A STUDY ON WITHDRAWN MERGER PROPOSALS INVOLVING PRIVATE TARGET

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A STUDY ON WITHDRAWN MERGER PROPOSALS INVOLVING PRIVATE TARGET

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1 FOREIGN TRADE UNIVERSITY FACULTY OF BUSINESS ADMINISTRATION -*** GRADUATION THESIS Major: International Business Administration A STUDY ON WITHDRAWN MERGER PROPOSALS INVOLVING PRIVATE TARGET Student name : Truong Huy Hoang Student code : 1111260037 Class : Advanced Business Administration Intake : 50 Supervisor : Assoc Prof Dr Nguyen Thu Thuy Hanoi, May 2015 TABLE OF CONTENTS LIST OF ABBREVIATIONS ANNCAR BIDDERCASH BIDDERDEBT FINCRISIS FDI GPD MULTIBID PRIV PRIVSTOCK Announced cumulative abnormal return Bidder's cash level Bidder's cash level Financial crisis Foreign direct investment Gross domestic product Multiple bidders Private target Private target and the intended method of payment for the RELATED RESIZE ROA VIF WITHCAR merger is stock Bidder and target are in related industries Relative size of bidder over target Return on assets Variance inflation factor Withdrawn cumulative abnormal return LIST OF FIGURES LIST OF TABLES Table 3.1: Statistical descriptions of variables using in models .22 Table 3.2: Correlation matrix for variables with event window (0, +1) 23 Table 3.3: Results of multicollinearity test for sample event window (0,+1) 25 Table 4.1: Mean cumulative abnormal returns of proposal announcements 29 Table 4.2: Mean cumulative abnormal returns of proposal withdrawals 30 Table 4.3: MHW test for withdrawn abnormal return with event window (0,+1) 31 Table 4.4: Non-parametric T-test for withdrawn abnormal return with event window (0,+1) 32 Table 4.5: Bidder’s valuation effects based upon target public status and .33 Table 4.6: Multivariate analysis result of model 35 Table 4.7: Multivariate analysis result of model 36 Table 4.8: Multivariate analysis result of model 37 Table 4.9: Multivariate analysis result of model 38 Table 4.10: Multivariate analysis result of model .39 Table 4.11: Multivariate analysis result of model .40 Table 4.12: Summary of multivariate analysis results of six models for event window (0,+1) .41 Table 4.13: Multivariate analysis result of model .46 Table 4.14: Multivariate analysis result of model .47 Table 4.15: Multivariate analysis result of model .48 Table 4.16: Multivariate analysis result of model .49 Table 4.17: Multivariate analysis result of model .50 Table 4.18: Multivariate analysis result of model .51 Table 4.19: Summary of multivariate analysis results of six models for event window (-1,+1) 52 Table 4.20: Multivariate analysis result of model .55 Table 4.21: Multivariate analysis result of model .56 Table 4.22: Multivariate analysis result of model .57 Table 4.23: Multivariate analysis result of model .58 Table 4.24: Multivariate analysis result of model .59 Table 4.25: Multivariate analysis result of model .60 Table 4.26: Summary of multivariate analysis results of six models for event window (-2,+1) 61 ACKNOWLEDGEMENTS I cannot express enough thanks to my thesis supervisor – Associate Prof., Dr Nguyen Thu Thuy – for her continued support and encouragement A complicated quantitative study like this thesis is really a huge challenge in which I have to admit that sometimes I felt lost and demotivated However, with just a few short talks, Mrs Thuy could clearly guide me the strategy to complete the thesis, helped me on how to tackle problems, and really inspired me to strive for my best for the study I was also surprised by her professionalism and enthusiasm while I submitted my thesis draft in the evening and could receive so detailed and essential comments for my thesis in just the morning next day It is my luck to have an opportunity to work with her, in which I can not only complete a good thesis but also learn much from her professionalism and her research skill I also would like to express my most sincere gratitude to Dr Cao Dinh Kien, for all his support and advices If it would not be Dr Kien, I could not approach a wide range of highly quality papers and database, and find the idea for this thesis In addition, thanks to the great knowledge and skills of Dr Kien about running qualitative models, I can have lots of advices which are crucial for my thesis I am also indebted my friends with all their helps in this work For Nguyen Viet Duong, I would like to thank him very much for his sharing about the experience in doing thesis and for guiding and reminding me the basics about statistics and econometrics For Hoang Ngoc Anh and Nguyen Duc Hung, thanks to their help, I can access to the database of California State University Fullerton and of La Trobe University, which are the critical condition to complete my thesis And it does not come to this day by chance, but for all past four years, I owe special thanks to my lecturers and friends at Foreign Trade University for everything they have done for me And foremost, to my family, words cannot express my gratefulness For this and more, this is my gift to them Truong Huy Hoang Hanoi, May 2015 CHAPTER 1: INTRODUCTION 1.1 Background The phenomenon of mergers and acquisitions has developed to become a highly popular form of corporate development to create growth and diversity (Cartwright and Schoenberg, 2006) Merger and acquisition are a vital part of both healthy and weak economies and are often the primary way in which companies are able to provide returns to their investors, stakeholders, and owners (Sherman, 2010) However, in general, out of ten proposals for a merger in Australian Stock Exchange, one of them will be withdrawn In the world as a whole, proposals that are withdrawn constitute a ratio of one over twenty (summarized from Thomson Financial SDC Platinum™ database) Because of its large proportion in the population of total merger proposals, the withdrawn merger proposals should account for an important part of academic research in merger and acquisition field and also in real life business practices A withdrawn proposal is intriguing as it can reverse previous effects caused by the results from the announcement of the proposal By how much important the effects of an announcement to firm valuation, we would expect that much important the effects of a withdrawn proposal for investors in the valuation of firm value But the sad fact is that many researchers have been focusing on examining the effects of the announcement of a proposal but not many of them pay proper attention on effects of withdrawn merger proposal In consideration of a research in merger and acquisition field, it is widely known that effects of an announcement of a proposal from a public bidder can vary by many characteristics, such as those of bidders, targets, market, and from the proposal itself Therefore, it would be expected that the signal resulting from a withdrawn proposal would also be affected by that many attributes A withdrawn merger proposal requires more thorough and more attentive dedication in examining what influences its variations In particular, there is an important research aspect, in which we try to examine the valuation of a bidder in response to a merger bid may be conditioned on whether its corresponding target is a privately-held or is a publicly-traded company Effect 10 causing by whether the target is public or private company, which I call it as target status, in firm valuation is expected to be significant as private and public targets are inherently different because of information asymmetry, and in general, acquirers will have different ownership implications for takeover strategy for private targets versus for public targets In other word, the signal relayed from the withdrawal of merger bids for private targets may be unique in comparison with those of their public counterparts Previous studies generally ignored merger proposals involving private targets or did not put proper attention to this unique characteristic Given the implications might have in firm valuation, this thesis contributes an effort to illuminate whether the characteristic of a firm status affects firm value Researching on the effect of firm status on merger deal abnormal return is important for both academics and business practitioners For academic researchers, this studies dig into a new corner of merger and acquisition field, which is withdrawals involving private targets, in which helps to enrich the theoretical framework and might offer opportunity for further exploration One aspect of information asymmetry, which represents by whether the firm status is public or private, is further examined through the effect of withdrawn merger proposals In addition, the effects of other characteristics previously pointed out by other researchers that affect firm valuation in a deal are now more strengthened with evidences from this study In practical business life, the implications from this study can provide insights and useful knowledge for investors and merger consultants Investors can have a better approach in understanding how valuation of a public firm is different from a private one in a deal Based on this, they can offer fair price between target and bidder, which is one of the crucial factors contributing to the success of a deal Additionally, understanding of impact of other characteristics about the deal, such as the method of payment and effect of financial crisis, is also useful in the process of making a successful deal In addition, an important noticeable point here is that not many researches on the topic of withdrawals of mergers involving private targets have been done in Asia countries context but there are only very few of them have been done for the United States In other words, as there are significant differences among above countries’ This table provides the summary of multivariate analysis result of six models for event window (-2,+1) Coefficients of each variable, adjusted R2, F-statistics, and number of observations are reported in the table below *, **, ***, and **** indicate the significance level at 10, 5, 1, and 0.1%, respectively Model Model Model Independent Variables Coefficients p-value Coefficients p-value Coefficients p-value Intercept 0.02 0.634 0.02 0.626 0.01 0.824 ANNCAR (-1,2) 0.15* 0.052 0.20*** 0.001 PRIV -0.18** 0.012 -0.22**** 0.003 -0.23**** 0.002 PRIVSTOCK 0.05 0.596 0.09 0.302 0.12 0.195 MULTIBID 0.05 0.235 0.04 0.398 0.03 0.437 RELATED 0.07* 0.092 0.07* 0.073 0.06* 0.096 FINCRISIS -0.08** 0.039 -0.08** 0.049 -0.08** 0.045 ROA -0.02 0.638 0.06 0.202 0.10*** 0.001 RESIZE 0.00 0.560 0.00 0.454 0.00 0.475 BIDDERCASH -0.04 0.713 0.09 0.384 BIDDERDEBT -0.03**** 0.005 -0.01 0.480 F-statistics 4.49*** 5.20**** 5.25**** Adjusted R 31.91% 36.07% 36.36% Number of observations 68 68 68 Table 4.26 (cont.): Summary of multivariate analysis results of six models for event window (-2,+1) From the multivariate analysis results for event window (-2,+1), I am able to draw the same conclusions as did for event window (0,+1) and event window (-1,+1) Two variables which are PRIV and PRIVSTOCK are as expectation PRIV is negative and statistically significant in all models, and PRIVSTOCK is not statistically significant in all six models The observation above allows us to draw the conclusion that withdrawals of mergers involving private targets have negative impact on bidder’s returns Therefore, by running multivariate analysis against different event window’s measures, I can safely conclude that the findings from multivariate analysis section are robust CHAPTER 5: CONCLUSIONS, RECOMMENDATIONS, AND LIMITATIONS 5.1 Conclusions As pointed out by literature, withdrawn merger proposal can reverse a previous gain or loss of the acquirer that has been resulted from the announcement of the proposal Since the previous signal about the public acquirer can be impacted with many particular variables, from the deal characteristics, from firm characteristics, and from macroeconomics and financial situation, the signal resulting from a withdrawal of the proposed merger is also affected by many characteristics Through the results of this study, we find that in Australian context, the announced withdrawal of mergers involving private targets produces negative and significant valuation effects on average in comparison with withdrawal of mergers involving public targets In other word, the valuation effects of acquirers in response to withdrawn mergers are significantly worse when involving private targets than public targets Even when controlling the sample of observations according to stock payment only or cash payment, these results still hold true This contributes to the literature by affirming that the effects of target status on withdrawn merger abnormal returns are not conditioned on the method of payment Considering that besides firm status and method of payment, there are some other factors might also influence withdrawn abnormal returns, I also implement various multivariate analysis models It turns out that the same findings are also found when applying various multivariate models to the entire sample, in which other control variables are added to examine the correlation effects The multivariate analysis is also applied robustness check over different measures, which are different window lengths It is found that the same conclusions are found even for different robustness checks Therefore, it is safe to conclude that our findings are robust in the research context In summary, this leads to an implication that in Australian context, the effect of withdrawal of a merger is a partial correction of the benefits that were previously anticipated as a result of the merger announcement, and target status has significant impact on withdrawn merger abnormal return This result holds true even when controlling for the method of payment The similar implication about the impact of withdrawn merger proposals involving private targets on bidder’s returns is also found in US context We might expect that this unique response of mergers involving private targets is universal and can be found in other markets, such as markets in the region of South East Asia and East Asia Further work in these countries’ contexts needed to be done to confirm our anticipation 5.2 Recommendations 5.2.1 Bidders and targets a) Bidders Thanks to results of this study, future bidders can have insights and knowledge about the effects of the withdrawals of mergers As proved by this study’s result, the withdrawals of mergers involving private targets would bring bad impact on bidder’s returns Bidders need to understand that this effect is normal; therefore, in case of a withdrawal of a merger, on the one hand, they can expect a decrease in their stock’s returns and keep calm the managing board and shareholders On the other hand, they can isolate the bad impact of the announcement of the withdrawals to analyze if there is any other factors badly affect the stock’s price to propose proper management solutions In addition, as pointed out in this study, in general, mergers involving private targets have positive returns in comparison with public ones Therefore, the management board should re-consider their merger and acquisition strategy, focusing more on buying private targets to increase shareholders’ value b) Targets As for targets side, some of the reasons that make targets less attractive to prospective investors and are likely to be sold at a discounted price are the unavailability of information and the bad impact of information asymmetry Therefore, in case private targets would like to sell their firms, they should proactive express their interests and disclose their information as reliable and public as much as possible, such as hiring a well-known auditor to audit their financial statements and public them, and organizing information seminars for potential investors The effort to eliminate information asymmetry would bring advantages for targets to reach a more beneficial deal However, targets should understand that private targets are often sold at a lower price in comparison with public targets, even when two firms are comparable Therefore, in the negotiation phase, targets should propose proper price so that the deals can be successful 5.2.2 Investors With regard to investors side, this study points out the arbitrage opportunity that investors should utilize It is shown that the announcement of a merger involving private targets produces better cumulative abnormal returns in comparison with those involving public targets If investors anticipate an announcement of a merger is likely to happen, and have to choose to invest in one of two options: one is for a merger involving private target, the other is for merger involving public target, they should spend their money to invest in stocks of bidder of merger involving private target to have better returns Conversely, there is large discrepancy in abnormal returns of the withdrawals of mergers involving private target It can be seen in the research result that withdrawals of mergers involving private targets produce significant negative abnormal returns Therefore, if the investors expect the deals to be cancelled, they should try to sell their shares prior the announcement of the withdrawals to avoid a loss In addition, understanding about how other variables, such as the method of payment and announcement abnormal returns, influence withdrawn abnormal returns also helps financial experts have more insights in building proper financial models in predicting stock prices and in estimating firm valuation Besides some traditional variables about firm and deal characteristics that have been introduced in previous literature, financial experts should also focus on macro-level variables as financial crisis (FINCRISIS) is proved to have significant correlation with bidder’s abnormal returns in this study 5.2.3 Government As discussed in this study, private targets have substantial disadvantages over public ones; therefore, they are often sold at a discounted price The major problem for this is because of the information asymmetry In order to compensate for this, Government should have some information centers where private targets can provide their information to prospective buyers or where potential bidders can approach information of their targets with a high level of confidence in data obtained This will be an efficient policy in facilitating mergers in economy, especially for private firms, which often are small and medium sized companies 5.3 Limitations and suggestions for further study Due to the time limitation, I can just conduct data from Australian for a period of ten years only It would be an ideal situation if this study can apply for more countries, especially in Southeast Asia and East Asia context, and for a longer time window It could be more informative and persuasive if the data would be more various Therefore, further researches with larger panel, more sources of data, and with different country contexts should be conducted If the same finding is also found in different contexts other than Australian, the finding about effects of target ownership on withdrawn merger abnormal returns can be generalized universally In addition, in this study, because I cannot find the median ratio of industry, the results of bidder’s cash level (BIDDERCASH) and bidder’s debt level (BIDDERDEBT) are not in line with our expectation Therefore, I anticipate that industry effects have significant impact on bidder’s returns, and further researches about the impact of industry effects should be done in the future Last but not least, as far as my knowledge, not many macro-level variables are utilized in models which predict bidder’s abnormal returns However, financial crisis (FINCRISIS) is proved to be consistently significant in our models Therefore, researchers should consider in applying macro-level variables, such as financial crisis, in their future researches REFERENCES Amihud Y, Lev B., 1981, Risk reduction as a managerial motive for conglomerate mergers, Bell Journal of Economics, No 12, 605–617 Australian economy to outperform the world: IMF | SBS World News, Sbs.com.au, retrieved 22 April 2015 Bang Nam Jeon, Seung Hee Choi, 2011, The impact of the macroeconomic environment on merger activity: evidence from US time-series data, Applied Financial Economics, No 21, 233-249 Cartwright, S and Schoenberg, R., 2006, Thirty Years of Mergers and Acquisitions Research: Recent Advances and Future Opportunities, British Journal of Management, Vol 17, Issue 1, 1-5 Choe, Hyuk, Ronald W Masulis, and Vikram Nanda, 1993, Common stock offerings across the business cycle: Theory and evidence, Journal of Empirical Finance, No 1, 3-31 Credit Suisse Global Wealth Report credit-suisse.com, retrieved 22 April 2015 Cyree, Ken B and Ramon P DeGennaro, 2002, A Generalized Method for Detecting Abnormal Returns and Changes in Systematic Risk, Review of Quantitative Finance and Accounting 19, 399-416 Dodd, P., 1980, Merger proposals management discretion and stockholder wealth, Journal of Financial Economics 8, No 2, 105-138 Donaldson, G., 1994, Corporate Restructuring: Managing the Change Process from Within Harvard Business School Press, Cambridge, MA Foreign direct investment (FDI) in Australia, http://www.habc.gr/australia_fdi.asp retrieved 22 April 2015 Fuller, K., Netter, J and Stegemoller, M., 2002, What returns to acquiring firms tell us? Evidence from firms that make many acquisitions, Journal of Finance, 57, 1763-93 Galai, Dan, and Ronald W Masulis, 1976, The option pricing model and the risk factor of stock, Journal of Financial Economics 3, 53‐81 Gaughan, P., A., 2011, Mergers, Acquisitions and corporate restructuring, Fifth Edition.John Wiley & Sons Gibbons, J.D., 1976, Nonparametric methods for quantitative analysis, American Sciences Press, 463 Hair, J F Jr., Anderson, R E., Tatham, R L & Black, W C., 1995, Multivariate Data Analysis (3rd ed) New York: Macmillan Harford, J., 1999, Corporate cash reserves and acquisitions, Journal of Finance 54, 1969-1997 Jensen M.C and Meckling W.H., 1976, Theory of the firm: managerial behavior, agency costs and ownership structure, Journal of Financial Economics, 3, 350-360 Kearney's 2012 FDI Confidence Index http://www.atkearney.com/researchstudies/foreign-direct-investment-confidence-index/2015, retrieved 22 April 2015 Kennedy, P., 1992, A Guide to Econometrics, Oxford: Blackwell Madura and Ngo 2012, Withdrawals of mergers involving private targets, Applied Financial Economics, No 22, 313-320 Marquardt, D W., 1970, Generalized inverses, ridge regression, biased linear estimation, and nonlinear estimation Technometrics, 12, 591–256 Marsh, Paul, 1982, The choice between equity and debt: An empirical study, Journal of Finance, No 37, 121-14 Martin, K., 1996, The method of payment in corporate acquisitions, investment opportunities, and managerial ownership, Journal of Finance 51, 1227-46 Morck, R., Schleifer, A and Vishny, R., 1990, Do managerial objectives drive bad acquisitions, Journal of Finance, 45, 31-48 Myers S.C and Majluf N., 1984, Corporate financing and investment decisions when firms have information that investors not have, Journal of Financial Economics, 13, 187-221 Neter, J., Wasserman, W & Kutner, M H., 1989, Applied Linear Regression Models Homewood, IL: Irwin Officer, M., Poulsen, A and Stegemoller, M., 2009, Target firm information asymmetry and acquirer returns, Review of Finance, 13, 467-93 Refsnes, 2012, What Explains Mergers’ Success or Failure?, Centre for Technology, Innovation, and Culture, University of Oslo Schipper, K., and R Thompson, 1983, Evidence on the capitalized value of merger activity for acquiring firms, Journal of Financial Economics, 11 Scott, R., W., 2003, Organizations Rational, Natural, and Open Systems Fifth Edition, Pearson Education Sherman, A., J., 2010, Mergers and Acquisitions from A to Z Third Edition, New York American Management Association Shleifer, Andrei and Robert W Vishny, 1991, Takeovers in the ‘60s and ‘80s: Evidence and Implications, Strategic Management Journal 12, 51-59 The World Factbook, https://www.cia.gov/library/publications/the-world- factbook/geos/as.html, retrieved 22 April 2015 Travlos, Nickolaos G., 1987, Corporate takeover bids, methods of payment, and bidding firms' stock returns, Journal of Finance 42, 943‐963 Walkling & Edminster, Determinants of Tender Offer Premiums, Financial Analyst Journal, Jan-Feb 1985, 27 World Bank Australia Index http://data.worldbank.org/country/australia, retrieved 22 April 2015 Zikmund, William G 1997 Business research methods, 8th edition, Cengage learning APPENDIX Table 1: Correlation matrix for variables with event window (-1, +1) WITH CAR ANN CAR PRIV WITHCAR ANNCAR PRIV PRIV STOCK MULTI BID -0.023 -0.387 0.393 -0.343 0.143 0.176 -0.082 RELATED FIN CRISIS 0.279 0.088 -0.084 -0.067 0.352 -0.438 -0.101 -0.020 0.115 -0.020 0.751 0.270 0.048 0.217 0.452 0.001 0.134 -0.357 -0.059 0.287 ROA RESIZE BIDDER CASH BIDDER DEBT PRIV MULTI STOCK BID RELATED FIN CRISIS ROA RESIZE BIDDER CASH BIDDER DEBT 1 -0.203 -0.028 0.103 -0.077 0.167 0.119 -0.553 0.187 0.028 -0.009 -0.001 -0.132 -0.096 -0.071 -0.170 -0.009 0.257 0.252 0.377 -0.067 -0.207 -0.169 0.033 0.082 0.668 -0.149 0.029 -0.119 Table 2: Correlation matrix for variables with event window (-1, +2) WITH CAR ANN CAR PRIV WITHCAR ANNCAR PRIV PRIV STOCK MULTI BID -0.071 -0.425 0.320 -0.349 0.250 0.227 -0.070 RELATED FIN CRISIS 0.270 0.103 -0.041 0.049 0.383 -0.529 -0.087 -0.012 0.052 -0.081 0.751 0.270 0.048 0.217 0.452 0.001 0.134 -0.470 -0.086 0.287 ROA RESIZE BIDDER CASH BIDDER DEBT PRIV MULTI STOCK BID RELATED FIN CRISIS ROA RESIZE BIDDER CASH BIDDER DEBT 1 -0.203 -0.028 0.103 -0.077 0.167 0.119 -0.553 0.187 0.028 -0.009 -0.001 -0.132 -0.096 -0.071 -0.170 -0.009 0.257 0.252 0.377 -0.067 -0.207 -0.169 0.033 0.082 0.668 -0.149 0.029 -0.119 Table 3: Results of multicollinearity test for sample event window (-1,+1) Variable ANNCAR (-1,1) WITHCAR (1,1) PRIV PRIVSTOCK MULTIBID RELATED FINCRISIS ROA RESIZE BIDDERCASH BIDDERDEBT Toleranc e 36.0% 65.2% 26.6% 26.1% 84.0% 82.4% 75.8% 18.1% 94.3% 72.1% 29.1% R 64.0% 34.8% 73.4% 73.9% 16.0% 17.6% 24.2% 81.9% 5.7% 27.9% 70.9% VIF 2.78 1.53 3.76 3.82 1.19 1.21 1.32 5.53 1.06 1.39 3.44 Benchmar k 10 10 10 10 10 10 10 10 10 10 10 Presence of Multicollinearit y FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Table 4: Results of multicollinearity test for sample event window (-2,+1) Variable ANNCAR (-2,1) WITHCAR (2,1) PRIV PRIVSTOCK MULTIBID RELATED FINCRISIS ROA RESIZE BIDDERCASH BIDDERDEBT Toleranc e 25.2% 13.5% 29.9% 25.5% 83.3% 87.1% 81.0% 11.2% 95.0% 59.4% 18.8% R2 74.8% 86.5% 70.1% 74.5% 16.7% 12.9% 19.0% 88.8% 5.0% 40.6% 81.2% VIF 3.97 7.43 3.34 3.92 1.20 1.15 1.23 8.89 1.05 1.68 5.31 Benchmar k 10 10 10 10 10 10 10 10 10 10 10 Presence of Multicollinearit y FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Table 5: Sample description Year 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 Total Panel A - Sample distribution by year By merger proposal By merger proposal announcement date withdrawal date No of No of No of No of public targets private targets public targets private targets 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 12 2008 2008 10 2009 2009 2010 2010 2011 2011 2012 2012 55 Panel B - Sample distribution by other characteristics Intended method of payment No of No of public targets private targets Cash-out 13 Stock 34 Hybrid Total 55 13 Multiple bidders No of No of public targets private targets Yes 39 No 16 13 Total 55 13 Financial crisis No of No of public targets private targets Yes 36 No 19 Total 55 13 0 13 ... acquire a private target relays a favorable signal Consequently the termination of that merger may eliminate that favorable signal and result in the negative withdrawn abnormal return This contends... thesis, which is named A study on withdrawn merger proposals involving private target , contributes to literature by assessing the signal relayed by withdrawn mergers involving private targets By using... return has negative valuation effects on withdrawn mergers of private targets Announcement of a merger and the withdrawal of that merger are two opposite events, hence a withdrawal of a merger

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Mục lục

  • LIST OF ABBREVIATIONS

  • LIST OF FIGURES

  • LIST OF TABLES

  • Table 3.1: Statistical descriptions of variables using in models 22

  • Table 3.2: Correlation matrix for variables with event window (0, +1) 23

  • Table 3.3: Results of multicollinearity test for sample event window (0,+1) 25

  • Table 4.1: Mean cumulative abnormal returns of proposal announcements 29

  • Table 4.2: Mean cumulative abnormal returns of proposal withdrawals 30

  • Table 4.3: MHW test for withdrawn abnormal return with event window (0,+1) 31

  • Table 4.4: Non-parametric T-test for withdrawn abnormal return with event window (0,+1) 32

  • Table 4.5: Bidder’s valuation effects based upon target public status and 33

  • Table 4.6: Multivariate analysis result of model 1 35

  • Table 4.7: Multivariate analysis result of model 2 36

  • Table 4.8: Multivariate analysis result of model 3 37

  • Table 4.9: Multivariate analysis result of model 4 38

  • Table 4.10: Multivariate analysis result of model 5 39

  • ACKNOWLEDGEMENTS

  • CHAPTER 1: INTRODUCTION

    • 1.1. Background

    • 1.2. Research questions and research objectives

    • 1.3. Scope of the study

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