Exegy, a provider of market data and trading technology, has spent nearly two decades building reliable, secure, low-latency technology for capital markets. For the past three years, the company has been broadening that mission by leveraging artificial intelligence technology and research into market microstructure to provide relevant, actionable, and timely insights to clients.

The goal, said Exegy CEO Jim O’Donnell, is to provide customers with intelligence-enabled data they can use to underpin their own unique strategies and solutions. This approach allows them to make more informed trading decisions and generate new alpha without having to invest in expensive infrastructure.

“What surprised us is how creative our clients are in using the building blocks that we give them to construct their own solutions,” O’Donnell said. 

Andy Lee, Exegy’s Director of Quantitative Research, puts it: “We provide the ingredients that customers can use to bake a cake. How you use those ingredients is what makes you a good chef.”

A transition from speed to speed+intelligence

O’Donnell said Exegy’s emphasis on intelligence-enabled market data grew out of its efforts to solve the challenges of normalizing and delivering larger volumes of data due to increasingly volatile markets.

“Exegy was in the market data aggregation business, and our claim to fame was that we could do this very quickly using our hardware acceleration technology,” O’Donnell said.

Even as Exegy delivered new breakthroughs in latency, O’Donnell added that it became clear that market participants would require more to thrive in an era of market complexity and volatility. 

“They needed more than data or information – they needed intelligence, the context that drives decisions,” he said. “And they needed it across the latency spectrum – from latency-sensitive strategies employing FPGA to latency-agnostic trading using a consolidated feed.”

@CloudQuant CEO Morgan Slade was kind enough to do an interview with us regarding Signum's predictive analytics power. Read the full blog post to learn how CloudQuant and its customers are seeing the Signum difference: https://t.co/PsmSLvoRaw#PredictiveAnalytics pic.twitter.com/dkqQrpi8Vz

— Exegy (@ExegyInc) May 31, 2022

O’Donnell said Exegy was in a unique position to meet that challenge of deriving additional value from market data without sacrificing speed, thanks to a high-capacity technology stack that could decode market data and perform analysis at the same time. 

“We are the first technology company who could publish normalized market data and the analysis simultaneously, which is why we continue to hold the leading position today,” O’Donnell said. “It is hard to do if you do not have exactly the right equipment, in exactly the right locations around the world.”

He noted that proprietary trading firms have been developing predictive analytics to generate alpha for a long time. Exegy has been able to democratize this emerging technology by providing access to intelligent market data to those who lack the resources to build in-house, including firms serving retail investors.

Exegy started on its quest to provide intelligent data three years ago. O’Donnell said: “I think that in the next three years, our customers can look forward to intelligent predictors across our market data portfolio.”

A range of intelligence-enabled choices

Out of Exegy’s initial research into US equity markets, the firm has developed a number of breakthrough technologies that make up its Signum suite:

– Liquidity detection capability that can identify and track iceberg orders, providing a useful predictor of institutional sentiment at both the stock and index levels. Lee and his quant research team have amplified this ability with machine learning to create strategies that were highly predictive of next-day performance of stocks and indices.

“Institutions can take multiple days or weeks to change their positions, so we can create alpha by predicting demand coming in or going out of a symbol,” Lee said. “We believe our customers can go even further with it.”

– The ability to predict how soon a National Best Bid and Offer (NBBO) price will change, as well as the direction of that change. This information will soon be integrated into Exegy’s new consolidated market data feed, delivering probabilities for NBBO price changes for US SIP feeds simultaneously with quotes.

Exegy’s iceberg order detection signal immediately recognized that institutional investors were selling BBBY, even as the stock price rose. What could your firm do with those insights? Learn More: https://t.co/lhCaJasHXY #BBBY #InstittionalOrderFlow #InstitutionalInvestor pic.twitter.com/LvSEZprWu0

— Exegy (@ExegyInc) August 22, 2022

Lee noted that these technologies have been resilient in uncovering alpha opportunities in both bear and bull markets.

The next phase of Exegy’s plan to enhance market data with intelligence is Metrix, a service that derives metrics from a microstructure analysis of depth-of-book feeds from the US equity exchanges. In collaboration with customers, Lee’s team identified more than 150 unique data points that provide order-by-order insights without requiring expensive direct access to multiple market data feeds. 

“Over the years we have been taking the computational load from clients by, for example, calculating the net asset value of ETFs or creating a composite view of the market,” Lee said. “Metrix allows us to do more computation for customers, such as calculating the imbalance of the price book or how many trades were executed at the midpoint, while also delivering market data.”

These insights can also improve execution quality without the costs of beefing up ultra-low latency infrastructure. Lee argued that execution algorithms have become commoditized, so market participants are looking for differentiated analytics to drive innovation – a resource that Exegy can provide.

While initial research has focused on US equities, the company plans to expand into European equities and US derivatives in the coming year.

O’Donnell said Exegy’s overarching goal is to be able to deliver intelligent data to clients in whatever form they require – real-time signals or summary data, via the company’s ticker plants or their consolidated market data feed. This flexibility gives firms of any size the opportunity to incorporate intelligence into their market data.

“For example, we have clients that only care about the intelligent data that we provide for the last trading hour of the day, while others use signals throughout the day,” O’Donnell said.

As Lee’s research continues, he anticipates that intelligence-enabled data will become the new table stakes for success in financial markets.

“We are really excited about the next phase of bringing this data to life and helping everyone understand why this is the future of trading,” Lee said.