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Detecting Information Pooling: Evidence from Earnings Forecasts after Brokerage Mergers

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. Research Question and Motivation.

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Detecting Information Pooling: Evidence from Earnings Forecasts after Brokerage Mergers

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  1. 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

  2. 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? FDIC Conference on M&A of Financial Institutions

  3. 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 FDIC Conference on M&A of Financial Institutions

  4. What is Driving Results? • Authors examine four brokerage mergers • 1994 to 2000 - 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 FDIC Conference on M&A of Financial Institutions

  5. 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 FDIC Conference on M&A of Financial Institutions

  6. 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? FDIC Conference on M&A of Financial Institutions

  7. 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? FDIC Conference on M&A of Financial Institutions

  8. 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 FDIC Conference on M&A of Financial Institutions

  9. 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 + 532 acquisition of assets FDIC Conference on M&A of Financial Institutions

  10. 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… FDIC Conference on M&A of Financial Institutions

  11. 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? FDIC Conference on M&A of Financial Institutions

  12. 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 FDIC Conference on M&A of Financial Institutions

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