An Analysis Of A Mergers Profitability

An Analysis Of A Mergers ProfitabilityAbstractIntroductionIn the last few geezerhood we feel observed a revived surge in the number of mergers. They are much frequently observed in countries with better depicting standards. Companies undergo mergers for a number of reasons. The primary reason is the decent anyocation of resources and thus, increasing cost efficiency. A sm each(prenominal) amount of explore has been done in the retiring(a) years analyzing the short and long term exploits of mergers in creating appreciate for the companies. It has been seen that some mergers result in failures but not much research has been done in analyzing the reasons behind it. My research would be establish on few of the biggest mergers that have taken place in the last few years. Firstly, my synopsis of a mergers profitability would be based on standard event study mannerology. It would take into account the offspring to shareholders. Secondly, it would also aim to provide evidence regarding the signalling theory and the synergistic and the agency views. This would be based on an in-depth outline of various determinants such as the excess returns roughly the announcement of the merger bid and most the termination of the merger and the signifi peckt differences in the responses of watertights acting centre versus diversifying mergers respectively. Lastly, this would be followed by a thorough compendium of the valuation effects of mergers. There have been varied views but no one conclusion has been reached. I would thus, like to investigate deeper into it2. Literature Review and HypothesesAnalysis revealedMy research concentrates on the effects of a cerebrate and diversifying merger on the supernormal returns around the announcement achievement of the merger. The study by Delong (1999) can be seen as an extension to my research. He based his research on evaluating the occupation pricing behaviour of the bidder and the steer in bank mergers. He move on studied the affected returns according to the nature of the merger i.e. focusing or diversifying. In my analysis, I take into account only activity focused mergers, whereas Delong (1999) considers mergers which focus on both activity and geography. His results show an enhancement in value of a focusing firm of slightly 2 % to 3 % as compared to a diversifying firm irrespective of the time period. On investigating further, he found that the congenator foodstuff size of the tush to the bidder and the pre-merger performance of the targets show an apparent relationship with the cumulative abnormal returns so placed.Wong and Cheung (2009) analyse the changes in the stock prices of the bidding and target firms in Hong Kong, China, Taiwan, Singapore, South Korea and Japan, adjacent a merger or an acquisition announcement. It can be seen from their analysis that such an announcement yields optimistic results for the bidding firms but does not prove to be very beneficial for the t arget firms. Their hypotheses considered the consequences of the mode of payment, the typewrite of acquisition and the type of the target firm on the stock pricing. Out of them only the second multivariate seems to have a direct effect on the post announcement returns of the bidding firm.Huang and Walkling (1987) conducted mistakable research by extracting a judge of acquisitions from the Wall Street Journal which consisted of all initial front-page acquisition announcements. only if this, took into account slightly different variables as compared to the other analyses discussed above. They determined the effect of tender tenders vs. mergers cash offers vs stock offers and resisted offers vs. unresisted offers. Their analysis revealed high abnormal returns for tender offers which were quite insignificant once the effect of the extent of granting immunity and the payment type were isolated from it. The deals which faced resistance during a merger or tender offer showed higher abnormal returns irrespective to the mode of payment. only the results obtained above were either insignificant or meteally significant, but the effects of the third variable i.e. the form of payment showed some concrete results. The cumulative abnormal returns obtained from cash offers were radically higher than those obtained from stock offer. This research carried out by Huang and Walkling gave quite a holistic overview of the effect of the announcement of an acquisition, as it took into consideration, variables which are affected by both the bidding and target firms decisions.All the literature discussed earlier in this paper, has illustrated some positive effects of an acquisition for both the bidders and the target firms. But, the analysis conducted by Bruner (2001) showed a little variation to the above. It suggested that only the target shareholders draw upon the benefits of the acquisition. No such fat return is observed for the bidding firms. But, the combined returns of the bidder and the target yield positive results.The greet followed by Bruner differs importantly from most of the research discussed earlier. He measures the performance of a merger and acquisition based on the investors indispensable returns.After observing the abnormal returns of the acquirer around the announcement date of the merger as per my research, the most obvious next step would be to analyse the long term effects of the merger. Various studies have been done in order to rightfully determine the outcome .The study by Asquith (1983) showed drastic forbid returns after about three years of the merger. One of the best analyses that I found was by Agrawal, Jaffe and Mandelkar (1992) in their paper The Post-Merger Performance of Acquiring Firms A Re-examination of an Anomaly. Their results are based on a thorough analysis of a number of mergers that took place from 1955 to 1987. They explored the effect of the size of the firm and its beta risk, and found a neediness o f 10 % in the total wealth of the acquiring firm, five years after the merger was completed. An attempt was also made to disclose the additional NPV which is not captured by the announcement returns analysis. But, it was seen that the modification of the market was similar for both the announcement and post merger analyses.Cole et al (2006)Investigate a number of self-defeating mergers in order to determine if they create or destroy value for acquirers by using in general two approaches. Their signalling approaches show that the value of the bidding firm is reduced by a large margin in the market, which is a form of a punishment for considering the acquisition of a low NPV project. They also find that horizontal mergers yield negative CAR.Hypothesis 1 The average abnormal returns (AAR) yield positive results for all sub-periods in the eventHypothesis 2 The Cumulative average abnormal returns (CAAR) yield positive results for all sub-periods in the event.Hypothesis 3 The type of a cquisition, broad of acquisition, the mode of payment and the type of target firms affects the value of the cumulative abnormal returns (CAR) around the announcement twenty-four hours t=0 in the event.Take into account focusing and diversifying3. MethodologyWe begin by classifying the effective sample into two categories Focusing and Diversifying. The classification approach has been adopted by Mann and Sicherman (1991).This can be done by comparing the two-digit fix Codes of the acquirer and the target firm respectively. If both the firms involved in a deal have the same two-digit SIC Code, it can be classified as a focusing acquisition, whereas, if both firms have different codes, it is classified as a diversifying acquisition.Now we progress towards analysing the cumulative value created by a focusing and diversifying acquisition around the announcement date, using a standard event-study methodology described by MacKinlay (1997), Huang and Walkling (1987) and Wong and Cheung (2009). The Market Return poser is used in this case, to compute the abnormal returns of the sample using a linear relationship amid stock returns and market return.Rit = i + iRmt + it (1)E (it = 0) var (it) = t2WhereRit Return on security i on day tRmt Return on market portfolio on day tit Zero hateful disturbance termi, expected value of the difference between Ri and iRmti co variability between Rit and Rmt divided by the variance of Rmtt2 variance of the error termWe use the market model instead of the constant incriminate return model as it gives us a more accurate judgement of the effect of the event. This is dependable as it does not take into account the variation of the market return , thus, giving us more accurate abnormal returns.( if any words remain add how to project rit and rmt)In order to calculate the abnormal returns, we use the market model parameter estimates. ARit = Rit (i + iRmt) (2)WhereARit the abnormal return for security i on day t i and i es timates of i and iIn order to calculate the abnormal returns we use a maximum of 351 daily observations (Huang and Walkling, 1987). We start collecting data from t -300 to t +50 days, with t = 0 being the announcement date of the acquisition. These 351 days include non- commerce days as well. In other words, we actually gather data from t -214 to t +36, taking only trading days into account. We use different time periods of an event for a complete comparative analysis of abnormal returns in each sub period which is described as belowEvent period day t -10 day t +30 (41 days)Pre-announcement period day t -10 day t -2 ( 9 days) declaration period day t -1 day t 0 ( 2 days)Post Announcement Period day t +1 day t +30 (30 days)diagramTo analyse the effect of the event , we like a shot calculate the average abnormal return (AAR) for all the securities for a time period t. AAR is the sum of all abnormal returns of firms on day t divided by N( the number of firms)(3)The t statistic , , is calculated by dividing AARt by the standard remainder of the average abnormal returns. This is final step of the model, which helps in determining the significance of the AARt in the event period.(4)While calculating the standard error, an estimator is used to calculate the variance of the abnormal returns in the absence of but in this case we use the sample variance measure of that we derive from the market model regression. The estimator is as followsIn order to establish a more holistic viewpoint, the cumulative average abnormal returns (CAAR) are calculatedWhere T1 to T2 is the duration of the event in which the AARt is collected.According to our hypotheses we have to calculate one more variable, the cumulative average abnormal return (CAAR) over a certain period. In order to find out the significance of CAAR we calculate its t statistic as followsWhere var(CAAR) is the variance of the cumulative average abnormal returns.We could use a variety of formulas to calculate th e standard deviation and t statistic such as those described in Campbell, Lo and MacKinlay (1997) and Brown and Warner (1985). But we calculate using the method adopted by Kothari and Warner (1985)Where Variance of the average abnormal return for one period.L Longer the L, the higher is the variance of CAARTo test the third hypothesis, another variable is taken into consideration the Cumulative abnormal returns (CAR). We now develop a regression model using dummy variables to test the effect of the type of acquisition, kind of acquisition, the type of the target firm and the mode of payment on the CAR of the acquirers. The control variables are the relative market size of the market value of the target to acquirer (RMV) and the market size of the acquiring firm (M) (Wong and Cheung, 2009).Where Cumulative abnormal return from day d1 day d2D1 1 if the type is acquisitionD1 0 otherwise i.e. mergerD2 1 if it is focusingD2 0 otherwise i.e. diversifyingD3 1 if target firm is pri vateD3 0 otherwise i.e. publicD4 1 if mode of payment is cashD4 0 otherwise i.e. stockM Market Value of the acquiring firm=Number of outstanding share *closing price on the announcement dateThe tests of hypotheses 1, 2 and 3 can be described as the following testsH1 H0 AARt = 0H1 AARt 0H2 H0 CAARt = 0H1 CAARt 0H3 H3i 1 = 0 (Acquisitions vs. Mergers)H3ii 2 = 0 (Focusing vs. Diversifying)H3iii 3 = 0 (Public vs. underground target firms)H3iv 4 = 0 (Cash offer vs. Share offer)4. Data DescriptionThe number of mergers and acquisitions carried out in India has been quite extensive. Hence, certain criterion has been used to select a suitable sample.The deals carried out with Morgan Stanley, JP Morgan, Goldman Sachs, UBS, Deustche Bank and Citi as their financial advisors should be included. These banks have been chosen as they deal with high valued mergers which are holy for highlighting the true effects of a focusing or diversifying merger.All deals should have been completed from January, 2003 to March, 2010. The sample consists of only 178 completed transactions.All the acquirer firms must be publicly listed in the Bombay Stock Exchange.The SIC Codes for the target and acquirer should be available in the CRSP Database. This helps in dividing the sample into focusing and diversifying mergers.Because of these restrictions, the sample reduces to 70 firms, three of which have some data missing regarding the stock returns etc and hence our effective sample is 67. It has been further classified into 44 focusing and 23 diversifying deals.Using only publicly listed firms enables us to extract information about these deals such as announcement dates, termination dates, stock returns, market returns etc. from the Thomson One database, alliance websites and the Bombay Stock Exchange.The Bombay Stock Exchange Sensitivity Index or the BSE Sensex (30) has been used to gather the market returns of the firms.