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The Perverse Effects of Investment Bank Rankings: Evidence from M&A League Tables

Explore how league tables impact bank behavior in M&A deals, including fairness opinions, fees, and rankings management.

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The Perverse Effects of Investment Bank Rankings: Evidence from M&A League Tables

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  1. The Perverse Effects of Investment Bank Rankings:Evidence from M&A League Tables François Derrien, HEC Paris Olivier Dessaint, HEC Paris November 8, 2012 Corporate Governance of Financial Institutions Conference

  2. What is a League Table?

  3. Questions • Do league tables matter? • Do banks respond to incentives created by league table rankings? • With what consequences?

  4. Some Evidence that League Tables Matter Weekly frequency of reporting to Thomson by banks (« Date advisor added » item in SDC) 4

  5. Data and League Table Construction • M&A data from SDC • Bank data: All banksthatappearat least once in the LT since 2000 and do at least two deals in the year 101 banks • Deal data: All deals in which the banks above are involved  38,839 deal-bank observations • Wereconstructhistorical M&A league tables since 1999 • We use the samecriteria as Thomson • LT credit = sum of « rank value » (deal value + target’s net debt if acquirergoesfrom <50% to 100% of ownership) • Includes all pending and completed deals (not rumored or withdrawn deals) • Most advisoryrolesget full credit for the deal

  6. League Table Management Hypothesis • Trade-off between current and future fees • Banks are willing to give up on current fees and focus on activities that will increase their league table ranking, and their future fees • League table management tools • Fairness opinions • Assessment of the fairness of a deal price • Low effort / low fees • Same league table credit as regular advisory work • Free-riding on existing mandates • Low effort / low fees • Late co-advisors are likely to be free-riders • Low fees

  7. League Table Management Hypothesis • When do banks engage in league table management? • When they lost ranks recently • We use the Deviation variable • Deviation = Number of LT ranks gained by the bank since the end of previous year • At the deal level, when a deal has more impact on the bank’s rank • We use the LT_contribution variable, which measures the deal credit relative to gap with closest competitors

  8. Do LT Rankings Affect MarketShare? • Dependent variable: quarterlymarketshare • One-rankincrease 0.3% marketshareincrease (i.e., 6% of the within-bank std. dev. of this variable) 8

  9. Banks’ Response • League table management hypothesis • Banks should • do more fairness opinions • do more lateco-mandates • lowertheirfees • When • they have lostranks in recent league tables • the relative impact of the deal on theirrankingis large 9

  10. Determinants of Fairness Opinions • Deal-level tests • Dependent variable • 1 if the bank does a FO in a co-mandate context • 0 if the bank does a FO in a sole-mandate context (no suspicion of league table management) • Weinclude standard control variables 10

  11. Determinants of Late Co-Mandates • Deal-level tests • Dependent variable • 1 if the bank reports itsrolelate • 0 if the bank reports itsroleearly (first bank to report) • Weinclude standard control variables 11

  12. Determinants of Fees • One std. dev. decrease in Deviation drop of 5bp in fees(about $250k for average deal) 12

  13. Consequences of LT Management • For banks • Is league table management effective? • One within-bank std. dev. increase in thesetwo variables  gain of 0.5 ranks 13

  14. Consequences of LT Management • For M&A clients • In fairness opinions, higherLT_contributionassociatedwith • Lowerprobability of deal completion • Highervaluation range of the FO • Lowercombined CAR (-1,+1) around deal announcement 14

  15. Conclusion • League tables affect banks’ behavior • Banks are more likely to do FOs, co-mandates, and to cuttheirfeeswhentheirincentives to manage their position in the ranking are higher (i.e., whentheylostranks in recent league tables, or when the relative impact of the deal on their LT position isbigger) • Someevidencethat league table management hurts the banks’ clients • Questions • Why are clients naive about the banks’ incentives to manage league tables? • How couldweimprove the criteriaused to construct league tables? 15

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