Getting granular with data
BMLL Technologies: Best Data Science Solution Provider – An increasing number of market participants are depending on more granular quality data to improve alpha generation and manage risk exposures. This results in new resource and cost challenges which many are alleviating by looking at alternatives to building these systems in house and buying-in data and analytics capabilities from third parties.
“A recent industry survey* showed a massive growth in hedge funds looking to third parties for data and analytics; 41 percent of hedge funds are significantly increasing budgets towards third party data and analytics. Simultaneously, 24 percent are reducing budgets in data infrastructure as more move to the cloud, away from internal server farms and to a new breed of outsourced vendors rather than relying on the traditional market data providers,” highlights Dr Elliot Banks, Chief Product Officer, BMLL Technologies.
According to Dr Banks, in the last year, flexibility has become a key delivery requirement. Sophisticated players want to be able to analyse both the market as a whole and deep dive in to the market microstructure within the same tool. They also are looking for ways of analysing the market via integrated workflow tools “We are seeing greater adoption of our solutions which allow clients to interrogate the data in different ways such as via the BMLL Data Lab or the BMLL Data Feed. Clients can more easily access the data they need to better understand market activity and execution performance.”
High quality data has become a necessity for industry players who manage their AUM quantitatively. To successfully manage their AUM, quant funds need access to the greatest granularity of data, enabling them to draw predictive inference on future market states.
Dr Banks comments: “The granularity of Level 3 data gives them access to five years of microsecond, message by message data covering major equity exchanges in a harmonised format, with unlimited cloud and a full suite of analytics libraries. This enables them to unlock the full predictability of pricing data, and to understand exactly how each venue they trade behaves and the probable intentions of each trader.” It is only by having access to this level of granular data, combined with the ability to manipulate and query it in a cost-effective manner that quant funds are able to generate this type of insight.
Hedge funds need to find alpha, which in turn means they must search for new sources of data and discover new ways to create value and generate return. While doing so, they need to monitor execution risk and understand the microstructure of the market. All of this requires comprehensive data science capabilities that many firms don’t have in house and therefore aren’t able to fully leverage the depth of data required to derive predictable insight. BMLL has deployed a fully managed data science service within hedge funds looking to optimise their quant resource time.
Firms can now take advantage of a fully managed service. BMLL Data Lab and BMLL Data Feed provide access to a five-year history of harmonised Level 3 data in a scalable and flexible manner.
Due to increasing demand, BMLL now offers its Data Lab to smaller funds who might not have the resources to build a full data science capability but which still have teams which can gain predictive insight from the market microstructure.
“Overall, the rise of data science technology has enabled data science techniques, such as those provided by BMLL Technologies, to become more widely recognised and adopted,” Dr Banks observes. “BMLL’s business objectives are to continue working with our existing hedge fund customers to keep delivering insight that helps them to remain competitive. We are also expanding our solutions with more analytics across the core markets of US and EU equities, ETFs as well as global futures.”
*‘Buy-side usage of Level 3 data analytics for algorithmic performance’ (WBR Insights & BMLL Technologies White Paper)
Elliot Banks, Chief Product Officer, BMLL Technologies
At BMLL Technologies Elliot Banks is responsible for data science, product development and product delivery, working closely with both clients and development teams to deliver its analytics and product suite to clients. Prior to joining BMLL, Elliot held a mixture of commercial and technical roles, including roles within the infrastructure private equity arm of Macquarie and as a Faculty AI Data Science Fellow.