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Ivy Schmerken
Ivy Schmerken
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SunGard's Top Ten Historical Data Predictions Call For Ecosystem

While banks and asset managers are facing demands for more frequent risk reporting and analytics, big banks and asset managers still run multiple historical data silos.

Yesterday SunGard published a list of ten historical market data trends for 2012, forecasting that firms will need more timely and consistent risk reporting to meet new regulations and investor demands. No. 2 is that regulators and investors will want more frequent risk reports, almost daily, while on-demand data will be needed to meet more advanced analytics.

I spoke with Oliver Muhr, SVP of SunGard’s MarketMap business unit, which spans the gamut of real-time and historical market data solutions, to get his view on the underlying drivers for these 2012 predictions. “While everybody is talking about new regulations, they need to get ready,” says Muhr, who predicts there will be more and more demand from internal and external business customers for historical data.

Beyond compliance with new regulations, firms can use data management solutions to “differentiate themselves with new or better services to make their data more quickly,” Muhr suggested.

Practitioners such as MBAs and CFAs want more flexible data management solutions that require less IT support so they can spend more time discovering market opportunities, wrote SunGard's Muhr in his list of top 10 predictions. Quants who are supporting electronic trading strategies will need for their firms to implement platforms that can store vast quantities of data and quickly retrieve and accurately process historical and time series data.

However, SunGard is also predicting that demand for more timely risk reporting by regulators and investors as well as the need for larger data sets to feed predictive models, will put a strain on existing data infrastructures.

Home-grown tools are the norm inside big banks, big asset managers with portfolio managers and risk managers who need access to historical data. Also economists or public sector agencies have to deal with historical data and run analytics on top of the data.

“On the historical side of market data, we see more home-grown systems, silos for US equity prices,” said Muhr. SunGard has found that banks have four, five or six homegrown systems for U.S.equities alone, says Muhr. These home grown applications and silos are not designed for nor are they capable of handling those new demands, Muhr contends.

“What banks and other firms want is more of an ecosystem where you can create scale and efficiencies around your existing data," said Muhr. This will enable them to use historical data with other open source tools such as R, a statistical toolkit for creating queries on top of historical data, and open source programs like Jasper Software for creating reports, said Muhr.

On the data and content side, there is a lot of work involved in maintaining data quality and consistency, such as checking on the accuracy and format of data from the exchanges. While firms can do this on their own, managed data can bring efficiencies and scale, notes Muhr.

Another challenge is analyzing the relationships between asset classes, such as complex derivatives, and this in turn is going to fuel the need for standardized entity and security identifiers and cross symbology services. These are translators between various identifiers offered by Bloomberg and Reuters, notes Muhr. This is a huge problem for big financial institutions, but takes two minutes for MarketMap, said Muir.

Another aspect of historical data management is storage. “Historical data management is all about a technology container and logic and how to store historical information,” explained Muhr. Vector storage, rather than traditional relational database, will be needed since it lends itself to storage of tick data from exchanges, every data, week or month, and then to run analytics on top of that, said the company.

Firms are focused on controlling variable data costs by centralizing historical data in one location to assess best price, according to the vendor’s top 10 predictions. “We’re talking more about an ecosystem where you can cross leverage data for your applications,” emphasized Muhr. By sharing data across different units, “You can break down those silos of having ten databases for US equities within the same company,” he said.

Obviously, SunGard sees a business opportunity in these predictions since it provides a range of light-weight and scalable data feeds and analytics as well as a technology stack that firms can use to store their own proprietary data, and clean it and run reports on top of it.

Ivy is Editor-at-Large for Advanced Trading and Wall Street & Technology. Ivy is responsible for writing in-depth feature articles, daily blogs and news articles with a focus on automated trading in the capital markets. As an industry expert, Ivy has reported on a myriad ... View Full Bio
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