Detecting Information Pooling: Evidence from Earnings Forecasts after Brokerage Mergers by Serena Ng & Matthew Shum Discussed by David Becher FDIC Conference on Mergers and Acquisitions of Financial Institutions

November 2007FDIC Conference on M&A of Financial Institutions Research Question and Motivation  Do forecasts improve after brokerage mergers? Pooling of information and information resources may improve forecast accuracy Examine stocks where target & bidder analysts retained  Compare to those deals where only one analyst retained No information pooling exists Plus distinguish info. pooling from analyst selection  Does analyst selection improve forecast estimates?

November 2007FDIC Conference on M&A of Financial Institutions Contribution of Paper  Main Takeaway Interesting paper, asks important and unique questions in the literature Clear others think this is a good paper…  Matthew Shum’s Vita Detecting Information Pooling: Analysts' Forecasts After Brokerage Firm Mergers (with Serena Ng) Accepted, Advances in Economic Analysis and Policy

November 2007FDIC Conference on M&A of Financial Institutions What is Driving Results?  Authors examine four brokerage mergers 1994 to market conditions very different In all deals, majority of analyst from bidder (70% – 90%) Inconsistency in firm selection  Two deals involve foreign bidders (Switzerland)  Plus, one firm appears as both bidder and target Inconsistency in the merger form  One deal involves acquisition of assets (subsidiary)  Second deal, target is majority owned by another firm Action of analysts may not be independent

November 2007FDIC Conference on M&A of Financial Institutions What is Driving Results?  Different results “affected” vs. “non-affected” Compare bidder MSE pre- to post-merger  Significant improvement in 2/4 deals for all stocks  No improvement in any deals for affected stocks ALL STOCKSAFFECTED Merger Pre-MSE Post-MSEPost vs Pre Pre-MSE Post-MSEPost vs Pre A B *** C *** D **

November 2007FDIC Conference on M&A of Financial Institutions What is Driving Results?  Firm-level Can we draw conclusions based on 2/4 or 0/4?  Multivariate results also mixed Affected vs. both stay vs. both cover Sample sizes limiting – information pooling  Only 7% of cases both analysts stay  24/2,251 cases where both stay/cover same stock (1%) Yet estimate (stder) unusually large in merger C (4 out of 744) Is this information pooling?

November 2007FDIC Conference on M&A of Financial Institutions What is Driving Results?  Impact of non-merging brokerage firms Control for fact accuracy could be changing for all brokerage firms (unrelated to merger)  Binary variable if involved in merger plus binary variable if both analysts (target and bidder) stay after the merger Both are set to zero for non-merging firms (footnote 14)  Include merge, bothstay, and merge*bothstay Appears merge*bothstay is co-linear to bothstay & merge Perhaps look at more/other deals and other variables that contribute to accuracy and analyst quality?

November 2007FDIC Conference on M&A of Financial Institutions Sample of Brokerage Mergers  Examine SDC Pull all targets with SIC code of  621: Security Brokers, Dealers, And Flotation  622: Commodity Contracts Brokers And Dealers  623: Security And Commodity Exchanges Not 6311 (as noted in paper) - life insurance firms 2,911 potential deals

November 2007FDIC Conference on M&A of Financial Institutions Acquisitions of U.S. Brokerage Firms  All deals announced from 1980 – 2005; exclude: Acquisitions of certain assets (29), remaining interests (156), or majority interest (496) + Acquisition of assets (1,388)  532 involve acquisition of 100% of U.S. entity PW – KP deal: 100% acquisition of assets DLJ majority owned by AXA (insurance firm) No foreign targets (must be in 50 U.S. states or DC)  289 mergers/acquisitions acquisition of assets

November 2007FDIC Conference on M&A of Financial Institutions Summary Statistics of 289 Deals 37% of deals between 2 brokerage firms 56 of targets are public, 49 subs of another firm 176 of bidders are public, 47 are not in U.S. At least five other deals of similar size  Shearson-EF Hutton; CS-First Boston; Alex Brown- Bankers Trust; Salomon-Citi; JP Morgan-Chase… 20+ deals if include acquisition of assets  Robertson Stephens-BofA, Oppenheimer-CIBC, Herzog- Merrill; Greenwich-NatWest, Spears-Goldman…

November 2007FDIC Conference on M&A of Financial Institutions Other Factors  Future areas of study? Compare deals by broker vs. non-broker firms  Any improvements for non-brokerage bidders? Examine stocks with highest variation  Do brokerages have IB relation for these firms? Examine mergers post 2000 (Reg FD)  Is information sharing different afterwards What is impact of analyst recommendations?  Could information pooling exist here as well?

November 2007FDIC Conference on M&A of Financial Institutions In Summary  Overall, interesting paper Attempts to address the issue of information sharing  Results suggest information pooling occurs May be suspicious: small samples, issues with regressions  Disagreement between univariate and multiple regression approach  Frame paper as merged brokerage firms retain better employees  increased analyst accuracy post-merger Many additional questions can be asked as well