SIGTech, a quant trading platform, is establishing a new office in New York as it looks to expand its reach among US asset managers.

The service provider, which already counts AllianceBernstein, Brevan Howard, GAM and MasterLink among its clients, is making a “conscious decision to grow the business” in New York with a permanent presence that can service the existing client base, while serving as an additional quant and development hub, according to chief operating officer Andrew Liddle.

To lead the effort, SIGTech has brought on Vera Shulgina and Josh Diamant in New York. Shulgina has joined as US operations manager from Two Sigma, where she previously worked on the data strategy team. Diamant has joined as SIGTech’s director of sales from Numerix, where he spent nearly seven years in sales.

Since the beginning of the year, SIGTech has added several new clients to its platform and its pipeline suggests continued growth over the next 18 months in its core user markets of Europe, Asia and North America, according to Liddle.

SIGTech was built over eight years as the in-house platform for Brevan Howard's Systematic Investment Group. In 2019, SIGTech was spun off from Brevan Howard and began independently selling its SaaS platform to hedge funds, asset managers, pension funds and banks that wanted to create new systematic trading capabilities.

In addition to handling data onboarding and normalisation, signal generation, backtesting, execution optimisation and order generation, SIGTech’s platform also gives clients fully integrated research data, as well as tools to discover that data’s alpha-generating properties, Liddle explained.

“In their day-to-day lives, users can access datasets provided by SIGTech, as well as their own datasets, and can access our code to start to build up and iteratively add complexity to their strategies,” Liddle said. “After optimising their strategies, they can go downstream to have strategies that integrate with their OEMS [order- and execution-management system] provider.”

Asset managers frequently debate whether it’s better to “build or buy” these types of systems. At a recent Neudata event, panellists debated the topic, noting that they consider several criteria when making a decision about whether to build a technology platform in-house or outsource it to a vendor, namely the costs associated with building and maintaining their own models, the speed at which they want to deploy a strategy, how long they plan to use the data for and how confidential they consider the underlying data to be.

For SIGTech, all those considerations make sense. “It’s an acceleration question as well,” Liddle explained. “If you see a dataset that has alpha-generative properties, we will help you test that more quickly. But if you’re going to fail, fail fast. Don’t spend six months cleaning, normalising and testing [a dataset] and then figure out it’s not going to work.”

In addition to allowing clients to integrate their own datasets, the platform also houses data from channel partners, including CLS, IHS Markit and Refinitiv. “For idiosyncratic datasets that have a higher risk of alpha decay, we may want clients to pass that data through the platform themselves via the client data onboarding API, and have governance structures in place to make sure we don’t remarket those datasets,” Shulgina explained. “Datasets that are preloaded have broad coverage and diverse use cases for different asset classes or time horizons for trading.”

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