In support of transparent financial benchmarks

Darrell Duffie, Piotr Dworczak, Haoxiang Zhu

Trillions of dollars’ worth of transactions depend on financial benchmarks such as LIBOR, but recent scandals have called their reliability into question. This column argues that reliable benchmarks reduce informational asymmetries between customers and dealers, thereby increasing the volume of socially beneficial trades. Indeed, the increase in trading volume may offset the reduction in profit margins, giving dealers who can coordinate an incentive to introduce benchmarks. The authors argue that benchmarks deserve strong and well-coordinated support by regulators around the world.

Benchmarks are heavily wired into modern financial markets. For example, trillions of dollars in bank loans and several hundred trillion dollars (notional) of derivatives transactions depend on daily announcements of LIBOR. The WM/Reuters foreign exchange fixings dominate the currency markets, in which there are over $5 trillion of transactions per day. Benchmarks are the basis for trade of a wide range of commodities such as gold, silver, oil, and natural gas. They have also been the focus of scandals (Brousseau et al. 2013).

Almost weekly revelations of corrupt manipulation of these benchmarks call into question the continued reliance on them by market participants. What would happen if the financial industry and regulators were to find themselves unable to support reliable benchmarks?

Without a benchmark, it is impossible to contract in advance for the formulaic cash settlement of asset trades. (Physical delivery of an asset is usually much more costly.) Without benchmarks, moreover, investors would have difficulty monitoring the execution quality of trades conducted on their behalf by dealers or brokers, through a comparison between the benchmark price and the price actually paid or received.

In recent research (Duffie et al. 2014), we show that benchmarks also provide valuable pre-trade price transparency in over-the-counter (OTC) markets. For many types of financial instruments and commodities, benchmarks offer less informed market participants a much better idea of the ‘going price’. By reducing the informational disadvantage of ‘buy-side’ market participants relative to dealers, benchmarks encourage greater market participation, lower the cost of delays associated with ‘shopping around’ for a better price, and improve the ability of OTC markets to efficiently match buyers with the most cost-effective sellers, and vice versa.

Consider, for example, a world without LIBOR, and a firm that is anxious to quickly obtain $100 million in six-month financing. The firm’s CFO is only vaguely aware of the best available interest rates. The CFO contacts Bank A, which, after some discussion, offers the loan at an interest rate of 3.7%. Unsure of how much profit margin is built into the quote from Bank A, the CFO discusses terms with Bank B, which eventually offers to lend at 3.8%. The loan discussions are already costing precious time for the CFO and his firm. Rather than contacting additional banks in search of a lower rate, the CFO simply takes the rate offered by Bank A. The opaqueness of this market reduces competition among banks, even to the point in some cases of raising average lending rates enough to discourage the CFO from entering the market.

Now consider a parallel world with a benchmark six-month LIBOR rate. Suppose LIBOR is fixed at 3.25%, publicly revealing the average cost of funds to major banks. When contacted by the CFO, Bank A knows that the CFO can get a reasonable estimate of the bank’s profit margin by comparing the quoted rate to LIBOR. Bank A thus offers a lower rate of LIBOR plus 0.25%, or 3.5%. Although the CFO could contact other banks and perhaps get a slightly lower rate, the scope for improved terms is relatively small relative to the cost of delay. The quote from Bank A is quickly accepted.

This example illustrates three types of social gains offered by reliable benchmarks:

A benchmark reduces information asymmetry between customers and dealers. With a published benchmark, customers have a better idea of the relative competitiveness of dealer quotes. Costly search is correspondingly reduced. Equipped with benchmarks, customers have better information about the ‘going price’. As a result, when they trade, they do so more frequently with those dealers quoting better prices. Matching efficiency is correspondingly improved. In a market without a benchmark, dealers’ prices are less competitive, causing some potential ‘buy-side’ market participants to simply fail to attempt certain trades. Adding a benchmark can increase the volume of socially beneficial trades.

Who introduces benchmarks? Perhaps surprisingly, dealers often do

It might superficially seem that dealers have little incentive to introduce a benchmark. By revealing the going price, dealers lose some of the advantage of their superior information over buy-side firms. As a result, benchmarks force dealers to compete more aggressively, narrowing their profit margins on each trade. In many cases, however, what is lost in reduced margins is more than offset by increased trading volumes. With a benchmark, it is easier for customers to find good quotes and they are more eager to participate in the market. With the ability to coordinate, dealers may therefore collectively commit to publish a benchmark. Which markets have a benchmark and which don’t is not a matter of accident. Dealers introduce benchmarks when and where this is profitable.

Moreover, dealers that are inherently more cost effective, and can therefore offer better quotes, have an additional incentive to introduce a benchmark. For example, if a specific group of banks is generally able to obtain funding at a lower interest rate, this group can use a benchmark rate as a ‘transparency weapon’ that draws business away from other banks. It is probably not a coincidence that LIBOR was started in London by a ‘benchmark club’ of major global banks.

When dealers would not profit by introducing an OTC market benchmark, this may sometimes be left up to governments or central banks. For example, the Euro OverNight Index Average (EONIA) is produced by the ECB. In 2002, FINRA introduced TRACE, a form of post-trade price transparency that has arguably brought lower transaction costs to the corporate bond market (e.g. Bessembinder et al. 2006, Edwards et al. 2007, and Goldstein et al. 2007), although there is a lack of unanimity on the effect of TRACE on overall liquidity (Asquith et al. 2013). Commercial information services also establish benchmarks (such as the Kelley Blue Book average sale prices of automobiles.)

If benchmarks are manipulated, some of the transparency benefits will be lost. Coulter and Shapiro (2014) and Duffie and Dworczak (2014) have proposed new benchmark fixing methods that are less susceptible to manipulation.

Implications for the supervision of benchmarks

Policymakers in various jurisdictions have not yet reached agreement on the best approach to benchmarks. The UK and Japan have recently set up regulations in support of regulatory frameworks for financial benchmarks. The UK also plans to extend its framework to a wider set of benchmarks (Bank of England 2014). The European Commission has proposed an EU law enabling regulation of “critical” benchmarks. The US, however, “does not plan to adopt direct supervision of benchmarks”, according to Randall De Valk, a US Treasury official. De Valk further described the European Commission’s draft legislation as “prescriptive” and going beyond new globally agreed supervisory principles applied by the US, according to a letter by De Valk recently cited by Reuters (Jones 2015).

For the reasons that we have outlined, financial benchmarks aid market efficiency in a variety of important ways, and deserve strong and well-coordinated support by regulators across the globe.

References

Asquith, P, T R Covert, and P Pathak (2013), “The Effects of Mandatory Transparency in Financial Market Design: Evidence from the Corporate Bond Market”, Working paper.

Bank of England (2014), “Recommendations on Additional Financial Benchmarks to be Brought into UK Regulatory Scope”, Fair and Effective Markets Review, Report to Her Majesty’s Treasury, August.

Bessembinder, H, W Maxwellb, and K Venkataramanc (2006), “Market transparency, liquidity externalities, and institutional trading costs in corporate bonds”, Journal of Financial Economics 82(2): 251–288.

Brousseau, V, A Chailloux, and A Durré (2013), “The LIBOR scandal: What’s next? A possible way forward”, VoxEU.org, 9 December.

Coulter, B and J D Shapiro (2014 ) , “A Mechanism for LIBOR”, Working paper.

Duffie, D and P Dworczak (2014), “Robust financial market benchmarks”, VoxEU.org, 1 November.

Duffie, D, P Dworczak, and H Zhu (2014), “Benchmarks in Search Markets”, Stanford University Graduate School of Business Research Paper 14-47.

Edwards, A K, L E Harris, and M S Piwowar (2007), “Corporate Bond Market Transaction Costs and Transparency”, Journal of Finance 62(3): 1421–1451.

Goldstein, M A, E S Hotchkiss, and E R Sirri (2007), “Transparency and Liquidity: A Controlled Experiment on Corporate Bonds”, Review of Financial Studies 20(2): 235–273.

Jones, H (2015), “EU Lawmakers Eye Compromise for U.S. on Benchmarks”, Reuters, 8 January.