Data aggregators are enabling trading firms on the buy- and sell-side to better access to information that can increase the efficiency of trading and strategy development, according to panellist at TradeTech in Paris.
Laurent de Barry, director of hardware trading solutions, Exegy said, “Aggregation is the first step that we provide, if you need to go faster, then we have a whole offering that goes down to FPGA-based trading, So if you underperform, trust me, there’s always someone that’s trading faster than you and our role as a partner to our customers is to make sure that we have that offering laid out, so when they’re ready to progress to the next step, we have something that’s easy for them to step into.”
Delivery of data is key, says Russell Hart, COO at Alcova, as this is reducing the operational costs and stresses for investment firms who need to use data frequently, allowing the specialists using it to focus its use and not storage.
“Historically you got flat files from your providers on FTP sites, but even if you get it via an API, you’re probably pulling the data down, storing in your own database in a flat file, augmenting it with some of the symbology that you use,” he says. “Your research teams has to think about how you store data. Increasingly over the last three years, we’ve seen a lot more data as a service, where we don’t own a lot of the data we just rent it – which is good business for the vendors who could potentially have perpetual licence model because you can’t get away from that model – but we don’t have to bother about where we store it or how, we just pull it on demand where we need it.”
The relationship between data providers is also changing because they are often now delivering data via a cloud provider – such as AWS – rather than directly from their own store, meaning the investments need only deal with a single cloud relationship.
Firms also need to assess how they should analyse alternative data, and capture ideas from large non-traditional data sets said Brad Levy, CEO of Symphony.
“The data conversation has exploded in the last three to six months, part of it just the whole chat GPT discussion,” he said. “But from the markets perspective, we generally think about market data, exchange data, tick data, getting down to chips and colocation, which is very important and more about speed, from insight to action. The data conversation has definitely bubbled up into the analogy that we need to fly above the larger datasets now, and then figure out when to snorkel or scuba dive. There’s a lot more data out there than traditional market data, whether earnings calls, or research or news.”
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