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Cross-border bank mergers and acquisitions

Learning outcomes

 Review the rationale for cross-border banking

 Use risk-return framework to identify benefits of diversification

 Examine trends in and determinants of cross-border bank M&A

 Consider risk effects of cross-border merges and implications for

public policy arising from financial conglomeration

 Does cross-border consolidation create value for shareholders

 Which factors drive abnormal returns to bank shareholders

Rationale for cross-border M&A

 Various explanations …

 Banks follow customers to new markets

 Increase earnings and diversify risks

 Exploit growth potential in host countries

 Avoid limited growth opportunities in highly concentrated home markets

 Expected efficiency gains including economies of scale & scope

 Improve profitability

Dovetail of supply & demand

 Intensification of competition in mature markets …

 Prompts banks to look further afield for profits & to diversify risk

 Liberalisation in EM unleashes credit booms … crises …

 Extensive State intervention … sanitisation … recapitalisation …

sale of domestic banking assets

 Foreign banks = capital

 Emerging markets = opportunities

Portfolio theory and

the risk-return framework

 Diversification – the expansion of investments into activities that are not perfectly correlated – reduces portfolio risk

 Entering a new geographic market should reduce the risk specific to each market, leaving only risk common to all

 Diversification eliminates idiosyncratic risk to leave only systematic risk

 𝑅𝑖,𝑡 =∝𝑖 +𝛽𝑀𝑅𝑀,𝑡 + 𝜀𝑖,𝑡

 Bank returns (Ri,t) depends on single risk factor, the market (RM,t), and an idiosyncratic component (εi,t). Independence of residuals implies

 𝜎𝑖 2 = 𝛽𝑀𝜎𝑀

2 + 𝜎𝜀,𝑖 2

 Total risk = systematic risk + idiosyncratic risk

 Since diversification reduces idiosyncratic risk it lessens total risk

 Is risk management optimal? Should banks try to lessen idiosyncratic risk when investors can their already well-diversified portfolios? 5

In favour of risk management

 Why should bank executives manage risk which shareholders

could manage risk themselves by adjusting their portfolios?

 Should lenders diversify or specialise?

 Should banks reduce idiosyncratic risk via diversification?

 Banks are highly regulated and regulations often provide

conflicting incentives to diversify or focus

 Bank executives tend to be risk-averse and may prefer to diversify &

reduce total volatility even if it isn’t in shareholders’ best interests

 But empire-building & self-interest can create inefficient diversification

 Diversification can reduce the probability of insolvency risk

(downside risk) – bankruptcy costs, loss of value during asset

sales, search costs for new management - implies both bank

shareholders and bank should show concern for total risk

Risk and Return when the

Opportunity Set Expands

Risk

Expected

Return

X 1

2 2’

X 2

X 3

Source: Stiroh (2010)

Notation

 Geographic expansion shifts the risk-return frontier

 A given set of regulatory, market and technological constraints lets

banks earn higher expected returns only by assuming additional risk

 Line A shows the opportunity set

 Marginal expected return for increased risk falls with the level of risk

 Utility curve 1 shows bank owners’ preferences

 X1 is the optimal point where UC1 is tangential to line A

 Geographical expansion shifts opportunity set to line B

 Does not have to lead to lower risk-taking; risk-taking depends on the

preferences of bank owners and managers

 More risk-averse owners may choose to increase returns and reduce

risk-taking by shifting from X1 to X2

 Less risk-averse could increase returns and risk-taking by shifting from

X1 to X3

Bank mergers

200

400

600

800

1000

1200

1400

1600

1 9

8 5

1 9

8 7

1 9

8 9

1 9

9 1

1 9

9 3

1 9

9 5

1 9

9 7

1 9

9 9

2 0

0 1

2 0

0 3

2 0

0 5

Cross-border mergers All mergers % cross border (right scale)

Source: Buch and DeLong (2010)

Cross-border activity by continent

Europe Americas Africa/

Middle East

Asia Austral-Asia Total

Panel A: 1985 to 2006

Number of bank mergers 7,774 10,318 514 1,737 413 19,506

Cross-border mergers 3,131 1,347 266 784 220 5,748

Cross-border as % of total 40.3 13.1 51.8 45.1 53.3 29.5

Intra-continental as % of total 59.6 91.6 61.1 72.1 63.0 81.6

Panel B: 1985 to 1995

Number of bank mergers 3,064 5,082 137 440 158 8,356

Cross-border mergers 1,005 442 65 221 90 1,823

Cross-border as % of total 20.7 2.8 12.5 16.7 15.3 10.5

Intra-continental as % of total 87.0 94.0 57.7 65.7 57.0 70.5

Panel C: 1996 to 2006

Number of bank mergers 4,710 5,236 377 1,297 255 11,147

Cross-border mergers 2,216 905 201 563 130 3,925

Cross-border as % of total 27.1 5.6 15.1 13.7 17.2 15.9

Intra-continental as % of total 84.5 89.2 62.3 74.3 66.7 89.9

Differences between Panels B and C

Cross-border as a percent of total

(z-statistic)

6.4***

(6.58)

2.8***

(7.01)

2.6

(0.76)

-3.0

(-1.47)

1.9

(0.51)

5.4***

(11.24)

Intra-continental as % of total

(z-statistic)

-2.5***

(-3.07)

-4.7***

(-8.72)

4.7

(0.95)

8.6***

(3.37)

9.7**

(1.97)

-4.6***

(-12.21)

Source: Buch and DeLong (2010)

Trends

 Cross-border bank mergers are relatively few c.f. domestic,

which suggests either implicit or explicit barriers exist

 In the early 1990s, cross-border merges stood around 15% of all

merges, growing to almost 30% in 2000 and 35% in 2006

 Europe and the Americas saw significant growth in cross-border

mergers between 1996-2006 c.f. 1985-1995

 Note the increase in intra-continental mergers (more later)

Determinants of cross-border

bank mergers

 Why should banks merge across border?

 Information costs are an impediment or barrier

 Differences in laws, regulations, currency, language, culture, tax

 Difficulties in monitoring behaviour of managers of foreign subsidiary

 Preference of foreign firms for concierge services

 The physical distance between HQ and subsidiary can be a barrier

 Obviously, less distance and similarities e.g. in language explain why

some banks locate where they do e.g. Spanish banks in LatAM

 Regulations as incentive and disincentive

 Easier to penetrate when a country privatises banking assets

 Implicit versus explicit barriers (see lecture on location decision)

 Large, relatively poor countries tend to be targets for international banks to reach a widely spaced population

 More open countries receive higher share of cross-border M&A

Risk effects of cross-border mergers

 A priori geographic diversification is risk-reducing, but …

1. Banks face incentives to shift risk when the regulatory safety net (implicit

and explicit) are under-priced

 A bank could acquire other (risky) banks via cross-border M&A and gain upside

returns if the risky investment pays off

 But, if the acquisition fails, it will threaten the solvency of the parent bank

implying the need for bail out either by the home and/or host regulator i.e. M&A

increases insolvency risk exposure of possibly two bank regulators

2. Cross-border M&A could increase risk because the acquiring bank faces

new and risk increasing monitoring problems relating to the loan

customer base, operating cost structure of the target bank

 High monitoring costs imply higher levels of insolvency risk for acquirers and

also for bank regulators in both home and host countries

Bank and nonbank mergers

 Casu et al (2014) investigate the risk effects of international bank

acquisitions of insurance companies and securities firms over 1991-2012

i.e. the process of financial conglomeration

 Why do banks engage in conglomeration?

 Opportunity to generate revenue through cross-selling, lower risk

 But, combining formerly segmented business activities exposes banks to

common shocks, increasing systematic & hence total risk

 Our results highlight differential risk effects of mergers …

 Bank acquisitions of securities firms increases total risk via higher levels of

systematic and idiosyncratic risks

 Risk levels are higher post-crisis, which suggests the crisis did make markets

wary of bank diversification

 Fundamental differences exist across the risk profiles of acquiring banks

meaning banks self-select to diversify into particular nonbank activities. Yet,

banks become more alike after deals

Implications of conglomeration

1. The reform process should distinguish the types of bank diversification …

 That bank combinations with securities firms increases risk augurs in support of

the US and European decision to legislate for the functional separation of

banks. In comparison, bank combinations with insurance companies would

appear to pose fewer risks to universal style banks

2. Consider the characteristics of diversifying banks …

 The choice of target activity may reflect the strategic goals of banks, yet

policymakers should monitor the effects of deals on banks’ risk profiles. Vital

given the positive relationship between systematic risk, default probabilities and

systemic risk, and that banks are becoming more similar following deals

3. Role of bank size in contributing to systematic risk …

 Subject large banks to greater regulatory scrutiny e.g. via enhancements to

risk-based capital, leverage and liquidity requirements, contingent capital

requirements, resolution plans and greater public disclosure of information

4. Regulators should be aware of the risks on the safety net imposed by the

post-merger introduction of nonbanks to the banking group 15

Consolidation across markets

 Differences between mature & emerging markets …

1. cross-border M&A more important source of consolidation in EM

2. consolidation used to restructure EM banking sectors after financial crisis rather than eliminate excess capacity

3. EM governments active participants in consolidation process

 M&A in mature markets driven by market forces

 Gelos and Roldós (2004)

Bank M&A literature

1. Event studies: significant abnormal returns around deal date

 US … value gains to targets … at expense of acquiring bank … latter offsets former  insignificant joint returns to combined bank

 European deals create value: gains accrue to target bank with no significant value destruction for acquiring bank

2. Bank operating performance (measured by financial ratios or estimated bank efficiency) compared pre-&-post merger

 On average, no cost efficiency gains (Berger & Humphrey, 1997)

 Big profit efficiency in large bank mergers (Akhavein et al, 1997)

Event study

 Between 1998 & 2005, we identify 73 cross-border M&A transactions involving the purchase of an ownership stake in 46 listed EME target banks by listed banks from developing countries

 What effect do M&A announcements have on bank stock prices?

 For shareholders of target banks

 For shareholders of acquiring banks

 For shareholders of combined banks

 Win-win situations occur when stockmarkets in target & acquiring countries expect M&A transactions to create value

 How are gains distributed between sets of shareholders (i.e. between countries)?

Event study methodology

Event windowEstimation windowT1 T2 t1 t2

Event

t = 0

 itRmtiiRit 

Estimate market model i.e. regress bank returns against market returns for T1 to T2 e.g. start 18 months

and end 6 before M&A announcement (t = 0). We use equation [1] to obtain estimates of α and .

To calculate abnormal returns in t1 to t2, use the estimated α and  from equation [1] and plug them

into equation [2] in which abnormal return is actual return minus predicted return. Cumulative return is

summed returns over specific window lengths e.g. -1 day before M&A announcement to +1 day after.

 

  

  

  R mt

ii R

it AR

it *

 {1} {2}

Event study methodology

 Three measures of return to shareholders …

1. Abnormal returns to target bank shareholders

2. Abnormal returns to acquiring bank shareholders

3. Joint weighted abnormal returns to combined bank shareholders

 Equation [1] estimated for 12 months (beginning 18 months & ending

6 months before M&A announcement i.e. -392 to -130 days

 Cumulative abnormal returns constructed for event windows

 Symmetric & asymmetric e.g. [-2, +2] days

 To account for leakage of information e.g. [-2, 0] days

 To account for thin trading in EME stock markets e.g. [-10, +10] days

Data

 M&A transactions sourced from Acquisitions Monthly

 Further deal information sourced from Thomson SDC

 Daily stockmarket data sourced from DataStream

 Total of $797.5 billion of EME bank assets was acquired for $37.5 billion in Asia, Latin America, & Central & Eastern Europe

 Classification of M&A transactions …

 D1 = acquisition of majority stake

 D2 = acquisition of minority stake

 D3 = increase minority stake

 D4 = increase minority to majority stake

 D5 = increase majority stake

FDI flow No. of deals No. of targets Value,

$ m

Share of value, % Average value, $

EUR-CEE 18 10 4,079.80 10.88 226.66

EUR-LAT 25 12 13,919.07 37.13 556.76

EUR-ASIA 14 12 2,670.52 7.12 190.75

ASIA-ASIA 5 3 791.53 2.11 158.31

NA-CEE 3 1 969.50 2.59 323.17

NA-LAT 4 4 12,970.54 34.60 3,242.63

NA-ASIA 4 4 2,082.69 5.56 520.67

Total EME 73 46 37,483.66 100.00 513.47

Trends in cross-border M&A

Sample: Listed EM banks acquired by international banks, 1998 to 2005

Note: EUR = European Community; CEE = Central and Eastern Europe; LAT = Latin America; NA = North America

(Canada and the US); EME = Emerging market economies.

Acquisition of EME target banks

Holding Deal value Mean deal

value

Market cap.

target (2) Assets of

target (2) Deals No.

D1 – acquire majority (> 50%) 17,099

(45.62%)

1,440.70

(52.01%)

8,623

(17.63%)

91,607

(11.49%)

(16.44%)

D2 – acquire minority (< 50%) 8,371

(22.33%)

492.39

(17.78%)

24,208

(49.50%)

503,682

(63.16%)

(23.29%)

D3 – increase minority

(from n < 50% to < 50%)

3,132

(8.36%)

313.23

(11.31%)

4,223

(8.64%)

52,595

(6.59%)

(13.70%)

D4 – minority to majority

(from < 50% to > 50%)

4,723

(12.60%)

314.85

(11.37%)

4,784

(9.78)

35,903

(4.50%)

(20.55%)

D5 – increase majority (from n > 50%) 3,970

(10.59%)

208.93

(7.54%)

7,064

(14.45%)

113,720

(14.26%)

(26.03%

M&A activity in Latin America

Target bank resident in Acquiring bank(s)

Argentina Brazil Chile Colombi

Mexico Venezuel

Avg $ m Value $ m

Acquiring bank home country

NA-LAT 1 (1) 1 (1) 2 (2) 4 (4)

n = 4 261.2 118.22 12591.1 3242.63 12970.54

Canada 1 (1) 1 (1)

n = 1 118.22 118.22

US 1 (1) 2 (2) 3 (3)

n = 3 261.2 12591.1 4284.11 12852.32

EC-LAT 2 (7) 3 (7) 2 (3) 2 (5) 3 (3) 1 (1) 13 (26)

n = 4 1925.58 8393.37 1058.9 551.58 2570.68 106.97 561.81 14607.07

Netherlands 2 (4) 2 (4)

n = 1 3545.77 886.44 3545.77

Spain 2 (7) 1 (3) 2 (3) 2 (5) 2 (2) 1 (1) 10 (21)

n = 2 1925.58 4847.60 1058.9 551.58 1481.58 106.97 474.87 9972.20

UK 1 (1) 1 (1)

n = 1 1089.10 1089.10

Value $ m 2186.78 8393.37 1177.1 551.58 15161.8 106.97 27,957.02

Mean value 273.35 1199.05 294.28 110.32 3032.36 - 931.90

M&A activity in CEE

Target bank resident in Acquiring bank(s)

Czech Republic Hungary Poland Slovenia Avg $m Value $ m

Acquiring bank home country

US 1 (3) 1 (3)

n=1 969.50 969.50

EC-CEE 4 (5) 1 (1) 5 (11) 1 (1) 11 (19)

n = 9 2186.20 25.30 1739.33 130.47 4081.30

Austria 1 (2) 1 (2)

n = 1 1158.49 1158.49

Belgium 1 (4) 1 (4)

n = 1 340.97 85.24 340.97

France 1 (1) 1 (1) 2 (2)

n = 1 996.10 130.47 563.29 1126.57

Germany 2 (2) 3 (5) 5 (7)

n = 4 31.60 1052.56 154.88 1084.16

Italy 1 (1) 1 (1)

n = 1 25.3 25.30

Netherlands 1 (2) 1 (2)

n = 1 345.80 172.90 345.80

Value $ m 2,186 25 2,709 130 5,051

Mean 437.24 - 193.49 - 229.58

M&A activity in Asia

Target bank resident in Acquiring bank(s)

China India Indonesia Korea Phils Thai Avg $ m Value $m

Acquiring bank home country

US 1 (1) 1 (1) 2 (2) 4 (4)

n = 2 69.49 32.45

1980.75 2082.69

EC-Asia 1 (1) 3 (4) 2 (2) 4 (5) 10 (12)

n = 8 929.70 279.32 196.89 983.07 199.08 2388.98

France 1 (1) 1 (1)

n = 1 118.65 - 118.65

Germany 1 (1) 1 (2) 2 (3)

n = 2 146.87 432.74 48.30 579.61

Netherlands 1 (2) 1 (1) 2 (3)

n = 2 67.91 286.81 29.56 354.72

Switzerland 1 (1) 1 (1)

n = 1 131.99 - 131.99

UK 1 (1) 1 (1) 1 (1) 1 (1) 4 (4)

n = 2 929.70 64.53 64.90 144.87

100.33 1203.99

Asia-Asia 2 (2) 1 (1) 1 (2) 4 (5)

n = 3 108.47 92.68 590.38 158.31 791.53

Australia 1 (1) 1 (1)

n = 1 3.07

0.26 3.07

Singapore 1 (1) 1 (1) 1 (2) 3 (4)

n = 2 105.41 92.68 590.38 65.71 788.47

Value $ m 999.19 311.77 305.36 2963.82 92.68 590.38 5263.20

Mean 499.60 62.35 76.34 423.40 - 295.19 250.63

CAR: region, %

Note: ***, **, * significant at 1%, 5%, and 10%, respectively

Region Latin America (1)

CEE (2)

Asia (3)

All Regions

Returns to Target bank

CAAR[-2,0] 3.9669*** 0.2663 1.1356** 2.0103***

CAAR[-2,1] 3.3025*** 1.7890*** 1.9309*** 2.4349***

CAAR[-2,2] 4.4029*** 2.9803*** 1.7866*** 3.1693***

CAAR[-10,-1] 3.7566*** 0.4946*** 0.0152 1.6394***

CAAR[-10,2] 6.9035*** 2.8545 1.3803 3.9985***

CAAR[-10,10] 6.4265*** 0.6378*** -0.1898 2.6767***

CAAR[-15,15] 4.3957*** 0.6680*** -2.6770*** 1.0950***

Returns to Acquiring bank

CAAR[-2,0] -0.2051** 0.4707** 0.1612 0.1047

CAAR[-2,1] -0.4243*** 0.3019 0.6866*** 0.1346

CAAR[-2,2] -1.4014*** 0.3554** 0.6850*** -0.2387***

CAAR[-10,-1] -0.5296*** 1.1775*** 0.3413*** 0.2359***

CAAR[-10,2] -1.9420*** 1.5660 0.8849 -0.0422

CAAR[-10,10] -1.4325*** 1.2006*** 0.2923*** -0.1316***

CAAR[-15,15] -0.4651*** 1.4461*** 0.3624*** 0.3454***

Returns to Combined bank

CAAR[-2,0] -0.0763 0.2461 0.5987*** 0.2291**

CAAR[-2,1] -0.2928*** 0.1346 1.0795*** 0.2625***

CAAR[-2,2] -1.1416*** 0.1598 1.0582*** -0.0741

CAAR[-10,-1] -0.5229*** 1.3829*** 0.6440*** 0.3930***

CAAR[-10,2] -1.6996*** 1.6281 1.2344 0.1821

CAAR[-10,10] -1.1950*** 0.7292*** 0.3775*** -0.1460***

CAAR[-15,15] -0.5394*** 0.9203*** -0.1769*** -0.0052

CAR: ownership stake (control), %

Note: ***, **, * significant at 1%, 5%, and 10%, respectively

Ownership stake D1 D2 D3 D4 D5

Returns to Target bank

CAAR[-2,0] 1.7699*** 2.7961*** 6.9518*** -2.3316*** 2.5587***

CAAR[-2,1] 2.4491*** 4.9108*** 7.1732*** -4.1859*** 3.1925***

CAAR[-2,2] 3.2761*** 5.1096*** 6.1181*** -2.2720*** 4.2592***

CAAR[-10,-1] 2.3784*** 1.9561*** -1.2313*** 3.6303*** 0.6386***

CAAR[-10,2] 5.9765** 5.3357* 3.6286 1.8554 3.3160

CAAR[-10,10] 5.5462*** 2.3688*** 2.7149*** -0.5075*** 3.4845***

CAAR[-15,15] 4.8051*** 1.0143*** 0.3096* -4.7002*** 3.5758***

Returns to Acquiring bank

CAAR[-2,0] 0.2948 -0.6311*** -0.0381 0.8081*** 0.1454

CAAR[-2,1] 0.2439 -0.4491** 0.1679 0.4167** 0.3437**

CAAR[-2,2] 0.4988*** -0.5785*** 0.1667 -1.1572*** 0.0940

CAAR[-10,-1] 0.8047*** -0.7914*** -0.0146 -0.7747*** 1.6822***

CAAR[-10,2] 1.6129* -1.1116 0.1472 -2.7378** 1.8207

CAAR[-10,10] 1.1338 -1.1161*** 0.1583 -2.3595*** 1.5050***

CAAR[-15,15] 2.0591** -0.4949*** 1.8381*** -3.7975*** 2.4883***

Returns to Combined bank

CAAR[-2,0] -0.2878 0.2524 0.2462 0.7831*** 0.1165

CAAR[-2,1] -0.3949* 0.4670** 0.5189** 0.4549** 0.2561

CAAR[-2,2] -0.2301 0.3401** 0.6188*** -0.9871*** 0.0544

CAAR[-10,-1] 0.8561*** -0.1616 -0.3410** -0.2245* 1.4075***

CAAR[-10,2] 0.8908 0.0671 0.0053 -1.9045 1.5312

CAAR[-10,10] 0.1911** -0.0063 0.1027 -2.3346*** 1.1083***

CAAR[-15,15] 0.5486*** 0.1789*** 1.9470*** -4.0382*** 1.7103***

CAR: method of acquisition, %

Note: ***, **, * significant at 1%, 5%, and 10%, respectively

Type of acquisition Open market Tender offer Private neg Stock swap Privatisation Other

Returns to Target bank

CAAR[-2,0] -2.0118*** 4.6940*** 2.2928*** 6.9303*** -1.5879** -1.3096**

CAAR[-2,1] -4.5644*** 7.8447*** 3.5198*** 6.3686*** -1.3480** -4.2166***

CAAR[-2,2] -6.4300*** 10.7396*** 3.5606*** 6.6984*** -0.4255 -4.5170***

CAAR[-10,-1] -2.9657*** 3.3416*** 0.6299*** -0.4020 -4.2846*** 9.0138***

CAAR[-10,2] -9.4030** 13.3619*** 3.3040 5.9370 -3.5229 3.9823

CAAR[-10,10] -9.8522*** 11.0897*** 2.9383*** 7.7432*** -4.5922*** 2.3351***

CAAR[-15,15] -12.6598*** 10.0020*** 0.7579*** 5.7107*** -2.9548*** 0.5432***

Returns to Acquiring bank

CAAR[-2,0] 0.4633** 0.0016 0.0730 -0.6844* -0.1092 0.4784

CAAR[-2,1] 0.3112* -0.4783*** 0.2909** -1.1714*** -1.3942*** 1.4877***

CAAR[-2,2] -1.0926*** -1.0114*** 0.4461*** -3.0155*** -2.9978*** 1.8375***

CAAR[-10,-1] -1.3066*** 0.5443*** 0.8591*** -0.3815* -0.1404 -0.6956***

CAAR[-10,2] -2.8093** -0.3054 1.1716 -3.7362* -4.4129 1.4388

CAAR[-10,10] -3.8709*** 0.9899*** 0.9698*** -1.6768*** 0.5683*** -0.2147*

CAAR[-15,15] -5.3909*** 1.7810*** 0.7895*** -3.5561*** 3.3347*** 1.5013***

Returns to Combined bank

CAAR[-2,0] 0.4449** 0.0410 0.5820*** -0.6671* -0.8367* 0.3096

CAAR[-2,1] 0.0913 -0.2526 0.8588*** -1.1373*** -2.2647*** 1.2497***

CAAR[-2,2] -1.1817*** -0.6017*** 0.9669*** -2.8429*** -3.7747*** 1.3945***

CAAR[-10,-1] -1.5184*** 0.9406*** 0.9998*** -0.1160 -0.5247** -0.1497

CAAR[-10,2] -3.1646** 0.4778 1.6615 -3.1083 -5.2094* 1.2178

CAAR[-10,10] -4.6591*** 1.0722*** 1.3550*** -1.6175*** 0.2993* 0.0280

CAAR[-15,15] -6.3224*** 1.9977*** 0.7282*** -3.3319*** 2.9261*** 0.6432***

CAR: acquirer’s nationality, %

Note: ***, **, * significant at 1%, 5%, and 10%, respectively

Nationality of Acquirers US European (1)

Dutch Spain UK

Returns to Target bank

CAAR[-2,0] 2.1186*** -0.7347** 3.7503*** 2.3242*** 5.9066***

CAAR[-2,1] 1.5013*** 0.3104 6.3440*** 1.8716*** 4.1524***

CAAR[-2,2] 1.2516*** 0.9241*** 6.9481*** 3.4860*** 5.2814***

CAAR[-10,-1] 3.9580*** 0.3125 -3.3150*** 2.5502*** 5.0400***

CAAR[-10,2] 4.3399 1.4086 2.7302 4.3912** 9.9604

CAAR[-10,10] 6.2277*** -1.9934*** 2.8828*** 3.4960*** 8.2538***

CAAR[-15,15] 3.1551*** -0.3803*** -2.2800*** 1.2571*** 7.9943***

Returns to Acquiring bank

CAAR[-2,0] -0.3344 0.2222 0.9572*** 0.1228 -0.7539***

CAAR[-2,1] -0.0713 -0.0656 1.9295*** -0.3035** -1.0611***

CAAR[-2,2] 0.0285 0.0142 1.7617*** -1.5773*** -0.8849***

CAAR[-10,-1] 1.3583*** 1.1437*** 0.1932 -1.1296*** 0.0605

CAAR[-10,2] 1.6947 1.2388 1.3968 -2.8847*** -1.3408

CAAR[-10,10] 0.9634*** 1.3205*** -0.2687*** -2.1486*** -0.6513***

CAAR[-15,15] 1.6219*** 1.9707*** 0.0161 -1.1925*** -0.8978***

Returns to Combined bank

CAAR[-2,0] -0.2599 -0.0157 0.5234** 0.1808 -0.5483**

CAAR[-2,1] 0.0045 -0.2529 1.3928*** -0.2444* -0.8090***

CAAR[-2,2] 0.1900 -0.2234 1.1576*** -1.3569*** -0.6294***

CAAR[-10,-1] 1.3454*** 1.4302*** -0.0939 -1.3152*** 0.1900

CAAR[-10,2] 1.8303 1.2315 0.6351 -2.8245*** -1.0466

CAAR[-10,10] 1.1589*** 0.9609*** -1.5693*** -1.9223*** -0.8071***

CAAR[-15,15] 1.9586*** 1.4266*** -1.6333*** -1.3528*** -0.7689***

Do M&A transactions create value?

Which factors drive abnormal returns? We consider the following hypotheses:

Are returns related to types of ownership (control)?

Does target bank assets size &/or market cap influence returns?

Are returns sensitive to host country conditions?

Are returns sensitive to the method of acquisition of control?

Does past target bank performance influence returns?

Are returns sensitive to stockmarket movements?

[2]

it Tender

ti TA

ti CAP

ti RoE

FirstD tj

Bear tj

INF tj

Law iit

CAR





  

 

   

 

 

 

 



81, ln

71, ln

61,5

45.0,31,21,1

Descriptive statistics

Mean Median Std dev Minimum Maximum

Dependent variables – cumulative abnormal returns, %

TCAR[-2,0] 2.0103 1.0230 7.7628 -12.4985 39.8334

TCAR[-2,1] 2.4349 0.9882 10.4087 -36.5000 41.0337

TCAR[-2,2] 3.1694 1.5325 12.0595 -39.1861 41.8326

TCAR[-10,2] 3.9985 1.8316 15.0105 -46.9198 43.6999

TCAR[-10,10] 2.6767 2.2249 15.6372 -53.6214 45.1807

Environmental conditions in Target country (1)

Rule of law 0.2091 0.2398 0.5833 -0.9741 1.2609

Inflation change, % 6.78 5.50 5.34 -0.80 35.80

Bear market, % (2)

-23.27 -19.72 16.14 -65.54 -0.59

Ownership

D-First (3)

0.3973 0.0000 0.4893 0.0000 1.0000

Target bank profitability, % (1)

Return on equity 4.2760 11.3747 22.6662 -70.6592 35.4463

Target bank size indicators ($ million, 2000 prices) (1)

Market capitalisation 918.2 506.3 1,464.8 0.0 10,481.9

Total assets 14,393.1 6,887.0 25,214.8 62.0 184,268.0

Method of acquisition

Tender 0.2466 0.0000 0.4310 0.0000 1.0000

CAR to target banks

Window lengths [-2, 0] [-2, 1] [-2, 2] [-10, 2]

Variable Parameter Coefficient P-

value

Coefficient P-

value

Coefficient P-

value

Coefficient P-

value

Constant α -5.292 0.373 -0.082 0.991 -7.170 0.371 4.210 0.687

LAW β1 -8.279*** 0.000 -8.121*** 0.000 -9.238*** 0.000 -8.275*** 0.004

INF β2 -0.527** 0.014 -0.639** 0.011 -0.696** 0.016 -0.829** 0.028 BEAR β3 -0.061 0.274 -0.095 0.147 -0.130* 0.085 -0.125 0.203 D-first β4 0.074 0.966 1.687 0.405 1.518 0.516 2.035 0.506 RoE β5 0.111*** 0.003 0.103** 0.018 0.094* 0.063 0.159** 0.016 CAP β6 -0.832* 0.054 -0.848* 0.092 -1.113* 0.056 -0.566 0.453 TA β7 1.693** 0.013 1.057 0.176 2.061** 0.024 0.498 0.671 Tender β8 5.348*** 0.007 8.737*** 0.000 12.166*** 0.000 13.969*** 0.000 Adj R

2 31.20% 29.50% 33.50% 23.80%