Max Bowie: Give a Little and You Get a Little

In the run-up to the US election, political contributions—plus the motives of wealthy donors—will no doubt come under scrutiny from wonks and voters alike. In the market data industry, contributions are also a hot issue: Like the so-called ask-the-audience “lifeline” from the TV game show Who Wants to be a Millionaire?, firms are realizing that the wider the audience being asked, the more likely they are to get an accurate result.

For example, the Chicago Board Options Exchange’s (CBOE’s) new options valuation service will collect prices from at least three market-makers for its Flex options products and other over-the-counter (OTC) options, primarily to increase mutual fund participation in Flex options trading, and will share a portion of subscriber revenues with contributing firms.

The service will provide daily evaluations for around 3,000 options series covering 300 underlying equity indexes or exchange-traded funds (ETFs), with participants taking 3 p.m. closing prices, running their pricing methodologies and returning their prices to the exchange by 3:25 p.m., after which the CBOE excludes outliers and creates an aggregate price in time for mutual funds’ net asset valuation processes.

Meanwhile, Credit Benchmark—a new startup founded by former Thomson Financial and Data Explorers executives Donal Smith and Mark Faulkner set to launch early next year—is enlisting firms for a proof-of-concept phase of its service, which will take credit rating and default probability data produced in house by banks and others, and consolidate them into an aggregate spread of credit positions that shows participants where their opinions on a credit issue stand in comparison to the rest of the market, to provide greater transparency around credit pricing and risk.

Though targeted mainly at banks, the service will also appeal to asset managers, sovereign funds, central banks and clearing providers. But unlike the CBOE’s service, anyone wanting to subscribe to Credit Benchmark’s data will first have to sign up as a contributor—in effect, demanding that firms put some skin in the game, so they see subscribing to the service as an investment.

Firms are realizing that the wider the audience being asked, the more likely they are to get an accurate result.

In theory, anyone paying for a service that is not a mandatory rate-setting benchmark should see no advantage in manipulating their prices to “fix” the results, as the value they derive from any service designed to provide additional market context is a result of that context accurately reflecting the marketplace. In addition, by crowd-sourcing from an ever-widening pool, the services minimize the risk of any manipulation—even if some firms collude on pricing, a broad base minimizes those firms’ ability to impact the overall result. Besides, says the CBOE’s McFarland, “If customers have issues with our valuations, there are other sources they can use that provide similar services.”

Like Credit Benchmark, the CBOE’s approach co-mingles the results of the models used by all its contributing participants, compared to a vendor using its own methodology. “The models that the market-makers will use are the same ones they use to calculate the options prices that they stream into the market,” McFarland adds.

Still Hazards
However, even without deliberate manipulation, there are still hazards associated with any process involving contributed rates, says Sheena Clark, founder of Data Contributions, a new consultancy set up to address this issue by auditing a firm’s contributions management infrastructure—from the process by which it contributes prices to vendor services, such as to OTC pricing pages run by Thomson Reuters and Bloomberg, to management of who can see what prices, so that clients see a firm’s price to trade with it, but competitors cannot see prices and adjust their own to be more competitive.

Clark says mismanagement of contributed pricing is rife, and her service will help firms enforce best practices, tighten compliance, and identify potential revenue opportunities. “It will tell you who is seeing what and whether they should be or not, and—for example, if a firm controls a large amount of liquidity in a particular asset or asset class—whether that firm should be making money from this,” she adds.