The three firms join a growing list within Sustainable Trading’s global membership network of investment managers, banks, brokers, exchanges, trading platforms and service providers who share the goal of improving the sustainability of global markets.

Members of the network are now making progress with the implementation of the Sustainable Trading Best Practices, Sustainable Trading confirmed, through which the associated measurement framework will be utilised by members to track their progress and benchmark themselves against their peers.

Watch now: Sustainable Trading’s Duncan Higgins on integrating ESG into trading

The addition of Exegy, ING and Optiver follows the recent appointment of Eleni Coldrey of Euqinix, Asha Patel of Instinet and Ebrahim Patel of RMB, to Sustainable Trading’s board.

“We are delighted to welcome Exegy, ING, and Optiver to our membership network. Their extensive experience of global markets, and common commitment to driving a more sustainable future for the financial industry, will bring invaluable insights to Sustainable Trading,” said Duncan Higgins, founder and chief executive at Sustainable Trading. 

“Their participation further strengthens our collective efforts to drive positive industry change and greater sustainability in the global markets trading industry.”

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The development will offer quantitative traders visibility on the volume of iceberg orders throughout the day using summary files delivered every 10 minutes.

Exegy claims that Liquidity Lamp offers a distinct perspective on US equities trading, helping filter out the ‘noise’ created by retail and high-frequency trading (HFT) activities.

Summarised updates on iceberg trading activity are provided as a CSV file via a cross-connect at the NY4 data centre or to a chosen AWS S3 bucket.

The addition of intraday files to Liquidity Lamp allows quant traders to make data-driven decisions while iceberg trades are happening and ahead of market close, reducing time spent while also allowing traders to react in real-time to opportunistic trades.

“Liquidity Lamp Intraday is a novel dataset for systematic trading,” said David Taylor, chief executive of Exegy.

“Using this data, quantitative traders will be able to seize trading opportunities that conventional models might have missed or considered too risky.”

The intraday volume signal will enable traders to uncover institutional order flows, reveal informed investor actions and provide insights into price impact dynamics.

Traders will also be able to optimise portfolio positioning, respond to unusual institutional volume promptly, and enhance predictive models and market responsiveness.

“This dataset represents an opportunity for the quant trading community to elevate their strategies with a unique view on intraday institutional trading activity,” continued Taylor.

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Data analytics in financial markets has reached the point where clients have access to complete global data sets, and we see 2024 as the year where this will drive change in how counterparties interact and in automating trading workflows. Firstly, with more data freely available in data networks it will become easier for buy- and sell-side firms to interact and collaborate, using data to make decisions about who they trade with and how they execute trades most effectively and profitably. Trading data made available via APIs informs trading decision making, and trading desks are starting to automate their workflows using the information contained in the data sets.

In 2024, we to see an increased use of trading algos in FX. As the use of data increases, we also see increased demand for data networks supporting multiple asset classes. Tradefeedr’s initial focus was FX, and in response to client requests we will launch equities and futures in 2024.

David Taylor, chief executive officer, Exegy

In 2022, we conducted a survey of executives in principal trading, brokerage, and asset management firms to quantify demand for buying predictive signals and content from third-party providers (like us) as a supplement to internal development. Around 10% of firms were engaged with third-party providers, 20% were actively evaluating third-party offerings, and 40% predicted that an engagement with a third-party provider was likely in the next one to two years. This aligned with other industry analysts who projected the alternative data market to grow at over 50% CAGR over the next five years. 

As the table stakes continue to rise to be competitive in electronic trading globally, firms will expand their sourcing and integration of solutions from trusted third-party experts. Increasingly, this will include AI technology, predictive signals, and components of quantitative strategies, as firms are forced to rethink the boundaries of their own expertise and drivers of their sustained alpha.

Robin Mess, chief executive officer and co-founder, big xyt

In recent years, navigating the European market has proven to be a formidable challenge, marked by growing competition, additional legislations and venues. The industry shares the hope that policymakers will transform the entire region into a more alluring investment hub, fostering consistency over internal European competition.

Propelled by innovation and technology, 2024 will witness exchanges and venue operators enhancing their appeal to market participants through the introduction of novel or revised mechanisms, whilst liquidity providers increasingly engage with buy-side firms. Asset managers are anticipated to spearhead and embrace emerging trends, particularly the rise of active ETFs along with ETF-specific execution algorithms. Across all asset classes, the significance of execution analytics, pre-trade estimations, and the automation of processes such as swing pricing will be more pronounced than ever.

As the trading industry increasingly becomes data-centric, its pivotal role in driving and implementing long-term initiatives will include actively contributing to the realisation of the consolidated tape and transitioning towards T+1 settlement. The year will also bring more clarity about use cases leveraging generative AI and digital assets.

Kamala Kannan, director, corporate actions, S&P Global Market Intelligence

Trade data between parties has always been undisclosed, with anonymity maintained throughout the trade life cycle leading to difficulties in tracking the end-to-end trade movement, eventually leading to trade matching or settlement failures. Considering recent developments around Unique Transaction Identifier (UTI) and fintech firms offering collaborating solutions, remaining undisclosed will no longer be possible, as further data sharing platforms emerge focused on marrying both sides of the transactions and provide a unified view to the final consumer.

As participants openly share their data, platforms can link entire settlement parties involved in the trade life cycle and provide end-to-end transaction visibility with the transaction status (both buy- and sell-side), discrepancy details etc., using a common reference like UTI or other trade parameters. When settlement information is shared reciprocally between counterparties, it will enable firms to identify and correct the inefficiencies at early stages of the trade and prevent failure in matching or settlement, which will be crucial in T+1 environments with shortened settlement cycles.

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What does the future role of AI look like in terms of execution?

We see the pursuit of prediction following a similar trajectory as the quest for speed. First, we expect predictive capabilities to become table stakes for most participants in electronic markets. For example, market data systems will be expected to be not only fast and content-rich, but also predictive, delivering the expected direction and timing of price changes synchronously with the latest prices. 

This mirrors the evolution of low latency trading technology. Early movers gained an edge by automating and collocating their trading systems, then optimising them using purpose-built hardware logic in FPGAs and wireless network links between data centres. This is now de rigueur for most quantitative trading firms, agency brokerages, and exchanges.

Second, we expect firms increasingly will develop their AI-driven trading systems by identifying their differentiator or their “secret sauce”, focusing their internal development on capturing that edge, and buying the remainder of the capabilities from a trusted partner. Firms will recognise that they will develop more sophisticated quantitative capabilities more quickly by leveraging foundational signals, datasets, and tools from specialist providers. Many quant teams still suffer from “not invented here” syndrome, but we see this changing across the industry as competition heats up, talent remains scarce, and the need to accelerate development increases.

How important is data when considering AI?

How important is thrust when building a rocket? Data is both the fuel and purpose of AI much like thrust is both the driving force and purpose of a rocket. We discover, build, and train new AI models using vast datasets. Once ready for use, their purpose is to automate the synthesis of data at scales and speeds that were previously unimaginable.

Therefore, data quality is imperative. The ability of a firm to build AI models that are both effective and trustworthy is directly tied to the quality of datasets used in the discover, build, and train process, as well as operation.

In capital markets, data quality is judged at minimum by its timeliness, granularity, consistency, and completeness. Ensuring that the data is reliably delivered to the model, even in the presence of faults in other parts of the trading infrastructure, is an equal consideration to the accuracy and recall of a predictive model.

In terms of automation, what are the priorities for the buy-side, sell-side, exchanges specifically? 

On the buy-side, we are helping an increasing number of firms push more of their automated trading strategies into purpose-built hardware. Firms see an advantage or necessity in having more of their tick-to-trade logic operating in the nanosecond realm. Encouragingly, we also see quantitative firms consuming more of our predictive datasets to use as inputs and building blocks for their algos. 

On the sell-side, the dominant theme is deploying low latency market data and brokerage systems to more collocation data centres globally. We typically begin relationships with sell-side firms by addressing their high volume, low latency market data needs in US equities and options. We then work in partnership to deploy a tech stack to equities and futures markets in Canada, Europe, and Asia Pacific. Across the capital markets ecosystem, there are common requirements for reliably fast and resilient market data, especially under stressful market conditions. 

What role can/do providers play in capital market democratisation?

The table stakes for competing in today’s electronic, automated, and data-driven capital markets are raising relentlessly. Specialist providers promote competitive and resilient capital markets by enabling a diverse community of firms to participate successfully. Lowering barriers to entry helps prevent brittle markets dominated by a continuously consolidating club of the largest trading firms. 

Good providers help their customers achieve business results that they otherwise could not achieve on their own. In Exegy’s case, we help our customers grow revenues by expanding to new markets faster and more cost-effectively, improve trading returns with faster systems and more intelligent data, expand margins by reducing data centre footprints, or a combination thereof.

The process works best when firms view their providers as an extension of their own technology and operations teams. Tighter partnerships yield better results in our experience. This has held true across a diverse community of firms in terms of their roles in the ecosystem (buy-side, sell-side, trading venue), number of markets and asset classes traded, size and sophistication of their technology teams.

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OPRA previously confirmed that it was expanding its data dissemination from a 48-line to a 96-line multicast data distribution network in a move aimed at optimal symbol balancing and line capacity utilisation.

OPRA’s subscribers have now requested additional test time, which the authority has granted, with the go live now set for 5 February 2024, as opposed to the previously confirmed 5 October 2023.

It has also been confirmed that the next capacity test will be carried out 18 November this year, before a functional test and capacity test on 20 January 2024, three weeks before the go live.

As the authority plans to scale the capacity of its distribution, the market is preparing for the significant change and putting in place measures to consume around 120 million messages a second following the go live.

Speaking to The TRADE, David Taylor, chief executive of trading infrastructure provider, Exegy, explained: “That’s an enormous amount of data. As a firm who acquired a company that previously ran a traditional software implementation of a ticker plant to consume that feed, we know that it can take a dozen, two dozen, maybe more servers to consume that data with software and current market participants are looking at doubling the amount of hardware they need to deploy in order to consume that data.”

Read more – Data arms race heats up as venues and vendors eye buy-side business through new initiatives

Exegy recently announced its sixth generation ticker plant which is purpose-built for processing this options market data, processing the OPRA feed on a single 2U server and providing an immediate two times latency reduction (when compared to the previous fifth generation). 

Specifically, the changes being made by OPRA: “Help facilitate capacity upgrades to the ICE Global Network (IGN), new subnets, rendezvous points, source addresses, and multicast addresses are being introduced (including Global Trading Hours).” 

The process is split into two phases, with the migration of the current 48-line symbol distribution schema to new network subnets, rendezvous points, source addresses, and multicast addresses coming first, before phase two wherein migration of the new symbol distribution schema over 96 lines will happen.

In terms of how prepared the market is for such a move, Taylor told The TRADE: “I think most firms are prepared or preparing as well as they can. There was recently a capacity test by the consolidated tape […] they approached that 120 million message per second level of performance.

“[…] the industry has been vocal and in fact this change has been delayed a few times just to give the industry the ability to be ready and I think that’s a very important point – that this issue of capacity and the ability to handle the data is an important market stability issue so we view our efforts to provide these very efficient, high capacity systems as our contribution to having stable, reliable markets.”

As a securities information processor, OPRA members consist of the national securities exchanges that have been approved by the SEC to provide markets for the listing and trading of exchange-traded securities options.

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The partnership will offer qualitative traders the ability to manually take granular, historical data to enhance algos and derive alpha by using the data in Exegy’s back-testing and simulation solutions.

“Accessing BMLL data now enables our clients to do strategy back-testing on high-fidelity data and execute using our real-time data. What sets BMLL apart is the way the data is sourced, saved and curated,” said David Taylor, chief executive of Exegy.

According to Exegy, up to 80% of a quant’s time is spent on data analysis, leaving only 20% to develop algos.

This partnership will help free up the time spent on the analysis process, alongside democratising access to trading intelligence.

“Firms increasingly need a deeper understanding of market shifts, liquidity dynamics and opportunities for alpha. This requires rapid access to full-depth order book historical data— engineered and formatted ready for use,” said Paul Humphrey, chief executive of BMLL.

“BMLL’s Level 3 data and Exegy’s low latency capabilities are built on the same PCAP source data, making it easy for users to access both real-time and historical data sets with the same precision and granularity for their research.”

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Nomura Securities appointed Joshua Lukeman as managing director and head of US Delta One Index. Lukeman joined Nomura from Credit Suisse, where he spent nearly 19 years in various leadership and trading roles within the firm’s equity finance business. Most recently, Lukeman served as head of the equity finance group for the Americas, where he oversaw multiple trading desks including equity synthetics, ETF and systematic marketing making. Before joining Credit Suisse, Lukeman spent six years at Morgan Stanley as an equity and index option market maker. At Nomura, Lukeman will expand the firm’s D1 Index and ETF products, alongside bringing additional expertise in related financing products to scale Normura’s broader US equities offering.

AI quantitative analytics provider Overbond appointed Chaim Hack as its new director of sales, based in London. Hack was previously director of business development at Coremont for just under a year, and for Coremont Digital for eight months before that. He was formerly with cybersecurity firm QOMPLX from May 2020 in a variety of roles. Hack first came to the UK in January 2014 as managing director of EMEA business for investment management software firm Enfusion, for whom he set up the firm’s first London office. He started his career in derivatives at JP Morgan, where he worked for six years.  

Fixed income investment banking boutique KNG Securities appointed CIS specialist Igor Nartov as emerging markets (EM) senior advisor. Nartov is a senior fixed income trader with more than 12 years’ experience in EM FX and rates markets. He joined KNG Securities from investment bank VTB Capital, where he oversaw the local currency government bonds trading franchise. Nartov also brings market-making experience in a wide range of products including FX, local rates, interest rates derivatives and structured notes in both EM and G10 areas.

Talomon Capital junior investment director and trader, Michael Truckle, left the firm to join Hudson Bay Capital Management. Truckle was appointed associate analyst at Hudson River Bay Capital after spending the last two years at Talomon. Prior to joining Talomon in 2021, Truckle spent nearly two years at JP Morgan in an emerging markets equities trading role and later in an equity capital markets syndicate role. Truckle was recognised as one of The TRADE’s Rising Stars of Trading and Execution in 2021 alongside peers from across various other buy-side institutions.

Global trading infrastructure provider Exegy made a string of key senior appointments including a new chief executive office, chief financial officer and chief technology officer – as part of its accelerated growth strategy. David Taylor was promoted to the role of chief executive officer, after serving in product strategy and engineering leadership roles at Exegy over the last 18 years. Taylor replaces James O’Donnel, who announced his retirement after leading the company since 2005.

Alongside Taylor’s appointment, Peter Feret was named chief financial officer. Feret brings 25 years of experience in shaping financial strategy for growing companies including Scripps Networks Interactive, which was acquired by Discovery Inc. and Ministry Brands. Elsewhere, Jason White, who has spent 20 years at Exegy, was promoted to the role of chief technology officer. During his tenure at Exegy, White has held leadership roles in engineering, solutions consulting, managed services and product strategy, most recently serving as vice president of product management for market data.

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David Taylor has been promoted to the role of chief executive officer, after serving in product strategy and engineering leadership roles at Exegy over the last 18 years.

Taylor will replace James O’Donnel, who announced his retirement after leading the company since 2005.

Taylor will also serve on Exegy’s board, joining O’Donnell, who will remain a member following his retirement.

“Jim was a visionary and stalwart investor during our startup years, as well as an innovative and revered CEO for over 17 years. We’re fortunate to retain his guidance as we embark on the next stage of Exegy’s growth,” said Taylor.

O’Donnell added: “David helped us span much of that distance through his expertise, vision, and drive. I’m confident that under his leadership, that progress will only accelerate.”

Alongside Taylor’s appointment, Peter Feret has been named as chief financial officer. Feret brings 25 years of experience in shaping financial strategy for growing companies including Scripps Networks Interactive, which was acquired by Discovery Inc. and Ministry Brands.

“Peter’s experience with private equity-backed growth firms will be a tremendous asset in this role,” said Taylor.

Elsewhere, Jason White, who has spent 20 years at Exegy, has been promoted to the role of chief technology officer. During his tenure at Exegy, White has held leadership roles in engineering, solutions consulting, managed services and product strategy, most recently serving as vice president of product management for market data.

As CTO, White will lead Exegy’s global engineering organisation alongside overseeing the company’s security and IT infrastructure team.

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Aquis will use Exegy’s consolidated European venue market data feed, Axiom, in its internal matching engines on its UK and EU venues.

According to Aquis, it selected Axiom based on the consolidated feed’s low latency, stability and resiliency. The exchange began using the feed on its venues earlier this year, most recently in Aquis Matching Pool (AMP), its newly launched dark pool.

“We took the decision to use the Axiom consolidated feed due to its exemplary performance. In our decision-making process, we examined the latency profile of the data from all the source markets where we provide mid-point trading on the Aquis Matching Pool (AMP),” Adrian Ip, managing director at Aquis Exchange, told The TRADE.

“We ensure that clients who trade at the mid on Aquis, whether via the AMP or Auction on Demand (AoD) get the most up to date price possible; ultimately supporting our promise to clients of the best price available at any given point in time.”

Aquis develops exchange trading technology through its Aquis Technologies division, which is currently being used by other venues. Aquis’ deployment of Exegy’s Axiom consolidated feed will allow these other venues to easily leverage Axiom market data on their own platforms.

“For more than a decade, we’ve focused on delivering mission-critical market data solutions to leading market participants, including exchanges and alternative trading systems with exacting performance and compliance needs,” said David Taylor, co-president and chief technology officer at Exegy.

“We’re proud of our track record of building feature-rich, resilient solutions that hold up under the most volatile market conditions with consistent microsecond-latency.”

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