MSc in Finance and Investment, Copenhagen Business School Master’s Thesis The Impact of Financial Crises, CEO Overconfidence, and Cultural Distance on Acquisition Value Creation - AN EMPIRICAL STUDY ON EUROPEAN ACQUISITIONS BETWEEN 1999-2018 Anders Hess Christensen (116655) & Jonas Vendelbo Olesen (115845) Advisor: Torben Vinter Søstrup Date of submission: May 14, 2019 Characters incl. blanks: 269,758, equivalent to 118.6 standard pages Abstract The last few decades have seen increasing globalisation and new technologies continuously being innovated more rapidly, which drives economic growth. At the same time acquisitions have become a gradually more popular expansion strategy for CEOs. One feature of acquisitions is their tendency to occur in waves. Six waves during the last century are commonly pointed out in the literature and two of those occurred recently, but were abruptly ended due to financial crises. It appears that financial crises occur within shorter time spans. Consequently, this paper contributes by investigating how acquisitions are affected by financial crises while also studying the CEO’s acquisition history, and cultural distance. A thorough analysis of 1,453 acquisitions undertaken by European companies from 1999 to 2018 is conducted by applying the event study methodology. The value creation is measured using the acquirer’s shareholders’ return on the share price around the announcement. It is estimated using a [-1;1], [-5;5], and [-10,10] event window and by utilising both a market model with local indices and European index as well as the constant mean return model. A battery of seven statistical tests is applied to test the overall announcement return while a cross-sectional regression is conducted to delve deeper into which factors affect the cumulative abnormal return. The findings in this paper can be summarised as: (i) The acquisitions lead to a statistically significant value creation of approximately 1% around announcement. The result is significant across the three return models and event windows. (ii) We find evidence of a financial crisis having a negative impact on the shareholder return. This negative impact is caused solely by the Dot-com Crisis, which has significantly lower returns than the 2008 Financial Crisis. (iii) Contrary to previous literature, this paper finds that acquiring a financial distressed target results in lower CAR. However, the result is insignificant due to a difference between acquisitions of distressed and very distressed targets. Moreover, it is found that acquiring a distressed target during crisis results in greater CAR, possibly because of larger bargaining power for acquirer. (iv) Weak evidence is presented showing that CEO’s higher order deals lead to significantly lower return due to overconfidence caused by the self-attribution bias. The overconfidence is dominated by the CEO’s acquisition experience when acquiring during a crisis, thus, resulting in a positive relationship. (v) Domestic acquisitions generate significantly higher returns than cross-country acquisitions. (vi) Cultural distance has no relationship with CAR for the cross- country acquisitions. We find signs of polynomial relationships between cultural distance and CAR depending on the relatedness of the target, however, they cannot be confirmed statistically. ii Contents 1 Introduction 1 1.1 Motivation and problem statement . 2 1.2 Delimitations and definitions . 4 1.3 Thesis structure . 7 2 Theory and literature 8 2.1 Theory overview . 8 2.2 Review of relevant empirical evidence . 12 3 Sample data 24 3.1 Data selection process . 24 3.2 Descriptive statistics . 27 4 Event study methodology 35 4.1 Efficient market hypothesis . 35 4.2 Estimation period and event window . 36 4.3 Normal and abnormal returns . 38 4.4 Statistical tests . 40 4.5 Cross-sectional regression . 43 5 Empirical findings 49 5.1 Hypothesis 1: General acquisition value creation . 49 5.2 Introduction to regression results . 58 5.3 Hypothesis 2: The impact of financial crises . 60 5.4 Hypothesis 3: CEO acquisition history and overconfidence . 70 5.5 Hypothesis 4: Cross-country and cultural distance . 81 5.6 Additional findings . 93 5.7 General discussion of findings . 98 6 Conclusion 101 6.1 Conclusion . 101 6.2 Further research . 103 Bibliography 105 Appendices I A Financial Crisis . I iii B Description of test statistics . VI C Regression assumptions . X D Regression results . XIII E List of acquisitions . XXI F STATA code . XLVIII List of Figures 1.1 Overview of thesis structure . 7 2.1 M&As overview in Europe from 1999-2018 . 9 2.2 Theory overview framework . 9 3.1 Historical development of sample data . 28 3.2 Timeline of acquisitions in fall 2010 . 28 3.3 Geographical map of acquirers . 33 4.1 Timeline of estimation period and event windows . 38 4.2 Leverage-versus-Squared-Residual plot . 48 5.1 Cumulative average abnormal return using local indices . 51 5.2 Cumulative average abnormal return using European index . 53 5.3 Cumulative average abnormal return using constant mean return . 56 5.4 Cumulative abnormal return across time . 61 5.5 VIX-index . 63 5.6 Geographical map of all domestic acquisitions . 85 5.7 Geographical map of all cross-country acquisitions . 86 5.8 CAR by cultural distance and relatedness . 88 List of Tables 3.1 Second selection process . 26 3.2 Deal characteristics . 29 3.3 Missing data on targets overview . 30 iv 3.4 Cultural distance of cross-country acquisitions . 31 3.5 Overview of other deal characteristics . 31 3.6 Relative size overview . 34 4.1 Overview of variables included in the regressions . 45 5.1 Average abnormal return using local indices . 50 5.2 Statistics for CAR for local indices . 51 5.3 T-tests on CAR for local indices . 52 5.4 Average abnormal return using European index . 53 5.5 Statistics for CAR for European index . 54 5.6 T-tests on CAR for European index . 54 5.7 Average abnormal return using constant mean return . 55 5.8 Statistics for CAR for constant mean return . 56 5.9 T-tests on CAR for constant mean return . 57 5.10 Regression results with European index . 59 5.11 Carve-out of regression results for financial crisis . 62 5.12 Average CAR by financial crisis for different event windows . 62 5.13 Differences in CAR by financial crisis and method of payment . 64 5.14 Differences in CAR for financial crisis . 65 5.15 Differences in CAR for industries during the Dot-com Crisis . 66 5.16 Carve-out of regression results for financial distress . 67 5.17 Size of acquirers . 68 5.18 Differences in CAR by Altman’s Z”-score . 68 5.19 CAR by CEO deal order . 72 5.20 Frequent vs. infrequent acquirers . 73 5.21 Carve-out of regression results for CEO acquisitiveness and higher order deals . 74 5.22 CAR by deal order and method of payment . 75 5.23 CAR for deal order by relatedness and investment opportunities . 75 5.24 CAR by sign of first deal . 77 5.25 Carve-out of regression results for interaction between crisis and higher deal order . 77 5.26 CAR by CEO acquisitiveness and crisis . 78 5.27 Differences in CAR by cross-country . 82 5.28 Carve-out of regression results for cross-country . 83 5.29 Differences in CAR by cross-country and target listing . 84 5.30 Target industry by relatedness and target country for cross-country acquisitions . 87 5.31 Differences in CAR by cultural distance . 87 5.32 Carve-out of regression results for cultural distance . 88 5.33 Differences in CAR by cultural distance and relatedness . 89 5.34 Differences in CAR by cultural distance and crisis . 90 5.35 Carve-out of regression results for polynomial effect of cultural distance . 91 5.36 Carve-out of regression results for control variables . 97 v CHAPTER 1 Introduction There are two primary mechanisms by which control and ownership of a corporation can change. First, mergers are referring to a process where two or more entities join forces to form a single new entity. In contrast, an acquisition refers to the event where the bidder (hereafter acquirer) purchase the seller (hereafter target) (Berk and DeMarzo, 2016). The global market for mergers and acquisitions (hereafter M&A) constitutes a multi-trillion euro industry, which reached an annual value of EUR 3.1tn in 2018. 94.8% of the takeover activity and value was generated in USA, Europe, and the Asian-Pacific region (Mergermarket, 2019). Interestingly, the global M&A value was EUR 4.2tn, EUR 1.8tn, and EUR 4.1tn in 2007, 2009, and 2014, respectively, implying a convex relationship between total deal value and business cycles (IMAA, 2019a). This is coherent with the findings made by Gaughan (2009, page 45), namely that “merger waves tend to occur in economic expansion” since companies look to expand more rapidly than organic growth allows. Moreover, he argue that “as credit markets undergo upheavals, the M&A business must adjust to the challenging market conditions”, which translates into less M&A activity. It is evident that M&A is of great importance in a competitive environment, especially with regards to expansion of operations and maintaining a competitive advantage. While several incentives for M&A exist, the most common are related to synergies, management incentives, or changes in macro factors including regulatory and technological changes (Bruner and Perella, 2004). Over the past decade several theories of acquisition finance have taken shape. It remains an interesting topic to investigate as new discoveries continuously emerge. There is a separation of the ownership and the controlling power of the company in the majority of.