Max Bowie: When Competition Fails, Data Quality and Cost Suffer

max-bowie
Max Bowie, editor, Inside Market Data

As one of the largest single costs for any trading firm—behind staff and real estate—market data, and the price that data sources charge for it, is constantly under scrutiny with competition between vendors keeping data quality high and costs low, or at least reasonable.

One of the most important areas is pricing of over-the-counter (OTC) instruments, where no reference exchange price exists, and firms have traditionally depended on trade prices from brokers, evaluated prices derived from various inputs on a daily or intra-day basis—but not real time—or services that provide prices based on contributions from other dealers or buy-side firms.

But contributed prices can be manipulated, as evidenced by the UK’s Financial Services Authority (FSA) and US Commodity Futures Trading Commission’s (CFTC’s) investigation into Barclays’ misconduct over Libor rate pricing, culminating in massive fines and the resignations of the bank’s chief executive and chief operating officer.

Tell-Tale Signs
It is possible to spot tell-tale signs of price manipulation: Vancouver, BC-based derivatives valuation and risk management software vendor Fincad spotted a divergence between Libor-based swap pricing and OIS-based pricing that began around the start of the financial crisis and continued to result in Libor swaps being priced too low and not accounting for embedded risk, officials say, prompting the vendor to incorporate an overnight index swap-based pricing curve into its Insight Solutions derivatives valuation and hedge accounting platform.

But properly maintained benchmarks are an important tool in over-the-counter markets, and will become increasingly so for asset classes that regulators cannot shoehorn onto exchange-like venues, where participants will start to demand similar levels of transparency to other marketplaces—for example, Tullett Prebon Information’s recently launched benchmark oil curves to provide transparency into commodity derivatives.

Once the authorities have pored over Libor, it should emerge more transparent and stronger than others that have not been subject to the same scrutiny. In the meantime, consumers may resent paying for data that is now being called into question. Of course, consumers usually resent data fees—especially for “public” benchmark or index data—and at a time when budgets aren’t increasing in line with the costs of data services, forcing unpopular cuts, that frustration is understandable, though the old argument that “market data fees are like charging to look at the price list,” no longer reflects the extent to which content has broadened, especially in the OTC markets.

But there are signs that data sources are softening their stance and being more proactive in introducing policies that costs cannot simply continue to increase. One thing that especially irks users are constraints on how data can be used, such as non-display fees or derived data fees—both of which are addressed in a new Global Data License Agreement covering data from all of NYSE Euronext’s marketplaces, which will be rolled out next year, and which is designed to simplify policies and reduce costs for end-users. This license agreement—modeled in part on one rolled out by the London Stock Exchange last year—has won praise from user groups for proposing more flexible policies, as well as for the process by which NYSE has consulted with end-users along the way—instead of simply announcing the changes with a 30- or 90-day notice period to make the changes less painful.

Adoption
With luck, the adoption of these policies will lead to more competition between data sources, forcing them to use cost and quality as differentiators. Firms seem willing to pay more for guaranteed quality, so long as there are opportunities to reduce spend in other areas. By addressing quality issues and easing cost pressures, end-users can turn their attention to growth—and to purchasing more data to support new business—rather than focusing on cuts. Only then can the data industry once again be a driver of growth.

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