Buy- and sell-side firms have so far failed to capitalise on opportunities offered by big data, according to new research, but a growing number of market participants are using unstructured data in their trading strategies.
The financial markets have been uncharacteristically slow to adapt to the increasing use of big data by firms in other sectors over the last ten years. Retail firms such as Amazon and eBay have captured and harnessed the petabytes of data given up by customers, using that information to implement incremental changes that have propelled them to market leader status.
Thomson Reuters and Aite Group have examined the big data strategies and technologies currently under development among financial market participants in a new report, ‘Big Data in Capital Markets: At the Start of the Journey’.
According to a survey contained in the report, 41% of responding firms – banks, broker-dealers, asset managers and hedge funds – do not currently have a big data initiative or strategy in place.
“The capital markets have been relatively slow to adopt big data strategies,” says Virginie O’Shea, senior analyst, Aite Group, “but they have begun to make some impact in a select few areas of the markets over recent years.”
Over the past decade, capital market participants have tended to perceive the structured data sets on which investment and trading is traditionally based as providing the most valuable insight. By contrast, the retail sector has been able to amass and successfully analyse vast sets of unstructured data from a wide variety of sources.
However, perception and practice are beginning to change, the research finds. The increased use of sentiment analysis as a method of identifying trends has resulted in a greater value being placed on unstructured data. While the industry has now grasped its importance, strategies to deal with big data are still in the early stage of formation.
“In addition to traditional market data, growing interest around non-traditional, unstructured data has added more complexity in terms of firms’ ability to deal with data,” O’Shea says.
Looking forward, the report asserts that successful big data strategies can have a positive effect for financial firms in three key business areas: revenue generation, compliance and cost reduction.
First, with execution speed offering diminishing returns, a number of trading firms are looking at unstructured data as part of their efforts to identify new competitive advantages. ‘Scanner algorithms’ – used predominantly by hedge funds – inspect social media sites, news articles and weather forecasts on the hunt for market intelligence. The aim of such tools is to develop an all-inclusive view of the state of the market, and to identify exploitable trading signals.
Second, with financial regulators demanding greater transparency and increased reporting, big data strategies can bring together disparate data sets across a firm, helping particularly with trade reconstruction reporting, fraud exposure and monitoring of suspicious activity.
Finally, big data strategies can help firms implement long-lasting data retention capabilities that will be able to cope with the exponentially increasing volume of data input over time.
“As more financial services firms move off the sidelines and ramp up their big data strategies,” says Debra Walton, chief content officer, financial and risk, Thomson Reuters. “They will need to find insight, speed of response and future scalability in order to boost their success in the market and take their business to the next level.”