HPR Preps Market Data Entry with Databot

The Massachusetts-based infrastructure provider is looking to become a one-stop shop in the low-latency trading space.

This fall, Needham, Mass.-based HPR (formerly known as Hyannis Port Research) will roll out a new appliance for market data distribution, Databot, delivered initially as part of its Omnibot switch, for latency-sensitive trading firms to manage their market data flows.

The offering—which is already in beta with a current client that is an ultra-low latency trading firm—will be available via a field-programmable gate array (FPGA) or via a software-based cloud solution. HPR will first go to market with the FPGA implementation within Omnibot. But, because Databot is built into Omnibot, which also serves as a router and pre-trade risk gateway, firms will eventually be able to purchase a software-based version of the appliance.

HPR has traditionally been laser focused on the ultra-low latency, pre-trade risk, and market-access gateway spaces. In recent years, though, it has looked to expand its suite of solutions to provide something more akin to a one-stop-shop environment for a wider array of users. This move into the market data arena is the latest representation of that philosophical shift.

“Historically, we haven’t been that interested in the data market because it’s been a crowded vendor space,” says Tony Amicangioli, founder and CEO of HPR. “We now believe, though, that by providing leading performance and the completeness [of a service], it will allow our clients to achieve better performance, reliability, and efficiency.”

Built into Databot is A-B line arbitration, which allows a firm to switch between incoming datafeeds in the event of a disturbance in data transmission via, say, a microwave beam or fiber-optic cable. Other features include data normalization between exchanges like NYSE, Nasdaq, and Cboe, as well as book-building capabilities to track trade book logic for clients, and multi-feed aggregation of multiple global exchanges to create a single view of market activity.

While HPR already had the A-B line and data normalization capabilities built, as they are part of the vendor’s Riskbot for pre-trade risk offering, the book-building and multi-feed aggregation hardware components are still in testing. Once those are completed—which is expected to happen in Q3 or Q4HPR will officially begin to roll out Databot to the wider trading community, Amicangioli says.

“The key to our offering is its completeness and flexibility, along with the performance and power that we get from the Omnibot switch, which puts us in an industry-leading position as it relates to latency and the amount of information we can deliver to the end users,” he says.

End-to-End

Amicangioli contends that elite high-frequency trading shops often build their own low-latency technology for managing incoming datafeeds, but says global investment banks don’t typically have the teams in house required to build and support such high-performance technology.

But for banks looking to cut costs, software and cloud are the way of the future. HPR already offers high-performance market access gateways, FIX gateways, and pre-trade risk, but in order to be a full one-stop shop, Amicangioli says, the vendor needed to get into the market data space.

“We are your one-stop shop, whatever your needs are for market access. We’re similarly looking to offer data across the spectrum of needs for our client base.”

This spectrum includes offering a software version of Databot, so that the vendor can target those large investment banks while pushing into the cloud services space. Amicangioli says banks—which are under pressure to cut costs and find efficiencies in their trading workflows—are growing weary of cobbling together low-latency risk platforms and high-frequency trading tools. This is leading banks toward tools delivered via a cloud model.

Amicangioli says that while HPR’s institutional clients predominantly use its FPGA products, the vendor is seeing a growing base for its software tools among individual users within firms.

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