TY - JOUR
AU - Wagner, Hannes F.
AB - This paper provides evidence on the incidence, characteristics, and performance of activist engagements across countries. We find that the incidence of activism is greatest with high institutional ownership, particularly for U.S. institutions. We use a sample of 1,740 activist engagements across 23 countries and find that almost one-quarter of engagements are by multi-activists engaging the same target. These engagements perform strikingly better than single activist engagements. Engagement outcomes, such as board changes and takeovers, vary across countries and significantly contribute to the returns to activism. Japan is an exception, with high initial expectations and low outcomes. Received March 3, 2015; editorial decision December 21, 2016 by Editor Andrew Karolyi. This paper provides evidence on the incidence, characteristics, and performance of activist engagements across countries. The scope of this paper allows us to address the question of how different patterns of ownership and institutional arrangements influence the growth and performance of activism. Our paper is the first comparative study of publicly observable activism across 23 countries in Asia, Europe, and North America. We analyze 1,740 activist interventions, mainly initiated by hedge funds and focus funds, for the 2000-2010 period. The three largest markets for shareholder activism are the United States (1,125 interventions), Japan (184 interventions), and the United Kingdom (165 interventions). Despite this apparent concentration, activism is a significant phenomenon relative to the size of stock markets in other countries (e.g., Italy). Further, because activists hold limited stakes—11%, on average—they require the support of other investors, including pension funds and other activists. We interpret our results as showing that the pattern of ownership is an important source of influence on activism activity across countries. Our sample covers 330 different activist funds. Most funds have a clear domestic focus, but foreign engagements account for 24% of the total, roughly equally split between U.S.-based and non-U.S.-based activists, allowing us to compare domestic and foreign models of activism. Hedge fund engagements frequently involve more than one hedge fund (“wolf pack”) that may coordinate formally or informally. We estimate that wolf packs are associated with almost one quarter of all engagements and we show that they achieve some of the highest returns for target shareholders. How do activist engagements perform? The conventional measure of activists’ performance is the abnormal return around the public announcement of the activist’s stake. We find abnormal announcement returns of 7.0% for the United States during a (⁠|$-$|20, 20) day window, which are virtually identical to those reported by Brav et al. (2008) and related studies. The European and Asian announcement returns are significant at 4.8% and 6.4%, respectively, and are comparable to the United States. How successful are activists in their engagements with target firms? For this analysis, we identify the outcomes of each engagement, including changes to payout policy, governance, corporate restructuring and takeovers. Compiling data on activist outcomes internationally is particularly challenging; while activists engaging U.S.-listed firms need to provide information on the stated purpose of their investment in Schedule 13D filings, no exact equivalent exists elsewhere. Through extensive news searches, we identify outcomes of the engagements. For the entire sample, the unconditional probability of an activist being successful in achieving at least one engagement outcome is 53%. However, the incidence of outcomes varies considerably across countries. In North America activists achieve outcomes in 61% of all engagements and 50% in Europe, but only 18% in Asia. Japan, in particular, is a country of unfulfilled expectations with high disclosure returns but very few outcomes. We also show that the incidence of engagement outcomes and the type of outcome dramatically affect the abnormal returns over the entire engagement, from block disclosure to exit. The announcement of an engagement outcome contributes significantly to holding period returns during the engagement. Abnormal returns around the announcement of outcomes average 6.4% across all countries during a (⁠|$-$|20, 20) window, with the highest returns of 8.8% in Europe, 6.0% in North America and 2.7% in Asia. These returns are in addition to the block disclosure returns for the subsample of engagements with successful outcomes. To investigate the potential importance of governance changes initiated by the activist, we test whether engagements with multiple outcomes, for example, a board change or spin-off followed by a takeover, have a higher total return than a single outcome, such as a takeover. The differences are striking, particularly engagements with multiple outcomes that involve a takeover have abnormal returns of 18.1%, whereas those engagements with only the outcome of a takeover have abnormal returns of roughly half that size (9.7%). Disclosure returns should reflect the expected value from a successful engagement with an outcome and the expected value from a “no outcome” result, weighted by their respective probabilities. When it becomes clear that there will be no successful engagement, we expect the stock price reaction to the block disclosure announcement to reverse itself. To test this, we compare abnormal returns from the first disclosure date of the engagement by the activist to its disclosed exit for two subsamples of engagements, with and without outcomes. On an annualized basis using a Fama-French four-factor model, activism with outcomes generates value-weighted abnormal returns over the engagement period of 8.0%, compared with 2.3% for activism without outcomes. When returns are equal-weighted, activism with outcomes generates annualized abnormal returns of just 1.1%, compared with minus 9.8% without. Activism therefore generates positive alpha on average in large firms, but in all engagements the returns crucially depend on the activist achieving outcomes. The differences are economically significant, and usually statistically significant. Our interpretation is that the achievement of outcomes resolves the uncertainty at the block disclosure date about the activist’s chances of success.1 Results by region confirm that outcomes are always crucial for generating positive abnormal returns. Our results make several contributions to the literature. To our knowledge, we are the first to document the incidence, performance, and specific outcomes of activist engagements for a large cross-section of companies in different countries. We base our analysis on a standardized set of engagements and engagement outcomes that allows us to perform tests across jurisdictions. Second, we extend prior work by Clifford (2008), Klein and Zur (2008), Gantchev (2013), Bebchuk, Brav, and Jiang (2014), Brav et al. (2014), and particularly Brav et al. (2008), and Greenwood and Schor (2009), who analyze the short-term and long-term performance of U.S. target firms. We show that activism outside the United States similarly depends on the activist achieving outcomes. We also show that takeovers that are preceded by governance changes, such as a board turnover or other restructurings, are much more profitable than takeovers on their own. This result extends and modifies the evidence in Greenwood and Schor (2009), who argue that activists “put companies into play.” Third, we use our international data set to compare domestic against foreign activism and U.S. activists against their foreign peers. Most prior research has focused on domestic activism in the United States, and our paper is the first to compare the performance of U.S. activists at home with the performance of U.S. activists abroad, as well as a comparison of other non-U.S. activists at home and abroad. We find that domestic activism outperforms foreign activism, everywhere. Fourth, our findings complement the prior literature focusing on the role of institutional investors and specifically foreign institutional investors for shareholder value (e.g., Gillan and Starks 2003; Ferreira and Matos 2008; Leuz, Lins, and Warnock 2009; Aggarwal et al. 2009; especially Aggarwal et al. 2011). This paper shows that hedge fund activism is an important channel of influence for institutional investors. Hedge fund activists seek out targets with high institutional ownership; outside the United States, foreign and, in particular, (foreign) U.S. institutions play a key role. The results are consistent with case study evidence that shows that domestic institutional investors are less willing to collaborate with more aggressive U.S. or U.K. activists. Fifth, we provide the first comprehensive evidence of hedge fund wolf packs internationally. Wolf pack formation is a choice variable for the activist, and conditional on a wolf pack arising, it is the most profitable type of engagement, reflecting the high probability of achieving successful outcomes. The success of wolf packs is related only in small part to their larger aggregated stakes. This is consistent with highly profitable engagements attracting multiple funds. However, we cannot distinguish whether the superior performance is due to active coordination amongst the hedge funds or simply the congregation of like-minded investors who expect a highly profitable engagement. Our results contribute to the emerging literature on hedge fund wolf packs (see Brav, Dasgupta, and Mathews 2016; Coffee and Palia 2016). 1. Data Description 1.1 Database construction We construct an international database of hedge fund activist engagements that includes 23 countries from three regions, Asia, Europe, and North America. The data were hand-collected for Asia, Europe, and Canada; for the United States, we relied on 13D Monitor, a commercial provider. The data include the initial disclosure date of the activist block, the block size, the identity, and country of origin of the activist and the date when the engagement was completed. In addition, we collected data on the successful outcomes of each hedge fund activist engagement, in particular on takeovers, other types of corporate restructuring, board changes and changes in payout policy. We describe in the Internet Appendix the search process, the data sources across countries, and how our U.S. data compare to those compiled by Brav et al. (2008). The final database includes 1,740 publicly disclosed hedge fund interventions in publicly traded firms initiated between January 2000 and December 2010.2Figure 1 describes the timeline of a stylized activist engagement from entry (t|$=$|1) to exit (t|$=$|3).3 In case there are successful engagement outcomes reported during the holding period, these are classified by type and recorded with their earliest announcement dates (t|$=$|2). It is possible that there are multiple outcome announcements, for example, a board change announcement that precedes a takeover announcement. Figure 1 Open in new tabDownload slide Activist engagement time line. Figure 1 Open in new tabDownload slide Activist engagement time line. We combine the hedge fund activist database with data from several other sources. We obtain from the FactSet ownership database (Lionshares) detailed information on the institutional investor holdings for all firms included in our data set.4 FactSet data are available for 45 countries, including the 23 countries for which we observe at least one hedge fund activist engagement during the sample period. The data cover institutional investors’ equity holdings collected directly from fund reports, regulatory filings, and the fund management companies themselves; they include ordinary shares, preferred shares, ADRs, Global Depositary Receipts (GDRs), and dual listings. We rely on the methodology of Ferreira and Matos (2008) to obtain statistics on institutional holdings that include the overall ownership of domestic and foreign institutions, broken down into U.S.-domiciled and non-U.S. domiciled institutions. To complete the database at the company level, we obtain annual firm financials from Factset Fundamentals, and daily stock prices and trading volume data from CRSP for U.S. firms and from Datastream for non-U.S. firms. At the country level, we collect data on the institutional and legal environment, including Market cap/GDP, Rule of Law, and Control of Corruption; the minimum regulatory disclosure threshold for blockholders; the Common Law indicator and the Revised Anti-Director Rights index from Djankov et al. (2008) and the G|$_{\mathrm{44}}$|Quality of Governance index and its components from Aggarwal et al. (2009). 1.2 Activism across countries Table 1 reports our sample of activist engagements, broken down by country, and a number of country-level metrics related to activism. Table 1 Hedge fund activism across countries . . . . . . . Subsample of engagements with FS coverage . FS firm population . Country . Number of engage-ments . Fraction wolf-packs . Fraction foreign activists . Fraction U.S. foreign activist . Fraction of shares held by hedge fund activist(s) . Regulatory disclosure threshold . Market cap US|${\$}$| (median) . Fraction held by inst. inv. (median) . Market cap US|${\$}$| (median) . Fraction held by inst. inv., 25th pctile . Fraction held by inst. inv., 50th pctile . Fraction held by inst. inv., 75th pctile . Region: Asia Hong Kong 7 0.00 1.00 0.14 0.11 0.05 4,290 0.12 252 0.01 0.04 0.12 Israel 1 0.00 1.00 1.00 0.10 0.05 – – 121 0.01 0.03 0.12 Japan 184 0.10 0.73 0.42 0.13 0.05 360 0.07 241 0.01 0.04 0.09 South Korea 23 0.09 0.22 0.17 0.10 0.05 256 0.04 158 0.00 0.03 0.09 Region: Europe Austria 1 0.00 1.00 1.00 0.05 0.05 – – 330 0.02 0.08 0.16 Belgium 9 0.00 0.44 0.33 0.07 0.05 3,105 0.23 221 0.02 0.06 0.14 Denmark 1 0.00 1.00 0.00 0.05 0.05 1,092 0.28 193 0.03 0.14 0.23 Finland 3 0.00 1.00 0.00 0.08 0.05 147 0.53 197 0.06 0.18 0.29 France 27 0.22 0.78 0.56 0.11 0.05 4,548 0.32 173 0.02 0.07 0.16 Germany 53 0.32 1.00 0.53 0.08 0.03 2,089 0.22 149 0.02 0.08 0.20 Greece 3 0.00 1.00 0.00 0.08 0.05 14,961 0.22 200 0.00 0.01 0.08 Ireland 2 0.00 1.00 0.50 0.05 0.05 2,090 0.48 187 0.09 0.19 0.32 Italy 42 0.19 0.86 0.48 0.05 0.02 2,533 0.13 373 0.02 0.06 0.14 Luxembourg 5 0.00 1.00 0.20 0.03 0.05 26,294 0.12 506 0.01 0.10 0.26 Netherlands 22 0.27 1.00 0.32 0.10 0.05 1134 0.33 615 0.10 0.22 0.39 Norway 7 0.00 1.00 0.29 0.11 0.05 738 0.35 188 0.06 0.14 0.26 Portugal 1 0.00 1.00 0.00 0.01 0.05 8,878 0.10 389 0.02 0.06 0.12 Spain 5 0.00 1.00 0.00 0.05 0.05 165 0.11 929 0.02 0.08 0.16 Sweden 15 0.27 0.60 0.00 0.08 0.05 1,407 0.36 146 0.06 0.17 0.33 Switzerland 19 0.11 0.68 0.26 0.14 0.03 775 0.30 475 0.03 0.13 0.26 U.K. 165 0.12 0.38 0.23 0.13 0.03 278 0.27 97 0.09 0.20 0.32 Region: North America Canada 20 0.00 0.75 0.70 0.16 0.10 2,475 0.41 87 0.05 0.13 0.30 U.S. 1,125 0.26 0.01 0.00 0.11 0.05 359 0.77 203 0.11 0.43 0.78 Asia 214 0.09 0.68 0.39 0.12 – 360 0.07 224 0.01 0.04 0.09 Europe 381 0.17 0.66 0.32 0.10 – 1,411 0.24 180 0.04 0.12 0.25 N. America 1,145 0.26 0.02 0.01 0.11 – 370 0.77 181 0.09 0.35 0.74 Total 1,740 0.22 0.24 0.13 0.11 – 423 0.56 201 0.02 0.10 0.32 . . . . . . . Subsample of engagements with FS coverage . FS firm population . Country . Number of engage-ments . Fraction wolf-packs . Fraction foreign activists . Fraction U.S. foreign activist . Fraction of shares held by hedge fund activist(s) . Regulatory disclosure threshold . Market cap US|${\$}$| (median) . Fraction held by inst. inv. (median) . Market cap US|${\$}$| (median) . Fraction held by inst. inv., 25th pctile . Fraction held by inst. inv., 50th pctile . Fraction held by inst. inv., 75th pctile . Region: Asia Hong Kong 7 0.00 1.00 0.14 0.11 0.05 4,290 0.12 252 0.01 0.04 0.12 Israel 1 0.00 1.00 1.00 0.10 0.05 – – 121 0.01 0.03 0.12 Japan 184 0.10 0.73 0.42 0.13 0.05 360 0.07 241 0.01 0.04 0.09 South Korea 23 0.09 0.22 0.17 0.10 0.05 256 0.04 158 0.00 0.03 0.09 Region: Europe Austria 1 0.00 1.00 1.00 0.05 0.05 – – 330 0.02 0.08 0.16 Belgium 9 0.00 0.44 0.33 0.07 0.05 3,105 0.23 221 0.02 0.06 0.14 Denmark 1 0.00 1.00 0.00 0.05 0.05 1,092 0.28 193 0.03 0.14 0.23 Finland 3 0.00 1.00 0.00 0.08 0.05 147 0.53 197 0.06 0.18 0.29 France 27 0.22 0.78 0.56 0.11 0.05 4,548 0.32 173 0.02 0.07 0.16 Germany 53 0.32 1.00 0.53 0.08 0.03 2,089 0.22 149 0.02 0.08 0.20 Greece 3 0.00 1.00 0.00 0.08 0.05 14,961 0.22 200 0.00 0.01 0.08 Ireland 2 0.00 1.00 0.50 0.05 0.05 2,090 0.48 187 0.09 0.19 0.32 Italy 42 0.19 0.86 0.48 0.05 0.02 2,533 0.13 373 0.02 0.06 0.14 Luxembourg 5 0.00 1.00 0.20 0.03 0.05 26,294 0.12 506 0.01 0.10 0.26 Netherlands 22 0.27 1.00 0.32 0.10 0.05 1134 0.33 615 0.10 0.22 0.39 Norway 7 0.00 1.00 0.29 0.11 0.05 738 0.35 188 0.06 0.14 0.26 Portugal 1 0.00 1.00 0.00 0.01 0.05 8,878 0.10 389 0.02 0.06 0.12 Spain 5 0.00 1.00 0.00 0.05 0.05 165 0.11 929 0.02 0.08 0.16 Sweden 15 0.27 0.60 0.00 0.08 0.05 1,407 0.36 146 0.06 0.17 0.33 Switzerland 19 0.11 0.68 0.26 0.14 0.03 775 0.30 475 0.03 0.13 0.26 U.K. 165 0.12 0.38 0.23 0.13 0.03 278 0.27 97 0.09 0.20 0.32 Region: North America Canada 20 0.00 0.75 0.70 0.16 0.10 2,475 0.41 87 0.05 0.13 0.30 U.S. 1,125 0.26 0.01 0.00 0.11 0.05 359 0.77 203 0.11 0.43 0.78 Asia 214 0.09 0.68 0.39 0.12 – 360 0.07 224 0.01 0.04 0.09 Europe 381 0.17 0.66 0.32 0.10 – 1,411 0.24 180 0.04 0.12 0.25 N. America 1,145 0.26 0.02 0.01 0.11 – 370 0.77 181 0.09 0.35 0.74 Total 1,740 0.22 0.24 0.13 0.11 – 423 0.56 201 0.02 0.10 0.32 This table describes the number of engagements by a hedge fund between 2000 and 2010, the fraction of such engagements that involved a wolf pack (two or more hedge fund activists engaging the same target), the fraction of engagements that involve a foreign activist, the fraction of engagements that involve a U.S.-based foreign activist, the maximum stake held by the activists during the engagement period, and the country-specific regulatory ownership disclosure threshold. For a subsample of engagements with coverage on FactSet (FS) in the engagement year (n |$=$| 958 engagements) the table reports market capitalization of the target and institutional investor shareholdings, as well as market capitalization and institutional shareholdings for the population of firms on FS. Reported numbers are averages, except where indicated. Open in new tab Table 1 Hedge fund activism across countries . . . . . . . Subsample of engagements with FS coverage . FS firm population . Country . Number of engage-ments . Fraction wolf-packs . Fraction foreign activists . Fraction U.S. foreign activist . Fraction of shares held by hedge fund activist(s) . Regulatory disclosure threshold . Market cap US|${\$}$| (median) . Fraction held by inst. inv. (median) . Market cap US|${\$}$| (median) . Fraction held by inst. inv., 25th pctile . Fraction held by inst. inv., 50th pctile . Fraction held by inst. inv., 75th pctile . Region: Asia Hong Kong 7 0.00 1.00 0.14 0.11 0.05 4,290 0.12 252 0.01 0.04 0.12 Israel 1 0.00 1.00 1.00 0.10 0.05 – – 121 0.01 0.03 0.12 Japan 184 0.10 0.73 0.42 0.13 0.05 360 0.07 241 0.01 0.04 0.09 South Korea 23 0.09 0.22 0.17 0.10 0.05 256 0.04 158 0.00 0.03 0.09 Region: Europe Austria 1 0.00 1.00 1.00 0.05 0.05 – – 330 0.02 0.08 0.16 Belgium 9 0.00 0.44 0.33 0.07 0.05 3,105 0.23 221 0.02 0.06 0.14 Denmark 1 0.00 1.00 0.00 0.05 0.05 1,092 0.28 193 0.03 0.14 0.23 Finland 3 0.00 1.00 0.00 0.08 0.05 147 0.53 197 0.06 0.18 0.29 France 27 0.22 0.78 0.56 0.11 0.05 4,548 0.32 173 0.02 0.07 0.16 Germany 53 0.32 1.00 0.53 0.08 0.03 2,089 0.22 149 0.02 0.08 0.20 Greece 3 0.00 1.00 0.00 0.08 0.05 14,961 0.22 200 0.00 0.01 0.08 Ireland 2 0.00 1.00 0.50 0.05 0.05 2,090 0.48 187 0.09 0.19 0.32 Italy 42 0.19 0.86 0.48 0.05 0.02 2,533 0.13 373 0.02 0.06 0.14 Luxembourg 5 0.00 1.00 0.20 0.03 0.05 26,294 0.12 506 0.01 0.10 0.26 Netherlands 22 0.27 1.00 0.32 0.10 0.05 1134 0.33 615 0.10 0.22 0.39 Norway 7 0.00 1.00 0.29 0.11 0.05 738 0.35 188 0.06 0.14 0.26 Portugal 1 0.00 1.00 0.00 0.01 0.05 8,878 0.10 389 0.02 0.06 0.12 Spain 5 0.00 1.00 0.00 0.05 0.05 165 0.11 929 0.02 0.08 0.16 Sweden 15 0.27 0.60 0.00 0.08 0.05 1,407 0.36 146 0.06 0.17 0.33 Switzerland 19 0.11 0.68 0.26 0.14 0.03 775 0.30 475 0.03 0.13 0.26 U.K. 165 0.12 0.38 0.23 0.13 0.03 278 0.27 97 0.09 0.20 0.32 Region: North America Canada 20 0.00 0.75 0.70 0.16 0.10 2,475 0.41 87 0.05 0.13 0.30 U.S. 1,125 0.26 0.01 0.00 0.11 0.05 359 0.77 203 0.11 0.43 0.78 Asia 214 0.09 0.68 0.39 0.12 – 360 0.07 224 0.01 0.04 0.09 Europe 381 0.17 0.66 0.32 0.10 – 1,411 0.24 180 0.04 0.12 0.25 N. America 1,145 0.26 0.02 0.01 0.11 – 370 0.77 181 0.09 0.35 0.74 Total 1,740 0.22 0.24 0.13 0.11 – 423 0.56 201 0.02 0.10 0.32 . . . . . . . Subsample of engagements with FS coverage . FS firm population . Country . Number of engage-ments . Fraction wolf-packs . Fraction foreign activists . Fraction U.S. foreign activist . Fraction of shares held by hedge fund activist(s) . Regulatory disclosure threshold . Market cap US|${\$}$| (median) . Fraction held by inst. inv. (median) . Market cap US|${\$}$| (median) . Fraction held by inst. inv., 25th pctile . Fraction held by inst. inv., 50th pctile . Fraction held by inst. inv., 75th pctile . Region: Asia Hong Kong 7 0.00 1.00 0.14 0.11 0.05 4,290 0.12 252 0.01 0.04 0.12 Israel 1 0.00 1.00 1.00 0.10 0.05 – – 121 0.01 0.03 0.12 Japan 184 0.10 0.73 0.42 0.13 0.05 360 0.07 241 0.01 0.04 0.09 South Korea 23 0.09 0.22 0.17 0.10 0.05 256 0.04 158 0.00 0.03 0.09 Region: Europe Austria 1 0.00 1.00 1.00 0.05 0.05 – – 330 0.02 0.08 0.16 Belgium 9 0.00 0.44 0.33 0.07 0.05 3,105 0.23 221 0.02 0.06 0.14 Denmark 1 0.00 1.00 0.00 0.05 0.05 1,092 0.28 193 0.03 0.14 0.23 Finland 3 0.00 1.00 0.00 0.08 0.05 147 0.53 197 0.06 0.18 0.29 France 27 0.22 0.78 0.56 0.11 0.05 4,548 0.32 173 0.02 0.07 0.16 Germany 53 0.32 1.00 0.53 0.08 0.03 2,089 0.22 149 0.02 0.08 0.20 Greece 3 0.00 1.00 0.00 0.08 0.05 14,961 0.22 200 0.00 0.01 0.08 Ireland 2 0.00 1.00 0.50 0.05 0.05 2,090 0.48 187 0.09 0.19 0.32 Italy 42 0.19 0.86 0.48 0.05 0.02 2,533 0.13 373 0.02 0.06 0.14 Luxembourg 5 0.00 1.00 0.20 0.03 0.05 26,294 0.12 506 0.01 0.10 0.26 Netherlands 22 0.27 1.00 0.32 0.10 0.05 1134 0.33 615 0.10 0.22 0.39 Norway 7 0.00 1.00 0.29 0.11 0.05 738 0.35 188 0.06 0.14 0.26 Portugal 1 0.00 1.00 0.00 0.01 0.05 8,878 0.10 389 0.02 0.06 0.12 Spain 5 0.00 1.00 0.00 0.05 0.05 165 0.11 929 0.02 0.08 0.16 Sweden 15 0.27 0.60 0.00 0.08 0.05 1,407 0.36 146 0.06 0.17 0.33 Switzerland 19 0.11 0.68 0.26 0.14 0.03 775 0.30 475 0.03 0.13 0.26 U.K. 165 0.12 0.38 0.23 0.13 0.03 278 0.27 97 0.09 0.20 0.32 Region: North America Canada 20 0.00 0.75 0.70 0.16 0.10 2,475 0.41 87 0.05 0.13 0.30 U.S. 1,125 0.26 0.01 0.00 0.11 0.05 359 0.77 203 0.11 0.43 0.78 Asia 214 0.09 0.68 0.39 0.12 – 360 0.07 224 0.01 0.04 0.09 Europe 381 0.17 0.66 0.32 0.10 – 1,411 0.24 180 0.04 0.12 0.25 N. America 1,145 0.26 0.02 0.01 0.11 – 370 0.77 181 0.09 0.35 0.74 Total 1,740 0.22 0.24 0.13 0.11 – 423 0.56 201 0.02 0.10 0.32 This table describes the number of engagements by a hedge fund between 2000 and 2010, the fraction of such engagements that involved a wolf pack (two or more hedge fund activists engaging the same target), the fraction of engagements that involve a foreign activist, the fraction of engagements that involve a U.S.-based foreign activist, the maximum stake held by the activists during the engagement period, and the country-specific regulatory ownership disclosure threshold. For a subsample of engagements with coverage on FactSet (FS) in the engagement year (n |$=$| 958 engagements) the table reports market capitalization of the target and institutional investor shareholdings, as well as market capitalization and institutional shareholdings for the population of firms on FS. Reported numbers are averages, except where indicated. Open in new tab The 1,740 engagements are unevenly distributed across countries, with 85% concentrated in just three countries: the United States with 1,125 interventions, Japan with 184 interventions, and the United Kingdom with 165 interventions. Six other countries have at least twenty interventions: Germany, Italy, France, South Korea, the Netherlands, and Canada (in declining order). In addition, the table reports summary statistics for all 958 engagements in our sample for which we have FactSet coverage, and for comparative purposes the same data for all other companies with FactSet coverage, in each of the respective countries. Engagement characteristics vary considerably across countries. First, in several markets multiple activists are involved in the same engagement, that is, wolf packs; they are an important feature of activism in France, Germany, the Netherlands, Sweden, and the United States, where they involve more than 20% of engagements. Second, in a significant proportion of cases, the activist is a foreign hedge fund, and frequently a U.S. hedge fund. For example, in the 53 engagements in Germany, all activists were foreign hedge funds and more than half originated from the United States. In contrast, in the United States, virtually all activists are domestic. The United Kingdom is an intermediate case; a significant proportion of funds are domestic, and most of the remainder come from the United States. We also find similarities across markets. First, institutional holdings are important because activists hold stakes that are on average 11% and therefore require the support of these investors to put pressure on the company, for example, via board elections. There is significant variation across countries in institutional holdings among the target firms engaged by a hedge fund activist; the median holding in North America is 77% of shares issued, 24% in Europe, and only 7% in Asia. In most countries institutional holdings are larger in targeted firms than in the population of companies recorded in FactSet, as one would expect, and consistent with prior U.S. evidence. Second, in most countries firms engaged by activists are larger than the median firm in that market. Finland and Spain are the only exceptions, but activism in both countries is low in absolute terms. Third, all jurisdictions in our sample require shareholders to disclose when stakes reach a minimum threshold. We report disclosure thresholds as of the year 2000, and in the vast majority of countries, this threshold is 5% of capital and/or voting rights, depending on the type of security. Germany, Italy, Switzerland and the United Kingdom have lower thresholds of 2% or 3%, while Canada is the only country with a higher threshold of 10%.5 While the United States and the United Kingdom have the largest number of engagements, in relative terms activism is less frequent after adjusting for the number of listed companies than in Italy or Germany. Table 2 shows activist activity as engagements per 1,000 listed firms. After the United States, among large economies activism is relatively most frequent in Italy, the Netherlands, Germany and Switzerland (in declining order), none of which are typically labeled as having active markets for corporate control. The table also compares activism to unsolicited takeover bids. While activism differs from hostile takeovers with respect to the size of ownership in the target firm, the comparison is useful since the hostile takeovers are frequently used as a proxy for the level of managerial disciplining in a capital market. In Asia activist engagements exceed hostile bids by 6.4 times (3.2/0.5), in North America by 2.5 times, and in Europe by 1.6 times. Similar results obtain when we annualize activist activity. Overall, activism appears widespread and frequent. Table 2 Activist engagements relative to market size and takeovers Region/Country . Total number of activist engagements . Activist engagements per 1,000 listed firms . Unsolicited bids per 1,000 listed firms . Activist engagements per year (avg) . Unsolicited bids per year (avg) . Region Asia 214 3.2 0.5 19.5 2.8 Europe 381 3.4 2.1 34.6 20.5 North America 1,145 11.7 4.6 104.1 40.1 Countries with at least five activist engagements during sample period U.S. 1,125 19.6 5.8 102.3 31.4 Italy 42 13.3 1.6 3.8 0.5 Luxembourg 5 12.4 5.3 0.5 0.2 Netherlands 22 11.6 7.4 2 1.2 Germany 53 7.3 1.1 4.8 0.7 Switzerland 19 6.6 4.9 1.7 1.3 U.K. 165 6 4.1 15 9.9 Japan 184 4.9 0.7 16.7 2.5 Sweden 15 4.8 4 1.4 1.2 Belgium 9 4.6 1.2 0.8 0.3 Norway 7 3.6 4.8 0.6 0.9 France 27 3 1.2 2.5 1 South Korea 23 1.2 0.1 2.1 0.2 Hong Kong 7 0.6 0.2 0.6 0.2 Canada 20 0.6 3.3 1.8 8.7 Spain 5 0.2 0.6 0.5 1.5 Region/Country . Total number of activist engagements . Activist engagements per 1,000 listed firms . Unsolicited bids per 1,000 listed firms . Activist engagements per year (avg) . Unsolicited bids per year (avg) . Region Asia 214 3.2 0.5 19.5 2.8 Europe 381 3.4 2.1 34.6 20.5 North America 1,145 11.7 4.6 104.1 40.1 Countries with at least five activist engagements during sample period U.S. 1,125 19.6 5.8 102.3 31.4 Italy 42 13.3 1.6 3.8 0.5 Luxembourg 5 12.4 5.3 0.5 0.2 Netherlands 22 11.6 7.4 2 1.2 Germany 53 7.3 1.1 4.8 0.7 Switzerland 19 6.6 4.9 1.7 1.3 U.K. 165 6 4.1 15 9.9 Japan 184 4.9 0.7 16.7 2.5 Sweden 15 4.8 4 1.4 1.2 Belgium 9 4.6 1.2 0.8 0.3 Norway 7 3.6 4.8 0.6 0.9 France 27 3 1.2 2.5 1 South Korea 23 1.2 0.1 2.1 0.2 Hong Kong 7 0.6 0.2 0.6 0.2 Canada 20 0.6 3.3 1.8 8.7 Spain 5 0.2 0.6 0.5 1.5 The table compares the incidence of activist engagements and unsolicited takeover offers across regions and countries. Unsolicited takeover offers are from SDC Platinum and include all listed targets with market capitalization of at least |${\$}10$| million. The number of (domestic) listed firms is from the World Bank. Countries are sorted in declining order by “Activist engagements per 1,000 listed firms.” Open in new tab Table 2 Activist engagements relative to market size and takeovers Region/Country . Total number of activist engagements . Activist engagements per 1,000 listed firms . Unsolicited bids per 1,000 listed firms . Activist engagements per year (avg) . Unsolicited bids per year (avg) . Region Asia 214 3.2 0.5 19.5 2.8 Europe 381 3.4 2.1 34.6 20.5 North America 1,145 11.7 4.6 104.1 40.1 Countries with at least five activist engagements during sample period U.S. 1,125 19.6 5.8 102.3 31.4 Italy 42 13.3 1.6 3.8 0.5 Luxembourg 5 12.4 5.3 0.5 0.2 Netherlands 22 11.6 7.4 2 1.2 Germany 53 7.3 1.1 4.8 0.7 Switzerland 19 6.6 4.9 1.7 1.3 U.K. 165 6 4.1 15 9.9 Japan 184 4.9 0.7 16.7 2.5 Sweden 15 4.8 4 1.4 1.2 Belgium 9 4.6 1.2 0.8 0.3 Norway 7 3.6 4.8 0.6 0.9 France 27 3 1.2 2.5 1 South Korea 23 1.2 0.1 2.1 0.2 Hong Kong 7 0.6 0.2 0.6 0.2 Canada 20 0.6 3.3 1.8 8.7 Spain 5 0.2 0.6 0.5 1.5 Region/Country . Total number of activist engagements . Activist engagements per 1,000 listed firms . Unsolicited bids per 1,000 listed firms . Activist engagements per year (avg) . Unsolicited bids per year (avg) . Region Asia 214 3.2 0.5 19.5 2.8 Europe 381 3.4 2.1 34.6 20.5 North America 1,145 11.7 4.6 104.1 40.1 Countries with at least five activist engagements during sample period U.S. 1,125 19.6 5.8 102.3 31.4 Italy 42 13.3 1.6 3.8 0.5 Luxembourg 5 12.4 5.3 0.5 0.2 Netherlands 22 11.6 7.4 2 1.2 Germany 53 7.3 1.1 4.8 0.7 Switzerland 19 6.6 4.9 1.7 1.3 U.K. 165 6 4.1 15 9.9 Japan 184 4.9 0.7 16.7 2.5 Sweden 15 4.8 4 1.4 1.2 Belgium 9 4.6 1.2 0.8 0.3 Norway 7 3.6 4.8 0.6 0.9 France 27 3 1.2 2.5 1 South Korea 23 1.2 0.1 2.1 0.2 Hong Kong 7 0.6 0.2 0.6 0.2 Canada 20 0.6 3.3 1.8 8.7 Spain 5 0.2 0.6 0.5 1.5 The table compares the incidence of activist engagements and unsolicited takeover offers across regions and countries. Unsolicited takeover offers are from SDC Platinum and include all listed targets with market capitalization of at least |${\$}10$| million. The number of (domestic) listed firms is from the World Bank. Countries are sorted in declining order by “Activist engagements per 1,000 listed firms.” Open in new tab 1.3 Wolf packs Panel A of Table 3 provides further details on engagements involving multiple funds, that is, wolf packs, previously reported in Table 1. The term “wolf pack” is an analogy to a group of wolves attacking prey, where a lead wolf is visible and a potentially large number of pack members are not necessarily visible. The pack members communicate by “howling” (Harrington and Asa 2010). Under U.S. securities laws such a coordinated pack would be considered a group and would have to notify a joint stake. An alternative view articulated by Phil Goldstein, the CEO of Bulldog Investor (a hedge fund activist), is that multiple funds can be found in the same engagement but without coordination, rather like “if you go to a Grateful Dead concert, you’re going to find a lot of Grateful Dead fans,” he said. “They’re not a group. They just like the same music.” (Wall Street Journal, 4 June 2015). From a legal viewpoint, Coffee and Palia (2016) argue that hedge fund activists have managed to obtain the benefits of pack hunting but the legal treatment of music fans. They define wolf packs as “a loose network of activist investors that act in a parallel fashion, but deliberately avoid forming a “group” under Section 13(d)(3) of the Securities Exchange Act of 1934.” Brav, Dasgupta, and Mathews (2016) model the formation of this type of pack, where a loose coalition of smaller investors forms around a lead activist. Table 3 Activist engagements by year, country and fund group A. Wolf pack engagements . . Engagements . Percentage . Target firms . Percentage . Stand-alone activist 1,362 78.3 1,315 88.2 Wolf pack 378 21.7 172 11.8 Total 1,740 100.0 1,534 100.0 If wolf pack |$\quad$|2 hedge funds involved 290 76.7 142 83.5 |$\quad$|3 or more hedge funds involved 88 23.3 28 16.5 Total 378 100.0 170 100.0 A. Wolf pack engagements . . Engagements . Percentage . Target firms . Percentage . Stand-alone activist 1,362 78.3 1,315 88.2 Wolf pack 378 21.7 172 11.8 Total 1,740 100.0 1,534 100.0 If wolf pack |$\quad$|2 hedge funds involved 290 76.7 142 83.5 |$\quad$|3 or more hedge funds involved 88 23.3 28 16.5 Total 378 100.0 170 100.0 B. Domestic and foreign engagements by activist origin . Type . Number of engagements . . Percentage . Domestic non-U.S. engagements: Country of origin of the hedge fund U.K. 102 Japan 50 South Korea 18 France 6 Switzerland 6 Sweden 6 Italy 6 All other countries 10 Total non-U.S. activists 204 Domestic non-U.S. engagements 11.7 U.S. activists at home 1,115 Domestic U.S. engagements 64.1 Foreign non-U.S. engagements: Country of origin of the hedge fund U.K. 109 Singapore 36 Switzerland 15 Sweden 8 Monaco 8 All other countries 26 Total non-U.S. activists 202 Foreign non-U.S. engagements 11.6 U.S. activists abroad 219 Foreign U.S. engagements 12.6 Total 1,740 100 B. Domestic and foreign engagements by activist origin . Type . Number of engagements . . Percentage . Domestic non-U.S. engagements: Country of origin of the hedge fund U.K. 102 Japan 50 South Korea 18 France 6 Switzerland 6 Sweden 6 Italy 6 All other countries 10 Total non-U.S. activists 204 Domestic non-U.S. engagements 11.7 U.S. activists at home 1,115 Domestic U.S. engagements 64.1 Foreign non-U.S. engagements: Country of origin of the hedge fund U.K. 109 Singapore 36 Switzerland 15 Sweden 8 Monaco 8 All other countries 26 Total non-U.S. activists 202 Foreign non-U.S. engagements 11.6 U.S. activists abroad 219 Foreign U.S. engagements 12.6 Total 1,740 100 The table shows descriptive statistics for all 1,740 activist engagements between January 1, 2000 and December 31, 2010. In panel A, wolf pack indicates an engagement of multiple activists with the same target. Panel B tabulates the country of origin of both activists and targets. Open in new tab Table 3 Activist engagements by year, country and fund group A. Wolf pack engagements . . Engagements . Percentage . Target firms . Percentage . Stand-alone activist 1,362 78.3 1,315 88.2 Wolf pack 378 21.7 172 11.8 Total 1,740 100.0 1,534 100.0 If wolf pack |$\quad$|2 hedge funds involved 290 76.7 142 83.5 |$\quad$|3 or more hedge funds involved 88 23.3 28 16.5 Total 378 100.0 170 100.0 A. Wolf pack engagements . . Engagements . Percentage . Target firms . Percentage . Stand-alone activist 1,362 78.3 1,315 88.2 Wolf pack 378 21.7 172 11.8 Total 1,740 100.0 1,534 100.0 If wolf pack |$\quad$|2 hedge funds involved 290 76.7 142 83.5 |$\quad$|3 or more hedge funds involved 88 23.3 28 16.5 Total 378 100.0 170 100.0 B. Domestic and foreign engagements by activist origin . Type . Number of engagements . . Percentage . Domestic non-U.S. engagements: Country of origin of the hedge fund U.K. 102 Japan 50 South Korea 18 France 6 Switzerland 6 Sweden 6 Italy 6 All other countries 10 Total non-U.S. activists 204 Domestic non-U.S. engagements 11.7 U.S. activists at home 1,115 Domestic U.S. engagements 64.1 Foreign non-U.S. engagements: Country of origin of the hedge fund U.K. 109 Singapore 36 Switzerland 15 Sweden 8 Monaco 8 All other countries 26 Total non-U.S. activists 202 Foreign non-U.S. engagements 11.6 U.S. activists abroad 219 Foreign U.S. engagements 12.6 Total 1,740 100 B. Domestic and foreign engagements by activist origin . Type . Number of engagements . . Percentage . Domestic non-U.S. engagements: Country of origin of the hedge fund U.K. 102 Japan 50 South Korea 18 France 6 Switzerland 6 Sweden 6 Italy 6 All other countries 10 Total non-U.S. activists 204 Domestic non-U.S. engagements 11.7 U.S. activists at home 1,115 Domestic U.S. engagements 64.1 Foreign non-U.S. engagements: Country of origin of the hedge fund U.K. 109 Singapore 36 Switzerland 15 Sweden 8 Monaco 8 All other countries 26 Total non-U.S. activists 202 Foreign non-U.S. engagements 11.6 U.S. activists abroad 219 Foreign U.S. engagements 12.6 Total 1,740 100 The table shows descriptive statistics for all 1,740 activist engagements between January 1, 2000 and December 31, 2010. In panel A, wolf pack indicates an engagement of multiple activists with the same target. Panel B tabulates the country of origin of both activists and targets. Open in new tab The foremost international wolf pack case is the 2005 activist engagement with Deutsche Börse when the lead hedge fund (TCI) sent an e-mail to supervisory board members claiming support from 14 other funds, to abandon an acquisition attempt by Deutsche Börse for the London Stock Exchange. German media referred to this group as an “alliance of locusts”. Participants included three hedge funds with publicly observable stakes above the disclosure threshold (TCI, Atticus, and Och-Ziff), eight hedge funds that at the time did not disclose their holdings (Harris, Seneca, Jana, Lone Pine, Third Point, RIT, Alta, and Parvus) and other institutional investors (Capital Group, Fidelity, Generali, and Merril Lynch). Combined, these investors owned 59\% of the voting rights (Der Spiegel, 13 June 2005). The German securities regulator (Bafin) investigated the case but did not conclude that these funds acted as a group.6 It is hard to measure the number of such groupings among hedge fund activist cases, because the funds below the regulatory disclosure threshold are not observable, unless they voluntarily disclose their holding. Investors like the Capital Group and Fidelity may or may not support the hedge fund. Hence we use a restricted but empirically robust definition, where a wolf pack is simply defined as a case where multiple hedge fund activists with a disclosed stake are involved in the same engagement. They may or may not coordinate their activities but the disclosure of each fund is at least publicly observable. There are 1,534 unique target companies involved in the 1,740 engagements.7 As Panel A of Table 3 shows, in 22% of these cases there are at least two hedge funds in the same engagement; of these, 77% involve two hedge funds, while 23% involve three or more. The aggregate stakes held by wolf packs are higher than the stakes held in a single activist engagement, 13.4% versus 8.3%. We examine below the question whether such larger stakes increase the probability of a successful engagement measured by the incidence of outcomes and whether packs have better performance. 1.4 Do hedge funds engage targets internationally? Panel B of Table 3 separates engagements into foreign and domestic by fund origin. We follow Ferreira and Matos (2008) and consider the geographic origin of both target firm and activists. The panel shows that 76% of the engagements are purely domestic, mostly in the United States. Regarding foreign engagements, U.K. funds engage relatively more frequently outside the United Kingdom than do U.S. funds, but the number of foreign U.S. hedge fund engagements is the largest in absolute terms. This is consistent with pattern of institutional ownership; U.S. foreign institutional ownership is the largest in absolute terms. This raises the issue as to whether domestic activists perform better than foreign activists, particularly those originating in the United States and targeting foreign companies. We examine this issue below. 2. International Activism In all markets, to generate positive returns activists must be able to bring about profitable change in the target company, which is only possible when the fund has sufficient influence. Three key factors can shape this influence: (1) the size of the hedge fund’s own stake, (2) support from other shareholders, and (3) the institutions and the legal framework of a country. We review these in turn. First, hedge fund activists rarely hold large stakes in the target company.8 For the entire sample, the average stake held during the engagement is 11%. Average stakes vary relatively little across countries: In the three main activist markets, average stakes are 11% in the United States, 13% in Japan, and 13% in the United Kingdom. (Table 1). Second, due to their relatively low percentage of total ownership, activists depend on support from other shareholders. Block holders, such as families or founders and employee shareholders, will generally support the incumbent directors. Foreign institutional investors, particularly U.S. investors, are more likely to cooperate with hedge fund activists. A closer examination of important cases from Europe and Asia illustrates the importance of the ownership landscape and investors support. 2.1 Germany: Deutsche Börse (TCI and Atticus) The previously detailed 2005 engagement of Deutsche Börse in Germany by the London-based The Children’s Investment Fund Ltd (TCI) was important in demonstrating the ability of a foreign activist fund to successfully engage with a blue chip target outside the United States, provided its demands were supported by a sufficient number of investors. The engagement became possible because Deutsche Börse had become a widely held company after its initial public offering in 2001. In 2004 management reported that “93 percent of the shares are now held by institutional investors,” 26% from the United States, 24% from the United Kingdom, and 35% from Germany (DB Annual Report 2004). TCI saw the opportunity to solicit the support of these owners. 2.2 France: Euronext (TCI) TCI employed the same strategy again in 2006 at Euronext, this time putting pressure on the exchange to merge with its rivals DB or the NYSE. On February 15, 2006, almost 76% of the voting rights were controlled by international institutional shareholders. Euronext merged with the NYSE in 2007. 2.3 Japan: J-Power (TCI) and Aderans (Steel Partners) TCI tried to employ similar tactics at J-Power in Japan starting in October 2006. Thirty-five percent of J-Power’s shares were held by foreign institutional investors (Buchanan et al. 2012). TCI nominated two outside directors: J-Power’s board refused to support them. In May 2008, the Japanese government refused TCI’s request to raise its stake to 20%. TCI launched a proxy contest and purchased positions in ten institutions that were shareholders of J-Power. In June 2008 a majority of shareholders rejected TCI’s proposal. The engagement failed because TCI was unable to gain sufficient support from other shareholders, including other activists. However, in contrast, in 2008 Steel Partners were able to replace the board of Aderans because the fund held a 24.6% stake, and they had the support of State Street Banks and Trust that held a 16.3% stake (Greenwood and Schor 2009).9 2.4 South Korea: KT&G (Carl Icahn and Steel Partners) In South Korea, Carl Icahn engaged KT&G, the country’s largest tobacco and ginseng group, in January 2006. He acquired a 6% stake and was supported by Steel Partners. KT&G was widely held and 60% of its shareholders were foreigner investors. Carl Icahn managed to appoint a director and KT&G accepted nearly all of Icahn’s demands. He sold his stake with a 44.2% net return at the end of the year (Financial Times 2006; Kim 2008). In the case studies considered above, the presence of (foreign) institutional investors is crucial in determining the outcome. The general trend in institutional ownership between 2000 and 2007 in many Asian and European markets is consistent with the case study evidence. The value of foreign equity holdings of U.S. institutions increased more than threefold between 2001 and 2007 (Department of the Treasury 2008). In 2005, U.S. institutional investors held 65% of the total US|${\$}$|18 trillion in equity positions held by 5,300 institutions in 27 countries in the FactSet/Lionshare database (Aggarwal et al. 2011, Table A3). The percentage of total market capitalization held by foreign institutions exceeded 20% in 14 of these markets.10 At the company level, foreign holdings are even higher in widely held companies, as illustrated by the case studies of Deutsche Börse and Euronext. Finally, institutional and legal characteristics of a country may influence activism. Prior research suggests that several dimensions of country characteristics might be important for hedge fund activism. For example, the anti-director rights index in Djankov et al. (2008) has as one of its components whether shareholders have the right to call a special meeting and propose candidates for election to the board. Across countries, shareholders may require as little as 5% or as much as 20% to exercise this right (the United States/Delaware being an exception, where shareholders generally cannot call an EGM, but can launch a proxy fight). Differences in anti-director rights should therefore affect the ease with which activists can engage. Other country characteristics that are likely to matter are institutional ownership, board composition, governance quality, reporting regulations for ownership, among others. We investigate the importance of these country characteristics, which significantly vary, in our analysis below. 3. Results In this section we describe four sets of our results. First, we report the probability of a firm becoming a target of an activist in a given country, conditional on target characteristics. Second, we calculate various metrics of performance of engagements, measuring the target’s abnormal returns around the initial block disclosure by the activist, the probability of occurrence of different successful outcomes during the engagement, the abnormal returns around the announcement of these outcomes, and the long-term abnormal returns for the entire engagement period from entry of the activist to exit. Third, we examine the influence of the nationality of the activist, domestic, foreign or foreign-U.S., on the success of the engagements. Fourth, and finally, we examine how country specific characteristics affect activism performance and outcomes. 3.1 Likelihood of engagement across countries We investigate what factors affect the probability of an engagement by an activist hedge fund. Table 4 reports probit regressions, where the dependent variable is a dummy indicating whether a firm is engaged by an activist or not in a given year. We control for firm characteristics, such as size (market cap), leverage and market to book, a firm’s accounting standards, index membership, illiquidity of target firm shares and institutional ownership (domestic and foreign). Institutional ownership is important since, as discussed earlier, we expect that institutional investors, particularly those from the United States, increase the probability of an activist engagement. Index membership and illiquidity are correlated with institutional ownership but might also have a direct effect on activists’ decision to engage a target. We report results using two different samples: The “All countries” sample in Columns 1 and 2 covers 45 countries and 25,018 firms, including 22 countries without any recorded activist events (from Column 2 onward, we require nonmissing data also for Illiquidity, reducing sample size). The “Only activist markets” sample in Columns 3 and 4 is limited to markets with at least five engagements during the sample period. All columns include year fixed effects, and Column 4 additionally includes country fixed effects. Table 4 Probability of activist engagements . (1) . (2) . (3) . (4) . Sample . All countries . All countries . Only activist markets . Only activist markets . IO_domestic 0.037*** 0.040*** 0.047*** 0.049*** [0.002] [0.002] [0.003] [0.003] IO_foreign U.S. 0.063*** 0.110*** 0.180*** 0.209*** [0.010] [0.014] [0.021] [0.022] IO_foreign non-U.S. 0.034*** 0.036*** 0.037* 0.031 [0.012] [0.014] [0.019] [0.021] Ln(Market cap) –0.000 –0.002*** –0.002*** –0.001** [0.000] [0.000] [0.001] [0.001] Market-to-book –0.006*** –0.007*** –0.008*** –0.008*** [0.001] [0.001] [0.001] [0.001] Profitability 0.003 –0.003 –0.002 –0.003 [0.002] [0.003] [0.004] [0.004] Leverage 0.010*** 0.007*** 0.011*** 0.010*** [0.002] [0.003] [0.003] [0.003] Cash 0.014*** 0.008*** 0.011*** 0.011*** [0.002] [0.003] [0.004] [0.004] Div yield –0.112*** –0.117*** –0.095*** –0.073** [0.024] [0.027] [0.033] [0.033] Payout 0.000*** 0.000*** 0.000*** 0.000** [0.000] [0.000] [0.000] [0.000] Investment –0.037*** –0.028*** –0.012 –0.008 [0.007] [0.009] [0.012] [0.012] U.S. GAAP 0.018*** 0.014*** 0.011*** 0.007** [0.001] [0.002] [0.002] [0.003] Index member 0.005*** 0.005*** 0.002 –0.002 [0.001] [0.001] [0.002] [0.002] Illiquidity –0.038*** –0.031*** –0.013 [0.006] [0.007] [0.008] Year FE Yes Yes Yes Yes Country FE No No No Yes Observations 114,987 90,470 68,157 68,157 Pseudo R-squared 0.112 0.106 0.0842 0.0891 . (1) . (2) . (3) . (4) . Sample . All countries . All countries . Only activist markets . Only activist markets . IO_domestic 0.037*** 0.040*** 0.047*** 0.049*** [0.002] [0.002] [0.003] [0.003] IO_foreign U.S. 0.063*** 0.110*** 0.180*** 0.209*** [0.010] [0.014] [0.021] [0.022] IO_foreign non-U.S. 0.034*** 0.036*** 0.037* 0.031 [0.012] [0.014] [0.019] [0.021] Ln(Market cap) –0.000 –0.002*** –0.002*** –0.001** [0.000] [0.000] [0.001] [0.001] Market-to-book –0.006*** –0.007*** –0.008*** –0.008*** [0.001] [0.001] [0.001] [0.001] Profitability 0.003 –0.003 –0.002 –0.003 [0.002] [0.003] [0.004] [0.004] Leverage 0.010*** 0.007*** 0.011*** 0.010*** [0.002] [0.003] [0.003] [0.003] Cash 0.014*** 0.008*** 0.011*** 0.011*** [0.002] [0.003] [0.004] [0.004] Div yield –0.112*** –0.117*** –0.095*** –0.073** [0.024] [0.027] [0.033] [0.033] Payout 0.000*** 0.000*** 0.000*** 0.000** [0.000] [0.000] [0.000] [0.000] Investment –0.037*** –0.028*** –0.012 –0.008 [0.007] [0.009] [0.012] [0.012] U.S. GAAP 0.018*** 0.014*** 0.011*** 0.007** [0.001] [0.002] [0.002] [0.003] Index member 0.005*** 0.005*** 0.002 –0.002 [0.001] [0.001] [0.002] [0.002] Illiquidity –0.038*** –0.031*** –0.013 [0.006] [0.007] [0.008] Year FE Yes Yes Yes Yes Country FE No No No Yes Observations 114,987 90,470 68,157 68,157 Pseudo R-squared 0.112 0.106 0.0842 0.0891 The table provides the results of probit regressions in which the dependent variable is whether a firm is engaged by an activist (1) or not (0) in a given year. All nonbinary coefficients are reported as marginal effects. The “All countries” sample includes all firms from the FactSet database from 2000 to 2010 with nonmissing data (45 countries, 25,018 firms, 114,978 firm-years; of these, 90,470 firm-years have nonmissing data also for Illiquidity). The “Only activist markets” sample includes only countries in which we observe at least five engagements during the sample period (13 countries, 13,479 firms, 68,157 firm-years). The main independent variables are institutional ownership by domestic institutions (IO_Domestic), foreign U.S.-based institutions (IO_Foreign U.S.), and foreign non-U.S.-based institutions (IO_Foreign Non-U.S.); firm size (log of market capitalization); Market-to-book (total assets minus book value of equity plus market value of equity over total assets); Profitability (EBITDA over total assets); Leverage (Total debt over total assets); Cash (cash and cash equivalents over total assets); Dividend yield (Common cash dividends over book equity); Payout (Dividend payout per share); Investment (Capex over total assets); U.S. GAAP (whether (1) or not (0) a firm uses U.S. accounting standards); Index member (whether (1) or not (0) a firm belongs to one of 48 major domestic stock market indices); and Illiquidity (number of zero daily returns per year divided by the number of available daily returns per year, minimum of 200 available daily returns per year). All continuous variables are winsorized at the 1st and 99th percentiles. White (1980) heteroscedasticity-robust standard errors are reported in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab Table 4 Probability of activist engagements . (1) . (2) . (3) . (4) . Sample . All countries . All countries . Only activist markets . Only activist markets . IO_domestic 0.037*** 0.040*** 0.047*** 0.049*** [0.002] [0.002] [0.003] [0.003] IO_foreign U.S. 0.063*** 0.110*** 0.180*** 0.209*** [0.010] [0.014] [0.021] [0.022] IO_foreign non-U.S. 0.034*** 0.036*** 0.037* 0.031 [0.012] [0.014] [0.019] [0.021] Ln(Market cap) –0.000 –0.002*** –0.002*** –0.001** [0.000] [0.000] [0.001] [0.001] Market-to-book –0.006*** –0.007*** –0.008*** –0.008*** [0.001] [0.001] [0.001] [0.001] Profitability 0.003 –0.003 –0.002 –0.003 [0.002] [0.003] [0.004] [0.004] Leverage 0.010*** 0.007*** 0.011*** 0.010*** [0.002] [0.003] [0.003] [0.003] Cash 0.014*** 0.008*** 0.011*** 0.011*** [0.002] [0.003] [0.004] [0.004] Div yield –0.112*** –0.117*** –0.095*** –0.073** [0.024] [0.027] [0.033] [0.033] Payout 0.000*** 0.000*** 0.000*** 0.000** [0.000] [0.000] [0.000] [0.000] Investment –0.037*** –0.028*** –0.012 –0.008 [0.007] [0.009] [0.012] [0.012] U.S. GAAP 0.018*** 0.014*** 0.011*** 0.007** [0.001] [0.002] [0.002] [0.003] Index member 0.005*** 0.005*** 0.002 –0.002 [0.001] [0.001] [0.002] [0.002] Illiquidity –0.038*** –0.031*** –0.013 [0.006] [0.007] [0.008] Year FE Yes Yes Yes Yes Country FE No No No Yes Observations 114,987 90,470 68,157 68,157 Pseudo R-squared 0.112 0.106 0.0842 0.0891 . (1) . (2) . (3) . (4) . Sample . All countries . All countries . Only activist markets . Only activist markets . IO_domestic 0.037*** 0.040*** 0.047*** 0.049*** [0.002] [0.002] [0.003] [0.003] IO_foreign U.S. 0.063*** 0.110*** 0.180*** 0.209*** [0.010] [0.014] [0.021] [0.022] IO_foreign non-U.S. 0.034*** 0.036*** 0.037* 0.031 [0.012] [0.014] [0.019] [0.021] Ln(Market cap) –0.000 –0.002*** –0.002*** –0.001** [0.000] [0.000] [0.001] [0.001] Market-to-book –0.006*** –0.007*** –0.008*** –0.008*** [0.001] [0.001] [0.001] [0.001] Profitability 0.003 –0.003 –0.002 –0.003 [0.002] [0.003] [0.004] [0.004] Leverage 0.010*** 0.007*** 0.011*** 0.010*** [0.002] [0.003] [0.003] [0.003] Cash 0.014*** 0.008*** 0.011*** 0.011*** [0.002] [0.003] [0.004] [0.004] Div yield –0.112*** –0.117*** –0.095*** –0.073** [0.024] [0.027] [0.033] [0.033] Payout 0.000*** 0.000*** 0.000*** 0.000** [0.000] [0.000] [0.000] [0.000] Investment –0.037*** –0.028*** –0.012 –0.008 [0.007] [0.009] [0.012] [0.012] U.S. GAAP 0.018*** 0.014*** 0.011*** 0.007** [0.001] [0.002] [0.002] [0.003] Index member 0.005*** 0.005*** 0.002 –0.002 [0.001] [0.001] [0.002] [0.002] Illiquidity –0.038*** –0.031*** –0.013 [0.006] [0.007] [0.008] Year FE Yes Yes Yes Yes Country FE No No No Yes Observations 114,987 90,470 68,157 68,157 Pseudo R-squared 0.112 0.106 0.0842 0.0891 The table provides the results of probit regressions in which the dependent variable is whether a firm is engaged by an activist (1) or not (0) in a given year. All nonbinary coefficients are reported as marginal effects. The “All countries” sample includes all firms from the FactSet database from 2000 to 2010 with nonmissing data (45 countries, 25,018 firms, 114,978 firm-years; of these, 90,470 firm-years have nonmissing data also for Illiquidity). The “Only activist markets” sample includes only countries in which we observe at least five engagements during the sample period (13 countries, 13,479 firms, 68,157 firm-years). The main independent variables are institutional ownership by domestic institutions (IO_Domestic), foreign U.S.-based institutions (IO_Foreign U.S.), and foreign non-U.S.-based institutions (IO_Foreign Non-U.S.); firm size (log of market capitalization); Market-to-book (total assets minus book value of equity plus market value of equity over total assets); Profitability (EBITDA over total assets); Leverage (Total debt over total assets); Cash (cash and cash equivalents over total assets); Dividend yield (Common cash dividends over book equity); Payout (Dividend payout per share); Investment (Capex over total assets); U.S. GAAP (whether (1) or not (0) a firm uses U.S. accounting standards); Index member (whether (1) or not (0) a firm belongs to one of 48 major domestic stock market indices); and Illiquidity (number of zero daily returns per year divided by the number of available daily returns per year, minimum of 200 available daily returns per year). All continuous variables are winsorized at the 1st and 99th percentiles. White (1980) heteroscedasticity-robust standard errors are reported in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab The results in Table 4 confirm that institutional ownership is strongly correlated with the level of engagements at the firm level within a country, particularly if the institutional investor is U.S.-based. We thus confirm and extend prior evidence by Brav et al. (2008), who show that for U.S. domestic engagements, institutional ownership increases the likelihood of activist engagements. When we partition institutional ownership by domestic, foreign-U.S., and foreign non-U.S., two of the variables (domestic and foreign-U.S.) are significant at the 1% level and foreign non-U.S. is significant in two out of the three regressions at the 1% or 5% level. For all countries, foreign-U.S. ownership is almost twice as important as domestic ownership; for countries with at least five engagements (Regressions 2 and 3), it is more important than foreign non-U.S. by a factor of between 2.5 and 4.5 times. In a separate set of results reported in the Internet Appendix (Table 15), we interact institutional ownership with indicator variables for the seven countries with the highest absolute number of activist engagements, to test whether the role of institutional investors differs across markets. We find that Germany, France, and the United Kingdom have similar characteristics—foreign institutional investors, and particularly those from the United States, have a larger impact on engagement probabilities. Japan is similar to these three countries insofar as foreign U.S. investors make activism more likely; in contrast, domestic Japanese institutions have a dampening effect on shareholder activism. Italy is similar to Japan, with less activism when domestic institutional holdings are higher and foreign (U.S.) institutional holdings are lower. Considering how firm characteristics relate to activist engagements, Table 4 yields two additional insights. First, controlling for other factors, firm size has little effect on engagement probability. While Brav et al. (2008) find that engagements are concentrated among smaller firms in the United States from 2001 to 2006, this study finds that hedge fund activists around the world appears to be less constrained by the size of market capitalization of the target firm. Second, broadly consistent with Brav et al. (2008) and other prior U.S. findings, activists behave as value investors in their choice of targets. Those targets have lower market-to-book, higher payout ratios, lower investment, and higher cash balances. 3.2 Engagement announcement returns The first measure of engagement performance is the cumulative abnormal return around the initial disclosure of the activist engagement, measured across all jurisdictions. Table 5 reports the market-model adjusted abnormal returns around the disclosure date for two event windows, 21 days and 41 days (1,617 out of 1,740 engagement disclosures have sufficient data available; market models are country specific). In panel A, for the aggregate sample, average abnormal returns are 6.4% for the (⁠|$-$|20, 20) window, and 6.1% for the (⁠|$-$|10, 10) window, significantly different from zero at the 1% level.11 Table 5 Abnormal returns from activist engagement announcements . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Sample . Abn. ret. . SE . |$N$| . Abn. ret. . SE . |$N$| . A. Abnormal returns around engagement disclosure . Full 6.14*** [0.36] 1,617 6.40*** [0.486] 1,617 Asia 6.06*** [0.912] 213 6.43*** [1.238] 213 Europe 3.93*** [0.632] 377 4.75*** [0.898] 377 North America 6.97*** [0.480] 1,027 7.00*** [0.641] 1,027 . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Sample . Abn. ret. . SE . |$N$| . Abn. ret. . SE . |$N$| . A. Abnormal returns around engagement disclosure . Full 6.14*** [0.36] 1,617 6.40*** [0.486] 1,617 Asia 6.06*** [0.912] 213 6.43*** [1.238] 213 Europe 3.93*** [0.632] 377 4.75*** [0.898] 377 North America 6.97*** [0.480] 1,027 7.00*** [0.641] 1,027 B. Time series of abnormal returns around engagement disclosure . . Full sample . Asia . Europe . North America . Disclosure . CAR . CAR . CAR . CAR . CAR . CAR . CAR . CAR . year . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . 2000 12.8 13.5 7.0 7.2 6.3 5.6 16.9 18.8 2001 5.3 9.4 –2.1 4.7 0.1 –5.8 6.8 13.0 2002 6.8 8.1 8.6 12.4 4.5 2.5 8.3 11.8 2003 7.8 8.8 18.1 17.9 6.4 9.6 7.5 8.0 2004 7.3 7.5 10.7 15.6 3.4 5.2 8.6 6.1 2005 4.3 4.3 2.4 1.8 2.5 5.0 5.8 5.0 2006 6.0 6.2 6.2 6.6 3.3 3.4 6.9 7.0 2007 4.8 4.4 4.2 3.7 3.5 3.5 5.5 4.9 2008 7.8 7.5 14.0 12.1 4.0 5.7 7.8 7.2 2009 5.5 7.3 –8.8 1.3 12.1 17.8 4.5 4.9 2010 6.7 6.4 1.1 1.2 8.4 7.9 B. Time series of abnormal returns around engagement disclosure . . Full sample . Asia . Europe . North America . Disclosure . CAR . CAR . CAR . CAR . CAR . CAR . CAR . CAR . year . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . 2000 12.8 13.5 7.0 7.2 6.3 5.6 16.9 18.8 2001 5.3 9.4 –2.1 4.7 0.1 –5.8 6.8 13.0 2002 6.8 8.1 8.6 12.4 4.5 2.5 8.3 11.8 2003 7.8 8.8 18.1 17.9 6.4 9.6 7.5 8.0 2004 7.3 7.5 10.7 15.6 3.4 5.2 8.6 6.1 2005 4.3 4.3 2.4 1.8 2.5 5.0 5.8 5.0 2006 6.0 6.2 6.2 6.6 3.3 3.4 6.9 7.0 2007 4.8 4.4 4.2 3.7 3.5 3.5 5.5 4.9 2008 7.8 7.5 14.0 12.1 4.0 5.7 7.8 7.2 2009 5.5 7.3 –8.8 1.3 12.1 17.8 4.5 4.9 2010 6.7 6.4 1.1 1.2 8.4 7.9 C. Abnormal returns around stand-alone and wolf pack engagement disclosures . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Sample . Abn. ret. . SE . |$N$| . Abn. ret. . SE . |$N$| . Stand-alone activist 5.99*** [0.45] 1,264 6.32*** [0.63] 1,264 Wolf pack activist 14.05*** [1.87] 164 13.82*** [2.33] 164 Difference –8.06*** [1.41] –7.50*** [1.93] C. Abnormal returns around stand-alone and wolf pack engagement disclosures . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Sample . Abn. ret. . SE . |$N$| . Abn. ret. . SE . |$N$| . Stand-alone activist 5.99*** [0.45] 1,264 6.32*** [0.63] 1,264 Wolf pack activist 14.05*** [1.87] 164 13.82*** [2.33] 164 Difference –8.06*** [1.41] –7.50*** [1.93] D. Regression of abnormal return around engagement disclosure on activist stakes and wolf pack status . . CAR (⁠|$-$|10,10) . CAR (⁠|$-$|20,20) . Dependent variable: . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . Stake held 0.18** 0.27*** 0.19* 0.28*** |$\quad$|by activist [0.073] [0.071] [0.10] [0.097] |$\quad$|(start) Stake held 0.12** 0.15*** 0.031 0.064 |$\quad$|by activist [0.053] [0.053] [0.074] [0.073] |$\quad$|(high) Wolf pack 6.99*** 7.32*** 6.39*** 6.85*** |$\quad$| (1/0) [1.49] [1.47] [2.04] [2.04] Residual 7.26*** 7.04*** |$\quad$|wolf pack [1.52] [2.09] |$\quad$|(start) Residual 7.05*** 6.96*** |$\quad$|wolf pack [1.52] [2.10] |$\quad$|(high) Observations 1,216 1,216 1,048 1,048 1,216 1,216 1,048 1,048 Adjusted 0.028 0.028 0.029 0.026 0.013 0.014 0.010 0.009 |$\quad$|R-squared D. Regression of abnormal return around engagement disclosure on activist stakes and wolf pack status . . CAR (⁠|$-$|10,10) . CAR (⁠|$-$|20,20) . Dependent variable: . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . Stake held 0.18** 0.27*** 0.19* 0.28*** |$\quad$|by activist [0.073] [0.071] [0.10] [0.097] |$\quad$|(start) Stake held 0.12** 0.15*** 0.031 0.064 |$\quad$|by activist [0.053] [0.053] [0.074] [0.073] |$\quad$|(high) Wolf pack 6.99*** 7.32*** 6.39*** 6.85*** |$\quad$| (1/0) [1.49] [1.47] [2.04] [2.04] Residual 7.26*** 7.04*** |$\quad$|wolf pack [1.52] [2.09] |$\quad$|(start) Residual 7.05*** 6.96*** |$\quad$|wolf pack [1.52] [2.10] |$\quad$|(high) Observations 1,216 1,216 1,048 1,048 1,216 1,216 1,048 1,048 Adjusted 0.028 0.028 0.029 0.026 0.013 0.014 0.010 0.009 |$\quad$|R-squared E. Abnormal returns around domestic and foreign engagement disclosures . . Domestic non-U.S. (1) . Domestic U.S. (2) . Foreign non-U.S. (3) . Foreign U.S. (4) . Diff. (⁠|$t$|-stat) (1)&(2) - (3)&(4) . Event window: (⁠|$-$|10,10) 7.02*** 6.97*** 3.84*** 3.55*** 4.01*** [1.02] [0.49] [0.86] [0.74] Event window: (⁠|$-$|20,20) 7.34*** 6.94*** 4.27*** 4.87*** 2.21** [1.44] [0.65] [1.12] [1.10] E. Abnormal returns around domestic and foreign engagement disclosures . . Domestic non-U.S. (1) . Domestic U.S. (2) . Foreign non-U.S. (3) . Foreign U.S. (4) . Diff. (⁠|$t$|-stat) (1)&(2) - (3)&(4) . Event window: (⁠|$-$|10,10) 7.02*** 6.97*** 3.84*** 3.55*** 4.01*** [1.02] [0.49] [0.86] [0.74] Event window: (⁠|$-$|20,20) 7.34*** 6.94*** 4.27*** 4.87*** 2.21** [1.44] [0.65] [1.12] [1.10] The table shows average cumulative abnormal returns (CARs) around the initial filing date or the first press disclosure date of engagements, market model-adjusted. In panels C and D wolf pack engagements involving multiple funds are treated as one engagement only; in case within a wolf pack engagement are disclosed on separate dates, CARs are summed per wolf pack, across announcements. Stake held by activist (Start) indicates the activist stake at initial disclosure (summed over all members of the wolf pack if applicable); Stake held by activist (High) indicates the highest stake the activist reaches during the engagement (summed over all members of the wolf pack if applicable); and both variables are available for a subsample of engagements. In panel D, Wolf pack (1/0) is a dummy variable indicating a wolf pack (1) or stand-alone (0) engagement; and Residual wolf pack (start) is the residual from a regression of the Wolf pack (1/0) dummy on Stake held by activist (Start), with announcement year and country fixed effects. Residual wolf pack (High) is the residual from the same regression, but instead uses Stake held by activist (High). The event window is centered on day zero, where day zero corresponds to the filing or press disclosure date. For the market model, factor loadings are estimated over 250 trading days preceding the event window, using country-specific domestic market returns, with a minimum of 150 daily observations (1,617 out of 1,740 engagement disclosures have sufficient data). Abnormal returns are winsorized at the 1st and 99th percentiles. Standard errors (White 1980 heteroscedasticity robust in panel E) are reported in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab Table 5 Abnormal returns from activist engagement announcements . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Sample . Abn. ret. . SE . |$N$| . Abn. ret. . SE . |$N$| . A. Abnormal returns around engagement disclosure . Full 6.14*** [0.36] 1,617 6.40*** [0.486] 1,617 Asia 6.06*** [0.912] 213 6.43*** [1.238] 213 Europe 3.93*** [0.632] 377 4.75*** [0.898] 377 North America 6.97*** [0.480] 1,027 7.00*** [0.641] 1,027 . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Sample . Abn. ret. . SE . |$N$| . Abn. ret. . SE . |$N$| . A. Abnormal returns around engagement disclosure . Full 6.14*** [0.36] 1,617 6.40*** [0.486] 1,617 Asia 6.06*** [0.912] 213 6.43*** [1.238] 213 Europe 3.93*** [0.632] 377 4.75*** [0.898] 377 North America 6.97*** [0.480] 1,027 7.00*** [0.641] 1,027 B. Time series of abnormal returns around engagement disclosure . . Full sample . Asia . Europe . North America . Disclosure . CAR . CAR . CAR . CAR . CAR . CAR . CAR . CAR . year . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . 2000 12.8 13.5 7.0 7.2 6.3 5.6 16.9 18.8 2001 5.3 9.4 –2.1 4.7 0.1 –5.8 6.8 13.0 2002 6.8 8.1 8.6 12.4 4.5 2.5 8.3 11.8 2003 7.8 8.8 18.1 17.9 6.4 9.6 7.5 8.0 2004 7.3 7.5 10.7 15.6 3.4 5.2 8.6 6.1 2005 4.3 4.3 2.4 1.8 2.5 5.0 5.8 5.0 2006 6.0 6.2 6.2 6.6 3.3 3.4 6.9 7.0 2007 4.8 4.4 4.2 3.7 3.5 3.5 5.5 4.9 2008 7.8 7.5 14.0 12.1 4.0 5.7 7.8 7.2 2009 5.5 7.3 –8.8 1.3 12.1 17.8 4.5 4.9 2010 6.7 6.4 1.1 1.2 8.4 7.9 B. Time series of abnormal returns around engagement disclosure . . Full sample . Asia . Europe . North America . Disclosure . CAR . CAR . CAR . CAR . CAR . CAR . CAR . CAR . year . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . (⁠|$-$|10,10) . (⁠|$-$|20,20) . 2000 12.8 13.5 7.0 7.2 6.3 5.6 16.9 18.8 2001 5.3 9.4 –2.1 4.7 0.1 –5.8 6.8 13.0 2002 6.8 8.1 8.6 12.4 4.5 2.5 8.3 11.8 2003 7.8 8.8 18.1 17.9 6.4 9.6 7.5 8.0 2004 7.3 7.5 10.7 15.6 3.4 5.2 8.6 6.1 2005 4.3 4.3 2.4 1.8 2.5 5.0 5.8 5.0 2006 6.0 6.2 6.2 6.6 3.3 3.4 6.9 7.0 2007 4.8 4.4 4.2 3.7 3.5 3.5 5.5 4.9 2008 7.8 7.5 14.0 12.1 4.0 5.7 7.8 7.2 2009 5.5 7.3 –8.8 1.3 12.1 17.8 4.5 4.9 2010 6.7 6.4 1.1 1.2 8.4 7.9 C. Abnormal returns around stand-alone and wolf pack engagement disclosures . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Sample . Abn. ret. . SE . |$N$| . Abn. ret. . SE . |$N$| . Stand-alone activist 5.99*** [0.45] 1,264 6.32*** [0.63] 1,264 Wolf pack activist 14.05*** [1.87] 164 13.82*** [2.33] 164 Difference –8.06*** [1.41] –7.50*** [1.93] C. Abnormal returns around stand-alone and wolf pack engagement disclosures . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Sample . Abn. ret. . SE . |$N$| . Abn. ret. . SE . |$N$| . Stand-alone activist 5.99*** [0.45] 1,264 6.32*** [0.63] 1,264 Wolf pack activist 14.05*** [1.87] 164 13.82*** [2.33] 164 Difference –8.06*** [1.41] –7.50*** [1.93] D. Regression of abnormal return around engagement disclosure on activist stakes and wolf pack status . . CAR (⁠|$-$|10,10) . CAR (⁠|$-$|20,20) . Dependent variable: . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . Stake held 0.18** 0.27*** 0.19* 0.28*** |$\quad$|by activist [0.073] [0.071] [0.10] [0.097] |$\quad$|(start) Stake held 0.12** 0.15*** 0.031 0.064 |$\quad$|by activist [0.053] [0.053] [0.074] [0.073] |$\quad$|(high) Wolf pack 6.99*** 7.32*** 6.39*** 6.85*** |$\quad$| (1/0) [1.49] [1.47] [2.04] [2.04] Residual 7.26*** 7.04*** |$\quad$|wolf pack [1.52] [2.09] |$\quad$|(start) Residual 7.05*** 6.96*** |$\quad$|wolf pack [1.52] [2.10] |$\quad$|(high) Observations 1,216 1,216 1,048 1,048 1,216 1,216 1,048 1,048 Adjusted 0.028 0.028 0.029 0.026 0.013 0.014 0.010 0.009 |$\quad$|R-squared D. Regression of abnormal return around engagement disclosure on activist stakes and wolf pack status . . CAR (⁠|$-$|10,10) . CAR (⁠|$-$|20,20) . Dependent variable: . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . Stake held 0.18** 0.27*** 0.19* 0.28*** |$\quad$|by activist [0.073] [0.071] [0.10] [0.097] |$\quad$|(start) Stake held 0.12** 0.15*** 0.031 0.064 |$\quad$|by activist [0.053] [0.053] [0.074] [0.073] |$\quad$|(high) Wolf pack 6.99*** 7.32*** 6.39*** 6.85*** |$\quad$| (1/0) [1.49] [1.47] [2.04] [2.04] Residual 7.26*** 7.04*** |$\quad$|wolf pack [1.52] [2.09] |$\quad$|(start) Residual 7.05*** 6.96*** |$\quad$|wolf pack [1.52] [2.10] |$\quad$|(high) Observations 1,216 1,216 1,048 1,048 1,216 1,216 1,048 1,048 Adjusted 0.028 0.028 0.029 0.026 0.013 0.014 0.010 0.009 |$\quad$|R-squared E. Abnormal returns around domestic and foreign engagement disclosures . . Domestic non-U.S. (1) . Domestic U.S. (2) . Foreign non-U.S. (3) . Foreign U.S. (4) . Diff. (⁠|$t$|-stat) (1)&(2) - (3)&(4) . Event window: (⁠|$-$|10,10) 7.02*** 6.97*** 3.84*** 3.55*** 4.01*** [1.02] [0.49] [0.86] [0.74] Event window: (⁠|$-$|20,20) 7.34*** 6.94*** 4.27*** 4.87*** 2.21** [1.44] [0.65] [1.12] [1.10] E. Abnormal returns around domestic and foreign engagement disclosures . . Domestic non-U.S. (1) . Domestic U.S. (2) . Foreign non-U.S. (3) . Foreign U.S. (4) . Diff. (⁠|$t$|-stat) (1)&(2) - (3)&(4) . Event window: (⁠|$-$|10,10) 7.02*** 6.97*** 3.84*** 3.55*** 4.01*** [1.02] [0.49] [0.86] [0.74] Event window: (⁠|$-$|20,20) 7.34*** 6.94*** 4.27*** 4.87*** 2.21** [1.44] [0.65] [1.12] [1.10] The table shows average cumulative abnormal returns (CARs) around the initial filing date or the first press disclosure date of engagements, market model-adjusted. In panels C and D wolf pack engagements involving multiple funds are treated as one engagement only; in case within a wolf pack engagement are disclosed on separate dates, CARs are summed per wolf pack, across announcements. Stake held by activist (Start) indicates the activist stake at initial disclosure (summed over all members of the wolf pack if applicable); Stake held by activist (High) indicates the highest stake the activist reaches during the engagement (summed over all members of the wolf pack if applicable); and both variables are available for a subsample of engagements. In panel D, Wolf pack (1/0) is a dummy variable indicating a wolf pack (1) or stand-alone (0) engagement; and Residual wolf pack (start) is the residual from a regression of the Wolf pack (1/0) dummy on Stake held by activist (Start), with announcement year and country fixed effects. Residual wolf pack (High) is the residual from the same regression, but instead uses Stake held by activist (High). The event window is centered on day zero, where day zero corresponds to the filing or press disclosure date. For the market model, factor loadings are estimated over 250 trading days preceding the event window, using country-specific domestic market returns, with a minimum of 150 daily observations (1,617 out of 1,740 engagement disclosures have sufficient data). Abnormal returns are winsorized at the 1st and 99th percentiles. Standard errors (White 1980 heteroscedasticity robust in panel E) are reported in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab There is some variation across the three regions. For the (⁠|$-$|20, 20) window in panel A, North America has the highest disclosure returns at 7.0%, followed by Asia at 6.4% and Europe at 4.8%. North American abnormal returns are virtually identical to those reported for the United States by Brav et al. (2008) for the 2001-2006 period.12 As Figure 2 shows, there is some post-disclosure drift in abnormal returns in all three regions. Also shown is high abnormal share turnover (calculated relative to average turnover prior to the event window) around the activist engagement disclosure event; it increases by more than 80% over normal turnover prior to the event period, which in part reflects the stake purchases of the activist and, in some cases more than one activist. Figure 2 Open in new tabDownload slide Cumulative abnormal returns around disclosure of activist engagements The dotted line (right axis) shows average cumulative abnormal returns around the initial filing date or the first press disclosure date of engagements, market model adjusted. The event window is (-20, |$+$|20) days, where day zero corresponds to the filing or press disclosure date. Factor loadings are estimated over 250 trading days preceding the event window, using country-specific domestic market returns, with a minimum of 150 daily observations (1,617 out of 1,740 sample deals have sufficient data). The bars (left axis) show abnormal trading activity in the target’s equity during the event window, where trading activity is abnormal share turnover calculated relative to average turnover during 250 trading days preceding the event window. Abnormal returns and abnormal trading activity are winsorized at the 1st and 99th percentiles. Figure 2 Open in new tabDownload slide Cumulative abnormal returns around disclosure of activist engagements The dotted line (right axis) shows average cumulative abnormal returns around the initial filing date or the first press disclosure date of engagements, market model adjusted. The event window is (-20, |$+$|20) days, where day zero corresponds to the filing or press disclosure date. Factor loadings are estimated over 250 trading days preceding the event window, using country-specific domestic market returns, with a minimum of 150 daily observations (1,617 out of 1,740 sample deals have sufficient data). The bars (left axis) show abnormal trading activity in the target’s equity during the event window, where trading activity is abnormal share turnover calculated relative to average turnover during 250 trading days preceding the event window. Abnormal returns and abnormal trading activity are winsorized at the 1st and 99th percentiles. Focusing on the time series of disclosure returns for the full sample and by region, panel B of Table 5 shows they are on average higher in North America during the early 2000s than during the late 2000s (10.5% versus 5.8%, respectively), but in Europe the pattern is reversed. The years 2003 and 2004 in Asia stand out, with abnormal returns above 15%. These engagements include some of the most high-profile ones initiated by Steel Partners and Murakami in Japan and Sovereign Asset Management in South Korea. Panel C compares disclosure returns of stand-alone engagements with those of wolf packs, that is, multiple activists engaging the same target. The results show that disclosure returns for multiple engagements are strikingly higher at 13.8% compared with stand-alone deals at 6.3% (⁠|$-$|20, 20 event window). While it is possible that joint voting power of the hedge funds may contribute to these high returns through higher outcome probabilities, it is also plausible that wolf packs form in response to highly profitable engagements. We show below that these dramatically higher disclosure returns of wolf packs reflect much higher probabilities of successful outcomes. First, however, we investigate whether the higher disclosure returns of wolf packs are attributable to the larger stakes that they control: The aggregate ownership stakes held by wolf packs are significantly larger than those of stand-alone activist engagements. At the beginning of an engagement, stand-alone activists hold an 8.0% stake on average, while wolf packs, in aggregate, own 13.4% (unreported in the table). To investigate whether higher disclosure returns of wolf packs are attributable to these larger stakes, in panel D of Table 5, we regress announcement returns on activist stakes and three alternative wolf pack measures. The first, Wolf pack (1/0), is a dummy for an engagement that involves a wolf pack (1) or does not (0). The second and third variables attempt to remove the correlation between wolf packs and the size of their stakes. This helps separate the size of stake (more voting power) from a potential coordination effect that would be directly observable if a group or concert party had been notified. The second variable, Residual wolf pack (Start), is defined as the residual from a regression of Wolf pack (1/0) on Stake held by activist (Start) as well as announcement year and country fixed effects. The third variable is Residual wolf pack (High), which is the residual from the same regression using instead the maximum stake during the engagement, Stake held by activist (High). The results for both event windows and for all three measures of wolf pack status are consistent: While activist stakes, as expected, have a positive effect on disclosure returns, the effect of wolf packs is largely independent of the larger stakes they control. Controlling for activist stake size, wolf packs for the (⁠|$-$|20, 20) window continue to have between 6.4% and 7.0% larger disclosure returns than stand-alone engagements. Finally, in panel E of Table 5, we analyze the performance of domestic and foreign activist engagements. We compare the performance of U.S. activists at home against their performance overseas, and against their foreign peers, who themselves engage both domestic and foreign targets. We find that disclosure abnormal returns for domestic engagements are 7.0% during the (⁠|$-$|20, 20) event window for domestic engagements compared with 3.6% to 3.8% for foreign engagements. Again, domestic engagements are similar for U.S. and non-U.S. activists. This suggests that domestic activism may be more profitable than foreign activism if engagement costs are similar. 3.3 Outcome probabilities and disclosure returns around outcomes Table 6 reports the total number of all successful outcomes, grouped by year during which the outcome is announced. Outcomes are categorized as “Board” (replacement of the CEO, CFO, Chairman, or Nonexecutive directors), “Payout” (share buybacks or increased/special dividends) and corporate restructuring. We separate restructurings into “Takeover” (the target firm is acquired by a strategic buyer or private equity fund), and “Restructuring” (divestitures and spin-offs of non-core assets, and the blocking of diversifying acquisitions).13 These categories are based on the internal classification of engagement outcomes by one of the largest hedge funds in our sample (see Becht et al. 2009). They are broader than those typically used in studies of domestic U.S. engagements (see, e.g., Brav, Jiang, and Kim 2010; Greenwood and Schor 2009), and necessitated by having to identify outcomes consistently across many countries from non-standardized news reports. Table 6 Activist engagement outcomes . Ongoing engagements (Stock) . All successful outcomes . Outcomes by type . Outcome year . Asia . EU . NA . Total . Asia . EU . NA . Total . Board . Payout . Restr. . Takeo. . 2000 1 15 32 48 2 2 9 13 2 2 4 5 2001 3 24 76 103 1 6 19 26 8 5 9 4 2002 6 41 102 149 1 14 24 39 10 12 7 10 2003 9 57 146 212 2 26 31 59 24 9 14 12 2004 32 84 183 299 7 33 44 84 31 15 23 15 2005 78 121 278 477 8 49 69 126 58 17 29 22 2006 119 172 476 767 11 58 169 238 86 48 44 60 2007 138 219 585 942 17 75 180 272 83 70 44 75 2008 153 212 555 920 9 33 148 190 75 47 36 32 2009 122 180 449 751 5 18 101 124 64 25 17 18 2010 89 156 355 600 0 13 47 60 27 2 14 17 . Ongoing engagements (Stock) . All successful outcomes . Outcomes by type . Outcome year . Asia . EU . NA . Total . Asia . EU . NA . Total . Board . Payout . Restr. . Takeo. . 2000 1 15 32 48 2 2 9 13 2 2 4 5 2001 3 24 76 103 1 6 19 26 8 5 9 4 2002 6 41 102 149 1 14 24 39 10 12 7 10 2003 9 57 146 212 2 26 31 59 24 9 14 12 2004 32 84 183 299 7 33 44 84 31 15 23 15 2005 78 121 278 477 8 49 69 126 58 17 29 22 2006 119 172 476 767 11 58 169 238 86 48 44 60 2007 138 219 585 942 17 75 180 272 83 70 44 75 2008 153 212 555 920 9 33 148 190 75 47 36 32 2009 122 180 449 751 5 18 101 124 64 25 17 18 2010 89 156 355 600 0 13 47 60 27 2 14 17 . Board outcomes/stock . Payout outcomes/stock . Restruct. outcomes/stock . Takeover outcomes/stock . . Asia . EU . NA . Asia . EU . NA . Asia . EU . NA . Asia . EU . NA . 2000 0.00 0.07 0.03 1.00 0.00 0.03 0.00 0.00 0.13 1.00 0.07 0.09 2001 0.33 0.00 0.09 0.00 0.04 0.05 0.00 0.21 0.05 0.00 0.00 0.05 2002 0.00 0.10 0.06 0.17 0.10 0.07 0.00 0.10 0.03 0.00 0.05 0.08 2003 0.00 0.19 0.09 0.00 0.07 0.03 0.22 0.12 0.03 0.00 0.07 0.05 2004 0.06 0.14 0.09 0.13 0.02 0.05 0.03 0.14 0.05 0.00 0.08 0.04 2005 0.01 0.19 0.12 0.05 0.01 0.04 0.01 0.14 0.04 0.03 0.07 0.04 2006 0.04 0.07 0.14 0.01 0.07 0.07 0.03 0.08 0.06 0.02 0.12 0.08 2007 0.03 0.10 0.10 0.04 0.06 0.09 0.04 0.08 0.04 0.01 0.10 0.09 2008 0.01 0.08 0.10 0.04 0.01 0.07 0.01 0.03 0.05 0.00 0.03 0.05 2009 0.02 0.06 0.12 0.01 0.01 0.05 0.02 0.01 0.03 0.00 0.03 0.03 2010 0.00 0.02 0.07 0.00 0.01 0.00 0.00 0.03 0.03 0.00 0.03 0.04 . Board outcomes/stock . Payout outcomes/stock . Restruct. outcomes/stock . Takeover outcomes/stock . . Asia . EU . NA . Asia . EU . NA . Asia . EU . NA . Asia . EU . NA . 2000 0.00 0.07 0.03 1.00 0.00 0.03 0.00 0.00 0.13 1.00 0.07 0.09 2001 0.33 0.00 0.09 0.00 0.04 0.05 0.00 0.21 0.05 0.00 0.00 0.05 2002 0.00 0.10 0.06 0.17 0.10 0.07 0.00 0.10 0.03 0.00 0.05 0.08 2003 0.00 0.19 0.09 0.00 0.07 0.03 0.22 0.12 0.03 0.00 0.07 0.05 2004 0.06 0.14 0.09 0.13 0.02 0.05 0.03 0.14 0.05 0.00 0.08 0.04 2005 0.01 0.19 0.12 0.05 0.01 0.04 0.01 0.14 0.04 0.03 0.07 0.04 2006 0.04 0.07 0.14 0.01 0.07 0.07 0.03 0.08 0.06 0.02 0.12 0.08 2007 0.03 0.10 0.10 0.04 0.06 0.09 0.04 0.08 0.04 0.01 0.10 0.09 2008 0.01 0.08 0.10 0.04 0.01 0.07 0.01 0.03 0.05 0.00 0.03 0.05 2009 0.02 0.06 0.12 0.01 0.01 0.05 0.02 0.01 0.03 0.00 0.03 0.03 2010 0.00 0.02 0.07 0.00 0.01 0.00 0.00 0.03 0.03 0.00 0.03 0.04 The table provides the number of engagements and subsequent successful outcomes by year of the outcome announcement. Engagement outcomes are categorized as board changes (replacement of the CEO, Chairman, or Nonexecutive Directors), changes to pay-out policy (share buybacks or increased/special dividends), restructuring (divestitures and spin-offs of noncore assets, and blocking diversifying acquisitions), and takeovers (the target firm is acquired by a strategic buyer or private equity fund). Results are separately reported for Asia, Europe (EU), and North America (NA). The stock of ongoing engagements is number of outstanding engagements from the previous year plus entries minus exits. Open in new tab Table 6 Activist engagement outcomes . Ongoing engagements (Stock) . All successful outcomes . Outcomes by type . Outcome year . Asia . EU . NA . Total . Asia . EU . NA . Total . Board . Payout . Restr. . Takeo. . 2000 1 15 32 48 2 2 9 13 2 2 4 5 2001 3 24 76 103 1 6 19 26 8 5 9 4 2002 6 41 102 149 1 14 24 39 10 12 7 10 2003 9 57 146 212 2 26 31 59 24 9 14 12 2004 32 84 183 299 7 33 44 84 31 15 23 15 2005 78 121 278 477 8 49 69 126 58 17 29 22 2006 119 172 476 767 11 58 169 238 86 48 44 60 2007 138 219 585 942 17 75 180 272 83 70 44 75 2008 153 212 555 920 9 33 148 190 75 47 36 32 2009 122 180 449 751 5 18 101 124 64 25 17 18 2010 89 156 355 600 0 13 47 60 27 2 14 17 . Ongoing engagements (Stock) . All successful outcomes . Outcomes by type . Outcome year . Asia . EU . NA . Total . Asia . EU . NA . Total . Board . Payout . Restr. . Takeo. . 2000 1 15 32 48 2 2 9 13 2 2 4 5 2001 3 24 76 103 1 6 19 26 8 5 9 4 2002 6 41 102 149 1 14 24 39 10 12 7 10 2003 9 57 146 212 2 26 31 59 24 9 14 12 2004 32 84 183 299 7 33 44 84 31 15 23 15 2005 78 121 278 477 8 49 69 126 58 17 29 22 2006 119 172 476 767 11 58 169 238 86 48 44 60 2007 138 219 585 942 17 75 180 272 83 70 44 75 2008 153 212 555 920 9 33 148 190 75 47 36 32 2009 122 180 449 751 5 18 101 124 64 25 17 18 2010 89 156 355 600 0 13 47 60 27 2 14 17 . Board outcomes/stock . Payout outcomes/stock . Restruct. outcomes/stock . Takeover outcomes/stock . . Asia . EU . NA . Asia . EU . NA . Asia . EU . NA . Asia . EU . NA . 2000 0.00 0.07 0.03 1.00 0.00 0.03 0.00 0.00 0.13 1.00 0.07 0.09 2001 0.33 0.00 0.09 0.00 0.04 0.05 0.00 0.21 0.05 0.00 0.00 0.05 2002 0.00 0.10 0.06 0.17 0.10 0.07 0.00 0.10 0.03 0.00 0.05 0.08 2003 0.00 0.19 0.09 0.00 0.07 0.03 0.22 0.12 0.03 0.00 0.07 0.05 2004 0.06 0.14 0.09 0.13 0.02 0.05 0.03 0.14 0.05 0.00 0.08 0.04 2005 0.01 0.19 0.12 0.05 0.01 0.04 0.01 0.14 0.04 0.03 0.07 0.04 2006 0.04 0.07 0.14 0.01 0.07 0.07 0.03 0.08 0.06 0.02 0.12 0.08 2007 0.03 0.10 0.10 0.04 0.06 0.09 0.04 0.08 0.04 0.01 0.10 0.09 2008 0.01 0.08 0.10 0.04 0.01 0.07 0.01 0.03 0.05 0.00 0.03 0.05 2009 0.02 0.06 0.12 0.01 0.01 0.05 0.02 0.01 0.03 0.00 0.03 0.03 2010 0.00 0.02 0.07 0.00 0.01 0.00 0.00 0.03 0.03 0.00 0.03 0.04 . Board outcomes/stock . Payout outcomes/stock . Restruct. outcomes/stock . Takeover outcomes/stock . . Asia . EU . NA . Asia . EU . NA . Asia . EU . NA . Asia . EU . NA . 2000 0.00 0.07 0.03 1.00 0.00 0.03 0.00 0.00 0.13 1.00 0.07 0.09 2001 0.33 0.00 0.09 0.00 0.04 0.05 0.00 0.21 0.05 0.00 0.00 0.05 2002 0.00 0.10 0.06 0.17 0.10 0.07 0.00 0.10 0.03 0.00 0.05 0.08 2003 0.00 0.19 0.09 0.00 0.07 0.03 0.22 0.12 0.03 0.00 0.07 0.05 2004 0.06 0.14 0.09 0.13 0.02 0.05 0.03 0.14 0.05 0.00 0.08 0.04 2005 0.01 0.19 0.12 0.05 0.01 0.04 0.01 0.14 0.04 0.03 0.07 0.04 2006 0.04 0.07 0.14 0.01 0.07 0.07 0.03 0.08 0.06 0.02 0.12 0.08 2007 0.03 0.10 0.10 0.04 0.06 0.09 0.04 0.08 0.04 0.01 0.10 0.09 2008 0.01 0.08 0.10 0.04 0.01 0.07 0.01 0.03 0.05 0.00 0.03 0.05 2009 0.02 0.06 0.12 0.01 0.01 0.05 0.02 0.01 0.03 0.00 0.03 0.03 2010 0.00 0.02 0.07 0.00 0.01 0.00 0.00 0.03 0.03 0.00 0.03 0.04 The table provides the number of engagements and subsequent successful outcomes by year of the outcome announcement. Engagement outcomes are categorized as board changes (replacement of the CEO, Chairman, or Nonexecutive Directors), changes to pay-out policy (share buybacks or increased/special dividends), restructuring (divestitures and spin-offs of noncore assets, and blocking diversifying acquisitions), and takeovers (the target firm is acquired by a strategic buyer or private equity fund). Results are separately reported for Asia, Europe (EU), and North America (NA). The stock of ongoing engagements is number of outstanding engagements from the previous year plus entries minus exits. Open in new tab The impact of the financial crisis on activist engagements is significant. First, the steady increase in the global number of simultaneously ongoing engagements from 2000 onward peaks in 2007 and declines every year afterwards (in Asia the peak is in 2008). Second, the total number of outcomes drops, in Asia from 17 in 2007 to 9 in 2008 and further to 5 in 2009, with similar declines in Europe and North America. Third, since outcomes decline faster than the stock of engagements, the probability of achieving successful outcomes per engagement declines after 2007. The decline is spread unevenly across types of outcomes: the number of successful board outcomes continues to be relatively high while the number of takeovers associated with the activist engagement sharply declines. In Asia, where successful takeover outcomes are infrequent throughout the sample, there are no activist successes after 2007. This is also related to two important activist failures, Steel Partner’s engagement of Bull-Dog Sauce and TCI’s engagement of J-Power, that seriously undermined the prospects of confrontational activism in Japan. We discuss these cases in the Internet Appendix. In Europe successful takeover outcomes drop from 10% of all ongoing engagements in 2007 to 3% in 2008 and do not recover, with similar numbers for North America. Next, we examine the disclosure returns around outcome announcements. These returns were already partly anticipated by the initial block disclosure returns. The abnormal returns around the disclosure of activist engagements should reflect the probability and potential profitability of successful outcomes from the engagement. If investors correctly assess the probability of engagement success on average–ex ante, abnormal disclosure returns are higher for engagements with subsequent successful outcomes than for engagements without any outcomes. This is exactly what we find with 7.9% block disclosure returns for engagements with successful outcomes and 4.7% for engagements without outcomes (for the (⁠|$-$|20, 20) window); the difference is statistically significant at the 1% level. We would expect engagements with observable outcomes to be associated with additional post-disclosure abnormal returns, and those engagements without outcomes to be associated with losses post-disclosure. We therefore analyze the cumulative abnormal returns around the disclosure of observable outcomes of engagements. Since we can only measure these returns for successful engagements, we also provide below a comparison of the long-term performance of successful and unsuccessful engagements. Table 7 reports abnormal returns for all outcomes, again for (⁠|$-$|10, 10) and (⁠|$-$|20, 20) event windows. Out of 1740 engagements, 880 have at least one subsequent outcome and of those 850 have sufficient data to calculate abnormal returns. A significant number of engagements, 139 in total, achieve multiple outcomes, for example a takeover preceded by a board change or another type of restructuring. As well as reporting returns for engagements with multiple outcomes, we split them further into outcomes that include a takeover of the target (“Multiple|$+$|Takeover,” 58 engagements), and those which do not (“Multiple|$+$|NoTakeover,” 81 engagements). Table 7 Abnormal returns from engagement outcomes A. Abnormal returns around engagement outcomes . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . . Abn. ret. . SE . |$N$| . Abn. Ret. . SE . |$N$| . All outcomes 6.33*** [0.62] 850 6.42*** [0.78] 850 Board 4.04*** [1.00] 272 4.48*** [1.45] 272 Payout 1.42 [1.07] 134 –0.16 [1.54] 134 Restructuring 5.74*** [1.69] 118 5.60*** [1.92] 118 Takeover 9.33*** [1.16] 187 9.73*** [1.33] 187 Multiple|$+$|Takeover 18.3*** [3.68] 58 18.1*** [4.20] 58 Multiple|$+$|NoTakeover 7.46*** [2.44] 81 9.04*** [2.95] 81 A. Abnormal returns around engagement outcomes . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . . Abn. ret. . SE . |$N$| . Abn. Ret. . SE . |$N$| . All outcomes 6.33*** [0.62] 850 6.42*** [0.78] 850 Board 4.04*** [1.00] 272 4.48*** [1.45] 272 Payout 1.42 [1.07] 134 –0.16 [1.54] 134 Restructuring 5.74*** [1.69] 118 5.60*** [1.92] 118 Takeover 9.33*** [1.16] 187 9.73*** [1.33] 187 Multiple|$+$|Takeover 18.3*** [3.68] 58 18.1*** [4.20] 58 Multiple|$+$|NoTakeover 7.46*** [2.44] 81 9.04*** [2.95] 81 B. Abnormal returns around engagement outcomes by region . . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Region . Outcome . Abn. ret. . SE . |$N$| . Abn. Ret. . SE . |$N$| . Asia All outcomes 4.03** [1.91] 38 2.72 [3.48] 38 Board –1.03 [5.56] 6 –4.20 [10.6] 6 Payout 2.34 [2.22] 15 –1.62 [3.98] 15 Restructuring 8.03* [3.65] 9 4.60 [4.07] 9 Takeover 3.33 [8.16] 4 1.15 [13.7] 4 Multiple|$+$|Takeover 13.7*** [0.10] 2 1.70 [9.42] 2 Multiple|$+$|NoTakeover 5.60 [21.0] 2 51.7 [25.1] 2 Europe All outcomes 8.32*** [1.43] 183 8.77*** [1.74] 183 Board 1.75 [2.90] 43 4.03 [4.19] 43 Payout –0.21 [1.56] 12 1.30 [3.06] 12 Restructuring 5.53*** [1.81] 33 5.25** [2.09] 33 Takeover 9.87*** [1.88] 54 10.8*** [2.25] 54 Multiple|$+$|Takeover 27.3*** [7.51] 16 25.1** [9.45] 16 Multiple|$+$|NoTakeover 11.9** [5.27] 25 10.3* [5.93] 25 North America All outcomes 5.89*** [0.72] 629 5.97*** [0.90] 629 Board 4.62*** [1.07] 223 4.80*** [1.56] 223 Payout 1.47 [1.30] 107 –0.11 [1.83] 107 Restructuring 5.56** [2.48] 76 5.87** [2.81] 76 Takeover 9.29*** [1.48] 129 9.54*** [1.64] 129 Multiple|$+$|Takeover 15.0*** [4.34] 40 16.2*** [4.76] 40 Multiple|$+$|NoTakeover 5.49** [2.66] 54 6.89** [3.25] 54 B. Abnormal returns around engagement outcomes by region . . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Region . Outcome . Abn. ret. . SE . |$N$| . Abn. Ret. . SE . |$N$| . Asia All outcomes 4.03** [1.91] 38 2.72 [3.48] 38 Board –1.03 [5.56] 6 –4.20 [10.6] 6 Payout 2.34 [2.22] 15 –1.62 [3.98] 15 Restructuring 8.03* [3.65] 9 4.60 [4.07] 9 Takeover 3.33 [8.16] 4 1.15 [13.7] 4 Multiple|$+$|Takeover 13.7*** [0.10] 2 1.70 [9.42] 2 Multiple|$+$|NoTakeover 5.60 [21.0] 2 51.7 [25.1] 2 Europe All outcomes 8.32*** [1.43] 183 8.77*** [1.74] 183 Board 1.75 [2.90] 43 4.03 [4.19] 43 Payout –0.21 [1.56] 12 1.30 [3.06] 12 Restructuring 5.53*** [1.81] 33 5.25** [2.09] 33 Takeover 9.87*** [1.88] 54 10.8*** [2.25] 54 Multiple|$+$|Takeover 27.3*** [7.51] 16 25.1** [9.45] 16 Multiple|$+$|NoTakeover 11.9** [5.27] 25 10.3* [5.93] 25 North America All outcomes 5.89*** [0.72] 629 5.97*** [0.90] 629 Board 4.62*** [1.07] 223 4.80*** [1.56] 223 Payout 1.47 [1.30] 107 –0.11 [1.83] 107 Restructuring 5.56** [2.48] 76 5.87** [2.81] 76 Takeover 9.29*** [1.48] 129 9.54*** [1.64] 129 Multiple|$+$|Takeover 15.0*** [4.34] 40 16.2*** [4.76] 40 Multiple|$+$|NoTakeover 5.49** [2.66] 54 6.89** [3.25] 54 C. Sequence of engagement outcomes for engagements with multiple outcomes that involve a takeover . . Average engagement length with multiple outcome . Average waiting time to event . . . Board . Payout . Restructuring . Takeover . . . (1) . (2) . (3) . (4) . Time 806 days Percentage 100 36 48 44 76 |$t$|-test vs. takeover (4) |$-$|8.25*** |$-$|4.32*** |$-$|4.71*** C. Sequence of engagement outcomes for engagements with multiple outcomes that involve a takeover . . Average engagement length with multiple outcome . Average waiting time to event . . . Board . Payout . Restructuring . Takeover . . . (1) . (2) . (3) . (4) . Time 806 days Percentage 100 36 48 44 76 |$t$|-test vs. takeover (4) |$-$|8.25*** |$-$|4.32*** |$-$|4.71*** D. Abnormal returns around successful outcomes of stand-alone and wolf pack engagements . . Stand-alone . Wolf pack . Diff . . Stand-alone . Wolf pack . Diff . P(Any outcome) 46% 78% –8.11*** P(Restructuring) 6% 11% –2.73*** P(Board) 12% 32% –7.32*** P(Takeover) 11% 15% –1.59 P(Payout) 7% 9% –1.01 P(Multiple) 11% 11% –0.16 D. Abnormal returns around successful outcomes of stand-alone and wolf pack engagements . . Stand-alone . Wolf pack . Diff . . Stand-alone . Wolf pack . Diff . P(Any outcome) 46% 78% –8.11*** P(Restructuring) 6% 11% –2.73*** P(Board) 12% 32% –7.32*** P(Takeover) 11% 15% –1.59 P(Payout) 7% 9% –1.01 P(Multiple) 11% 11% –0.16 . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . . Stand-alone . Wolf pack . Diff . Stand-alone . Wolf pack . Diff . . Abn. ret. . SE . ARet. . SE . . ARet. . SE . ARet. . SE . . All outcomes 6.38*** [0.76] 7.22*** [1.59] –0.46 7.11*** [0.99] 5.89*** [1.81] 0.53 Board 2.49* [1.41] 4.74** [2.21] –0.84 4.20* [2.16] 4.5 [3.04] –0.07 Payout 1.66 [1.33] –1.03 [2.39] 0.77 –0.27 [1.95] –3.82 [3.11] 0.69 Restructuring 5.19*** [1.85] 5.8 [5.25] –0.14 6.25** [2.57] 4.07 [4.09] 0.4 Takeover 8.75*** [1.33] 14.0*** [3.44] –1.51 9.97*** [1.58] 11.6*** [3.36] –0.4 Multiple 12.0*** [2.13] 13.9** [5.13] –0.3 12.8*** [2.48] 12.6* [6.31] 0.03 . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . . Stand-alone . Wolf pack . Diff . Stand-alone . Wolf pack . Diff . . Abn. ret. . SE . ARet. . SE . . ARet. . SE . ARet. . SE . . All outcomes 6.38*** [0.76] 7.22*** [1.59] –0.46 7.11*** [0.99] 5.89*** [1.81] 0.53 Board 2.49* [1.41] 4.74** [2.21] –0.84 4.20* [2.16] 4.5 [3.04] –0.07 Payout 1.66 [1.33] –1.03 [2.39] 0.77 –0.27 [1.95] –3.82 [3.11] 0.69 Restructuring 5.19*** [1.85] 5.8 [5.25] –0.14 6.25** [2.57] 4.07 [4.09] 0.4 Takeover 8.75*** [1.33] 14.0*** [3.44] –1.51 9.97*** [1.58] 11.6*** [3.36] –0.4 Multiple 12.0*** [2.13] 13.9** [5.13] –0.3 12.8*** [2.48] 12.6* [6.31] 0.03 E. Abnormal returns around successful outcomes of domestic and foreign engagements . . Domestic non-U.S. . Domestic U.S. . Foreign non-U.S. . Foreign U.S. . Diff. (⁠|$t$|-stat) . . (1) . (2) . (3) . (4) . (1)&(2) - (3)&(4) . P(Any outcome) 37% 57% 39% 41% 5.18*** P(Board) 18% 27% 17% 12% 4.84*** P(Payout) 8% 13% 8% 10% 2.08** P(Restructuring) 10% 11% 10% 16% –1.39 P(Takeover) 15% 16% 13% 12% 1.54 E. Abnormal returns around successful outcomes of domestic and foreign engagements . . Domestic non-U.S. . Domestic U.S. . Foreign non-U.S. . Foreign U.S. . Diff. (⁠|$t$|-stat) . . (1) . (2) . (3) . (4) . (1)&(2) - (3)&(4) . P(Any outcome) 37% 57% 39% 41% 5.18*** P(Board) 18% 27% 17% 12% 4.84*** P(Payout) 8% 13% 8% 10% 2.08** P(Restructuring) 10% 11% 10% 16% –1.39 P(Takeover) 15% 16% 13% 12% 1.54 . . ARet. . SE . ARet. . SE . ARet. . SE . ARet. . SE . . (⁠|$-$|10,10) All outcomes 9.17*** [2.63] 6.19*** [0.73] 6.19*** [1.89] 5.11*** [1.69] 0.56 Board –3.06 [4.37] 4.90*** [1.08] 4.71 [4.86] 0.11 [2.30] 0.50 Payout 2.26 [2.90] 1.72 [1.33] –1.33 [2.27] 0.76 [2.15] 0.63 Restructuring 4.03 [3.88] 5.94** [2.54] 7.43** [2.70] 5.09** [2.30] –0.05 Takeover 10.8** [4.15] 9.33*** [1.49] 6.30** [2.20] 10.7*** [2.62] 0.30 Multiple 24.0*** [6.21] 10.2*** [2.46] 11.1* [5.69] 7.06 [9.47] 0.62 (⁠|$-$|20,20) All outcomes 8.91*** [3.25] 6.32*** [0.91] 7.39*** [2.76] 4.35** [1.96] 0.34 Board –3.74 [6.57] 5.18*** [1.56] 7.25 [7.23] 1.55 [3.86] 0.53 Payout 0.65 [9.07] 0.35 [1.86] –5.17 [3.89] –0.61 [2.95] 0.66 Restructuring 2.47 [3.59] 6.43** [2.86] 4.87 [3.93] 5.03** [2.51] 0.26 Takeover 12.0** [4.50] 9.61*** [1.66] 9.13** [3.88] 8.77** [3.23] 0.62 Multiple 23.5*** [7.51] 11.2*** [2.80] 14.6* [7.58] 5.02 [10.5] 0.47 . . ARet. . SE . ARet. . SE . ARet. . SE . ARet. . SE . . (⁠|$-$|10,10) All outcomes 9.17*** [2.63] 6.19*** [0.73] 6.19*** [1.89] 5.11*** [1.69] 0.56 Board –3.06 [4.37] 4.90*** [1.08] 4.71 [4.86] 0.11 [2.30] 0.50 Payout 2.26 [2.90] 1.72 [1.33] –1.33 [2.27] 0.76 [2.15] 0.63 Restructuring 4.03 [3.88] 5.94** [2.54] 7.43** [2.70] 5.09** [2.30] –0.05 Takeover 10.8** [4.15] 9.33*** [1.49] 6.30** [2.20] 10.7*** [2.62] 0.30 Multiple 24.0*** [6.21] 10.2*** [2.46] 11.1* [5.69] 7.06 [9.47] 0.62 (⁠|$-$|20,20) All outcomes 8.91*** [3.25] 6.32*** [0.91] 7.39*** [2.76] 4.35** [1.96] 0.34 Board –3.74 [6.57] 5.18*** [1.56] 7.25 [7.23] 1.55 [3.86] 0.53 Payout 0.65 [9.07] 0.35 [1.86] –5.17 [3.89] –0.61 [2.95] 0.66 Restructuring 2.47 [3.59] 6.43** [2.86] 4.87 [3.93] 5.03** [2.51] 0.26 Takeover 12.0** [4.50] 9.61*** [1.66] 9.13** [3.88] 8.77** [3.23] 0.62 Multiple 23.5*** [7.51] 11.2*** [2.80] 14.6* [7.58] 5.02 [10.5] 0.47 The table shows average cumulative abnormal returns (CARs) around the announcement of engagement outcomes (market model adjusted) in panels A and B, engagement outcome sequencing in panel C, and compares multiple activist and stand-alone engagements in panel D and domestic and foreign engagements in panel E. Engagement outcomes are categorized as board changes, changes to pay-out policy, restructuring, and takeovers. In case of multiple announcements of outcomes in an engagement, CARs are summed across announcements. In case of multiple outcome types within an engagement. the engagement is classified as “Multiple+Takeover” (if outcomes include a takeover) or “Multiple+NoTakeover.” The event window is centered on the earliest announcement date of the outcome. Factor loadings are estimated over 250 trading days preceding the event window, using country-specific domestic market returns, with a minimum of 150 daily observations. In panels A and B, 850 out of 1,740 engagements have sufficient data and at least one subsequent outcome. In panel C, data are reported for 150 outcomes of the 58 engagements that have multiple outcomes and involve a takeover (Multiple+Takeover). In panel D, wolf pack engagements involving multiple funds are treated as one engagement only if individual engagements within a wolf pack are disclosed on separate dates, CARs are summed per wolf pack, across announcements. Abnormal returns are winsorized at the 1st and 99th percentiles. Standard errors are reported in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab Table 7 Abnormal returns from engagement outcomes A. Abnormal returns around engagement outcomes . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . . Abn. ret. . SE . |$N$| . Abn. Ret. . SE . |$N$| . All outcomes 6.33*** [0.62] 850 6.42*** [0.78] 850 Board 4.04*** [1.00] 272 4.48*** [1.45] 272 Payout 1.42 [1.07] 134 –0.16 [1.54] 134 Restructuring 5.74*** [1.69] 118 5.60*** [1.92] 118 Takeover 9.33*** [1.16] 187 9.73*** [1.33] 187 Multiple|$+$|Takeover 18.3*** [3.68] 58 18.1*** [4.20] 58 Multiple|$+$|NoTakeover 7.46*** [2.44] 81 9.04*** [2.95] 81 A. Abnormal returns around engagement outcomes . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . . Abn. ret. . SE . |$N$| . Abn. Ret. . SE . |$N$| . All outcomes 6.33*** [0.62] 850 6.42*** [0.78] 850 Board 4.04*** [1.00] 272 4.48*** [1.45] 272 Payout 1.42 [1.07] 134 –0.16 [1.54] 134 Restructuring 5.74*** [1.69] 118 5.60*** [1.92] 118 Takeover 9.33*** [1.16] 187 9.73*** [1.33] 187 Multiple|$+$|Takeover 18.3*** [3.68] 58 18.1*** [4.20] 58 Multiple|$+$|NoTakeover 7.46*** [2.44] 81 9.04*** [2.95] 81 B. Abnormal returns around engagement outcomes by region . . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Region . Outcome . Abn. ret. . SE . |$N$| . Abn. Ret. . SE . |$N$| . Asia All outcomes 4.03** [1.91] 38 2.72 [3.48] 38 Board –1.03 [5.56] 6 –4.20 [10.6] 6 Payout 2.34 [2.22] 15 –1.62 [3.98] 15 Restructuring 8.03* [3.65] 9 4.60 [4.07] 9 Takeover 3.33 [8.16] 4 1.15 [13.7] 4 Multiple|$+$|Takeover 13.7*** [0.10] 2 1.70 [9.42] 2 Multiple|$+$|NoTakeover 5.60 [21.0] 2 51.7 [25.1] 2 Europe All outcomes 8.32*** [1.43] 183 8.77*** [1.74] 183 Board 1.75 [2.90] 43 4.03 [4.19] 43 Payout –0.21 [1.56] 12 1.30 [3.06] 12 Restructuring 5.53*** [1.81] 33 5.25** [2.09] 33 Takeover 9.87*** [1.88] 54 10.8*** [2.25] 54 Multiple|$+$|Takeover 27.3*** [7.51] 16 25.1** [9.45] 16 Multiple|$+$|NoTakeover 11.9** [5.27] 25 10.3* [5.93] 25 North America All outcomes 5.89*** [0.72] 629 5.97*** [0.90] 629 Board 4.62*** [1.07] 223 4.80*** [1.56] 223 Payout 1.47 [1.30] 107 –0.11 [1.83] 107 Restructuring 5.56** [2.48] 76 5.87** [2.81] 76 Takeover 9.29*** [1.48] 129 9.54*** [1.64] 129 Multiple|$+$|Takeover 15.0*** [4.34] 40 16.2*** [4.76] 40 Multiple|$+$|NoTakeover 5.49** [2.66] 54 6.89** [3.25] 54 B. Abnormal returns around engagement outcomes by region . . . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . Region . Outcome . Abn. ret. . SE . |$N$| . Abn. Ret. . SE . |$N$| . Asia All outcomes 4.03** [1.91] 38 2.72 [3.48] 38 Board –1.03 [5.56] 6 –4.20 [10.6] 6 Payout 2.34 [2.22] 15 –1.62 [3.98] 15 Restructuring 8.03* [3.65] 9 4.60 [4.07] 9 Takeover 3.33 [8.16] 4 1.15 [13.7] 4 Multiple|$+$|Takeover 13.7*** [0.10] 2 1.70 [9.42] 2 Multiple|$+$|NoTakeover 5.60 [21.0] 2 51.7 [25.1] 2 Europe All outcomes 8.32*** [1.43] 183 8.77*** [1.74] 183 Board 1.75 [2.90] 43 4.03 [4.19] 43 Payout –0.21 [1.56] 12 1.30 [3.06] 12 Restructuring 5.53*** [1.81] 33 5.25** [2.09] 33 Takeover 9.87*** [1.88] 54 10.8*** [2.25] 54 Multiple|$+$|Takeover 27.3*** [7.51] 16 25.1** [9.45] 16 Multiple|$+$|NoTakeover 11.9** [5.27] 25 10.3* [5.93] 25 North America All outcomes 5.89*** [0.72] 629 5.97*** [0.90] 629 Board 4.62*** [1.07] 223 4.80*** [1.56] 223 Payout 1.47 [1.30] 107 –0.11 [1.83] 107 Restructuring 5.56** [2.48] 76 5.87** [2.81] 76 Takeover 9.29*** [1.48] 129 9.54*** [1.64] 129 Multiple|$+$|Takeover 15.0*** [4.34] 40 16.2*** [4.76] 40 Multiple|$+$|NoTakeover 5.49** [2.66] 54 6.89** [3.25] 54 C. Sequence of engagement outcomes for engagements with multiple outcomes that involve a takeover . . Average engagement length with multiple outcome . Average waiting time to event . . . Board . Payout . Restructuring . Takeover . . . (1) . (2) . (3) . (4) . Time 806 days Percentage 100 36 48 44 76 |$t$|-test vs. takeover (4) |$-$|8.25*** |$-$|4.32*** |$-$|4.71*** C. Sequence of engagement outcomes for engagements with multiple outcomes that involve a takeover . . Average engagement length with multiple outcome . Average waiting time to event . . . Board . Payout . Restructuring . Takeover . . . (1) . (2) . (3) . (4) . Time 806 days Percentage 100 36 48 44 76 |$t$|-test vs. takeover (4) |$-$|8.25*** |$-$|4.32*** |$-$|4.71*** D. Abnormal returns around successful outcomes of stand-alone and wolf pack engagements . . Stand-alone . Wolf pack . Diff . . Stand-alone . Wolf pack . Diff . P(Any outcome) 46% 78% –8.11*** P(Restructuring) 6% 11% –2.73*** P(Board) 12% 32% –7.32*** P(Takeover) 11% 15% –1.59 P(Payout) 7% 9% –1.01 P(Multiple) 11% 11% –0.16 D. Abnormal returns around successful outcomes of stand-alone and wolf pack engagements . . Stand-alone . Wolf pack . Diff . . Stand-alone . Wolf pack . Diff . P(Any outcome) 46% 78% –8.11*** P(Restructuring) 6% 11% –2.73*** P(Board) 12% 32% –7.32*** P(Takeover) 11% 15% –1.59 P(Payout) 7% 9% –1.01 P(Multiple) 11% 11% –0.16 . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . . Stand-alone . Wolf pack . Diff . Stand-alone . Wolf pack . Diff . . Abn. ret. . SE . ARet. . SE . . ARet. . SE . ARet. . SE . . All outcomes 6.38*** [0.76] 7.22*** [1.59] –0.46 7.11*** [0.99] 5.89*** [1.81] 0.53 Board 2.49* [1.41] 4.74** [2.21] –0.84 4.20* [2.16] 4.5 [3.04] –0.07 Payout 1.66 [1.33] –1.03 [2.39] 0.77 –0.27 [1.95] –3.82 [3.11] 0.69 Restructuring 5.19*** [1.85] 5.8 [5.25] –0.14 6.25** [2.57] 4.07 [4.09] 0.4 Takeover 8.75*** [1.33] 14.0*** [3.44] –1.51 9.97*** [1.58] 11.6*** [3.36] –0.4 Multiple 12.0*** [2.13] 13.9** [5.13] –0.3 12.8*** [2.48] 12.6* [6.31] 0.03 . Event window: (⁠|$-$|10,10) . Event window: (⁠|$-$|20,20) . . Stand-alone . Wolf pack . Diff . Stand-alone . Wolf pack . Diff . . Abn. ret. . SE . ARet. . SE . . ARet. . SE . ARet. . SE . . All outcomes 6.38*** [0.76] 7.22*** [1.59] –0.46 7.11*** [0.99] 5.89*** [1.81] 0.53 Board 2.49* [1.41] 4.74** [2.21] –0.84 4.20* [2.16] 4.5 [3.04] –0.07 Payout 1.66 [1.33] –1.03 [2.39] 0.77 –0.27 [1.95] –3.82 [3.11] 0.69 Restructuring 5.19*** [1.85] 5.8 [5.25] –0.14 6.25** [2.57] 4.07 [4.09] 0.4 Takeover 8.75*** [1.33] 14.0*** [3.44] –1.51 9.97*** [1.58] 11.6*** [3.36] –0.4 Multiple 12.0*** [2.13] 13.9** [5.13] –0.3 12.8*** [2.48] 12.6* [6.31] 0.03 E. Abnormal returns around successful outcomes of domestic and foreign engagements . . Domestic non-U.S. . Domestic U.S. . Foreign non-U.S. . Foreign U.S. . Diff. (⁠|$t$|-stat) . . (1) . (2) . (3) . (4) . (1)&(2) - (3)&(4) . P(Any outcome) 37% 57% 39% 41% 5.18*** P(Board) 18% 27% 17% 12% 4.84*** P(Payout) 8% 13% 8% 10% 2.08** P(Restructuring) 10% 11% 10% 16% –1.39 P(Takeover) 15% 16% 13% 12% 1.54 E. Abnormal returns around successful outcomes of domestic and foreign engagements . . Domestic non-U.S. . Domestic U.S. . Foreign non-U.S. . Foreign U.S. . Diff. (⁠|$t$|-stat) . . (1) . (2) . (3) . (4) . (1)&(2) - (3)&(4) . P(Any outcome) 37% 57% 39% 41% 5.18*** P(Board) 18% 27% 17% 12% 4.84*** P(Payout) 8% 13% 8% 10% 2.08** P(Restructuring) 10% 11% 10% 16% –1.39 P(Takeover) 15% 16% 13% 12% 1.54 . . ARet. . SE . ARet. . SE . ARet. . SE . ARet. . SE . . (⁠|$-$|10,10) All outcomes 9.17*** [2.63] 6.19*** [0.73] 6.19*** [1.89] 5.11*** [1.69] 0.56 Board –3.06 [4.37] 4.90*** [1.08] 4.71 [4.86] 0.11 [2.30] 0.50 Payout 2.26 [2.90] 1.72 [1.33] –1.33 [2.27] 0.76 [2.15] 0.63 Restructuring 4.03 [3.88] 5.94** [2.54] 7.43** [2.70] 5.09** [2.30] –0.05 Takeover 10.8** [4.15] 9.33*** [1.49] 6.30** [2.20] 10.7*** [2.62] 0.30 Multiple 24.0*** [6.21] 10.2*** [2.46] 11.1* [5.69] 7.06 [9.47] 0.62 (⁠|$-$|20,20) All outcomes 8.91*** [3.25] 6.32*** [0.91] 7.39*** [2.76] 4.35** [1.96] 0.34 Board –3.74 [6.57] 5.18*** [1.56] 7.25 [7.23] 1.55 [3.86] 0.53 Payout 0.65 [9.07] 0.35 [1.86] –5.17 [3.89] –0.61 [2.95] 0.66 Restructuring 2.47 [3.59] 6.43** [2.86] 4.87 [3.93] 5.03** [2.51] 0.26 Takeover 12.0** [4.50] 9.61*** [1.66] 9.13** [3.88] 8.77** [3.23] 0.62 Multiple 23.5*** [7.51] 11.2*** [2.80] 14.6* [7.58] 5.02 [10.5] 0.47 . . ARet. . SE . ARet. . SE . ARet. . SE . ARet. . SE . . (⁠|$-$|10,10) All outcomes 9.17*** [2.63] 6.19*** [0.73] 6.19*** [1.89] 5.11*** [1.69] 0.56 Board –3.06 [4.37] 4.90*** [1.08] 4.71 [4.86] 0.11 [2.30] 0.50 Payout 2.26 [2.90] 1.72 [1.33] –1.33 [2.27] 0.76 [2.15] 0.63 Restructuring 4.03 [3.88] 5.94** [2.54] 7.43** [2.70] 5.09** [2.30] –0.05 Takeover 10.8** [4.15] 9.33*** [1.49] 6.30** [2.20] 10.7*** [2.62] 0.30 Multiple 24.0*** [6.21] 10.2*** [2.46] 11.1* [5.69] 7.06 [9.47] 0.62 (⁠|$-$|20,20) All outcomes 8.91*** [3.25] 6.32*** [0.91] 7.39*** [2.76] 4.35** [1.96] 0.34 Board –3.74 [6.57] 5.18*** [1.56] 7.25 [7.23] 1.55 [3.86] 0.53 Payout 0.65 [9.07] 0.35 [1.86] –5.17 [3.89] –0.61 [2.95] 0.66 Restructuring 2.47 [3.59] 6.43** [2.86] 4.87 [3.93] 5.03** [2.51] 0.26 Takeover 12.0** [4.50] 9.61*** [1.66] 9.13** [3.88] 8.77** [3.23] 0.62 Multiple 23.5*** [7.51] 11.2*** [2.80] 14.6* [7.58] 5.02 [10.5] 0.47 The table shows average cumulative abnormal returns (CARs) around the announcement of engagement outcomes (market model adjusted) in panels A and B, engagement outcome sequencing in panel C, and compares multiple activist and stand-alone engagements in panel D and domestic and foreign engagements in panel E. Engagement outcomes are categorized as board changes, changes to pay-out policy, restructuring, and takeovers. In case of multiple announcements of outcomes in an engagement, CARs are summed across announcements. In case of multiple outcome types within an engagement. the engagement is classified as “Multiple+Takeover” (if outcomes include a takeover) or “Multiple+NoTakeover.” The event window is centered on the earliest announcement date of the outcome. Factor loadings are estimated over 250 trading days preceding the event window, using country-specific domestic market returns, with a minimum of 150 daily observations. In panels A and B, 850 out of 1,740 engagements have sufficient data and at least one subsequent outcome. In panel C, data are reported for 150 outcomes of the 58 engagements that have multiple outcomes and involve a takeover (Multiple+Takeover). In panel D, wolf pack engagements involving multiple funds are treated as one engagement only if individual engagements within a wolf pack are disclosed on separate dates, CARs are summed per wolf pack, across announcements. Abnormal returns are winsorized at the 1st and 99th percentiles. Standard errors are reported in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab In panel A, the average abnormal return for all announced outcomes for the 41-day window is 6.4% and is statistically significant at the 1% level. The largest abnormal returns are generated by takeover transactions that also involve other outcomes, at 18.1%. An important feature of this table is that engagements with multiple outcomes are on average significantly more profitable, that is, have larger returns than single outcomes, regardless of the type of outcome. Takeovers involving other outcomes are likely to be the most profitable because the activist has to remove an obstacle, for example incumbent members of the board, which may have depressed the stock price. This evidence qualifies the results by Greenwood and Schor (2009) who provide evidence that a large proportion of activist returns are the result of “putting companies into play”; our evidence suggests that while activists might be good at picking likely takeover candidates, their other actions might also influence the probability of takeover, in particular since the other actions usually precedes the takeover bid. It might be necessary, for example, to replace board members to make the activist target more amendable to a partial or outright sale. All other types of outcomes have smaller abnormal returns. Restructurings that are not takeovers, including divestitures and spin-offs, average 5.6%. Payout is not distinguishable from zero at |$-$|0.2%. Board changes generate abnormal returns at 4.5%. These results show that engagements, conditional on successful outcomes, have much higher levels of returns than those shown at the disclosure date.14 There are also interesting differences in outcomes returns across region, in panel B. In Asia, there are very few engagements with outcomes and the outcome returns, except for two engagements with multiple outcomes, are small and for the (⁠|$-$|20,20) window all returns are insignificant. Such a low probability of successful outcomes and the low associated returns suggest that the large abnormal returns in Asia at disclosure proved optimistic.15 In Europe, outcomes are much more frequent and they have the highest average abnormal returns across the three regions with 8.8% for the (⁠|$-$|20,20) window. Pure-play takeovers and takeovers involving other outcomes stand out with 10.8% and 25.1%, respectively. Restructuring outcomes have returns of 5.3% and engagements with multiple outcomes (but no takeover) have 10.3%. In North America engagements have the highest probability of achieving outcomes, the average abnormal return is 6.0% and, like in Europe, takeovers on their own and with other outcomes stand out with the largest positive returns of 9.5% and 16.2%, respectively. These results are consistent with those of Brav et al. (2008) and Greenwood and Schor (2009) for U.S. domestic engagements. Restructuring outcomes and engagements with multiple outcomes (but no takeover) have returns that are comparable to Europe. Overall, the stock market responses to observable outcomes are similar for North America and Europe. Panel C examines further those 58 engagements with multiple outcomes that involve a takeover (Multiple|$+$|Takeover). If governance changes facilitate eventual takeovers, one would expect the announcement of other outcomes to precede the announcement of takeover outcomes during an engagement, and the results confirm this to be the case. Engagements with multiple outcomes last 806 days on average, and takeover outcomes are announced significantly later than all other types of outcomes. Board change announcements instead precede them and are announced about one-third into the average life of such engagements; payout changes and restructurings are announced roughly at half-time; and takeover outcomes are announced about three quarters into the engagement period.16 Next, we compare outcome probabilities and announcement returns between engagements for wolf packs and single activists. In this comparison, we treat the wolf pack as a single engagement and consider any achieved outcome only once, thus avoiding double counting. As panel D shows, the higher disclosure announcement returns for multiple engagements coincide with a much higher incidence of outcomes achieved for these deals: The probability of achieving at least one outcome is 46% for stand-alone engagements, while it is 78% for multiple activist engagements. The higher probability of achieving outcomes is mostly reflected in board changes, but all categories of possible outcomes are higher for multiple engagements than for stand-alone activists. In addition, the proportion of the most profitable outcomes (takeovers and restructurings) is a higher proportion of total outcomes than in the case of stand-alone engagements (40% versus 30%). Note that the abnormal returns around successful outcomes are not higher for wolf packs than for stand-alone engagements; wolf packs therefore have higher probabilities of outcomes, but not higher return upon outcome announcement. Overall, wolf packs have higher announcement returns on disclosure of a stake (compared with stand-alone activists), higher probabilities of achieving the outcomes they seek, and achieve more of the most profitable types of outcomes, that is, takeovers and restructurings.17 Finally, given our observation that U.S. institutional investors are an important influence on the level of activism in non-U.S. countries, it is reasonable to ask whether U.S.-style activism explains activism performance. We know that U.S. hedge fund activists successfully cooperate with U.S. institutional investors in the United States. We investigate whether this cooperation explains successful engagements in other countries. We first compare the performance of U.S. activists at home against their performance overseas, and against their foreign peers, who themselves engage both domestic and foreign targets. Table 7, panel E, reports engagement performance partitioned by the four categories of activist-target pairings. Among activists across all countries, U.S. activists targeting domestic firms have significantly higher probabilities of achieving an outcome, which is not surprising given our earlier results on outcomes in the United States. However, this advantage is not one of U.S.-style activism per se, as it does not carry over to U.S. activists targeting firms abroad, who are not different in their success rates from other foreign activists. While domestic activism (outside the United States) has higher disclosure returns than foreign activism, it does not have a higher probability of outcomes. Therefore, the superior performance of U.S. domestic activism seems to be related to its ability to generate more outcomes. We now turn to the degree to which hedge funds specialize in their choice of geography of target. In Figure 3, we provide a histogram of the proportion of funds’ engagements that are foreign, based upon a subsample of funds with at least ten engagements. As the distribution shows, the vast majority of funds specialize in engaging only firms in their respective domestic home markets. A minority of funds engages in foreign markets, among which a significant proportion exclusively engage in foreign markets. Few funds engage both domestic and foreign targets. The degree of specialization is even more pronounced—with relatively more funds investing only either in domestic or foreign engagements—when we consider all 330 funds in the sample (data not shown). Figure 3 Open in new tabDownload slide Foreign engagements per fund. Figure 3 Open in new tabDownload slide Foreign engagements per fund. To better understand this specialization of funds, we consider the engagement performance of the subsample of U.S. hedge funds which invest in targets both domestically and overseas. This provides evidence about the extent to which the success of a domestic engagement model can translate into successful foreign engagements. There are 24 hedge funds in our sample which engage with both domestic and foreign targets, out of a sample of 261 U.S. hedge funds. These include some of the largest funds in the sample by number of engagements, Steel Partners, ValueAct Capital Partners, Carl Icahn, and Third Point. We compare, for each such fund, the probability of achieving outcomes in foreign engagements to the probability of achieving outcomes in domestic engagements. We find a strong negative correlation between both probabilities for the sample of 24 hedge funds, suggesting that success domestically does not translate into success overseas, and vice versa.18 3.4 Total engagement returns To obtain measures of the overall performance of an engagement we measure the returns of activist engagements over the holding period of the activist. This enables us to compare the profitability of engagements with and without observable outcomes. We construct activist portfolio returns in calendar time. The portfolios are rebalanced each month to include all firms in the month that are subject to an ongoing activist engagement. Equal- and value-weighted portfolio raw returns are in the Internet Appendix. The portfolios’ excess returns are regressed on the excess return of the market and the four-factor Fama and French (1993) and Carhart (1997) mimicking portfolios. To illustrate for the four-factor model, we regress Rp,t−Rf,t=αP+βP,RMRF(Rm,t−Rf,t)+βP,SMBSMBt+βP,HMLHMLt+βP,MOMMOMt+εP,t, where RMRF, SMB, HML, and MOM are the excess return of the market, the difference between a portfolio of small stocks and big stocks, the difference between a portfolio of high book-to-market and low book-to-market stocks, and the difference between a portfolio of high and low momentum stocks, respectively, all based on U.S. stocks. We also estimate specifications where the excess returns of the activist portfolio are regressed on excess returns of a region’s market, where the regional market excess returns are weighted averages of the sample countries in that region, net of the U.S. risk-free rate. Alpha or |$\alpha_{P,}$| is the estimate of monthly abnormal performance of the target portfolio.19 In Table 8, panel A, reports equal-weighted and value-weighted results for annualized Alpha for engagements with at least one outcome, for engagements without any outcome, for the long/short portfolio that holds the portfolio of engagements with outcomes and sells short the portfolio of engagement with no outcomes, and for all engagements combined. The long/short portfolio serves to illustrate the magnitude of return differentials between successful and unsuccessful engagements, but ex ante does not represent an investable strategy.20 Table 8 Abnormal returns from activist engagements, announcement to exit A. Abnormal return, announcement to exit . Equal-weighted . With outcomes . With no outcomes . L/S (outcomes-no outcomes) . All engagements . . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . Full sample 8.399** 1.104 –5.513 –9.750*** 13.912*** 10.854*** 1.984 –3.547 [4.119] [3.407] [3.804] [3.608] [4.014] [4.078] [3.254] [2.737] Asia 13.379** 11.568** 1.204 –0.809 12.175** 12.377** 3.327 3.286 [5.141] [5.189] [5.458] [5.469] [5.267] [5.418] [3.745] [3.901] Europe 5.643 1.413 –8.853 –12.697** 14.496*** 14.110** –2.190 –5.904 [4.302] [4.199] [5.500] [5.390] [5.330] [5.544] [4.153] [4.022] N. America 8.104* –0.801 –5.271 –11.784*** 13.374*** 10.983** 1.753 –5.296* [4.559] [3.585] [4.763] [4.423] [4.475] [4.606] [3.520] [2.805] Value-weighted With outcomes With no outcomes L/S (outcomes-no outcomes) All engagements Full sample 11.254*** 7.987** 3.999 2.325 7.255 5.662 7.598** 4.966 [3.473] [3.340] [5.251] [5.379] [5.982] [6.140] [3.134] [3.064] Asia 14.183** 13.216** 2.587 0.588 11.596 12.628 4.482 4.509 [6.172] [6.299] [6.717] [6.820] [8.194] [8.350] [4.047] [4.211] Europe 8.238* 8.077* 4.587 3.209 3.650 4.868 6.397 5.757 [4.889] [4.781] [6.506] [6.702] [7.222] [7.417] [4.583] [4.611] N. America 11.309** 6.550 1.380 –1.206 9.930 7.756 8.065** 3.723 [4.613] [4.449] [6.633] [6.816] [8.513] [8.675] [3.964] [3.796] A. Abnormal return, announcement to exit . Equal-weighted . With outcomes . With no outcomes . L/S (outcomes-no outcomes) . All engagements . . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . Full sample 8.399** 1.104 –5.513 –9.750*** 13.912*** 10.854*** 1.984 –3.547 [4.119] [3.407] [3.804] [3.608] [4.014] [4.078] [3.254] [2.737] Asia 13.379** 11.568** 1.204 –0.809 12.175** 12.377** 3.327 3.286 [5.141] [5.189] [5.458] [5.469] [5.267] [5.418] [3.745] [3.901] Europe 5.643 1.413 –8.853 –12.697** 14.496*** 14.110** –2.190 –5.904 [4.302] [4.199] [5.500] [5.390] [5.330] [5.544] [4.153] [4.022] N. America 8.104* –0.801 –5.271 –11.784*** 13.374*** 10.983** 1.753 –5.296* [4.559] [3.585] [4.763] [4.423] [4.475] [4.606] [3.520] [2.805] Value-weighted With outcomes With no outcomes L/S (outcomes-no outcomes) All engagements Full sample 11.254*** 7.987** 3.999 2.325 7.255 5.662 7.598** 4.966 [3.473] [3.340] [5.251] [5.379] [5.982] [6.140] [3.134] [3.064] Asia 14.183** 13.216** 2.587 0.588 11.596 12.628 4.482 4.509 [6.172] [6.299] [6.717] [6.820] [8.194] [8.350] [4.047] [4.211] Europe 8.238* 8.077* 4.587 3.209 3.650 4.868 6.397 5.757 [4.889] [4.781] [6.506] [6.702] [7.222] [7.417] [4.583] [4.611] N. America 11.309** 6.550 1.380 –1.206 9.930 7.756 8.065** 3.723 [4.613] [4.449] [6.633] [6.816] [8.513] [8.675] [3.964] [3.796] B. Abnormal return, decomposition of event window . . With outcomes . With no outcomes . . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . Portfolio: Only months t|$=$|0 Equal-weighted 18.859*** 18. 552*** 14.213*** 16.841*** [3.671] [3.840] [3.779] [3.854] Value-weighted 18.781*** 18.449*** 14.505*** 16.976*** [5.256] [5.507] [4.465] [4.595] Portfolio: Only months with outcome announcements Equal-weighted 27.545*** 26.793*** – – [4.451] [4.619] – – Value-weighted 26.409*** 28.225*** – – [5.669] [5.870] – – Portfolio: All other months Equal-weighted –1.302 –6.670** –7.250* –11.677*** [3.090] [2.573] [3.674] [3.436] Value-weighted 5.842** 3.374 6.306 3.987 [2.917] [2.768] [4.970] [5.061] B. Abnormal return, decomposition of event window . . With outcomes . With no outcomes . . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . Portfolio: Only months t|$=$|0 Equal-weighted 18.859*** 18. 552*** 14.213*** 16.841*** [3.671] [3.840] [3.779] [3.854] Value-weighted 18.781*** 18.449*** 14.505*** 16.976*** [5.256] [5.507] [4.465] [4.595] Portfolio: Only months with outcome announcements Equal-weighted 27.545*** 26.793*** – – [4.451] [4.619] – – Value-weighted 26.409*** 28.225*** – – [5.669] [5.870] – – Portfolio: All other months Equal-weighted –1.302 –6.670** –7.250* –11.677*** [3.090] [2.573] [3.674] [3.436] Value-weighted 5.842** 3.374 6.306 3.987 [2.917] [2.768] [4.970] [5.061] The table reports calendar-time portfolio returns of all firms targeted by activists, using monthly return data (n|$=$|132). In panel A, portfolios are formed and rebalanced each month to include all firms that have been engaged by an activist within the event window. The event window for each engagement begins in t|$=$|0, the month of the initial filing date or the first press disclosure date and ends in the month during which the activist ended the engagement or, if no exit date is known, December 2010. In panel B, three portfolios are constructed similarly with the event window decomposed into “only months t|$=$|0”, “only months with outcome announcements”, and “all other months.” Alpha is the intercept on a regression of monthly portfolio excess returns. The explanatory variables are the excess return of the market (MktModel) and the four Fama and French 1993 and Carhart 1997 mimicking portfolios (Carhart), based on U.S. return data. Alphas are in annual percentages. L/S is annual average return of a zero cost portfolio that holds the portfolio of engagements with outcomes and sells short the portfolio of engagements with no outcomes. Returns are winsorized at the 1st and 99th percentiles. Standard errors are in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab Table 8 Abnormal returns from activist engagements, announcement to exit A. Abnormal return, announcement to exit . Equal-weighted . With outcomes . With no outcomes . L/S (outcomes-no outcomes) . All engagements . . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . Full sample 8.399** 1.104 –5.513 –9.750*** 13.912*** 10.854*** 1.984 –3.547 [4.119] [3.407] [3.804] [3.608] [4.014] [4.078] [3.254] [2.737] Asia 13.379** 11.568** 1.204 –0.809 12.175** 12.377** 3.327 3.286 [5.141] [5.189] [5.458] [5.469] [5.267] [5.418] [3.745] [3.901] Europe 5.643 1.413 –8.853 –12.697** 14.496*** 14.110** –2.190 –5.904 [4.302] [4.199] [5.500] [5.390] [5.330] [5.544] [4.153] [4.022] N. America 8.104* –0.801 –5.271 –11.784*** 13.374*** 10.983** 1.753 –5.296* [4.559] [3.585] [4.763] [4.423] [4.475] [4.606] [3.520] [2.805] Value-weighted With outcomes With no outcomes L/S (outcomes-no outcomes) All engagements Full sample 11.254*** 7.987** 3.999 2.325 7.255 5.662 7.598** 4.966 [3.473] [3.340] [5.251] [5.379] [5.982] [6.140] [3.134] [3.064] Asia 14.183** 13.216** 2.587 0.588 11.596 12.628 4.482 4.509 [6.172] [6.299] [6.717] [6.820] [8.194] [8.350] [4.047] [4.211] Europe 8.238* 8.077* 4.587 3.209 3.650 4.868 6.397 5.757 [4.889] [4.781] [6.506] [6.702] [7.222] [7.417] [4.583] [4.611] N. America 11.309** 6.550 1.380 –1.206 9.930 7.756 8.065** 3.723 [4.613] [4.449] [6.633] [6.816] [8.513] [8.675] [3.964] [3.796] A. Abnormal return, announcement to exit . Equal-weighted . With outcomes . With no outcomes . L/S (outcomes-no outcomes) . All engagements . . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . Full sample 8.399** 1.104 –5.513 –9.750*** 13.912*** 10.854*** 1.984 –3.547 [4.119] [3.407] [3.804] [3.608] [4.014] [4.078] [3.254] [2.737] Asia 13.379** 11.568** 1.204 –0.809 12.175** 12.377** 3.327 3.286 [5.141] [5.189] [5.458] [5.469] [5.267] [5.418] [3.745] [3.901] Europe 5.643 1.413 –8.853 –12.697** 14.496*** 14.110** –2.190 –5.904 [4.302] [4.199] [5.500] [5.390] [5.330] [5.544] [4.153] [4.022] N. America 8.104* –0.801 –5.271 –11.784*** 13.374*** 10.983** 1.753 –5.296* [4.559] [3.585] [4.763] [4.423] [4.475] [4.606] [3.520] [2.805] Value-weighted With outcomes With no outcomes L/S (outcomes-no outcomes) All engagements Full sample 11.254*** 7.987** 3.999 2.325 7.255 5.662 7.598** 4.966 [3.473] [3.340] [5.251] [5.379] [5.982] [6.140] [3.134] [3.064] Asia 14.183** 13.216** 2.587 0.588 11.596 12.628 4.482 4.509 [6.172] [6.299] [6.717] [6.820] [8.194] [8.350] [4.047] [4.211] Europe 8.238* 8.077* 4.587 3.209 3.650 4.868 6.397 5.757 [4.889] [4.781] [6.506] [6.702] [7.222] [7.417] [4.583] [4.611] N. America 11.309** 6.550 1.380 –1.206 9.930 7.756 8.065** 3.723 [4.613] [4.449] [6.633] [6.816] [8.513] [8.675] [3.964] [3.796] B. Abnormal return, decomposition of event window . . With outcomes . With no outcomes . . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . Portfolio: Only months t|$=$|0 Equal-weighted 18.859*** 18. 552*** 14.213*** 16.841*** [3.671] [3.840] [3.779] [3.854] Value-weighted 18.781*** 18.449*** 14.505*** 16.976*** [5.256] [5.507] [4.465] [4.595] Portfolio: Only months with outcome announcements Equal-weighted 27.545*** 26.793*** – – [4.451] [4.619] – – Value-weighted 26.409*** 28.225*** – – [5.669] [5.870] – – Portfolio: All other months Equal-weighted –1.302 –6.670** –7.250* –11.677*** [3.090] [2.573] [3.674] [3.436] Value-weighted 5.842** 3.374 6.306 3.987 [2.917] [2.768] [4.970] [5.061] B. Abnormal return, decomposition of event window . . With outcomes . With no outcomes . . MktModel alpha . Carhart alpha . MktModel alpha . Carhart alpha . Portfolio: Only months t|$=$|0 Equal-weighted 18.859*** 18. 552*** 14.213*** 16.841*** [3.671] [3.840] [3.779] [3.854] Value-weighted 18.781*** 18.449*** 14.505*** 16.976*** [5.256] [5.507] [4.465] [4.595] Portfolio: Only months with outcome announcements Equal-weighted 27.545*** 26.793*** – – [4.451] [4.619] – – Value-weighted 26.409*** 28.225*** – – [5.669] [5.870] – – Portfolio: All other months Equal-weighted –1.302 –6.670** –7.250* –11.677*** [3.090] [2.573] [3.674] [3.436] Value-weighted 5.842** 3.374 6.306 3.987 [2.917] [2.768] [4.970] [5.061] The table reports calendar-time portfolio returns of all firms targeted by activists, using monthly return data (n|$=$|132). In panel A, portfolios are formed and rebalanced each month to include all firms that have been engaged by an activist within the event window. The event window for each engagement begins in t|$=$|0, the month of the initial filing date or the first press disclosure date and ends in the month during which the activist ended the engagement or, if no exit date is known, December 2010. In panel B, three portfolios are constructed similarly with the event window decomposed into “only months t|$=$|0”, “only months with outcome announcements”, and “all other months.” Alpha is the intercept on a regression of monthly portfolio excess returns. The explanatory variables are the excess return of the market (MktModel) and the four Fama and French 1993 and Carhart 1997 mimicking portfolios (Carhart), based on U.S. return data. Alphas are in annual percentages. L/S is annual average return of a zero cost portfolio that holds the portfolio of engagements with outcomes and sells short the portfolio of engagements with no outcomes. Returns are winsorized at the 1st and 99th percentiles. Standard errors are in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab With equal-weighting, activist engagements with successful outcomes produce annualized positive abnormal returns of 8.4% (MktModel) and 1.1% (Carhart) for the entire sample, while engagements with no outcomes have abnormal returns of |$-$|5.5% (MktModel) and |$-$|9.8% (Carhart) and thus underperform similarly risky stocks. The long/short portfolio’s return is 13.9% and 10.9%, respectively, significant at the 1% level. The overall performance of activism for the pooled sample is not significantly different from zero, in line with prior U.S. evidence. We find similar results when we split portfolios by region. Significance levels remain high, as deals with outcomes continue to generate positive abnormal returns in all regions, while deals without outcomes generate zero or negative abnormal returns. Value-weighted abnormal returns increase overall, to 11.3% and 8.0%; statistically significant at the 1% and 5% level for engagements with successful outcomes. For engagements without outcomes, abnormal returns are 4.0% and 2.3%, neither of which are significant. The main conclusion is that the difference in performance between outcomes and no outcomes is always economically large and frequently statistically significant. Larger target engagements even with no outcomes on average exhibit positive performance, which leads to the long/short portfolio return being insignificant in the value-weighted specifications. We investigate this latter finding in more detail, particularly in light of prior U.S. evidence in which equal-weighted returns consistently outperform the value-weighted returns. Specifically, we investigate whether this is a recent phenomenon, as hedge funds in recent year have engaged some of the largest firms worldwide. Consistent with this, during our sample period average market capitalization of targeted firms increases from US|${\$}$| 600 million in 2000 to US|${\$}$| 3.4 billion in 2010. In unreported results (available on request), we split our sample into alternative sub-periods; first, using two equal time periods (January 2000-June 2005, July 2005-December 2010), and second using a structural break (October 2008) in the time series for Asia and Europe identified from Chow tests into pre- and post-break periods (January 2000-September 2008, October 2008-December 2010). For the entire sample we obtain two results, robust to as to how we split the time periods: First, the activist portfolio returns, both equal- and value-weighted decline over time. Second, relative to small engagements, the performance of large engagements improves over time. The outperformance of large engagements therefore appears to be a recent development.21 To generate insights into what drives the abnormal performance during the activist engagements, in panel B we decompose the returns over the engagement period into three portfolios: a portfolio containing only the disclosure months, that is, “Only months t|$=$|0”; a portfolio containing only months during which outcome announcements are made, that is, “Only months with outcome announcements”; and a portfolio that contains all other months, that is, “All other months.” There are two main results. First, engagements have significantly positive alphas both in the month of initial disclosure of the activist stake and in those months where successful outcomes are announced. While these are not investable strategies for outsiders, the annualized alphas from these portfolios are significant and range from 14.2% to 18.9% for the “Only months t|$=$|0” portfolio and from 26.4 to 28.2% for the “Only months with outcome announcements” portfolio. Second, in months after the block disclosure and excluding the outcome disclosure month(s), there are no significant abnormal returns generated by the activist, positive or negative. Overall, the results confirm that activist engagements without outcomes generally do not generate significant shareholder value under any specification. Engagements with outcomes however generate value for shareholders, with value generation being closely linked to these outcomes. It is unlikely that this consistent pattern across regions is a coincidence. These results suggest that activism is frequently not just about stock picking but also changing the governance of a company. 3.5 Country differences in activism Our evidence so far indicates that shareholder activism is successful in generating positive returns for target shareholders across countries. There are common themes: Activists are more likely to engage targets that have foreign institutional investors, in particular from the United States; activists generate positive abnormal returns if and only if they manage to achieve successful outcomes; and the value of achieving an outcome depends significantly on the exact nature of the change implemented by the activist. Finally, we consider whether country-level measures of economic development, the legal system and governance affect activist engagements and their success, and also consider the impact of institutional ownership. In Table 9 we report three sets of tests. First, in Columns 1 to 3, the dependent variable is the disclosure abnormal return. We control for firm-level characteristics as in Table 4, and for year fixed effects (entry year). Since we require firms to have coverage on FactSet for these regressions, our sample reduces to roughly 900 observations. As the results show, none of the country-level measures are statistically significant, and also institutional ownership is insignificant. Disclosure returns therefore neither depend on country characteristics nor on the cross-sectional differences of institutional holdings. The lack of significance is not too surprising, since disclosure abnormal returns are conditional on the activist choosing to go ahead with an engagement. For example, since activists will have considered institutional ownership in picking targets, targets should have conditionally optimal institutional ownership; ownership would then appear unrelated to announcement returns. Table 9 Engagement probabilities and returns across countries . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . (9) . (10) . (11) . (12) . Dependent variable . Engagement disclosure CAR (⁠|$-$|20,20) . Outcome disclosure CAR (⁠|$-$|20,20) . Firm engaged in year t (1) or not (0) . Fraction of firms engaged in country |$x$| in year |$t$| . IO_Domestic 2.165 0.554 –0.217 1.374 0.813 –0.164 0.043*** 0.052*** 0.054*** 5.952*** 8.728*** 8.070*** [2.714] [3.892] [3.908] [2.531] [3.330] [3.377] [0.002] [0.003] [0.003] [1.804] [1.594] [2.384] IO_Foreign_U.S. –0.648 –3.410 1.698 30.004 45.681* 48.629* 0.114*** 0.091*** 0.184*** –7.169 1.822 2.353 [21.954] [23.137] [22.396] [25.518] [23.647] [25.441] [0.014] [0.014] [0.019] [5.600] [5.733] [7.330] IO_Foreign Non-U.S. 10.174 11.557 14.014 24.599 29.628 26.282* 0.056*** 0.058*** 0.094*** 13.170*** 16.902*** 15.123*** [20.633] [21.568] [21.775] [16.250] [18.410] [15.864] [0.013] [0.014] [0.017] [4.673] [4.547] [5.222] Market cap/GDP 0.039* 0.001 –0.000*** –0.001 [0.024] [0.020] [0.000] [0.001] Rule of law –4.097 7.186** 0.022*** 1.200*** [3.160] [2.851] [0.001] [0.161] Disclosure threshold 1.797* –0.684 –0.007*** –0.279*** [0.972] [0.878] [0.001] [0.060] Common law 0.257 4.242* –0.020*** –0.988*** [2.834] [2.433] [0.002] [0.340] Antidirector rights –0.517 0.524 0.004*** –0.206* [1.253] [1.064] [0.001] [0.108] Quality of governance 16.228 3.783 –0.031 –5.488*** [29.748] [38.336] [0.025] [1.953] Board independence –3.074 3.893 –0.008* 1.146*** [6.161] [7.359] [0.005] [0.397] Board structure 10.649** 2.054 0.018*** –0.685** [4.452] [4.313] [0.004] [0.324] Year FE Entry Entry Entry Entry Entry Entry Calendar Calendar Calendar Calendar Calendar Calendar Firm-level controls Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 730 721 719 927 916 914 90,470 89,515 74,832 440 402 230 Adj. R-sq./Pseudo R-sq. –0.012 –0.012 –0.010 0.031 0.029 0.028 0.089 0.089 0.067 – – – Estimation OLS OLS OLS OLS OLS OLS Probit Probit Probit GLM GLM GLM . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . (9) . (10) . (11) . (12) . Dependent variable . Engagement disclosure CAR (⁠|$-$|20,20) . Outcome disclosure CAR (⁠|$-$|20,20) . Firm engaged in year t (1) or not (0) . Fraction of firms engaged in country |$x$| in year |$t$| . IO_Domestic 2.165 0.554 –0.217 1.374 0.813 –0.164 0.043*** 0.052*** 0.054*** 5.952*** 8.728*** 8.070*** [2.714] [3.892] [3.908] [2.531] [3.330] [3.377] [0.002] [0.003] [0.003] [1.804] [1.594] [2.384] IO_Foreign_U.S. –0.648 –3.410 1.698 30.004 45.681* 48.629* 0.114*** 0.091*** 0.184*** –7.169 1.822 2.353 [21.954] [23.137] [22.396] [25.518] [23.647] [25.441] [0.014] [0.014] [0.019] [5.600] [5.733] [7.330] IO_Foreign Non-U.S. 10.174 11.557 14.014 24.599 29.628 26.282* 0.056*** 0.058*** 0.094*** 13.170*** 16.902*** 15.123*** [20.633] [21.568] [21.775] [16.250] [18.410] [15.864] [0.013] [0.014] [0.017] [4.673] [4.547] [5.222] Market cap/GDP 0.039* 0.001 –0.000*** –0.001 [0.024] [0.020] [0.000] [0.001] Rule of law –4.097 7.186** 0.022*** 1.200*** [3.160] [2.851] [0.001] [0.161] Disclosure threshold 1.797* –0.684 –0.007*** –0.279*** [0.972] [0.878] [0.001] [0.060] Common law 0.257 4.242* –0.020*** –0.988*** [2.834] [2.433] [0.002] [0.340] Antidirector rights –0.517 0.524 0.004*** –0.206* [1.253] [1.064] [0.001] [0.108] Quality of governance 16.228 3.783 –0.031 –5.488*** [29.748] [38.336] [0.025] [1.953] Board independence –3.074 3.893 –0.008* 1.146*** [6.161] [7.359] [0.005] [0.397] Board structure 10.649** 2.054 0.018*** –0.685** [4.452] [4.313] [0.004] [0.324] Year FE Entry Entry Entry Entry Entry Entry Calendar Calendar Calendar Calendar Calendar Calendar Firm-level controls Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 730 721 719 927 916 914 90,470 89,515 74,832 440 402 230 Adj. R-sq./Pseudo R-sq. –0.012 –0.012 –0.010 0.031 0.029 0.028 0.089 0.089 0.067 – – – Estimation OLS OLS OLS OLS OLS OLS Probit Probit Probit GLM GLM GLM Dependent variables are as indicated in column titles. Columns 1 to 3: Engagement disclosure CARs are calculated as in Table 5. Columns 4 to 6: Outcome disclosure CARs are calculated as in Table 7; engagements without outcomes are assigned a zero return. Columns 7 to 9: Sample and variables are as in Table 4. Columns 10 to 12: The sample from Columns 7 to 9 is collapsed into country-year observations. The fraction of firms engaged in country |$x$| in year |$t$| is calculated as the number of firms that are currently engaged by an activist divided by the total number of firms, per country and year. Market cap/GDP (market capitalization of listed domestic firms over GDP), Rule of law (the perception of the extent to which agents have confidence in and abide by the rules of society) are from the Worldbank as of 2000; Disclosure threshold is the minimum regulatory disclosure threshold for blockholders; Common Law equals one for countries with common law, zero otherwise; the Revised antidirector index is from Djankov et al. 2008; Quality of governance (the percentage of governance attributes for which an average firm meets or exceeds the minimum satisfactory standard on 44 governance attributes), Board independence (whether or not an average firm’s board is controlled by more than 50% independent outside directors), and Board structure (whether or not an average firm’s board is annually elected/not staggered) are from Aggarwal et al. 2009. Institutional ownership variables include domestic and foreign institutional ownership, firm-level control variables include Market-to-book, Leverage, Cash, Dividend yield, Payout, Investment, U.S. accounting standards, Index membership, and Illiquidity, all as defined in Table 4. Firm-level explanatory variables are as of the year during which the engagement is announced. All nonbinary variables are winsorized at the 1st and 99th percentiles. White (1980) heteroscedasticity-robust standard errors are reported in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab Table 9 Engagement probabilities and returns across countries . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . (9) . (10) . (11) . (12) . Dependent variable . Engagement disclosure CAR (⁠|$-$|20,20) . Outcome disclosure CAR (⁠|$-$|20,20) . Firm engaged in year t (1) or not (0) . Fraction of firms engaged in country |$x$| in year |$t$| . IO_Domestic 2.165 0.554 –0.217 1.374 0.813 –0.164 0.043*** 0.052*** 0.054*** 5.952*** 8.728*** 8.070*** [2.714] [3.892] [3.908] [2.531] [3.330] [3.377] [0.002] [0.003] [0.003] [1.804] [1.594] [2.384] IO_Foreign_U.S. –0.648 –3.410 1.698 30.004 45.681* 48.629* 0.114*** 0.091*** 0.184*** –7.169 1.822 2.353 [21.954] [23.137] [22.396] [25.518] [23.647] [25.441] [0.014] [0.014] [0.019] [5.600] [5.733] [7.330] IO_Foreign Non-U.S. 10.174 11.557 14.014 24.599 29.628 26.282* 0.056*** 0.058*** 0.094*** 13.170*** 16.902*** 15.123*** [20.633] [21.568] [21.775] [16.250] [18.410] [15.864] [0.013] [0.014] [0.017] [4.673] [4.547] [5.222] Market cap/GDP 0.039* 0.001 –0.000*** –0.001 [0.024] [0.020] [0.000] [0.001] Rule of law –4.097 7.186** 0.022*** 1.200*** [3.160] [2.851] [0.001] [0.161] Disclosure threshold 1.797* –0.684 –0.007*** –0.279*** [0.972] [0.878] [0.001] [0.060] Common law 0.257 4.242* –0.020*** –0.988*** [2.834] [2.433] [0.002] [0.340] Antidirector rights –0.517 0.524 0.004*** –0.206* [1.253] [1.064] [0.001] [0.108] Quality of governance 16.228 3.783 –0.031 –5.488*** [29.748] [38.336] [0.025] [1.953] Board independence –3.074 3.893 –0.008* 1.146*** [6.161] [7.359] [0.005] [0.397] Board structure 10.649** 2.054 0.018*** –0.685** [4.452] [4.313] [0.004] [0.324] Year FE Entry Entry Entry Entry Entry Entry Calendar Calendar Calendar Calendar Calendar Calendar Firm-level controls Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 730 721 719 927 916 914 90,470 89,515 74,832 440 402 230 Adj. R-sq./Pseudo R-sq. –0.012 –0.012 –0.010 0.031 0.029 0.028 0.089 0.089 0.067 – – – Estimation OLS OLS OLS OLS OLS OLS Probit Probit Probit GLM GLM GLM . (1) . (2) . (3) . (4) . (5) . (6) . (7) . (8) . (9) . (10) . (11) . (12) . Dependent variable . Engagement disclosure CAR (⁠|$-$|20,20) . Outcome disclosure CAR (⁠|$-$|20,20) . Firm engaged in year t (1) or not (0) . Fraction of firms engaged in country |$x$| in year |$t$| . IO_Domestic 2.165 0.554 –0.217 1.374 0.813 –0.164 0.043*** 0.052*** 0.054*** 5.952*** 8.728*** 8.070*** [2.714] [3.892] [3.908] [2.531] [3.330] [3.377] [0.002] [0.003] [0.003] [1.804] [1.594] [2.384] IO_Foreign_U.S. –0.648 –3.410 1.698 30.004 45.681* 48.629* 0.114*** 0.091*** 0.184*** –7.169 1.822 2.353 [21.954] [23.137] [22.396] [25.518] [23.647] [25.441] [0.014] [0.014] [0.019] [5.600] [5.733] [7.330] IO_Foreign Non-U.S. 10.174 11.557 14.014 24.599 29.628 26.282* 0.056*** 0.058*** 0.094*** 13.170*** 16.902*** 15.123*** [20.633] [21.568] [21.775] [16.250] [18.410] [15.864] [0.013] [0.014] [0.017] [4.673] [4.547] [5.222] Market cap/GDP 0.039* 0.001 –0.000*** –0.001 [0.024] [0.020] [0.000] [0.001] Rule of law –4.097 7.186** 0.022*** 1.200*** [3.160] [2.851] [0.001] [0.161] Disclosure threshold 1.797* –0.684 –0.007*** –0.279*** [0.972] [0.878] [0.001] [0.060] Common law 0.257 4.242* –0.020*** –0.988*** [2.834] [2.433] [0.002] [0.340] Antidirector rights –0.517 0.524 0.004*** –0.206* [1.253] [1.064] [0.001] [0.108] Quality of governance 16.228 3.783 –0.031 –5.488*** [29.748] [38.336] [0.025] [1.953] Board independence –3.074 3.893 –0.008* 1.146*** [6.161] [7.359] [0.005] [0.397] Board structure 10.649** 2.054 0.018*** –0.685** [4.452] [4.313] [0.004] [0.324] Year FE Entry Entry Entry Entry Entry Entry Calendar Calendar Calendar Calendar Calendar Calendar Firm-level controls Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations 730 721 719 927 916 914 90,470 89,515 74,832 440 402 230 Adj. R-sq./Pseudo R-sq. –0.012 –0.012 –0.010 0.031 0.029 0.028 0.089 0.089 0.067 – – – Estimation OLS OLS OLS OLS OLS OLS Probit Probit Probit GLM GLM GLM Dependent variables are as indicated in column titles. Columns 1 to 3: Engagement disclosure CARs are calculated as in Table 5. Columns 4 to 6: Outcome disclosure CARs are calculated as in Table 7; engagements without outcomes are assigned a zero return. Columns 7 to 9: Sample and variables are as in Table 4. Columns 10 to 12: The sample from Columns 7 to 9 is collapsed into country-year observations. The fraction of firms engaged in country |$x$| in year |$t$| is calculated as the number of firms that are currently engaged by an activist divided by the total number of firms, per country and year. Market cap/GDP (market capitalization of listed domestic firms over GDP), Rule of law (the perception of the extent to which agents have confidence in and abide by the rules of society) are from the Worldbank as of 2000; Disclosure threshold is the minimum regulatory disclosure threshold for blockholders; Common Law equals one for countries with common law, zero otherwise; the Revised antidirector index is from Djankov et al. 2008; Quality of governance (the percentage of governance attributes for which an average firm meets or exceeds the minimum satisfactory standard on 44 governance attributes), Board independence (whether or not an average firm’s board is controlled by more than 50% independent outside directors), and Board structure (whether or not an average firm’s board is annually elected/not staggered) are from Aggarwal et al. 2009. Institutional ownership variables include domestic and foreign institutional ownership, firm-level control variables include Market-to-book, Leverage, Cash, Dividend yield, Payout, Investment, U.S. accounting standards, Index membership, and Illiquidity, all as defined in Table 4. Firm-level explanatory variables are as of the year during which the engagement is announced. All nonbinary variables are winsorized at the 1st and 99th percentiles. White (1980) heteroscedasticity-robust standard errors are reported in brackets. |$^{***}$|⁠, |$^{**}$|⁠, and |$^{*}$| indicate significance at the 1%, 5%, and 10% level, respectively. Open in new tab Second, in Columns 4 to 6, the dependent variable is the abnormal return in response to the disclosure of successful outcomes. For engagements without successful outcomes we assume an abnormal return of zero (alternatively excluding all observations with no outcomes does not change the results). These regressions are very similar in the sense that neither institutional ownership nor country-level characteristics have meaningful explanatory power for whether hedge fund activists generate successful outcomes. However, we do find that institutional ownership has a significant correlation with the number of outcomes achieved in an engagement (results are shown in Table 18 in the Internet Appendix); specifically, the total number of outcomes increases with ownership by domestic and foreign U.S. institutions. When we further test which outcome types are related, we find that board outcomes increase significantly with domestic and foreign U.S. ownership, restructurings increase with domestic ownership, but other outcome types do not increase, and foreign non-U.S. ownership even appears to have a negative relation to restructurings.22 Third, in the remaining six columns, the dependent variable is a measure of whether a firm is engaged by an activist or not (we have shown regressions with this dependent variable in Table 4). We show a firm-level version of the regression where the dependent variable is a dummy for a firm engaged by an activist in year |$t$| (1) or not engaged (0) in Columns 7 to 9, and we show a country-level version where the dependent variable is the percentage of firms being engaged by activists, for a given country in a given year, in Columns 10 to 12. For Columns 10 to 12, we use the aggregated sample from Columns 7 to 9; that is, all firm-level variables are averaged for each country-year. Since the dependent variable is a fraction, we estimate Columns 10 to 12 by GLM following Papke and Wooldridge (1996). The results show that activists are more likely to target firms in countries where the rule of law is strong; consistent with this, activism is rare in emerging markets. Further, activism is more frequent in those developed countries (e.g., France, Germany, and Italy) in which minimum regulatory disclosure thresholds for blockholders are low, the legal system is different from Common Law, and governance is relatively weak. The coefficients for investor protection and board structure are ambiguous, with sign changes.23 Our interpretation of these results is that while in absolute numbers activism is most prevalent in the United States and the United Kingdom (Common Law countries), relative to the number of listed companies it is most prominent in developed countries with Non-Common Law legal systems, accompanied by weaker governance. It may be that such targets provide greater potential for improvement from an activist point of view. Moreover, as our case studies on France and Germany illustrate, activists in those countries target companies with relatively dispersed ownership, where blocks are largely absent and that are more susceptible to the votes of foreign institutional shareholders. In summary, country characteristics matter for the decision of activists to engage a target, and for whether an outcome is achieved. However, conditional on observing an engagement, country characteristics do not correlate with measures of financial performance, such as initial disclosure returns and outcome disclosure returns. 4. Conclusion Our paper provides large-sample evidence about the incidence and performance of international hedge fund activism. The average share stake held by activists is 11\% across countries. As a consequence, activists must seek the support of other institutional shareholders or engage alongside other activists. Success of the activist business model appears to crucially depend on the activist achieving outcomes. We show that engagements with outcomes exhibit positive and significant abnormal performance for the entire engagement period, while activist engagements without outcomes do not; the differences are economically large and usually statistically significant. The most profitable outcomes are takeovers that are often preceded by governance changes, such as board restructurings. They signal that the outcome is a consequence of action taken by the activist and may not occur without engagement. Institutional investors are related to the incidence of activism across countries. However, foreign institutions, particularly those that originate in the United States, play a more important role than domestic institutional investors in activism. The increase and spread of U.S. foreign institutional holdings has significantly contributed to hedge fund activism becoming a global phenomenon. We are grateful to Robin Greenwood and Andrew Karolyi (the editors); two anonymous referees; and John Armour, Tara Bhandari, Alon Brav, Nick Gantchev, Pedro Matos, Janis Skrastins, Oren Sussman, Phillip Goldstein (Bulldog Investors), David Trenchard (formerly Knight Vinke), John Armstrong-Denby (Edmond de Rothschild), and Mark Levine (Elliott Management). We also thank the participants at the Transatlantic Corporate Governance Dialogue (TCGD) in Washington DC in December 2011, the EU-ASIA Corporate Governance Dialogue Inaugural Conference in Tokyo in June 2012, the European Financial Management Association in Rome in June 2014, the European Finance Association in Lugano in August 2014, the 4nations Cup in Rome in May 2015, and the Western Finance Association in Seattle in June 2015 and seminar participants at Bar Ilan, Bocconi University, the Hanken School of Economics, Koç Business School, the London Business School, Luxembourg School of Finance, Rotterdam University, University of Oxford, and Tilburg University for comments. Song Zhang and Yordana Mavrodieva provided excellent research assistance. We acknowledge research support from the ESRC [grant no. R060230004], the London Business School’s Centre for Corporate Governance, the BNP Paribas Hedge Fund Centre, the Goldschmidt Chair at the Solvay Brussels School of Economics and Management, Université libre de Bruxelles, and the PEGGED (Politics, Economics and Global Governance: The European Dimensions) collaborative research project supported by the Seventh Framework Programme for Research and Technological Development [contract no. SSH7-CT-2008-217559]. Supplementary data can be found on The Review of Financial Studies web site. References Aggarwal, R., Erel, I. Ferreira, M. and Matos. P. 2011 . Does governance travel around the world? Evidence from institutional investors. Journal of Financial Economics 100 : 154 – 81 . Google Scholar Crossref Search ADS WorldCat Aggarwal, R., Erel, I. Stulz, R. and Williamson. R. 2009 . Differences in governance practices between U.S. and foreign firms: Measurement, causes, and consequences. Review of Financial Studies 22 : 3131 – 69 . Google Scholar Crossref Search ADS WorldCat Appel, I., Gormley, T. A. and Keim. D. B. 2016 . Standing on the shoulders of giants: The effect of passive investors on activism. Working Paper. OpenURL Placeholder Text WorldCat Bebchuk, L. A., Brav, A. and Jiang. W. 2014 . The long-term effects of hedge fund activism. Columbia Law Review 114 : 13 – 66 . Google Scholar OpenURL Placeholder Text WorldCat Becht, M., Franks, J. and Grant. J. 2014 . Hedge fund activism in Europe: Does privacy matter? In Handbook in shareholder power . Eds. Hill J. and Cheltenham, R. Thomas. UK: Edward Elgar Publishing. Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Becht, M., Franks, J. Mayer, C., and Rossi. S. 2009 . Returns to shareholder activism: Evidence from a clinical study of the Hermes UK Focus Fund. Review of Financial Studies 22 : 3093 – 129 . Google Scholar Crossref Search ADS WorldCat Belcredi, M., and Enriques. L. 2014 . Institutional investor activism in a context of concentrated ownership and high private benefits of control: The case of Italy. ECGI Law Working Paper no. 225/2013. OpenURL Placeholder Text WorldCat Bessler, W., Drobetz, W. and Holler. J. 2015 . The returns to hedge fund activism in Germany. European Financial Management 21 : 106 – 47 . Google Scholar Crossref Search ADS WorldCat Bessière, V., Kaestner, M. and Lafont. A.-L. 2011 . Hedge fund activism: Insights from a French clinical study. Applied Financial Economics 21 : 1225 – 34 . Google Scholar Crossref Search ADS WorldCat Black, B. S., and Coffee. J. C. 1994 . Hail Britannia?: Institutional investor behavior under limited regulation. Michigan Law Review 92 : 1997 – 2087 . Google Scholar Crossref Search ADS WorldCat Boyson, N. M., and Mooradian. R. M. 2011 . Corporate governance and hedge fund activism. Review of Derivatives Research 14 : 169 – 204 . Google Scholar Crossref Search ADS WorldCat Brav, A., Dasgupta, A. and Mathews. R. D. 2016 . Wolf pack activism. Robert H . Smith School Research Paper No. OpenURL Placeholder Text WorldCat Brav, A., Jiang, W. and Kim. H. 2010 . Hedge fund activism: A review. Foundations and Trends in Finance 4 : 185 – 246 . Google Scholar Crossref Search ADS WorldCat Brav, A., Jiang, W. and Kim. H. 2015 . The real effects of hedge fund activism: Productivity, asset allocation and identification. Review of Financial Studies 28 : 2723 – 69 . Google Scholar Crossref Search ADS WorldCat Brav, A., Jiang, W. Ma, S. and Tian. X. 2014 . Shareholder power and corporate innovation: Evidence from hedge fund activism. Working Paper . Google Scholar OpenURL Placeholder Text WorldCat Brav, A., Jiang, W. Partnoy, F. and Thomas. R. 2008 . Hedge fund activism, corporate governance, and firm performance. Journal of Finance 63 : 1729 – 75 . Google Scholar Crossref Search ADS WorldCat Buchanan, B. G., Chai, D. H. and Deakin. S. 2013 . Hedge fund activism in Japan: The limits of shareholder primacy. Cambridge : Cambridge University Press . Google Scholar Crossref Search ADS Buchanan, B. G., Netter, J. M. Poulsen, A. B. and Yang. T. 2012 . Shareholder proposal rules and practice: Evidence from a comparison of the United States and United Kingdom. American Business Law Journal 49 : 739 – 803 . Google Scholar Crossref Search ADS WorldCat Carhart, M. M. 1997 . On persistence in mutual fund performance. Journal of Finance 52 : 57 – 82 . Google Scholar Crossref Search ADS WorldCat Croci, E., and Petrella. G. 2013 . Price changes around hedge fund trades: Disentangling trading and disclosure effects. Journal of Management & Governance 19 : 25 – 46 . Google Scholar Crossref Search ADS WorldCat Clifford, C. P. 2008 . Value creation or destruction? Hedge funds as shareholder activists. Journal of Corporate Finance 14 : 323 – 36 . Google Scholar Crossref Search ADS WorldCat Coffee, J. C., Jr., and Palia. D. 2016 . The wolf at the door: The impact of hedge fund activism on corporate governance. Annals of Corporate Governance 1 : 1 – 94 . Google Scholar Crossref Search ADS WorldCat Deutsche Bank Annual Report . 2004 . Deutsche Bank . Department of the Treasury . 2006 . Report on U.S. Portfolio Holdings of Foreign Securities as of December 31 , 2005. Department of the Treasury . Department of the Treasury . 2008 . Report on U.S. Portfolio Holdings of Foreign Securities as of December 31 , 2007. Department of the Treasury . Denes, M., Karpoff, J. M. and McWilliams. V. 2016 . Thirty years of shareholder activism: A survey of empirical research. Working Paper . Google Scholar OpenURL Placeholder Text WorldCat Djankov, S., La Porta, R. Lopez-de-Silanes, F. and Shleifer. A. 2008 . The law and economics of self-dealing. Journal of Financial Economics 88 : 430 – 65 . Google Scholar Crossref Search ADS WorldCat European Commission. 2012 . Application of Directive 2004/25/EC on takeover bids. Report from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of Regions. COM(2012) 347 final . Fama, E. F., and French. K. R. 1993 . Common risk factors in the returns on stocks and bonds. Journal of Financial Economics 33 : 3 – 56 . Google Scholar Crossref Search ADS WorldCat Ferreira, M. A., Massa, M. and Matos. P. 2010 . Shareholders at the gate? Institutional investors and cross-border mergers and acquisitions. Review of Financial Studies 23 : 601 – 44 . Google Scholar Crossref Search ADS WorldCat Ferreira, M. A., and Matos. P. 2008 . The colors of investors’ money: The role of institutional investors around the world. Journal of Financial Economics 88 : 499 – 533 . Google Scholar Crossref Search ADS WorldCat Financial Times. 2006 . Icahn brings investor activism to S Korea. January 17, 2006 . Foley, F. C., Greenwood, R. and Quinn J. 2008 . NEC Electronics. Harvard Business School Case 209-001 . Google Scholar Gantchev, N. 2013 . The costs of shareholder activism: Evidence from a sequential decision model. Journal of Financial Economics 107 : 610 – 31 . Google Scholar Crossref Search ADS WorldCat Gillan, S. L., and Starks. L. T. 2003 . Corporate governance, corporate ownership, and the role of institutional investors: A Global perspective. Journal of Applied Finance 13 : 4 – 22 . Google Scholar OpenURL Placeholder Text WorldCat Gillan, S. L., and Starks. L. T. 2007 . The evolution of shareholder activism in the United States. Journal of Applied Corporate Finance 19 : 55 – 73 . Google Scholar Crossref Search ADS WorldCat Greenwood, R., and Schor. M. 2009 . Investor activism and takeovers. Journal of Financial Economics 92 : 362 – 75 . Google Scholar Crossref Search ADS WorldCat Greenwood, R., Khurana, R. and Egawa. M. 2009 . Aderans. Harvard Business School Case 209-090 , March 2009 . OpenURL Placeholder Text WorldCat Hamao, Y., Kutsuna, K. and Matos, P. 2011 . Investor activism in Japan: The first 10 years. Working Paper , University of Southern California . Google Scholar Crossref Search ADS Google Preview WorldCat COPAC Harrington, F. H., and Asa. C. S. 2010 . Wolf communication, Chapter 3. In Wolves: Behavior, ecology, and Conservation . Eds. Mech L. D. and Boitani. L. Chicago : University of Chicago Press . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC Kahan, M., and Rock. E. B. 2007 . Hedge funds in corporate governance and corporate control. University of Pennsylvania Law Review 155 : 1021 – 93 . Google Scholar OpenURL Placeholder Text WorldCat Kim, H.-J. 2008 . Case for market and corporate control in Korea. Journal of Korean Law 8 : 227 – 76 . Google Scholar OpenURL Placeholder Text WorldCat Klein, A., and Zur. E. 2008 . Entrepreneurial shareholder activism: Hedge funds and other private investors. Journal of Finance 64 : 187 – 229 . Google Scholar Crossref Search ADS WorldCat Leuz, C., Lins, K. V. and Warnock. F. E. 2009 . Do foreigners invest less in poorly governed firms? Review of Financial Studies 23 : 3245 – 85 . Google Scholar Crossref Search ADS WorldCat Milhaupt, C. J. 2005 . In the shadow of Delaware? The rise of hostile takeovers in Japan. Columbia Law Review 105 : 2171 – 2216 . Google Scholar OpenURL Placeholder Text WorldCat Milhaupt, C. J. 2009 . Bull-Dog sauce for the Japanese soul - courts, corporations and communities - A comment on Haley’s view of Japanese law. Washington University Global Studies Law Review 8 : 345 – 61 . Google Scholar OpenURL Placeholder Text WorldCat Papke, L. E., and Wooldridge. J. M. 1996 . Econometric methods for fractional response variables with an application to 401(k) plan participation rates. Journal of Applied Econometrics 11 : 619 – 32 . Google Scholar Crossref Search ADS WorldCat Krishnan, C. N. V., Partnoy, F. and Thomas. R. S. 2016 . The second wave of hedge fund activism: the importance of reputation, clout, and expertise. Journal of Corporate Finance . 40 : 296 – 314 . Google Scholar Crossref Search ADS WorldCat van Tartwijk, M. 2010 . Dutch court quashes probe into ASMI board policy. Dow Jones News , September 2010 . Google Scholar OpenURL Placeholder Text WorldCat White, H. 1980 . A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica . 48 : 817 – 38 . Google Scholar Crossref Search ADS WorldCat 1 We find that fund size, measured by number of engagements during the sample period, does not affect performance. We classify large funds as those having at least 20 engagements in our sample. We test whether large funds exhibit different performance from other funds with respect to initial public disclosure, engagement outcomes, and long-term performance from entry to exit. We do not find any evidence of differential performance. 2 What we cannot capture is private activism, that is, activism that is disclosed to the target firm, but not to the wider public and because of smaller stakes is not subject to regulatory disclosure. 3 The number of entry disclosures and exits are reported in Table 11 in the Internet Appendix. 4 The FactSet Ownership database has been previously used by, for example, Ferreira and Matos (2008), Ferreira, Massa, and Matos (2010), and Aggarwal et al. (2011). 5 To address the potential concern that cross-country differences in disclosure thresholds might create some type of bias in our results, we exclude engagements where the initial activist stake is below 5% from our analysis. This excludes 273 out of 1,740 engagements in our sample. All of our performance results in later tables obtain for this smaller sample. 6 An example from France serves to illustrate the (rare) case of explicit collaboration between activists: In 2006, Centaurus Capital and Pardus Capital Management successfully engaged Atos Origin, a French information technology company (Bessière, Kaestner, and Lafont 2011). Centaurus disclosed a 5.5% stake in October 2006, followed by Pardus with a 7.3% stake in August 2007. In October 2006, the two funds notified a concert party with a joint stake of 19.4%. The market reaction to the disclosures was 7.8% for Centaurus, 1.7% for Pardus, and a further 5.5% for the joint stake. Since both hedge funds notified the authorities that they were acting as a “concert party,” their stakes for regulatory purposes were amalgamated, and they were free to coordinate. 7 The regulatory environment in some jurisdictions is not conducive to such wolf packs because of disclosure, “market abuse,” and mandatory bid rules. A comparison of the United Kingdom, the United States, and Germany illustrates this. In the United Kingdom, which has relatively restrictive rules, if one hedge fund informed another hedge fund about its intention to increase its holdings, the latter would be considered an insider and would be prevented from trading in the target’s shares. In the United States, which has less restrictive rules, in the same case the second fund generally would not be prevented from trading. In Germany, rules appear to be the weakest, considering that the market regulator found no market abuse in the Deutsche Börse case, although 5 of the 11 hedge funds in the pack were located in the same building in London and three shared an office. 8 The size of the stake acquired by a hedge fund activist in the United States, and thereby its voting power, is typically limited to 10% by poison pill trigger thresholds and Section 16(b) of the Securities and Exchange Act of 1934 that makes the activist liable to pay “short swing” profits back to the company during a given six month period (Coffee and Palia (2016)). Internationally mandatory bid thresholds, especially in Europe (European Commission (2012)), and poison pill style triggers, especially in Japan (Milhaupt 2005, 2009), impose similar constraints. The European Union’s Takeover Directive (2004/25/EC) imposes a mandatory bid requirement, typically at 30% or 33% of voting rights. Most countries have supplemented the formal voting power thresholds with “de facto” control criteria that can trigger a bid requirement at lower levels. 9 The 24.6% stake was just below Aderans’ 30% poison pill threshold. 10 A comparison of data on foreign holdings of U.S. institutions published by the U.S. Treasury shows holdings of U.S. institutions that are even higher than those reported by Factset: Factset reports total foreign U.S. equity holdings of US|${\$}$| 2,001 billion in December 2005 (Ferreira and Matos (2008), Table A2), compared with US|${\$}$| 3,318 billion for the same month and year (Department of the Treasury (2006), p. 3). 11 We alternatively calculate simple market index adjusted returns. Returns in this case are, on average, 1.3 percentage points lower and significant at the 1% level or better. 12 Further, while Brav, Jiang, and Kim (2015) find that disclosure returns in U.S. targets are declining over time, and Krishnan, Partnoy, and Thomas (2016) document larger disclosure returns in the United States from 2008 onward. The Internet Appendix provides a summary of disclosure returns from prior single-country studies of the United States, France, Germany, Italy, Japan, and the United Kingdom. See Brav, Jiang, and Kim (2010) and Denes, Karpoff, and McWilliams (2016) for recent surveys of the activism literature. 13 We verify for all 1,740 engagements whether SDC reports takeover attempts by third parties on the respective target firm. We identify 21 announcements of takeover outcomes in our sample (15 are in the United States), where a third party and not the activist may be responsible for the subsequent takeover. When we alternatively drop these 21 outcomes from our sample, our results and conclusions are materially unaltered. 14 In additional tests, we find that the individual outcomes of multiple outcomes are valued similar to single outcomes. For example, across all sample engagements, board changes generate roughly 4.5% abnormal returns, and restructurings generate roughly 5.5%, while board change plus restructuring generates roughly 10%. Therefore, engagements that generate multiple outcomes are more valuable not through making each outcome more valuable, but through generating more outcomes. 15 Japan is a special case. Ownership structures are prima facie conducive to activism; the average Japanese firm is widely held and foreign ownership has increased over the sample period. More importantly a former civil servant, Murakami Yoshiaki and various vehicles set up by him, loosely referred to as “Murakami Fund,” achieved a number of early successes employing confrontational activist tactics. Following this, several foreign activist funds entered the Japanese market: Dalton in 2001, Steel Partners in 2002, TCI in 2005, Ichigo in 2006, and Perry in 2007. Steel Partners and TCI adopted a confrontational style, and Steel Partners had some early success. However, the well-documented 2007 Bull-Dog Sauce and 2006-2008 J-Power cases cast doubt on whether confrontational activism can work in Japan. Some activists argue that changing attitudes among Japanese institutional investors and increasing foreign holdings can lead to successful and very profitable hostile engagements. An alternative type of private dialog-based activism is taking hold: Buchanan, Chai, and Deakin (2013) report the arrival of “quiet activism” in Japan and private discussions we have had with a U.K. hedge fund, Governance for Owners (GO), match this account. GO set up a joint venture with Japanese investors with the explicit objective to engage in private. These are developments that post-date the end of our sample period. To investigate this “new form” of activism in Japan will require data on private activism like the data that Becht et al. (2009) obtained for the Hermes UK Focus Fund and which is currently not available to us. 16 Takeover outcomes refer to the announcement of the takeover, not its completion, so it is possible that there are additional outcomes following takeover announcements. 17 We order activists by entry time for the same target and find (⁠|$-$|20, 20) disclosure returns of 7.8% (⁠|$t$|-statistic 5.82) for the first activist, 4.9% (⁠|$t$|-statistic 3.10) for the second activist, and 7.1% for the third activist (⁠|$t$|-statistic 1.50). Subsequent disclosures to the first activist therefore still generate large abnormal returns. While this evidence is consistent with sequential learning through activist entry, it may also be that multiple engagements increase the probability of outcomes and thereby increase the profitability of the engagement. 18 Figure A4 in the Internet Appendix shows a plot of these 24 funds. 19 For delisted firms, returns are used until the last month before delisting. For each portfolio, we require a minimum of five firm returns in each month and replace monthly portfolio returns with fewer than five firms with the excess return of the market (replacement biases our results against finding abnormal performance; depending on the portfolio, replacement is for 39 or 49 months for Asia, 5 or 10 months for Europe, and 4 or 5 months for North America). Factor portfolios in all regressions are based on U.S. stocks. We also estimate MktModel specifications in which excess returns of the activist portfolio are regressed on region-specific excess returns of the market (based on weighted averages of country stock market indices of all sample countries in each region). Results are similar, omitted for brevity, and available on request. 20 We alternatively report results calculated over one-, two-, and three-year fixed intervals in Table A17 in the Internet Appendix. For example, the results for the Carhart four-factor model show that the abnormal return is roughly equally spread across the first three years of an engagement. 21 We also find that the relative performance improvements in large engagements over time are most pronounced in those engagements without observable outcomes. Our data do not allow us to test why activist engagements without observable outcomes generate (relatively) superior performance. One conjecture is that activists, particularly in large firms, increasingly may be able to change how investors perceive firm value via outcomes that are more subtle and harder to measure than those specified by us. 22 See also Appel, Gormley, and Keim (2016), who find that a larger share held by passive institutional investors in the United States is related to a higher likelihood of (U.S.) activists achieving board outcomes. 23 Weak governance and independent boards are not necessarily inconsistent. For example, Italy requires that companies with block holders appoint special board members that represent minority shareholders. © The Author 2017. Published by Oxford University Press on behalf of The Society for Financial Studies. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License(http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contactjournals.permissions@oup.com. © The Author 2017. Published by Oxford University Press on behalf of The Society for Financial Studies.
TI - Returns to Hedge Fund Activism: An International Study
JO - The Review of Financial Studies
DO - 10.1093/rfs/hhx048
DA - 2017-09-01
UR - https://www.deepdyve.com/lp/oxford-university-press/returns-to-hedge-fund-activism-an-international-study-04em0Zykov
SP - 2933
EP - 2971
VL - 30
IS - 9
DP - DeepDyve
ER -