also exclude six companies with no turnover on more than 30% of the trading days within the 200 days prior to the announcement. Our final sample consists of 72 hedge funds transactions between 2001 and 20094. Table 1 gives the industry classification for the target companies.

3.3 CONSTRUCTION OF RIVAL PORTFOLIO

A survivorship-bias-free rival universe is compiled from "omson Financial DataStream by gathering all active and delisted firms that are included in this database. To compute the wealth e!ects of hedge fund and private equity investments on a target firm’s competitors (rivals), we use a three-step procedure:

First, we formed an equally weighted portfolio of all firms with the same four-digit standard industrial classification (SIC) code as the target firm5. Second, because this matching procedure constitutes a broad classification of industry rivals, we identify all firms with market value of equity between 50% and 250% of the market value of equity of the target firm. "ird, we assign each target firm up to three matching firms with minimal absolute percentage di!erences between their book-to-market ratios (at the end

3 Unlike the 13G filings in the U.S., the acquirer does not have to make public his investment purpose. 4 Note that we decided not to eliminate the observations where the hedge fund exited the target within a period

of 300 days. Since we are interested in the long-run valuation effects of the actions undertaken by hedge funds, share prices of targets and rivals should still reflect these actions even after the hedge fund exits. However, we ob-served only two cases of exit within this period. Eliminating these cases did not affect our results.

5 As a robustness check, we investigate whether our results are affected by the choice of industry classification codes. We find that the results remain stable when we use two- or three-digit SIC codes. Tables are available on request from the authors.


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of the fiscal year prior to investment of a new institutional investor). Finally, we remove both illiquid rival stocks and rivals that become targets during our sample period.

3.4 ESTIMATION OF VALUATION EFFECTS

We measure both a target’s and the respective rival’s market reaction to the announcement of a purchase of at least a 5% ownership share by hedge funds or private equity investors. We do so by calculating their abnormal returns around the disclosure date. Following Brown and Warner (1985) and Fuller, Netter, and Stegemoller (2002), we apply the standard event study method by using the modified market model and calculating the cumulative abnormal returns, as follows6:

CAR[t0 – !, t0 + !], i = " t = t0 – !

t0 + !

(Ri,t – ˆ#i – $%i · RCDAX,t), (1)

where Ri,t is the return of rival i at time t, ̂#i and $%i are estimates from an ordinary least square regression (OLS) during the estimation period (200 days), and RCDAX,t is the market return (CDAX®) at time t. We use a standard t-test statistic to draw statistical inferences for the di!erent event window cumulative average abnormal returns7.

As noted above, in Germany investors are required by law to disclose an acquisition of voting rights no later than nine days after the transaction. To avoid any biases caused by a lagged disclosure, we base the subsequent cross-sectional regression on a [–5; 4] event window, and estimate the sensitivity of market reactions to transaction, firm and industry characteristics8. We estimate the t-statistics of our cross-sectional regressions using White’s (1980) heteroskedasticity-consistent standard errors9.

We calculate the respective industry concentration by using the Herfindahl-Hirschman Index to detect whether the capital markets distinguish between competitive and non-competitive product market environments:

HHIj,t = " i = 1

Nj

S2ijt, (2)

6 We estimated market parameters based on a 200-day estimation period to calculate abnormal returns. We find that the results remain quantitatively and qualitatively similar when we use the constant mean model or a Fama and French (1993) three-factor model. Tables are available upon request from the authors.

7 We also applied the test according to Böhmer, Masumeci, and Poulsen (1991) to capture possible event-induced increases in variance, the test according to Lyon, Barber, and Tsai (1999) to control for the skewness bias, and the Wilcoxon rank sum z-score.

8 To detect the influence of outlier observations, we winsorized abnormal returns at different percentiles, includ-ing the 1st and 99th and the 5th and 95th percentiles. The results of our regression analysis remain quantitatively and qualitatively similar. Tables are available on request from the authors.

9 In unreported tables, we use variance decomposition according to Belsley, Kuh, and Welsch (1980) to detect col-linearity problems. We found no multicollinearity.


sbr 63 April 2011 151!185 163

where S2ijt is the market share of firm i in industry j at announcement day t and Nj

the number of firms in industry j. Again, we use the four-digit SIC code provided by "omson Worldscope10.

To determine the long-term impact of the acquisition of ownership claims by private equity investors or hedge funds, we calculate 150-, 200-, 250-, and 300-day buy-and-hold abnormal returns (BHARs) to measure the performance of our industry rival portfolio and of our targets. We estimate the BHAR for each company over T days by using the following regression11:

Ri, t – Rf, t = #i + %i · (R m,t – Rf, t) + &i · SMBt + 'i · HMLt + (i,t, (3)

where Ri,t is the return of rival i at time t, Rf,t is the risk-free rate and Rm,t is the market-return. SMB is the di!erence between returns on a portfolio of small and large stocks; HML is the di!erence between returns on a portfolio with high and low book-to-market firms. Since historical data on the SMB and HML portfolios is rarely available for Germany, we follow Cremers, Petajisto, and Zitzewitz (2008), Pham (2007), Cuthbertson, Nitzsche, and O’Sullivan (2008) and Fa! (2003) and create proxies for these two Fama and French (1993) factors by using the MSCI Germany Value and Growth indexes for small and large caps, the MSCI Germany Value and MSCI Germany Growth Index for low and high book-to-market firms, and the MSCI Germany Standard Index as market reference. To evaluate the statistical significance of the mean and median portfolio return of industry rivals, we use a standard t-statistic and the Wilcoxon rank sum z-score. To eliminate the skewness bias when we calculate long-run abnormal returns we use the skew-ness-adjusted t-statistic advocated by Lyon, Barber, and Tsai (1999).

Since the wealth e!ect surrounding the engagement of an activist shareholder may also depend on the governance mechanisms which the target and rival firm already have in place, one needs a measure for potential monitoring activities of large blockholders. We use %Closely Held Shares, which we define as the number of closely held shares divided by the number of outstanding common shares. We calculate Cash Holdings as cash and short-term investments divided by lagged net property, plant, and equipment. Addition-ally, we calculate the proportion of company’s cash positions to its market capitalization at the end of the year. We use the Current Ratio measured by current assets over current liabilities at year-end as our proxy for short-term liquidity requirements. We measure the Dividend Payout per Share ratio as dividends per share divided by earnings per share. Earnings per share represent the earnings for the fiscal year of the specific company divided by the number of shares outstanding. As our proxy for profitability we calculate the ratio of earnings before interest, taxes and depreciation divided by the market capitalization

10 We calculate the market share based on sales, but in robustness checks we also base the market share on year-end market capitalization and on total assets. Additionally, we use the two- and three-digit SIC code to calculate the industry concentration. Our results remain stable.

11 In robustness checks, we also calculate buy and hold abnormal returns against the CDAX® and the Carhart (1997) four-factor model. The results remain quantitatively and qualitatively similar. Tables are available on re-quest from the authors.


sbr 63 April 2011 151!185164

at year-end and the change in return on assets from the year prior to the announcement relative to the announcement year (EBITDA/YrEndMarketCap).

To determine whether the capital markets distinguish between competitive and non-competitive product market environments, we calculate the respective industry concentra-tion by using the Herfindahl-Hirschman Index (HHI) as defined above. We also examine the interaction between the level of industry concentration and a change in profitability (HHI*($ROA)).

We measure the equity ratio as a measure of firm leverage as the ratio of a company’s total common equity to the value of total capital. "e variable Investment measures a compa-ny’s investment policy; we define it as capital expenditures divided by net property, plant, and equipment at the end of the previous fiscal year. We use the natural logarithm of the year end market capitalization as a proxy for firm size (Ln(Market Cap)). We measure total assets and year-end market capitalization in millions of dollars.

"e Market to Book Value of equity is the market value of equity divided by the book value of equity. Additionally, we analyze the price/earnings ratio, which we calculate as the ratio of price per share at year end to earnings per share. We calculate target AR as the abnormal return of the target company during the event window [–5; +4]. "e definitions of all variables we use in both the univariate and the regression analyses are summarized in the Appendix.

4 EMPIRICAL RESULTS

4.1 DIFFERENCES IN TARGET AND RIVAL FIRM CHARACTERISTICS

We investigate the characteristics of target firms and compare them to the characteristics of their rivals. We use two separate analyses, one for our hedge fund targets and rivals sample and one for our private equity fund targets and rivals sample. We wish to find out whether hedge funds and private equity funds invest in target companies that are mark-edly di!erent to their respective peer group; after investment, how the characteristics of the target firms change relative to their rivals; and whether we see indications of profound di!erences in the ways private equity funds and hedge funds are influencing its portfolio companies. "e answers should give us a first clue on the hypothesis that hedge funds and private equity funds are driven by di!erent motives, and therefore, also try to address di!erent types of agency conflicts.

"us, we compare the targets’ and rivals’ medians of certain firm characteristics on a yearly basis from the year 2 prior to the investment in the target company until year 3 after acquisition. Doing so enables us to detect di!erences between target and rival companies in the cross-section and to trace changes over time. Tables 3 and 4 show the results for hedge fund and private equity activism, respectively.


sbr 63 April 2011 151!185 165

Table 3: Differences in Target and Rival Firm Characteristics Relative to the Hedge Fund Activism

Targ

ets M

edia

nRi

vals

Med

ian

Dif

fere

nce

t – 2

t – 1

t0t +

1t +

2t +

3t –

2t –

1t0

t + 1

t + 2

t + 3

t – 2

t – 1

t0t +

1t +

2t +

3

Cash

Hol

ding

s0.

680.

420.

611.

180.

740.

721.

711.

811.

681.

652.

11.

93–1

.025

***

–1.3

82**

*–1

.071

**–0

.478

*–1

.356

**–1

.213

***

Cash

/Tot

al L

iabi

litie

s 0.

14

0.11

0.

15

0.11

0.

12

0.09

0.

11

0.15

0.

110.

13

0.11

0.

13

0.02

8 –0

.038

0.

042

–0.0

14

0.00

5 –0

.034

Cash

/YrE

ndM

arke

tCap

0.

14

0.15

0.

13

0.11

0.

12

0.18

0.

09

0.10

0.

08

0.10

0.

15

0.18

0.

045*

* 0.

046*

* 0.

045*

0.

016

–0.0

27

0.00

0

Curr

ent R

atio

1.52

1.44

1.34

1.44

1.31

1.26

1.48

1.49

1.42

1.38

1.39

1.23

0.04

3–0

.041

–0.0

75*

0.05

6–0

.084

0.02

8

Div

iden

d Pa

yout

per

Sh

are

41.7

7 41

.14

46.2

1 46

.23

45.9

8 45

.98

33.0

6 37

.86

33.8

5 34

.97

34.3

8 33

.38

8.71

3 3.

281

12.3

61

11.4

52**

11

.602

** 1

2.84

4***

Earn

ings

Per

Sha

re0.

040.

050.

050.

490.

240.

10.

150.

210.

410.

420.

20.

13–0

.117

–0.1

61*

–0.3

51**

*0.

070.

048

–0.0

3

EBIT

DA

/ Yr

EndM

arke

tCap

0.

120.

10.

070.

110.

140.

160.

10

0.10

0.

10

0.11

0.12

0.14

0.01

90.

000

–0.0

27*

0.00

0 0.

021

0.01

8

Equi

ty %

Tot

al C

apita

l76

.41

77.6

880

.92

76.7

174

.72

71.8

386

.09

86.0

485

.41

83.19

80.3

283

.38

–9.6

77–8

.368

*–4

.491

–6.4

78–5

.594

–11.

555

Inve

stm

ent

0.18

0.22

0.21

0.28

0.26

0.19

0.22

0.29

0.37

0.38

0.34

0.44

–0.0

41*

–0.0

67*

–0.1

63**

*–0

.096

**–0

.079

**–0

.249

***

Mar

ket t

o Bo

ok V

alue

1.53

1.93

1.9

1.73

1.

40

0.94

1.55

1.74

1.91

1.79

1.35

1.14

–0.0

20

0.18

5–0

.010

–0

.06

0.05

–0.2

05

Pric

e Ea

rnin

gs R

atio

6.33

11.9

512

.28

15.9

10.1

89.

1512

.02

15.3

115

.04

14.8

27.

725.

73–5

.687

–3.3

6–2

.753

1.08

12.

456

3.42

7

Retu

rn O

n A

sset

2.26

2.84

2.57

4.38

2.87

2.74

3.62

4.22

4.89

4.80

4.

00

3.74

–1.3

68–1

.382

*–2

.318

***

–0.4

2–1

.126

–0.9

97

Tota

l Ass

ets

227.1

173.

419

1.6

197.

523

1.6

218.

862

.188

.710

7.9

134.

613

5.2

101.

416

5.02

***

84.7

1**

83.6

9**

62.8

6**

96.4

2***

117.

41**

*

YrEn

dMar

ketC

ap

58.5

73.0

0 12

4.8

166.

617

5.2

101

47

.773

.782

.977

53.5

36.8

10

.98

–0.7

00

41.8

989

.62*

**12

1.69

***

64.2

2***

%Cl

osel

y H

eld

Shar

es36

.8

36.8

27

.4

21.8

33

.335

.553

.251

.950

.253

.149

.746

.6

–16.

41**

*–1

5.12

***

–22.

83**

*–3

1.31

***

–16.

36**

*–1

1.15

***

***,

**, a

nd *

indi

cate

stat

istic

al si

gnifi

canc

e at

the

1%, 5

%, a

nd 1

0% le

vels

, res

pect

ivel

y.

This

tabl

e sh

ows t

he "

rm c

hara

cter

istic

s of h

edge

fund

act

ivism

targ

ets c

ompa

red

to th

eir r

ival

s. W

e w

inso

rize

each

of t

he v

aria

bles

at t

he to

p an

d bo

ttom

to

elim

inat

e th

e e#

ects

of o

utlie

rs. W

e de

"ne

Cash

Hol

ding

s as c

ash

and

shor

t-ter

m in

vest

men

ts o

ver l

agge

d ne

t pro

pert

y, p

lant

, and

equ

ipm

ent;

Cash

/To

tal L

iabi

litie

s equ

als C

ash

hold

ings

div

ided

by T

otal

Lia

bilit

ies,

whi

ch re

pres

ents

all

shor

t- an

d lo

ng-te

rm o

blig

atio

ns th

at th

e fu

nd e

xpec

ts to

be

satis

-"e

d by

the

com

pany

; Cas

h/Yr

EndM

arke

tCap

equ

als C

ash

hold

ings

div

ided

by Y

rEnd

Mar

ketC

ap; C

urre

nt R

atio

is c

urre

nt a

sset

s ove

r cur

rent

liab

ilitie

s; D

ivi-

dend

Pay

out p

er S

hare

is d

ivid

ends

per

shar

e di

vide

d by

ear

ning

s per

shar

e, w

hile

ear

ning

s per

shar

e re

pres

ents

the

earn

ings

for t

he 1

2 m

onth

s end

ing

the

"sca

l yea

r of t

he c

ompa

ny d

ivid

ed b

y th

e nu

mbe

r of s

hare

s out

stan

ding

; Ear

ning

s Per

Sha

re re

pres

ent t

he e

arni

ngs f

or th

e 12

mon

ths e

ndin

g th

e "s

cal y

ear o

f the

com

pany

; EBI

TDA/

YrEn

dMar

ketC

ap is

EBI

TDA,

whi

ch w

e ca

lcul

ate

by ta

king

the

pret

ax in

com

e an

d ad

ding

bac

k in

tere

st e

xpen

se o

n de

bt a

nd d

epre

ciat

ion,

dep

letio

n an

d am

ortiz

atio

n an

d su

btra

ctin

g in

tere

st c

apita

lized

, div

ided

by

YrEn

dMar

ketC

ap; E

quity

% To

tal C

apita

l = (C

omm

on

Equi

ty /

Tota

l Cap

ital)

* 10

0; In

vest

men

t is c

apita

l exp

endi

ture

s ove

r lag

ged

net p

rope

rty,

pla

nt, a

nd e

quip

men

t; M

arke

t to

Book

Val

ue =

Mar

ket P

rice-

Year

End

/ Bo

ok V

alue

Per

Sha

re; P

rice

Earn

ings

Rat

io =

Mar

ket P

rice-

Year

End

/ Ea

rnin

gs P

er S

hare

; Ret

urn

on A

sset

= (n

et in

com

e be

fore

pre

ferr

ed d

ivi-

dend

s + ((

inte

rest

exp

ense

on

debt

-inte

rest

cap

italiz

ed) *

(1-ta

x ra

te)))

/ la

st la

gged

tota

l ass

ets *

100

; Tot

al A

sset

s is t

he v

alue

of a

com

pany

’s bo

ok a

sset

s; Yr

EndM

arke

tCap

is th

e M

arke

t Pric

e-Ye

ar E

nd *

Com

mon

Sha

res O

utst

andi

ng; %

Clo

sely

Hel

d Sh

ares

is a

mea

sure

for i

nsid

er o

wne

rshi

p an

d is

de"n

ed

as (N

umbe

r of C

lose

ly H

eld

Shar

es /

Com

mon

Sha

res O

utst

andi

ng) *

100

.


sbr 63 April 2011 151!185166

For hedge fund activism, we find a strong tendency to extract liquidity from the target company relative to the liquidity status of their rivals. In Table 3, Row 1 (Cash Holdings) shows that the depletion of cash holdings is particularly pronounced in the Years 2 and 3 after acquisition. A similar picture emerges for dividend payments. Row 5 (Dividend Payout per Share) indicates that the dividend payout ratio per share increases after the investment of the hedge fund. Hence, these results support Jensen’s (1986) free cash flow hypothesis. Moreover, Row 9 (Investment) illustrates that the decrease over time of the real investment ratio of the target firms in comparison to their peer firms can also be interpreted in this direction. Furthermore, Row 13, Total Assets, shows that the target companies are large compared to their rivals. And in Row 15, %Closely Held Shares, we see that hedge funds typically invest in companies in which the free float of shares is high, even though the number of closely held shares increases over time after the investment. Hedge funds are apt to target firms with a relatively dispersed ownership structure. For implementing short-term devices to solve the agency conflicts that apparently show up as free cash flow problems, and to make sure that they are not blocked in the short-term, hedge funds need a certain degree of leeway and invest predominantly in companies without a controlling shareholder. However, from an investor’s perspective, the hedge fund activism seems to be attractive. Row 14, YrEndMarketCap, shows that year-end market capitalization rises markedly after the share acquisition. All in all it seems to be the case that firms targeted by hedge funds are acting aggressively in the market to increase its profitability on a short-term basis.

For private equity activism, the picture looks di!erent. Here too the cash holdings are significantly lower for the target companies, but they do not decrease over time after the acquisition. We do not observe an increase of the dividend payments in the aftermath of a private equity investment. Row 8, Equity % Total Capital, indicates that target firms increase leverage, since the equity ratio of the target firms decreases over time relative to their rivals, but Row 9, Investment, shows that real investment activity is not reduced significantly. Private equity firms also invest typically in larger firms (see Row 13, Total Assets), and if we compare the development of the total market capitalization to the peer firms, we see that at least in the first two years after investment, their engagements are profitable.

However, in Row 15, %Closely Held Shares, the fraction of closely held shares implies that private equity firms often invest in firms with concentrated ownership structures, and that they acquire a higher percentage of the shares in the target company (see Table 2). "us, the analysis points towards a fairly long-term strategy of private equity targets in dissolving agency conflicts. Such firms increase the leverage to address free cash flow prob-lems; however, this alternative is only attractive when the expected financial distress costs of the firm are not too large and require a long-term horizon, which could be undermined by a short-term aggressive behavior in the product marke12. Moreover, the increase in real investment indicates that the long-term perspective of the industrial sector in which the target firm is embedded seems to be a profitable investment opportunity. Both arguments

12 See Achleitner, Betzer, and Gider (2010) for similar results regarding hedge funds and private equity investments in Germany.


sbr 63 April 2011 151!185 167

Targ

ets M

edia

nRi

vals

Med

ian

Dif

fere

nce

t – 2

t – 1

t0t +

1t +

2t +

3t –

2t –

1t0

t + 1

t + 2

t + 3

t – 2

t – 1

t0t +

1t +

2t +

3

Cash

Hol

ding

s0.

350.

310.

350.

370.

610.

41.

782.

22.

951.

731.

241.

2–1

.431

***–

1.88

2***

–2.6

03**

*–1

.357

***–

0.63

2**

–0.7

93**

Cash

/Tot

al L

iabi

litie

s 0.

080.

080.

080.

110.

120.

140.

150.

120.

110.

110.

090.

08–0

.062

**–0

.038

**–0

.028

0.00

30.

034

0.06

4*

Cash

/YrE

ndM

arke

tCap

0.

090.

110.

100.

130.

130.

160.

110.

120.

120.

120.

130.

12–0

.021

–0.0

14–0

.025

0.00

7–0

.004

0.03

5**

Curr

ent R

atio

1.55

1.44

1.68

1.67

1.58

1.55

1.4

1.46

1.4

1.37

1.46

1.54

0.14

7–0

.024

0.28

30.

301

0.11

80.

01

Div

iden

d Pa

yout

per

Sh

are

46.3

043

.58

35.8

041

.92

31.5

734

.38

48.7

343

.83

43.6

145

.45

46.8

543

.23

–2.4

34–0

.251

–7.8

14–3

.531

–15.

279*

–8.8

56

Earn

ings

Per

Sha

re0.

30.

160.

330.

330.

110.

160.

10.

140.

160.

20.

20.

150.

196*

*0.

020.

167

0.13

–0.0

890.

006

EBIT

DA

/ Yr

EndM

arke

tCap

0.

160.

160.

190.

140.

170.

160.

110.

110.

130.

140.

130.

150.

052*

**0.

046*

**0.

057*

*–0

.004

0.03

30.

006

Equi

ty %

Tot

al C

apita

l 75

.93

78.2

674

.46

74.4

667

.55

63.3

686

.67

88.13

86.7

88.4

185

.38

82.6

3–1

0.74

***–

9.87

***

–12.

24**

*–1

3.95

***

–17.

84**

*–1

9.26

***

Inve

stm

ent

0.24

0.21

0.26

0.24

0.25

0.23

0.29

0.34

0.38

0.31

0.25

0.28

–0.0

53*

–0.13

3***

–0.11

3***

–0.0

70*

0.00

1–0

.048

Mar

ket t

o Bo

ok V

alue

1.55

1.87

1.62

1.81

1.96

1.33

1.46

1.52

1.52

1.52

1.51

1.36

0.08

50.

350.

10.

295

0.45

–0.0

25

Pric

e Ea

rnin

gs R

atio

13.9

312

.54

10.0

58.

686.

47.

9213

.26

10.4

89.

449.

4610

.138.

640.

667

2.05

70.

61–0

.786

–3.7

29*

–0.7

26

Retu

rn O

n A

sset

4.25

3.11

4.27

3.16

3.21

4.34

3.29

3.67

3.79

3.71

3.84

3.49

0.96

3–0

.552

0.47

8–0

.556

–0.6

340.

851

Tota

l Ass

ets

137.

714

513

9.6

166

194.

817

351

.757

.869

.475

.185

.287

.485

.88*

**87

.19**

*70

.18*

**90

.93*

**10

9.59

***

85.5

4***

YrEn

dMar

ketC

ap

125.

310

8.5

91.5

110.

912

082

.7

42.6

40.6

4040

.936

.538

.6 8

2.74

***

67.8

6***

51.5

4***

70.0

7***

83.4

9***

44.1

6**

%Cl

osel

y H

eld

Shar

es

51.8

56.0

558

.35

62.6

766

.22

64.5

3 5

5.59

54.7

853

.64

51.7

658

.07

55.6

2 –3

.791

1.26

64.

712

10.9

08**

*8.

146*

**8.

907*

*

***,

**, a

nd *

indi

cate

stat

istic

al si

gnifi

canc

e at

the

1%, 5

%, a

nd 1

0% le

vels

, res

pect

ivel

y.

Table 4: Differences in Target and Rival Firm Characteristics Relative to the Private Equity Activism

This

tabl

e sh

ows t

he "

rm c

hara

cter

istic

s of p

rivat

e eq

uity

act

ivism

targ

ets c

ompa

red

to th

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sbr 63 April 2011 151!185168

support the information signalling hypothesis, that the announcement of a private equity investment should benefit the target firm’s competitors.

4.2 SHORT-TERM VALUATION EFFECTS TO TARGETS AND INDUSTRY RIVALS

We find positive announcement returns for the announcements that hedge funds or private equity investors have reached the level of becoming active blockholders in a target company (see Figure 2). "ese short-term capital market reactions are in line with previous findings (see, e.g., Mietzner and Schweizer (2007); Klein and Zur (2009)) and compared with the findings in Table 5, are statistically significant. We note that the short-term abnormal returns around the announcement are slightly higher for the private equity target sample than for that of hedge funds targets.

Figure 2: Cumulative Average Abnormal Returns Around the Disclosure of Holding at least 5% of Voting Rights by Private Equity and Hedge Funds in Target Companies

–02%

00%

02%

04%

06%

08%

10%

12%

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Cum

ulat

ive

Aver

age

Abno

rmal

Ret

urns

Days Relative To Announcement Day

Private Equity Subsample – Target Reaction

Hedge Fund Subsample – Target Reaction

t-30

The graph illustrates the cumulative average abnormal returns of targets of hedge fund (hedge fund subsample) and private equity (private equity subsample) targets from Day -30 through Day +20 relative to the announcement day with CDAX® as the corresponding benchmark, when at least 5% of voting rights are acquired.


sbr 63 April 2011 151!185 169

Table 5: Cumulative Abnormal Returns to Targets

Panel I: Private Equity Targets Panel II: Hedge Fund Targets

CAR Böhmer Test

t–Test Johnson Test

Wilcoxonsigned

rank test

Nobs CAR Böhmer Test


Wilcoxonsigned

rank test

Nobs

Event window Mean z–score t–value J–value z–score Mean z–score t–value J–value z–score

[–20, +20] 7.61% 3.794*** 3.246*** 3.250*** –3.485*** 125 5.41% 2.500** 2.205** 2.199** –2.497** 72

[–20, +10] 8.37% 4.897*** 4.462*** 4.491*** –4.215*** 125 4.29% 2.197** 2.017** 2.017** –2.323** 72

[–10, +10] 7.49% 4.950*** 4.926*** 4.985*** –4.387*** 125 4.55% 2.437** 2.486** 2.525** –2.379** 72

[–5, +10] 7.27% 5.379*** 5.599*** 5.678*** –4.904*** 125 3.33% 1.864* 1.813* 1.856* –1.616 72

[–5, +4] 7.99% 6.152*** 6.408*** 6.547*** –5.434*** 125 2.67% 1.728* 1.623 1.661 –1.689* 72

This table reports the cumulative abnormal returns (CARs) for various event windows, the t-values, the J-value, the Wilcoxon’s and the Böhmer, Masumeci, and Poulsen (1991) z-scores associated with the cumula-tive average abnormal return and tested for statistical signi"cance (CDAX® is the corresponding benchmark). Panel I includes all private equity target "rms (n =125); Panel II includes all hedge fund target "rms (n =72). ***, **, and * indicate statistical signi"cance at the 1%, 5%, and 10% levels, respectively.

In contrast to the target companies, Figure 3 and Table 6 indicate that industry e!ects depend on the type of new investor. On average, the stock price e!ects for industry rivals of private equity investors cause significant and positive market reactions of between 1.78% ([–5,+4]) and 3.9% ([–20,+10]). In contrast, the stock price e!ects for rivals of hedge fund targets are significant and negative, with CARs ranging from –1.85% ([–5,+4]) to –4.65% ([–20,+20]) (see Panels I and II of Table 6 )13. Furthermore, the short-term e!ects for our private equity industry peer group portfolio are in line with those of Servaes and Tamayo (2007), who find a 1.3% stock price reaction following a takeover announce-ment by another firm.

13 The results of Table 6 are statistically significant and robust regardless of whether we define rivals by the three-or-four-digit INDG code or the three-digit SIC industry classification code.


sbr 63 April 2011 151!185170

Figure 3: Cumulative Average Abnormal Returns to Industry Rivals

-6%

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6%

t-25 t-20 t-15 t-10 t-5 t0 t5 t10 t15 t20

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ive

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Hedge Fund Subsample – Rival Reaction

Private Equity Subsample – Rival Reaction

t-30

The graph illustrates the cumulative average abnormal returns of industry rivals to targets of hedge fund (hedge fund subsample) and private equity (private equity subsample) targets from Day -30 through Day +20 relative to the announcement day with CDAX® as the corresponding benchmark.

Table 6: Cumulative Abnormal Returns to Industry Rivals

Panel I: Industry Rivals to Private Equity Targets Panel II: Industry Rivals to Hedge Fund Targets

CAR Böhmer Test


Wilcoxonsigned

rank test

Nobs CAR Böhmer Test


Wilcoxonsigned

rank test

Nobs

Event window Mean z–score t–value J–value z–score Mean z–score t–value J–value z–score

[–20, +20] 3.23% 2.041** 1.963* 1.970* –1.173 201 –4.65% –2.560** –2.841*** –2.844*** –2.922*** 166

[–20, +10] 3.90% 2.927*** 2.825*** 2.840*** –1.936* 201 –2.56% –1.862* –2.003** –1.991** –2.492** 166

[–10, +10] 2.05% 2.452** 2.089** 2.097** –0.948 201 –2.24% –2.281** –2.034** –2.009** –2.824*** 166

[–5, +10] 2.09% 3.017*** 2.517** 2.531** –1.837* 201 –2.03% –2.346** –2.289** –2.294** –2.498** 166

[–5, +4] 1.78% 3.174*** 2.639*** 2.649*** –2.357*** 201 –1.85% –2.499*** –2.565*** –2.583*** –2.708*** 166

***, **, and * indicate statistical signi"cance at the 1%, 5%, and 10% levels, respectively.This table reports the cumulative abnormal returns (CARs) for various event windows, the t-values, the J-value, the Wilcoxon’s and the Böhmer, Masumeci, and Poulsen (1991) z-score associated with the cumulative average abnormal return and tested for statistical signi"cance (CDAX® is the corresponding benchmark). Panel I includes all private equity target "rm industry rivals (n = 201); Panel II includes all hedge fund target "rm industry rivals (n = 166).


sbr 63 April 2011 151!185 171

In Table 6, when we compare stock price reactions of industry rivals to targets acquired by private equity investors with the returns of the hedge fund rivals portfolio, we find that market reactions di!er statistically at the 1% level. "ese results indicate that information signalling e!ects are prevalent within the private equity rival portfolio, but the competitive hypothesis is dominant for industry rivals to hedge fund targets.

In light of corporate governance theories this outcome is particularly interesting, because it indicates that acquisitions of at least 5% of voting rights by di!erent activist shareholders can manifest themselves at industry levels. More important, this finding extends the results of Cronqvist and Fahlenbrach (2009), who document that firm policy and performance di!er in the presence of di!erent large blockholders14.

We find a negative market reaction for rivals to hedge fund targets and positive valuation e!ects for our private equity rival portfolio. "ese findings suggest that heterogeneity across active shareholders plays a significant role in explaining stock returns to industry rival companies. Our results also indicate that the capital markets perceive that an engage-ment of hedge funds in a specific industry leads to an increase in product market compe-tition. Investments of private equity investors indicate, however, a positive information signal about the future of an industry.

4.3 CROSS-SECTIONAL REGRESSION ANALYSIS OF RIVALS’ SHORT-TERM VALUATION EFFECTS

To explore the di!erences in valuation e!ects across the rivals of companies targeted by new institutional investors in the short-term, we use four di!erent cross-sectional regres-sion models. "e first model (Model I) in both tables (Table 7 and 8) includes several primarily explanatory variables, such as Market-to-Book value, Investments, the cross-term HHI*($ROA) which we define as the Herfindahl-Hirschman Index (HHI) multiplied with change in return on assets from the year prior to the announcement relative to the announcement year ($ROA) and size of the company (Ln(Market Cap)). "ese variables indicate the competitive position of the rival company as well as the competitiveness of the industry itself.

Models II and III in Table 7 and 8 di!er only with regard to the variables Cash/Total Liabilities and Current Ratio. However, both models focus on the short-term liquidity situation of the company. Model IV (Robustness) is a robustness check with other finan-

14 The positive market reaction for target companies could be explained by superior stock picking and/or the tim-ing ability of these investors compared to traditional passive investors. We thank a referee for pointing this out. Therefore, observing positive excess returns around the filing date could be the result of selection ability rath-er than the result of (potential) activism. Griffin and Xu (2009) investigate this question in detail and find that hedge funds exhibit no ability to time sectors or to pick better stock styles. Overall, Griffin and Xu (2009) show no conclusive evidence for hedge fund managers’ superior stock picking and timing skills. Given their results, we believe that the capital market reactions that we observe cannot be attributed to superior market timing abili-ties by new institutional investors. However, to strengthen the results, robustness checks on a quantitative basis could be very interesting. Unfortunately, splitting up the data set reduces the number of observations to a level at which statistical test procedures cannot be applied anymore.


sbr 63 April 2011 151!185172

cial variables. We use this model to take care of collinearity between the explanatory variables.

Table 7: Determinants of the Cumulative Abnormal Returns for Hedge Fund Rivals

Industry Rivals to Hedge Fund Targets

Model I Model II Model III Robustness

Constant –0.0238 –0.0178 –0.0669*** –0.0346**

Cash/Total Liabilities – 0.0123*** – –

Current Ratio – – 0.0071 –

Earnings Per Share – – – –0.0003

EBITDA/YrEndMarketCap 0.1375*** 0.1170* 0.1139** –

Equity % Total Capital 0.0001 – – –

Herfindahl Index (HHI) – – – 0.0513

HHI* ($ROA) –0.0011 0.0001 –0.0002 –

Investment –0.0001 – – –0.0011

Ln(Market Cap) 0.0048 –0.0046 0.0029 –

Market to Book Value 0.0020 0.0009 0.0030 –

Price Earnings Ratio –0.0001 – – 0.0001

Target AR 0.1101*** 0.0945** 0.1641*** 0.1342***

Number of Observations 154 121 129 157

adj. R2 0.71% 6.03% 11.56% 0.21%

This table shows the six explanatory models for the hedge fund subsample. The dependent variable is the rival portfolio [–5, +4] event window cumulative abnormal return (CAR). The exogenous determinants are Cash/Total Liabilities equals Cash holdings divided by Total Liabilities, which represents all short- and long-term obli-gations that funds expect to be satis"ed by the company; Current Ratio is current assets over current liabilities; Earnings Per Share represents the earnings for the 12 months ending the "scal year of the company; EBITDA/YrEndMarketCap is EBITDA, which we calculate by taking the pretax income and adding back interest expense on debt and depreciation, depletion and amortization and subtracting interest capitalized, divided by YrEnd-MarketCap (Market Price-Year End * Common Shares Outstanding); Equity % Total Capital = (Common Equity / Total Capital) * 100; Her"ndahl (HHI) is the Her"ndahl-Hirschman index, computed as the sum of squared market shares (based on sales) of all "rms in a given four-digit SIC industry code. We obtain data on market shares from Thomson Financial DataStream using sales at the announcement day; the cross term HHI* ($ROA) equals the Her"ndahl-Hirschman index multiplied with change in return on assets from the year prior to the announcement relative to the announcement year ($ROA); Investment is capital expenditures over lagged net property, plant, and equipment; ln(Market Cap) = logarithm of market value at time of acquisition; Market to Book Value = Market Price-Year End / Book Value Per Share; Price Earnings Ratio = Market Price-Year End / Earn-ings Per Share; Return on Asset = (net income before preferred dividends + ((interest expense on debt-interest capitalized) * (1-tax rate))) / last lagged total assets * 100; Target AR is calculated as the abnormal return of the target during the event window [–5;+4]. We compute all test statistics using White’s (1980) heteroskedas-ticity-consistent covariance matrix.***, **, and * indicate statistical signi"cance at the 1%, 5%, and 10% levels, respectively.


sbr 63 April 2011 151!185 173

Table 8: Determinants of the Cumulative Abnormal Returns for Private Equity Rivals

Industry Rivals to Private Equity Targets

Model I Model II Model III RobustnessConstant 0.0508** 0.0280*** 0.0997*** 0.0063

Cash/Total Liabilities – –0.0200** – –

Current Ratio – – –0.0034 –

Earnings Per Share – – – 0.0015***

EBITDA/YrEndMarketCap –0.0164*** –0.0154*** –0.0186*** –

Equity % Total Capital –0.0003 – – –

Herfindahl Index (HHI) – – – 0.0047

HHI* ($ROA) 0.0000 0.0001 0.0000 –

Investment 0.0061* – – 0.0056*

Ln(Market Cap) –0.0113** –0.0103** –0.0137** –

Market to Book Value 0.0051*** 0.0051*** 0.0051*** –

Price Earnings Ratio 0.0001 – – 0.0001

Target AR –0.0291 –0.0035 –0.0412 0.0044

Number of Observations 134 135 125 159

adj. R2 12.56% 13.05% 14.33% 2.30%

This table shows the six explanatory models for the private equity subsample. The dependent variable is the rival portfolio [–5, +4] event window cumulative abnormal return (CAR). The exogenous determinants are: Cash/Total Liabilities equals Cash holdings divided by Total Liabilities, which represents all short- and long-term obligations that funds expect to be satis"ed by the company; Current Ratio is current assets over current liabilities; Earnings Per Share represents the earnings for the 12 months ending the "scal year of the company; EBITDA/YrEndMarketCap is de"ned as EBITDA, which we calculate by taking the pretax income and adding back interest expense on debt and depreciation, depletion and amortization and subtracting interest capi-talized, divided by YrEndMarketCap (Market Price-Year End * Common Shares Outstanding); Equity % Total Capital = (Common Equity / Total Capital) * 100; Her"ndahl (HHI) is the Her"ndahl-Hirschman index, computed as the sum of squared market shares (based on sales) of all "rms in a given four-digit SIC industry code. We obtain data on market shares from Thomson Financial DataStream using sales at the announcement day; the cross term HHI* ($ROA) equals the Her"ndahl-Hirschman index multiplied with change in return on assets from the year prior to the announcement relative to the announcement year ($ROA); Investment is capital expenditures over lagged net property, plant, and equipment; ln(Market Cap) = logarithm of market value at time of acquisition; Market to Book Value = Market Price-Year End / Book Value Per Share; Price Earnings Ratio = Market Price-Year End / Earnings Per Share; Return on Asset = (net income before preferred dividends + ((interest expense on debt-interest capitalized) * (1-tax rate))) / last lagged total assets * 100; Target AR is calculated as the abnormal return of the target during the event window [–5;+4]. We compute all test statis-tics using White’s (1980) heteroskedasticity-consistent covariance matrix.***, **, and * indicate statistical signi"cance at the 1%, 5%, and 10% levels, respectively.

As can be seen from Model I for the private equity rival subsample in Table 8, firms with higher Market-to-Book values have higher positive announcement returns. "e rationale behind is that the Market-to-Book value also measures whether growth opportunities are already reflected in the current share price. "e higher the ratio, the more growth oppor-tunities are currently reflected in the share price and the better is the expected competitive


sbr 63 April 2011 151!185174

position of the rival in the industry in the future. Furthermore, rivals with high Market-to-Book values have a higher valuation, which increases the likelihood of being acquired or becoming the next target of a private equity fund (see, e.g., Akhigbe, Martin, and Whyte (2007)). In addition, the Investments variable measures the past investments in the infrastructure of the firm. "us, this variable indicates the future returns and competitive market position, since on average higher past investments are followed by higher expected future returns, which can also be seen from Model I. Further, we see that size of the rival company is negatively related to the short-term stock performance. On the one hand, the size of the rival suggests the market position and the ability to respond on an increase in market competition. But on the other hand, there is a negative relation between firm size and the level of information asymmetry which was shown by Helwege, Pirinsky, and Stulz (2007). "ey argue that larger firms are covered by analysts and monitored by institutional investors and regulators more frequently. "is analyst coverage reduces infor-mation asymmetries and the potential agency costs due to, e.g., managerial ine#ciency. Furthermore, the probability of becoming the next target decreases with an increase in firm value (Ambrose and Megginson (1992); Song and Walkling (2000)). Remarkably, we do not find significance for these variables for our hedge fund rivals subsample, which implies that other driving factors are present. Notably, the competiveness of the industry and the rivals’ position within this industry has no e!ect on CARs, but might increase in relevance for the long-term.

In Tables 7 and 8, Models II and III show that the liquidity status for rivals to hedge fund activism is positively related to the short-term capital market reactions. We interpret this finding by the way that industry rivals with higher levels of liquidity can better react to competitive challenges. We do not find this relation for rivals to private equity targets.

When considering the robustness check (Table 8, Robustness Model), we see that all the above-mentioned relations remain stable. We also find that Earnings per Share is a positive driver of the short-term reaction for rivals of private equity activism. "is result can be explained by the way that higher Earnings per Share increase the attractiveness of the firm for future private equity investments, which results in a higher acquisition probability.

Our results support our hypothesis that private equity and hedge fund engagements are driven by di!erent motives, and suggest a link between the information signalling hypoth-esis and private equity activism on the one hand, and the competition hypothesis and hedge fund activism on the other hand.

4.4 LONG-TERM VALUATION EFFECTS TO TARGETS AND INDUSTRY RIVALS

"e long-term stock valuation e!ects for targets firms of both investors are reported in Table 9. "e table shows that the long-term buy-and-hold abnormal returns for the hedge funds and the private equity target portfolio, even after we correct for the Fama


sbr 63 April 2011 151!185 175

and French (1993) factors, exhibit profound di!erences from each other15. "e median BHARs for the private equity target portfolio are significant and positive over all holding periods, i.e., for the 150-day period as well as for the 300-day period. In contrast, the median BHARs for the hedge funds target portfolio are not significantly di!erent from zero; the sign is even negative over most holding periods.

"e overall picture looks di!erent if we compare the mean BHARs (see Table 9). However, these results are driven by just a few outliers. To check for robustness, we winsorize the BHARs at the 1% and 99% level, and found that the results remain stable. Hence, in the long-run, private equity targets perform better than the market. "ey also outperform the hedge fund targets, which cannot beat the market.

Table 9: Fama and French (1993), Buy-and-Hold Abnormal Returns to Targets

Panel I: Private Equity Subsample – Target Reactions

Panel II: Hedge Fund Subsample – Target Reactions

t-Test Wilcoxon signed rank

test

t-Test Wilcoxon signed

rank test

Window (in days)

Mean BHARs

Median BHARs t–value z–score Nobs

Mean BHARs

Median BHARs t–value z–score Nobs

[0;+150] 6.84% 6.40% 2.161** –1.961** 123 11.97% –1.48% 1.773* –0.786 72

[0;+200] 10.21% 7.33% 2.764*** –2.501** 123 18.07% –0.07% 1.734* –0.926 72

[0;+250] 9.28% 6.59% 2.150** –1.803* 122 17.41% –4.40% 1.559 –0.685 72

[0;+300] 12.02% 10.78% 2.570** –2.196** 122 18.68% 2.57% 1.662 –0.819 72

This table reports the Fama and French (1993) buy-and-hold abnormal returns (BHARs) for 150-, 200-, 250-, and 300-day holding periods. Panel I includes all private equity target "rms (n = 125); and Panel II includes all hedge fund target "rm industry rivals (n = 78). We test the mean (t-test) and median (Wilcoxon rank sum test) BHARs for all holding periods compared to their di#erence from zero. ***, **, and * indicate statistical signi"cance at the 1%, 5%, and 10% levels, respectively.

Even more interesting to us are the findings in Table 10 and Figure 4, in which we examine the long-term e!ects for the respective industry rivals. Here again the medians are more reliable because of some outliers. We find that the median BHARs for the portfolio of industry rivals to private equity target firms are not significantly di!erent from zero over all event windows. However, the median BHARs for the hedge fund rivals portfolio are strongly positive at a 1% significance level over every holding period.

15 We also calculate long-term returns based on other algorithms, such as calendar-time (see, e.g., Jagadeesh and Karceski (2009)) approaches. Furthermore, we apply other tests to control for the skewness bias or to capture possible event-induced increases in variance. Tables are available on request from the authors.


sbr 63 April 2011 151!185176

Figure 4: Fama and French (1993) Buy-and-Hold Abnormal Returns to Industry Rivals

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

22%

24%

t0 t25 t50 t75 t100 t125 t150 t175 t200 t225 t250 t275 t300

Fam

a-Fr

ench

Buy

-and

-Hol

d Re

turn

s


Hedge Fund Subsample - Rival Reaction

Private Equity Subsample - Rival Reaction

The graph illustrates the Fama and French (1993) mean buy-and-hold abnormal returns for the private eq-uity and the hedge fund subsample from Day-0 through Day+300 relative to the announcement day.

Table 10: Fama and French (1993), Buy-and-Hold Abnormal Returns to Industry Rivals

Panel I: Private Equity Subsample – Rival Reactions

Panel II: Hedge Fund Subsample – Rival Reactions

t–Test Wilcoxon signed rank

test

t–Test Wilcoxon signed

rank test

Window (in days)

Mean BHARs

Median BHARs

t–value z–score Nobs Mean BHARs

Median BHARs

t–value z–score Nobs

[0;+150] 8.04% 0.42% 2.218** –0.616 183 10.72% 4.92% 3.311*** –2.305** 166

[0;+200] 9.15% 1.36% 2.440** –1.172 183 16.07% 8.44% 4.059*** –3.572*** 166

[0;+250] 9.85% 0.34% 2.380** –0.914 183 22.43% 9.67% 3.971*** –3.717*** 166

[0;+300] 16.68% 2.71% 3.027*** –1.541 183 22.71% 8.29% 3.854*** –3.221*** 166

This table reports the Fama and French (1993) buy-and-hold abnormal returns (BHARs) for 150-, 200-, 250-, and 300-day holding periods. Panel I includes all private equity target "rm industry rivals (n = 201); and Panel II includes all hedge fund target "rm industry rivals (n = 166). We test the mean (t-test) and median (Wilcoxon rank sum test) BHARs for all holding periods compared to their di#erence from zero. ***, **, and * indicate statistical signi"cance at the 1%, 5%, and 10% levels, respectively.


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4.5 CROSS-SECTIONAL REGRESSION ANALYSIS OF RIVALS’ LONG-TERM VALUATION EFFECTS

"e results of the cross-sectional BHARs regressions for the private equity targets industry rivals and the hedge fund targets industry rivals are displayed in Table 11. Model I is a specification in which we include explanatory variables such as Market-to-Book value, change in Return on Assets, and the Herfindahl-Hirshman Index. Model II contains financial variables such as the Current Ratio, Earnings per Share, and equity over total capital. Model III again is a robustness check with other financial variables.

From Model I we see that industry rivals to private equity targets with a major increase in Return on Assets and with a higher Market-to-Book value perform better in the long-run. Also, the competitiveness of the industry has a positive e!ect on the BHARs. Hence, this result suggests that more competitive rivals show a higher performance. "is finding is exactly what we expect in the longer-term. While private equity firms address persistent agency conflicts in the target companies and try to improve their strategic positioning, it should be the case that only the very competitive rival firms can resist such a competitive pressure. Further, the results are more pronounced in markets with a higher degree of competitiveness. It should also be noted that none of these variables are significant for our hedge fund rivals sample, which suggests that other forces are at work.

From Model II and the robustness check (Model III) in Table 11 we can infer that the liquidity status of the rival companies (Cash/Total Liabilities and Current Ratio) has no e!ect on the abnormal returns for our private equity rival subsample. Again, the results di!er for the hedge fund sample. Here, the current ratio has a strong positive e!ect on the BHARs. "e results indicates that short-term financial aspects play a role in explaining the long-term performance of hedge funds targets rival companies, but only in case of hedge funds activism. For private equity funds, other considerations, i.e., the long-term competitive position, are apparently more relevant16.

16 The question remains, whether the effects will be stronger in case that private equity investors acquire a majori-ty stake in the target company as we then expect the investor to be in a position to implement a clear sharehold-er value orientation. However, our actual sample size is too small to conduct this analysis in a satisfactory way. Furthermore, it is not clear that a larger block of voting rights will cause stronger effects than a smaller stake. We know from anecdotic evidence that hedge fund investors are more aggressive investors and have quite often the ability to convince other blockholders to vote in favor of their interest. In contrast, private equity investors also seek to reach a consensus in corporate activities and, therefore, they can be regarded as less aggressive. As a con-sequence a larger stake of voting rights do not necessarily result in stronger effects as enforcement power (voting rights) and investor’s aggressiveness are partially offsetting each other. We believe that this is an interesting topic for a subsequent paper.


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Table 11: Cross-Sectional Fama and French (1993), Buy-and-Hold Abnormal Returns Regressions

Industry Rivals to Private Equity Targets

Industry Rivals to Hedge Fund Targets

Model I Model II Modell III Model I Model II Modell III

Constant 0.3645 0.4152 0.6125*** –0.0613 –0.0701 0.3242

Cash/Total Liabilities – – –0.0437 – – 0.0126

Current Ratio – 0.0037 – – 0.0607** –

$ROA 0.0204*** – 0.0107 – –

Earnings Per Share – 0.0127*** 0.0152*** –0.0303 0.0035*

EBITDA/YrEndMarketCap

–0.1403*** – – 1.1500** – –

Equity % Total Capital – –0.0026 – – –0.0018

Herfindahl Index (HHI) –0.4555* – –0.7500** –0.2712 – 0.1149

Investment –0.0380** – – 0.0221 – –

Ln(Market Cap) – – 0.1617** – – –0.0345

Market-to-Book-Value

0.0220*** 0.0270*** – 0.0736* 0.0929** –

Price Earnings Ratio –0.0012* –0.0019** – –0.0007 0.0003 –

Target AR – –1.0197* –1.2411** – 0.1072 –0.2501

Number of Observations

163 125 103 158 130 124

adj. R2 18.24% 5.91% 4.59% 10.13% 14.28% 2.21%

This table shows the results of cross-sectional regressions of 300-day private equity target industry rival Fama and French (1993) buy-and-hold abnormal returns (BHARs) on the following explanatory variables: Cash/Total Liabilities equals Cash holdings divided by Total Liabilities, which represents all short- and long-term obliga-tions that funds expect to be satis"ed by the company; Current Ratio is current assets over current liabilities; Change in return on assets ($ROA) is from the year prior to the announcement relative to the announcement year; Earnings Per Share represents the earnings for the 12 months ending the "scal year of the company; EBITDA/YrEndMarketCap is EBITDA, which we calculate by taking the pretax income and adding back interest expense on debt and depreciation, depletion and amortization and subtracting interest capitalized, divided by YrEndMarketCap (Market Price-Year End * Common Shares Outstanding); Equity % Total Capital = (Common Equity / Total Capital) * 100; Her"ndahl (HHI) is the Her"ndahl-Hirschman index, computed as the sum of squared market shares (based on sales) of all "rms in a given four-digit SIC industry code. We obtain data on market shares from Thomson Financial DataStream using sales at the announcement day; Investment is capital expenditures over lagged net property, plant, and equipment; ln(Market Cap) = logarithm of market value at time of acquisition; Market to Book Value = Market Price-Year End / Book Value Per Share; Price Earn-ings Ratio = Market Price-Year End / Earnings Per Share; Return on Asset = (net income before preferred divi-dends + ((interest expense on debt-interest capitalized) * (one-tax rate))) / last lagged total assets * 100; Target AR is the abnormal return of the target during the event window [–5;+4]. We compute all test statistics using White’s (1980) heteroskedasticity-consistent covariance matrix.***, **, and * indicate statistical signi"cance at the 1%, 5%, and 10% levels, respectively.


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4.6 THE MODEL OF ALLEN, CARLET TI, AND MARQUEZ (2009): A FRAMEWORK FOR EXPLAINING THE RESULTS

How can we explain the overall empirical results of our study? An explanation based on the model of Allen, Carletti, and Marquez (2009) will be sketched in this section. We found this model extremely suggestive since it allows us to interpret our results in a consistent framework, thereby integrating the information signalling and competition considerations mentioned in the paper.

Allen, Carletti, and Marquez (2009) use a standard two-period duopoly model to analyze the advantages and disadvantages of stakeholder-oriented firms that compete with share-holder firms. "e stakeholder-oriented firm is concerned with employees and suppliers, weighting in its objective function not only the interests of shareholders but also other stakeholders of the firm. "e idea is that these stakeholders earn rents from transacting with the firm, but only if the firm survives. If the firm does not survive, then the stake-holders have to search for new job or product opportunities, which results in private costs for them. Hence, a stakeholder-oriented firm takes these costs and benefits into account. Compared to a firm that maximizes the shareholder value, the stakeholder-friendly firm behaves in a way that increases its probability of survival, which in turn benefits stake-holders. Since in the first period firms are subject to random shocks, which in prin-ciple can stem from marginal cost uncertainty and demand uncertainty, they need to be concerned about the probability of bankruptcy, that is, how to survive until the second period. Hence, when they choose prices in the first period, stakeholder-oriented firms consider the probability of not surviving. Interestingly, stakeholder governance only leads to a softening of competition if firms face cost uncertainty: when firms are uncertain about what their cost will be, they are more cautious and set higher prices in order to make sure that they are covering their costs. However, higher prices mean lower competition which, in turn, results in higher profits for the firms in markets with imperfect competition. In contrast, with demand uncertainty, the stakeholder-oriented firms set very low prices in order to assure themselves of having at least some sales if demand turns out to be low. Since this behaviour increases competition and, hence, diminishes overall firm value, only in such a case stakeholder interests and those of shareholders are not aligned: stakeholder governance reduces shareholder value.

Here, we look at the model implications for the case in which stakeholder and shareholder firms compete with each other. Our analysis suggests that even when stakeholder orienta-tion is beneficial, shareholder firms profit the most because they can free-ride on stake-holder competitors, thus increasing their value relative to the case in which they compete with other shareholder-oriented firms. For stakeholder-oriented firms it is the other way around: they are worse o! when competing with a shareholder firm.

"e empirical results from our study support the model’s predictions. If we see hedge funds as investors with a particularly strong short-term shareholder orientation and the


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German corporate governance as stakeholder-friendly17, then we can interpret the short-term results in terms of a shareholder-oriented firm, i.e., the hedge fund target, competing with stakeholder firms. "is result can explain the particularly large positive short-term announcement e!ects of the hedge funds targets and the negative short-term announce-ment e!ects of the respective industry rivals. "e shareholders of the stakeholder-oriented rivals anticipate the behavior of the shareholder-oriented competitor, which implies a lower value for the stakeholder firms.

For private equity activism, the short-term announcement e!ects are also positive, although on a lower level. But here we observe positive short-term e!ects for the industry rivals as well, thus we should interpret the private equity investment not as being driven mainly by a pure short-term shareholder motive, but as investors who are typically long-term oriented. "ey address persistent agency conflicts and therefore adapt themselves better to the local corporate governance environment. Since the information spill-over e!ects are dominant in such a case, we see the positive short-term stock market reaction of the rivals. Our short-term cross-sectional regression results support this interpretation.

One way to explain the long-term valuation e!ects, which also follows Allen, Carletti, and Marquez (2009), is that hedge fund investors encounter greater resistance to imple-menting the short-term shareholder value-maximization principle. "is resistance may come either from inside the firm, i.e., other stakeholders, or from external sources such as pressure put by existing rival firms or stakeholders on the government to step in to support the stakeholder society. Initially, if the hedge fund management, and also the targets’ and the rivals’ shareholders, underestimate the resistance, then the result is the long-term return drifts as shown in our analysis. Shareholders and the hedge fund management learn over the long-term that the implementation of a pure shareholder orientation is not only di#cult in a corporate governance system such as that found in Germany, but also in many cases it is virtually impossible. Allen, Carletti, and Marquez (2009) find that the entry of an extremely shareholder-oriented firm into an otherwise stakeholder-dominated society is not successful in the long-run18. And of course, this implication is reflected in the long-term share price development of the hedge fund target and its corresponding rival companies. "us, we observe the long-run negative return drift for the target firms and the positive return drift for the rival firms.

17 The focus on stakeholders is not only in line with German corporate law, but also a focus on single groups with an interest in a company is against the law (Schmidt (2004)). For further information on the role of employees, union representatives or banks, see Schmidt (2004) and the references therein. Additionally, and in contrast to an Anglo-Saxon outsider-controlled system that relies on market mechanisms, insider-controlled systems focus on the interests of different groups of stakeholders, i.e., blockholders, employees, union representatives, or banks (Schmidt (2004); Hackethal, Schmidt, and Tyrell (2006)). The interests of these different stakeholders are im-posed via the supervisory board, which can, for example, hire or fire executives. However, the composition of the advisory board is critical, because it determines the potential influence individual stakeholders will have on man-agement (Schmidt (2004)).

18 This entry is particularly difficult if the corporate governance system is a system composed of a consistent config-uration of complementary elements. In fact, as demonstrated by Hackethal, Schmidt, and Tyrell (2002; 2006), in the past the German corporate governance system exhibited these features by being an insider control system with a clear stakeholder orientation. Whether this is still the case today, remains an open question.


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We note that such an underestimation explanation is not unusual for empirical studies that deal with corporate governance issues. In their paper on the relation between corporate governance and equity prices Gompers, Ishii, and Metrick (2003) find strong evidence that supports the underestimation hypothesis. Moreover, the fact that hedge fund activism is a recent phenomenon for the German capital market also emphasizes this explanation19.

5 CONCLUSION

In this paper we examine the valuation e!ects of targets and industry rivals to firms targeted by hedge funds and private equity investors. Since our target and rival firms are located in Germany, these activist investors, who try to change the status quo of firms through “voice”, must function in a corporate governance environment that is character-ized by a strong stakeholder orientation. Our results suggest that hedge funds in particular encounter strong resistance to their e!orts to increase shareholder value. Private equity funds seem to be more successful at creating shareholder value, which could be due to their longer-term perspective and a higher adaptability to the surrounding corporate governance.

One implication of our analysis is that in Germany, the extent to which hedge fund activism can have pervasive e!ects on corporate governance is limited. "is result is in line with a new study from the U.S. (Greenwood and Schor (2009)), in which the authors find that hedge funds primarily invest in small, undervalued companies. "eir goal is to have those targets which are bought out later on by some other investors. Since many hedge funds targets in the U.S. are taken over within 18 months, the high returns documented around the announcement of an investment by an activist hedge fund reflect the expecta-tion of investors that target firms will be acquired later on at a premium to the current stock price. Greenwood and Schor (2009) conclude that the activist hedge funds are not really interested in making corporate governance changes that might improve the firm.

Also in Germany we observe that there are positive short-term abnormal returns when activist hedge funds invest in a company, but for another reason. Because of concentrated ownership structures and the predominance of a stakeholder regime in Germany, activist hedge funds cannot force target firms into takeovers. "erefore, the short-term results can only be explained along the lines of the Allen, Carletti, and Marquez (2009) study, since shareholder-driven firms benefit from competition with stakeholder firms. However, as our long-term results show, investors overestimate the ability of hedge funds to overcome the resistance to far-reaching changes in the corporate governance.

19 We also analyze whether long-term effects are reduced over time through learning. Therefore, we construct vari-ous subsamples for different time periods and compare their mean and median long-term abnormal returns. We cannot detect significant decreasing long-term returns to either private equity or hedge fund rivals or targets. However, this result could be due to our small sample size.


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APPENDIX: VARIABLE DEFINITIONS

Variable Name Definition

%Closely Held Shares A measure of insider ownership, which we define as number of closely held shares over common shares outstanding.

$ROA Change in return on assets from the year prior to the announcement relative to the announcement year.

Cash Holdings Cash holdings is cash and short-term investments over lagged net property, plant, and equipment.

Cash/Total Liabilities Cash holdings divided by total liabilities, which represents all short- and long-term obligations that the fund expects to be satisfied by the company.

Cash/YrEndMarketCap The proportion of cash holdings to the year-end market capitalization.

Current Ratio Current assets over current liabilities.Dividend Payout per Share Dividend payout per share, which we define as dividends

per share divided by earnings per share.Earnings Per Share Earnings Per Share represent the earnings for the 12 months

ending the fiscal year of the company.EBITDA/YrEndMarketCap

EBITDA, which we calculate by taking the pretax income and adding back interest expense on debt and depreciation, depletion and amortization and subtracting interest capitalized, divided by year end market capitalization.

Equity % Total Capital Common equity divided by total capital.HHI Herfindahl-Hirschman Index, computed as the sum

of squared shares (based on sales) of all firms in a given four-digit SIC industry code.

Investment Investment, which we define as capital expenditures divided by net property, plant and equipment at the end of the previous year. It measures a company’s investment policy.

Ln(Market Cap) Natural logarithm of year-end market capitalization.

Market to Book Value The market-to-book ratio of equity, which we define as the market value of equity divided by the book value of equity.

Price Earnings Ratio The price earnings ratio, which we calculate as the ratio of price per share at year-end to earnings per share.

Target AR Target AR, which we calculate as the abnormal return of the target during the event window [–5;+4].

Total Assets The total assets in millions of dollars. YrEndMarketCap The year-end market capitalization in millions of dollars.


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