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Tanya’s EEM Placement
           July – Dec 2012
                   @
           Deutsche Bank
  Tech, Media & Telecoms M&A team
Contents

1.   What I sought in a placement
2.   What my role involved
3.   What I investigated for my thesis
4.   What I found
5.   What the difficulties were
6.   Why it was a valuable experience
Search
Role

         Deal origination & deal execution

                     Deal team



  Analyst  Associate  VP  Director  MD


                 -Valuation modelling
                 -Company research
                 -Market research
                 -Creating pitchbooks
                 -Finding /processing data
Project


      Strategic
      analysis




      Econometric
      analysis
Findings
                 What factors can explain short-term value created by telecoms M&A?

                                        Dependent variables (abnormal returns in various time windows)
                                                      [#days wrt deal announcement at t=0]

                                                                                                               Total support

Independent variables            [-30,30]     [-20,20]    [-15,15]       [-10,10]      [-7,7]     [-3,3]       score
                                    1                                                                                  1
Service-line relatedness
                                    1                                                    -2                            -1
Deal geography
                                                 2            2              2            2                            8
Deal size/Acquirer EV (%)
                                    -1           -1           -1                                                       -3
Bidder toehold
                                    -1           -2           -2             -2                     -1                 -8
Financing consideration
                                                                                                                       0
Financial advisor
                                                                                                                       0
Public target
                                    -1           -2           -2             -2                                        -7
Private target
                                    -2                                                                                 -2
Govt.-owned target
                                                                                                                       0
JV target
                                                                           Scoring key
                                             2           Strongly significant and +ve regression coefficient
                                             1           Weakly significant and +ve regression coefficient
                                            -1           Weakly significant and -ve regression coefficient
                                            -2           Strongly significant and -ve regression coefficient
Challenge
Value
?
sen.tanya@gmail.com
?
sen.tanya@gmail.com

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Tanya’s EEM Placement

  • 1. Tanya’s EEM Placement July – Dec 2012 @ Deutsche Bank Tech, Media & Telecoms M&A team
  • 2. Contents 1. What I sought in a placement 2. What my role involved 3. What I investigated for my thesis 4. What I found 5. What the difficulties were 6. Why it was a valuable experience
  • 4. Role Deal origination & deal execution Deal team Analyst  Associate  VP  Director  MD -Valuation modelling -Company research -Market research -Creating pitchbooks -Finding /processing data
  • 5. Project Strategic analysis Econometric analysis
  • 6. Findings What factors can explain short-term value created by telecoms M&A? Dependent variables (abnormal returns in various time windows) [#days wrt deal announcement at t=0] Total support Independent variables [-30,30] [-20,20] [-15,15] [-10,10] [-7,7] [-3,3] score 1 1 Service-line relatedness 1 -2 -1 Deal geography 2 2 2 2 8 Deal size/Acquirer EV (%) -1 -1 -1 -3 Bidder toehold -1 -2 -2 -2 -1 -8 Financing consideration 0 Financial advisor 0 Public target -1 -2 -2 -2 -7 Private target -2 -2 Govt.-owned target 0 JV target Scoring key 2 Strongly significant and +ve regression coefficient 1 Weakly significant and +ve regression coefficient -1 Weakly significant and -ve regression coefficient -2 Strongly significant and -ve regression coefficient

Hinweis der Redaktion

  1. I am going to talk about How I chose a placement What I did – at work and how this fit in with org What I wrote- for thesis – and my findings And then I will reflect on What the difficulties were What I gained from it and what the org gained from it Caveat: the nature of our course means that each one of us had a totally different experience – so many variables along which it can differ (subject, work culture, industry, function) – I ’ m going to give you my story – one data point and not a generalisation
  2. When I was thinking about how to pick a place to go – universe of choice is quite wide I decided to pick a placement which would be Interesting – either in terms of function or industry (I was in Tech, Media, Telecoms – an industry I find interesting and diverse- get a birds eye view on lots of different companies in different sectors) Relevance to life plans- wanted to test out this industry and see if it was for me Support available/resources- wanted to work for a big company – worked at pretty much the headquarters of DB ’ s IBD. For this placement in particular- important to me to get training, a lot of people whose experience I can draw upon, and resources in the form of subscriptions to analyst reports, data etc... Years of deal experience etc And of course actually have to get approval from the company and projects office and all
  3. Corporate Finance team – Tech, Media & Telecoms What do they do: Advisory work on M&A for large clients in Tech, Media and Telecoms in EMEA region Pitching  identify deal opportunities, scope out strategic synergies between acquirer/target – M&A, IPO etc – get a client to enlist you as their financial advisor to sell their business, or to buy another business, or to take their company public etc Execution  once you actually get the deal – you see it through. So for example if the deal is a sell side mandate- i.e. You are selling assets on behalf of your client – you need to write an info memorandum, you need to find buyers, pitch the deal to them, pit them against each other, negotiate so you get the best possible price ... To give you an idea – most of the work is pitching and less is execution – even once on execution, the chance of it actually ending up as a sale is quite low particularly in this climate. Execution deals – success fee What does the day to day role involve? Analyst  Associate  VP  Director  MD You work with a deal team – I was the analyst – so you do the ground work Valuation modelling – model the value of the company Creating pitchbooks – which is designed by more senior people on the team Doing research on the companies Finding and processing data
  4. My project: Strategic M&A in Europeans telecoms – finding the drivers of merger success Literature review/industry trade reports- very different – to get a picture of the telecoms industry, what are the business models that work, why acquisitions are common in telecoms. It turns out that telecoms is an acquisition-heavy industry because organic growth is difficult, costly, time consuming – its essentially an infrastructure/utility business- laying out cables/mobile networks etc is no easy feat. So it ’ s easier to acquire companies and there are high acquisition volumes. Also because I was focusing on Western European acquirers – the big firms like Vodafone, Deutsche Telekom, France Telecom etc- I did some research on the state of play in the markets at the moment – found that the domestic state of markets is pretty negative- most analysts are predicting there will never be any more growth in WE telecoms. So I hypothesised that those WE acquirers that make acquisitions abroad are more likely to generate more ‘ valuable ’ deals. Also that acquirers which diversify – start to go into industries other than their core service lines – can create more value. Also a number of other factors – such as the size of the deal etc influence value –will talk about these more later What does a ‘ value generating deal ’ mean? Used an event study – classic in financial econometrics – you look at share price returns for an acquirer before and after they did a deal. You do a regression against the market index to find out what you think the ‘ normal ’ share price returns should be (had the deal not happened) – and compare this with the actual returns that were observed – the difference is ‘ abnormal returns ’ – proxy for value created After this did I multivariate regression analysis – regressed the ‘ abnormal returns ’ against all the factors I had identified in my hypotheses. Data- 140 telecoms large deals (over 100 million euro) – WE telecoms acquirer etc
  5. Found support for size of deal – larger deals likely to receive more market attention Deals financed by cash alone were value destroying Risk sharing hypothesis – advantageous to pay in stock so that target has incentive to make transaction successful Deals involving privately owned targets were value destroying – because of information asymmetry Larger deals created value – these predicted to have more synergies- or simply that they get the attention of the market Implications for investment banking Identifying deal opportunitie s Structuring deals Media management Role of investment banks This thesis investigated a dataset of 140 majority acquisition deals by Western European telecommunications firms over the period 2001-2012. Using an event study methodology and statistical multivariate regression analysis, I find that deal size, target ownership, and financing method are strong predictors of the shareholder value created as a result of the deal announcement. The geography and service-line relatedness of the target with respect to the acquirer have no influence, suggesting that globalisation has reduced the differences between these types of deals in the eyes of the market. Surprisingly, bidder toehold and the reputation of the acquirer ’s financial advisor do not affect value creation.
  6. What was difficult about it ? Finding the balance – Talking to people – being open when you think it ’ s too much You have to write the thesis – on the other hand there ’ s a lot of pressure to work as a ‘ normal intern ’ and do the day to day support work for analyst. Working on thesis – would just write that off and give more work – bec not everyone knows about it Job hunt – have to figure out if this is for you, if not, a lot of other firms are recruiting in that time window so have to apply Time... Cluelessness- you know nothing about the subject, barely know what work culture is like...for me...finance was new to me, regressinos were new to me, and there was no immediate help at hand in doing the stats heavy stuff. How I would have done that differently – made more effort to search for advice from a Finance prof. Intersting doing the Finance class now to compare.
  7. When I say value I mean it goes both ways The project adds value to you and you add value to the project by appreciating that it needs to amalgamate two perspectives, the industry perspective and the academic perspective- and find an optimal balance For me... What did I get from my experience as an analyst in banking? Much more efficient, quick way to navigate through teh content – telecoms --- you learn rules of thumb/familiarity with companies/work with people who have worked witht hese comapneis for years and years and know them like the back of their hand. They know these companies so well it ’ s like intuition – which is why I call it a reality check Also in terms of skills- learned modelling/financial modelling/power of what excel can do – much faster – wouldnt have been able to build the model otherwise – would have probably overcomplicated it by trying to model it in matlab. Technical skills – implementation – which added a lot of value to me You get so many resources – datastream, factset, bloomberg etc... People as well – talked to people all over the organisation not just from my team. They are all pro networking anyway, and I found it interesting- my thesis almost became an excuse to talk to people who different things What did the academic perspective bring to my time in banking? The fact that I had to do an academic project while I was there –meant I needed to get a big picture view which an analyst intern would otherwise have found very very difficult to get. Need to zoom out of the excel cell and look at the whole industry in order to write my report – couldnt have done that as a ‘ normal intern ’ – just no time to You question the assumptions and read the theory and try to solve things in a rigorous way without skipping steps. Whereas in industry they will use the rule of thumb and you get used to mechanically applying it without stopping to understand why So the thesis made me appreciate my time in finance a lot more than I would have had otherwise In conclusion – Have shared with you some of the positives and negatives of my time in banking and writing the thesis. It was hard work and frustrating sometimes, but in the end think I got a unique experience so I ’ m glad i did it.