FindingNov 02, 2022

Know Your Customer: Informed Trading by Banks

Christian Leuz, Rainer Haselmann, Sebastian Schreiber
Banks’ lending relationships inform their trading and underscore the potential for conflicts of interest in universal banking, despite regulatory attempts to limit such exposure.

In response to the financial crisis that fueled the US Great Depression, Congress passed the Glass-Steagall Act in 1933 to separate commercial and investment banking. The goal was to prevent risky investments from threatening a bank’s—and thus the entire banking system’s—viability. Almost since its inception, efforts were made to roll back Glass-Steagall, finally succeeding in 1999 with the passage of the Gramm-Leach-Bliley Act (GLBA), which eliminated restrictions on the affiliations of commercial and investment banks (while also adding safeguards to address stability concerns). For some observers, GLBA was the tinder that ignited the financial crisis and Great Recession of 2007-2009.

As if on cue, Congress responded to this latest financial disaster by passing the Volcker Rule in 2013—advocated by the legendary former Federal Reserve Chairman, Paul Volcker—which harkens back to Glass-Steagall and bans proprietary trading by US banks. Europe discussed similar bans but took a different path by requiring universal banks (or those that provide a wide variety of services, from traditional banking to investing) to have organizational structures (e.g., ethical walls) that mitigate conflicts of interest arising from combining investment and corporate banking under one roof.

However, how effective are such organizational structures? Do those ethical walls actually prevent information and incentives from getting to the other side? Data limitations make these and related questions difficult to answer and have limited many researchers’ analyses. The authors of this paper, though, employ data that allow them to investigate proprietary trading by universal banks, which in turn allows them to assess the effectiveness of organizational structures with respect to information flows from the lending to the trading desk and the associated conflicts of interest.

Please see the working paper for a detailed description of the authors’ methodology, but in brief the authors focus on bank trading ahead of material corporate events that release new information to the market. The lending side of banks could obtain such information prior its release. For example, corporate debt contracts include clauses that require borrowers to inform their lenders, on a regular basis, about material changes to the business. Does this potentially private information from the borrowers make it to banks’ trading desks? Since these information flows cannot be directly observed, it is difficult to know. 

To examine this question, the authors combine several large micro-level data sets provided by German supervisory agencies as well as a comprehensive database for corporate events for German firms. The trading data include all individual trades by all financial institutions with a German banking license that are executed on any domestic or foreign exchange or in the OTC markets. In what is likely the first such analysis, the authors analyze around 168 million trades (with a volume of €3.5tn) around 39,994 corporate events to find the following:

  • Relationship banks (a firm’s largest lender or a lender that accounts for at least 25% of the firm’s loans) purchase more shares than non-relationship banks in the weeks prior to events with positive news (i.e., positive market-adjusted returns). Further, the authors find negative net positions for relationship banks ahead of events with negative returns, although the results are weaker. 
  • Strikingly, relationship banks build significant net positions prior to unscheduled positive and negative events, which are harder to anticipate and for which it should be harder to build positions in the “right” direction.
  • Relationship trading contributes 14% of banks’ total event-trading profits, even though relationship bank-event combinations account for only 1% of all bank-event combinations.
  • For all banks, successfully trading around corporate events is only marginally better than chance. However, for relationship banks, the probability of successfully trading increases by 6.2pp for unscheduled events with absolute abnormal returns above 2%, and further increases to 8.3pp when the authors restrict the analysis to banks with net positions above 0.5bp of the underlying stock’s market capitalization.

The authors also conduct a series of tests and analyses to shed light on the mechanism for these findings, to rule out bank specialization as an explanation for their results, and to study banks’ trading strategies when executing informed trades. Very broadly, their results find that:

  • Banks have profitable positions around corporate events only when they concurrently have lending relationships.
  • The informed trading results are stronger when information flows from the borrower to the bank are more likely, such as when granting new loans or before M&A transactions.
  • Relationship banks also trade profitably in other firms when they have joint information events with their clients. The probability of successfully trading around such joint events increases by roughly 20pp.
  • Exploring the role of banks’ risk management function, the authors analyze whether relationship banks are more likely to unwind an existing short (long) position before unscheduled positive (negative) news events. In these situations, the risk management could adjust the limits and thereby passively transmit information.
  • Relationship banks shroud their trades to fly below the radar of the supervisor.
  • Finally, relationship banks obtain worse prices for borrower stocks in the OTC market, where the identities of the trading parties are known, suggesting that other market participants are aware of relationship banks’ information advantages. 

Bottom line: Policymakers and regulators should take note. These findings not only underscore potential conflicts of interest in universal banking, but also question the extent to which banks’ organizational structures are effective in preventing information flows from the lending side to the trading desks. Based on the results, it seems that the ethical walls are porous, at least in an economic sense. Importantly, however, the information flows do not have to be direct, but could also occur indirectly via organizational structures that collect information centrally. Thus, in a twist that should give regulators pause, the findings point towards organizational structures that were strengthened since the Great Recession.