Accurate, real-time data feeds are essential to trading and this is even more critical today as buy and sellside firms navigate unprecedented volatility due to Covid 19. Distribution and infrastructure supporting data feeds have been put under greater stress as traders work remotely and firms need to take greater control of data management, distribution and allocation if they are to be successful, according a new study by Greenwich.
Ownership of these decisions have tended to be secondary considerations, according to Brad Tingley, Market Structure and Technology Analyst at Greenwich Associates and co-author of Market Data Budgets—Spending Trends and Outlook.
“However, in a big data world, these are the types of decisions that can come back to haunt firms years later,” he adds. “We believe that firms need to take strong hold of the data management process—beginning, middle and end—and make sure they are investing in the right tools, vendors and systems to ensure that they are helping to set themselves up to succeed in the future.”
This is especially important as respondents expect vendors to increase their prices for consolidated feeds, pricing and reference data in the future. “Third-party data providers and aggregators account for nearly 75% of market data budgets, although a third of this spend is ultimately passed onto exchanges for their direct feeds,” says Tingley.
On average the study, which polled 129 firms globally, shows that banks, brokers and other sellside firms pay an average $140m per year for market data while asset managers, hedge funds and other buyside organisations shell out around $44m annually.
Broken down, direct exchange feeds account for just over a fifth (21%) of the overall cost while pricing and reference data jointly comprise over a third (35%). A third goes to terminal products and/or desktop analytics, and consolidated data feeds represent 20% of participants’ third-party budgets
The report also notes that firms incur additional expenses for infrastructure, support, connectivity, and maintenance costs that can amount to half or more of annual data purchase spending. This is mainly due to maintenance of older systems, management of multiple data and delivery systems, and the need for frequent updating due to changing data requirements.