One is the use of anonymous wheels for venue selection. Customers are particularly keen to show that they are monitoring real time execution quality, venue selection etc. We’re also seeing the concentration of flow with fewer providers. ZebrA-X is creating a hub for trading globally for the bank. We’ll be able to concentrate venue choice, algo choice and a high level of customer service in one location. We’re working with a number of brand new venues and innovators in the market to keep this current. The key for us is to differentiate ourselves from bulge.

When you put technology in the middle of a brokerage offering it tends to accelerate successes and therefore you’d expect the big to get bigger. The more a brokerage business looks like an exchange, the better it does. Much like you’ve seen with internet businesses from 20 years ago, you tend to get the weak ones withering away quite quickly. Due to commission wallets and equity issuance, the market’s extremely competitive so you’re seeing some fallout across different business silos, including electronic and low touch trading.

How are market conditions driving these low touch developments?

A couple of years ago, the goal was to capture retail and reinvent RSP mechanisms. Several banks and brokerages tried to do that. Clients we speak to – in particular wealth managers – are trying to cut costs. They’re doing that by electronifying the smallest 10% of trades. Big clients want to be able to interact or harvest that flow. If on a company’s results day there’s lots of retail sellers, some clients love to build a position by trading against retail because they have better information.

ZebrA-X has one OMS provider called Infront where orders go for three seconds all or nothing. If they don’t execute, those clients’ tickets then go to the RSP of the whole street. In that respect, we’ve disintermediated part of the RSP mechanism. The first bite of ZebrA-X algo goes exclusively to Aquis for 12 microseconds on an all nothing basis so if there’s an institutional order resting there, the retail order can cross at mid or better against that ticket before it goes off and checks all the other venues. Clients can do these kind of trades on a match basis in Aquis Auction on Demand (AOD) and then further down the life cycle of the ticket, a piece will rest firm in Aquis for the life of the ticket which enables us to hand on heart say you cross institutional to retail, retail to retail etc.

The more you electronify the business the more business you do. TCA – traditionally on which execution wheels are built – looks at three things: one is average fill size, two is pre-trade signalling and three is post-trade reversion. Typically, five seconds pre-trade and five seconds post-trade.

How are clients leveraging low touch offerings differently today?

Overarchingly customers want to do block business. They want to finish their tickets by the close of business. There will be some clients who’ll flash our dark aggregator with their tickets for a couple of minutes and then change the order into a benchmark algo. They’ll be some clients who’ll rest the block with us all day long and there will be some clients who rest fractions of tickets and work out where the liquidity is on a particular day, using it as a radar.

One of the key things we’ve done is to connect to systematic internaliser’s (SI) directly. If you can rest benign blocks of stock in certain SIs and get good fill rates you will get extended better liquidity down the road much like reputational scoring seen on Cboe or Turquoise Block Discovery does reputation scoring. There’s a move amongst us and our peers to connect directly to these bilateral SIs because customers want it. Customers’ overarching need is to do the block. They don’t want to miss the print on an exchange where they’re not represented.

We’re building proprietary tools with big xyt. Traditional TCA is T+1 so heads of trading look at execution quality from the day, week, month before. What we are building are live tools that we can drop and drag into the Bloomberg chat and say to the customer look have you thought about doing this with this ticket in order to get this outcome? For us, over the years we’ve seen lots of client chats become quite dormant. On the buy-side, some customers we speak to have hundreds of chats. For us to be relevant in an electronic space we have to have interesting content. If we can drag and drop a picture with what they should do for that particular order based on 20 days of geometric moving averages which big xyt have worked out for us, that’s extremely valuable.

How do you expect the low touch competitive landscape to evolve in the years to come?

Looking at the McLagan survey numbers for EMEA including UK, the low touch wallet has gone from around 30% to just under 40%. Therefore, having an electronic offering at the centre of a broader execution offering is really important. I’d say commissions have bottomed out on the low touch side and so going forward the way to win in the electronic space is really understand your customer. Customers want to see that you’ve got some academic rigour around your processes and your venue selection as well as a good commission rate even though you’re basically offering a high touch service at a low touch commission rate.

The roles of the traditional high touch sales trader and low touch electronic sales trader role are converging and people are talking about where blocks are traded and how they can optimise their outcome on a particular ticket. We’re going to be producing fortnightly research on what’s going on in the dark venue space. Separately we’ve engaged with another three innovation companies BPX Exchange which is waiting for its MTF licence, OptimX and OneChronos.

What developments are you seeing in commissions?

Large, sophisticated buy-side can build their own algo suite and they’re members all the exchanges so in order to make a new connection you have to stand out on several metrics. Two key metrics are venue reach and customer service. In flight analytics and unique wealth management and retail flow are also key. Typically, a big buy-side customer might have five bulge algo connections and then one or two spaces for companies like Investec where we’ve got an angle or differentiation along those lines. Given the high market share of the cash business here – just under 6% of the FTSE 250 – there’s decent resident flow sitting in ZebrA-X along with other wealth management flow which new customers can interact via our mechanisms.

If you rigorously control costs, you can still create profitable business on a standalone basis. Depending on how you negotiate with venues and exchanges is massively important. No one saying that margins are huge anymore but I’ve seen it done where you can run the business profitably on a standalone basis.

The post Fireside Friday with… Investec’s Dominic Lowres appeared first on The TRADE.

We see a wide range of digital advancements that impact the buy-side, from artificial intelligence to digital asset creation. The ability to adapt and lead will rely on organisations being able to harness a combination of technology and talent in unison. A focus on people, in conjunction with technology, has the possibility to transform workflows, enhance productivity and drive overall growth.

With an undeniable digital transformation upon us, we find a renewed focus on resiliency. This is driven by an overarching business imperative but with increased impetus driven by regulations such as DORA. These regulations emphasise resiliency, prompting businesses to seek solutions that bolster internal operations and ensure the stability of third-party providers. There is increasing scrutiny on outsourcing partners, driven by regulations that prioritise operational resilience and governance.

What do you anticipate will be the main challenges faced by the buy- and sell-side this year?

The main challenge will be to balance opportunity with regulation in a cost-effective manner.  As regulations evolve, businesses must adapt to remain competitive and compliant. This requires a delicate balance: they need to capitalise on opportunities in areas like private credit and alternatives while managing regulatory pressures. The increasing complexity of operations may necessitate greater reliance on third-party services, prompting important questions about their reliability and resilience. Addressing these concerns is essential for maintaining operational integrity and seizing opportunity.

To navigate these evolving regulations, companies must constantly evaluate their technology and operational infrastructures. Regulatory frameworks such as DORA focus on operational resilience and third-party oversight, urging businesses to strengthen their systems accordingly. In Asia and EMEA, customers are adapting to stringent requirements and renewed regulatory reviews, such as those seen with European Market Infrastructure Regulation (EMIR) in Europe. As a result, organisations are scrutinising their partnerships more closely, reflecting a growing focus on quality and stability in a complex regulatory landscape.

How do you expect the disparities between UK and EU regulations to change in the coming years?

In recent months, we have seen an unprecedented amount of geopolitical change – this in turn creates a degree of uncertainty in the world of regulatory change. However, even with this backdrop, I anticipate that the UK will continue to make strategic moves to maintain and enhance its global relevance post-Brexit. While this might involve a closer alignment with Europe in some areas, a key priority will be ensuring that the UK remains an attractive hub for issuing securities and facilitating secondary market activities. A prime example of this is the expected transition to a T+1 settlement cycle, which we believe the UK will advance with swiftly. This change promises to be beneficial for the market – we have already witnessed the smooth transition in the US market. We are focusing on helping our clients navigate this shift and the broader move towards shorter settlement cycles globally. This trend is certainly on the radar for both the UK and Europe, and it will continue to be a focus as we look towards 2027.

The post Fireside Friday with… Broadridge International’s Mike Sleightholme appeared first on The TRADE.

Electronic trading is like Amazon, or the iPhone, or the internal combustion engine: it’s the story of technology writ large, applied to trading.

Like all technology, electronic trading represents a phase shift in productivity. Just as the personal computer compressed work timelines from days to minutes, electronic trading vastly improves the efficiency of trading workflows. What previously required a phone call with humans on each side can now be done instantly and without human intervention. This elimination of friction in turn unlocks all sorts of otherwise-uneconomical market activity. And in a competitive market, once this paradigm shift occurs, all firms are compelled to get on board to keep up. The automation train only goes in one direction.  

The implications of this transformation are widespread.

For dealers and asset managers, technology becomes a core business requirement, and market share tends to accrue to firms with the most efficient and scalable infrastructure. This tends to lead to consolidation, with less scaled players either acquired by larger firms or competed out of existence. This played out, for example, in equities in the 1990s/2000s, where flow used to diffuse among dozens of smaller dealers, but ended up concentrated primarily among a few large tech-driven liquidity providers.  

Greater efficiency also unlocks new business models. For example, the growth of the SMA (separately managed account) industry in the municipal market over the past decade was fuelled in large part by better technology, which allowed scaled providers to efficiently manage tens of thousands of accounts and millions of individual bond holdings. This in turn allowed SMA providers to lower account minimums, expanding accessibility of the asset class and fuelling AUM growth.

At the market level, electronic trading inevitably leads to a reduction in transaction costs, be it in the form of bid/ask spreads or explicit transactional fees. And as trading gets cheaper, you get more of it, leading to an increase in transaction volumes. This increase is often concentrated in smaller increments, leading to a reduction in average transaction size.

Ultimately, the main beneficiaries of electronic trading are investors, who gain better access to a larger selection of investment products at lower cost.  

How important is data when it comes to increased automated trading? What is the key thing that needs to be considered?  

Data is the lifeblood of any automated trading business. But this should not be surprising, because the same could be said for non-automated trading as well.

When a human is deciding how to make a trading decision, he or she relies on prior experiences and information at hand. Where was the last trade in this instrument? Was there any recent news? Is anything interesting happening in related tickers? How much can I generally charge for a trade in an instrument like this? These questions are answered, in one way or another, by data. The trader probably has a Bloomberg terminal with streaming order book data and a news feed. She also has a database, of sorts, in the form of prior experiences and memories.  

Automated trading systems operate similarly. They synthesise various forms of live and historical data into a series of trading decisions. The difference, of course, is that automated systems can utilise much larger quantities of data at much higher precision, and can apply quantitative techniques to such data near-instantaneously. But the general role of data as an input to decision-making is similar.  

The biggest mistake firms make during the transition to automated trading is simply throwing data away. People have limited processing capacity, so firms used to human-driven workflows are often sloppy about persisting the large quantities of valuable data flowing through their businesses. This failure mode is particularly pernicious because once data is gone, it is often only recoverable in real-time. If you need a year’s worth of training data for a new model, and you’ve thrown your prior data away, guess what? You now have to wait a year until you’ve rebuilt that dataset. Not fun.

What are the most impactful changes AI is making on electronic trading, and markets in a wider sense?

First, some terminology. When people say “AI” nowadays, they’re generally referring to a specific type of technology known as a large language model, or LLM. What’s an LLM? Basically, think: ChatGPT.

LLMs are an important development, to be sure. However, they are just one part of a much broader ecosystem of techniques collectively known as machine learning. Machine learning contains various forms of statistical techniques to understand data. The boundary between machine learning and 9th grade algebra is somewhat fuzzy – for example, is linear regression machine learning? But generally the term is used to refer to more complicated techniques, such as neural networks and random forests.  

I highlight this difference between classical machine learning and LLMs because the impact each has had on electronic trading to this point is quite different.

Classical machine learning techniques have been used in electronic trading for decades. They form the foundational building blocks of many trading algorithms. These techniques appeared first in more liquid asset classes, like equities and futures, but in recent years have proliferated in fixed income as well. For example, since bonds often trade only a few times per day (or less), it can be difficult to estimate the “current” price of a bond. Machine learning techniques such as Kalman filters have been applied to this problem for years.

By contrast, electronic trading use cases for AI/LLMs are in relative infancy. Applying LLMs to trading is less straightforward than for classical machine learning, and the reason is in the name: LLMs are about language, whereas automated trading is about math. ChatGPT can write a pretty convincing rap in the linguistic style of Benjamin Franklin, but it’s not yet great at predicting the price of the next bond trade. Direct applications to trading algorithms are therefore still limited.

The caveat is that all of this is changing rapidly. I anticipate more direct applications to trading strategies over time.

And widening the aperture a bit, AI is beginning to have the same impact in trading as in every other industry: as a major productivity enhancer. For example, copilot-style tooling is increasing the throughput of the software developers who write the code behind trading algorithms. I expect this form of impact to grow significantly over time.

Looking ahead to the rest of 2025, what industry developments/market structure changes are you most conscious of?  

The main theme that comes to mind is: we’re so much closer to the beginning of this journey than the end.  

We’ve come a long way, to be sure. In investment-grade credit, for example, electronic trading has grown from less than 10% to north of 50% market share over the past decade. High-yield credit is around 25%, and on a similar trend line.  

But this is just the start. There are many fixed income markets where electronification is just getting started. Municipal bonds, mortgage specified pools, loans, and others are still voice-dominated markets, with electronic volumes below 20%. Will these markets follow the precise path of credit or equities? No. But the direction of travel is clear.

And electronification of trading volumes is just the first step. When execution is cheap and instant, it unlocks forms of market activity that would be otherwise infeasible. For example, in credit we’ve seen the rise of portfolio trading, where hundreds or thousands of bonds are traded simultaneously as a single package. This kind of workflow could not exist without automation. I expect we will continue to see new forms of market activity like this, built on the back of electronic trading workflows. For example, OpenYield (in which, disclosure: my employer, TD Bank, is an investor) is building innovative trading protocols to create a more equity-like experience for fixed income investors.

I am also watching areas of the market which have not yet garnered as much attention. For example, electronic trading is mostly discussed in the context of secondary markets, but not as much in relation to primary markets. The process of debt issuance hasn’t changed much in 25 years. Timelines are long, processes are manual, and underwriting fees haven’t budged. These conditions are ideal for the emergence of a more automated solution. I would not be surprised to see a push into this space in the coming years.

The post Fireside Friday with… TD Securities’ Matthew Schrager appeared first on The TRADE.

If you step onto a broking floor today, you’ll hear the familiar buzz of brokers advising clients and executing trades. However, behind their screens, the technology at brokers’ disposal is undergoing a quiet revolution.  

Communication, connectivity, and clients’ trust are the backbone of our business. We need to be agile enough to meet changing client demands for new products, tools, and services, and to adapt to regulatory changes. Our technology must empower us to meet these needs effectively and efficiently. 

Migrating to the cloud is a game-changer for interdealer brokers (IDBs) and OTC markets. It allows us to leverage the latest technological advancements, like AI and machine learning, to enhance trading efficiency and market insights. The cloud also offers scalable resources that can be adjusted based on demand, and better data storage, management, and analytics. 

Given these benefits, it’s almost a given that any interdealer broker with scale and ambition will migrate to the cloud. That’s why, last December, we accelerated our ‘all in on cloud’ strategy by signing a major collaboration with Amazon Web Services. By the end of 2026, TP ICAP’s IT workload on AWS Cloud will nearly double to more than 80%. 

How is technology changing the role of individual OTC brokers? 

The role of the modern-day broker is multi-faceted. From processing information feeds from multiple sources, to providing market colour, and executing complex orders, brokers must add value at every stage of the transaction life cycle to earn clients’ trust. Technology is a key enabler in this process. 

Platforms built on cloud technology allow us to automate various tasks and workflows. For instance, using AI to derive actionable insights from multiple data sources or automating the trade confirmation process. Essentially, technology provides brokers with the tools and time to better understand their clients’ needs and offer value-adding advisory. This ultimately helps deliver superior liquidity solutions.  

What are the strategic implications of cloud adoption for OTC brokers overall and their clients? 

Fundamentally, cloud adoption can transform the operational landscape for OTC brokers, enabling us to serve clients more effectively and efficiently. For example, our flagship digital platform, Fusion, is fully-cloud enabled, and our collaboration with AWS involves 45 highly skilled AWS engineers working alongside our technology teams to co-develop Fusion. 

By utilising data analytics and generative AI, we aim to enhance developers’ productivity, more than halve new product development times, and improve scalability. This means we can respond to brokers’ and clients’ needs more swiftly by rolling out new functionality onto Fusion faster. Strategically, this enhances seat value for brokers – they want to work with the best tech as it helps them to do more business – and it helps institutionalise client relationships, enhancing sustainable revenue growth. 

As markets and clients evolve, so do we. The cloud provides the technology infrastructure necessary to stay ahead, ensuring we continue to deliver superior liquidity solutions and brilliant client service. 

The post Fireside Friday with… TP ICAP’s Max Spoto appeared first on The TRADE.

Before answering this question, let’s look at the key drivers transforming fixed income markets. First and foremost, the pace of electronification has been growing rapidly. Looking at trading activity on our platform alone, average daily volume in 2024 across Tradeweb Markets was 55.8% year-over-year, and overall volume processed on our platform now surpasses USD 2 trillion each day, which is really incredible. Secondly – and partly due to an increase in passive investment strategies – there has been a rise in portfolio trading, where a basket of bonds can be traded in one go with a single counterparty. Furthermore, when you look at the regulatory environment, there has been a wider push towards more transparency.

Electronification has led to digitisation, which in turn has spurred the growth of fixed income markets. This has led to more data being available, which in turn helps boost liquidity and subsequently more trading, and the continuation of this upward cycle of growth.

When we think how this data can be used to further modernise fixed income markets, we look back at our long track record of collaborative innovation with our clients. We keep asking ourselves how do we find new ways to advance trading and help to solve the problems they may face.

A good example of this approach is our Trade at Close functionality. Our clients told us they wanted to be able to execute trades when markets closed, but they needed a benchmark rate in order to do that. Since we had partnered with FTSE Russell in 2017 to take over from the UK DMO the calculation and publication of the official closing prices for UK Gilts, we were an obvious partner to deliver a solution. We have since launched benchmark closing prices for US Treasuries and European government bonds, and we have also expanded the methodology for UK Gilts to include bid- and offer-prices.

In the US, another pain point we solved for clients was the inclusion of less liquid securities in their portfolio trades on the platform. Before incorporating them in their basket, investors needed a price for every line item in that portfolio. By leveraging our Automated Intelligent Pricing (Ai-Price) tool, which uses advanced AI techniques and machine learning models, we were able to predict the price of a security based on information available on our platform, as well as from a number of public sources. As these less liquid securities begin to be included in portfolio transactions and trade, it leads to an uptick in liquidity from these discoverable prices.

Lastly, in Europe, there was growing demand from institutional clients for real-time Indicative Net Asset Values (iNAVs) for exchange-traded funds (ETFs). They enable investors to efficiently evaluate their positions, make better-informed trading decisions, and enhance their transaction cost analysis (TCA). So, in 2023, we partnered with BlackRock to deploy our iNAVs across their entire iShares ETF suite in Europe, using real-time prices from our trading platform. We now run over 900 different ETFs simultaneously, providing intraday indications of an ETF’s value based on the market price of its constituents, thus creating a more immediate and realistic view of the ETF market at any given point in time.

These examples are the key pieces that Tradeweb has built into our toolkit for investors to help to modernise fixed income markets.

What are the most impactful changes AI is making on electronic trading, and markets in a wider sense?

First, let’s separate out the traditional AI that is linked with machine learning, and the more nascent generative AI that has been proliferating in recent years. We have leveraged AI for building several of our pricing models and creating predictive execution algorithms, as well as to predict volumes on the platform. These tools have become more sophisticated, more precise and used more broadly in the industry.

Meanwhile, generative AI is largely being used as a productivity enhancement tool, with one of our largest use cases right now being code writing. We believe we may see that area broaden to what’s called agentic AI. These are tools that are built for a specific purpose and help automate what was previously more of an administrative function. We are only at the tip of the iceberg for how generative AI tools will be used in the future, and there are a lot more use cases that we are exploring.

It is important to note that these tools are not perfect. They can help with a lot of administrative functions, but they can sometimes hallucinate and produce incorrect outputs. There are ways to decrease that and make the models more precise and reliable, but that takes work and time experimenting as well. Overall, we are seeing the democratisation of information and access to that information. These tools make it easier to get not just data, but information too. But, we should bear in mind that although AI is an incredibly useful technology, it is only as good as the data that feeds it, so having high quality data is especially important.

What are the main benefits of using benchmark closing prices?

It is broadly understood in fixed income markets that evaluative prices lack precision. Prices are a really basic thing in the industry; they are part of the plumbing that keeps everything going. It is crucial that market participants have access to benchmark closing prices that are both accurate and reliable. The Tradeweb FTSE Benchmark Closing Prices serves as key market indicators and risk-free benchmarks that have been built in accordance with the EU and UK Benchmark Regulation and the IOSCO Principles for Financial Benchmarks.

We have a fully disclosed methodology that is published on the FTSE Russell website. Tradeweb is the calculation agent and FTSE Russell is the benchmark administrator. Their role is to verify that we did everything we said we would do. Having that third-party validation is really important to ensure that all the necessary steps were completed correctly.

Our prices are created out of actual streaming quote data from the Tradeweb platform. They are fully automated, so there is no human judgement determining what they should be. In FASB Fair Market Value regulation, specifically FASB 820-10, a Level 1 price has to be created out of quoted data from an active market. We understand from several market participants that our prices qualify for Level 1 status under that regulation, which is an important differentiator from evaluative prices that would not be eligible for this distinction.

We also do extensive back testing of our prices and can produce quantitative measures of how close these prices are to actual trades that occurred in the market at the time of the close. This additional data, coupled with the rigorous information that we can provide on them, can help participants who are regulated under Rule 2a-5 from the US Securities and Exchange Commission (SEC) to comply with providing greater detail on why the prices they are using are actually of high quality and appropriate for their use case.

Other benefits of our benchmark closing prices is that they can be used as reference rates in derivatives contracts, and can also be used for investors’ trade-at-close strategies. Moreover, as the prices are derived from actual real-time data on our platform, there should be a very minimal difference between what was actually occurring in the market at the close, and where the ending closing price is. This helps market participants, especially portfolio managers, to reduce both the noise in their portfolio and in their portfolio tracking error overall.

How exactly does publishing these prices 15 minutes earlier positively impact participants as regards their portfolios and trading strategies?

Expediting the publishing time of the Tradeweb FTSE UK Gilt and European Government Bond benchmark closing prices is a really exciting development and a significant step in further expanding our benchmark pricing capabilities to meet growing client demand. It enables market participants to complete their end-of-day trading strategies earlier, mark their books faster, and update their risk positions and portfolio valuations earlier.

This development is a reflection of Tradeweb’s ongoing commitment to enhancing our modern fixed income toolkit for institutional investors worldwide. By amplifying the information available to fixed income market participants, we aim to bring more transparency and efficiency into our space.

The post Fireside Friday with… Tradeweb’s Lisa Schirf appeared first on The TRADE.

I think it’s similar to 2024 to some extent, the main challenges are going to be political and macroeconomic uncertainties and how that will impact traders’ trading strategy. In 2025 we could have a bit more clarity than we had in 2024, with the US election – a big topic – now being decided. But other things such as the war in Ukraine, and the situation in Gaza and Israel are still developing, so I think we are looking at a bit more certainty, but it’s still a market of unpredictability – a main challenge for traders. 

Another point relates to more than just their trading activities, it’s more about how it’s going to impact their preparation for their long-term strategies. Looking at how predicted trends are panning out is more important than ever, for example increased focus more on emerging market markets and the nuance and technological needs are paramount.

Financial products are different in EM than in developed markets where products are more electronic, with more high frequency trading, etc. It’s all highly dependent on macroeconomics and political uncertainty. 

What can we expect to be prioritised on the regulatory front this year?

There are a few big regulatory changes which are probably not going to go live in 2025, but will need technological and infrastructure-related preparation and change before 2026 and 2027. 

The first one is the move to T+1 settlement in the UK and Europe. We already know the date – 11 October 2027 – less than three years away and people will need time to prepare, which means that the work should starts now.  

The second big one is the creation of the consolidated tape in the UK and in Europe for bonds, and then equities followed by the derivative products. People will need to start getting ready to look at the data, connect to the CTP in Europe and in the UK and they will need to reassess how it will impact their business model/trading activities. The first deadlines are coming in next quarter so it’s something important to put in the roadmap.

The third topic is artificial intelligence, with the implementation of the AI Act in Europe and potentially similar initiative happening in the UK means that AI is going to remain a big topic impacting the financial market industry. I would advise watching what the regulators are going to implement and also prepare your trading activity for that impact.

Number four that I’d put on my list is the current consultation by IOSCO on pre-hedging activities cross-asset. This one will take time before it goes to national regulators so probably another year or so away, but I think if you don’t engage with these early consultations it may impact your trading activities.

Overall, both the UK and Europe also have a competitive and growth agenda and it is going to be a necessary focus on simplification of existing regulation – to streamline processes and make it easier for market participants.

When it comes to EU and UK regulators, are these converging or diverging? What’s the outlook for 2025 and beyond? 

It really depends on the topics. In the last two to three years, the two sides couldn’t speak too much to each other until 2024, where this started to change. A good example is the T+1 reduction of settlement cycle for securities markets – where there needs very strong alignment between UK and Europe for the European time zone to be able to converge on the date of application. So convergence makes a lot of sense as the industry pushes for it and conversations are particularly important when it comes to project implementation. 

Another area where convergence is needed is potentially AI regulation. There will be differences due to the fact that Europe is more prescriptive into the way they make regulation, where the UK is going to focus on principle-based regulation. We can already see where Europe is heading with their AI act which was quite prescriptive.

In addition, digital assets could be something similar where the industry will need a global approach. Better alignment is a positive approach.

For this growth of competitive agendas into the UK and in Europe, it’s key to make sure that there are consultations on both sides and market participants can take a very key role there, through their trading associations, or through talking directly with regulators. When you look at an asset manager, pension fund, or bank, most of them who are in the UK also trade in Europe, so that’s why it’s such an important topic to discuss. 

How is the role of technology changing as market structure develops?

I think it’s even more important than it has been in the past. If you look at the last 20 years, where the traders could add a much more important role than the technologies that was supporting them, now it’s almost the opposite – you can see the rise of technology in the way that traders develop new trading activities very clearly and market structure is an important part of that. 

For me there are three key levels where market structure is vital.

Firstly, the technology focus – a company needs to have a very strong technological foundation, a sound system which is solid but flexible. Some companies are still playing catch up when it comes to their technology architecture level and it’s only when you have some technologies like that in place that you can move to the second level, the data. 

It’s increasingly important in financial market to become a data-led organisation, and it is about usage of internal data versus external data, and how to use your own data to develop clear and unique insights. That’s why the consolidated tape in the UK and Europe will be a very big added value for the market. 

The third layer, which I see is how AI can use this data layer and people are starting to realise the importance of the potential impact of AI in their business model. If you don’t do it, others will take the lead. We already see that in the very liquid instruments like equities, but it will develop in other asset classes like bonds.

Using technology, data and the intelligence layer will increase your productivity – which is where you already have developments like algorithmic trading. In that instance, of course, it is more developed in some asset classes than others, but development is these capabilities is happening. Then comes the artificial intelligence aspect, how the newest innovations in the future can pragmatically help traders and market makers. Essentially all are ‘efficiency tools’.

Suppose that you have a good technology foundation, a good data foundation, the focus must then become how do you make sure that your team are extremely efficient going forward. That’s the key to making the most of technology as market structure continues to change.

Malrait is set to join Etrading Software as chair of its industry stakeholder group (ISG) on the consolidated tape (CT) on 20 January, as revealed by The TRADE on Monday 13 January.

The post Fireside Friday with… ING Bank’s Stephane Malrait appeared first on The TRADE.

The main trend we’re observing is the increased demand for market data globally, particularly from international investors wanting access to US and European markets. In the third quarter of this year, Cboe saw 40% of our data sales coming from outside the US and we expect that to continue.  

This demand is being driven by global interest in the US market – investors want access to the outperformance of stocks like the ‘magnificent seven’ – as well as the expansion in retail trading across the globe. In Europe, we recently published our first retail survey with The Options Institute, Cboe’s education arm, and the results suggested a strong interest in exchange-traded equity options but that more education is needed. This could signal a shift of European retail investors from OTC leveraged products like CFDs to exchange-traded derivatives. Both trends are necessitating access to robust and reliable market data.  

Also, we’re seeing notable demand for our European equities data in Asia Pacific, as brokers look to offer a broader range of securities to their customers. Our strong market share in European equities and high levels of market quality makes our data attractive to these firms. 

What are some of the changes impacting how market participants are consuming market data, both in Europe and globally? 

As we look to enhance the distribution of our data globally, it is becoming even more apparent that customers want to consume data as seamlessly and efficiently as possible. One way to achieve that is by offering flexibility in the way customers access data. At Cboe we do that by making our own data available through various delivery mechanisms, including via cloud, helping to ensure lower infrastructure costs for those consuming it. Our North American, European and APAC equities data is available via the cloud, and we’ll be looking to bring on more content to meet the growing demand we’ve seen.  

The other change that will impact consumption in Europe is (finally) the introduction of a consolidated tape for equities. Incumbent European exchanges, through their operation of closing auctions and in the absence of a consolidated tape, enjoy a dominant position in the provision of market data to the institutional community. We believe the introduction of a real-time pre- and post-trade consolidated tape in both the EU and UK will be key to introducing a competitive dynamic in the provision of market data. It’s one of the reasons we launched SimpliCT in conjunction with Aquis Exchange to explore a bid for the CTP.  

Finally, there is also new regulatory technical standards from ESMA on what constitutes “reasonable commercial basis”, the principle by which market data is to be priced by EU exchanges. The final text came out this week and whilst the industry is still analysing what it may mean, it has the potential to change the market dynamic and licensing constructs we’re all familiar with today. All in all, 2025 will be an interesting year in Europe!  

What are some trends you expect to see in 2025 when it comes to market access? 

As with market data, customers are looking for better, globally consistent and more efficient services from their key providers when it comes to market access. Something that we have been really focused on is offering an enhanced access layer architecture for equities and options markets across the globe. 

Cboe has presence in 27 markets across five asset classes and all those markets now sit on one common technology platform (except our Canadian exchange, set to be migrated in 2025). One of the benefits of having a single technology platform is the efficiency and globally consistent experiences it allows us to offer. It creates an ability for us to launch something in one region and then easily replicate it in another. For example, ‘dedicated cores’ allows members and sponsored participants to host their specific logical order entry ports on their own CPU core(s), rather than sharing a core(s), which reduces latency, enhances throughput and improves performance through increased determinism. Dedicated cores is an optional service and Cboe will continue to offer shared access, as some customers will always want that service. 

We rolled this service out in US earlier this year and are now in the process of expanding it to Europe and Australia.  

What areas of the business is at the fore of Cboe Data Vantage’s priorities for 2025 and beyond?  

Cboe’s newly branded Data Vantage division better reflects the broad spectrum of services that were formerly part of our Data and Access Solutions business. Our priority is to continue to meet demand for data, access and analytical services through our three distinct pillars: risk and market analytics, Cboe global indices and market data and access services, along with the newly defined client experience arm, which will help our clients navigate the evolving landscape. 

We see Europe and APAC as key areas of growth for this business. Given that data is a precursor to trading, our focus is to leverage Cboe’s leading position in multiple asset classes around the world to export our data globally and import trading into our markets.  

There are lots of exciting projects on the horizon. One trend we’re leaning into is the desire of participants to consume more data and insights through cloud-based marketplaces rather than file-based delivery. As a result, Cboe offers a range of delivery methods for its historical and derived datasets and recently we made some of that data available within Snowflake to increase access to that data. We’re working with other vendors such as Google and AWS to do the same thing. 

Another significant trend we’ve seen in the US and has the potential to take off in Europe is the rise of defined outcome ETFs, an ETF with a derivative overlay with a defined upside whilst offering downside protection. Our Cboe Global Indices business has been a leader in this space and has developed the capabilities to deliver some interesting indices for our customers and issuers.

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Technology is transforming the industry including buy- and sell-side relationships. On the buy-side, ongoing market fragmentation in trading is forcing a continuous optimisation of sell-side relationships to reach all relevant liquidity pools available and guarantee best execution for their clients. This development is leading to more electronic interaction between buy-side counterparties, which requires the sell-side toward greater specialisation in order to deliver value. Also, AI will enhance this trend and the changes coming could be quite significant or even paradigm shifting.

How can you maintain relationships in a tech driven world to promote transparency, collaboration and market resilience?

Maintaining personal relationships is essential in a tech driven world both to establish a bond of trust with a client and grow that relationship. Real-time responsiveness, 24 hours a day, is most important. And tech tools enable that. But they also promote transparency which is key to trust building. For example, high quality TCA solutions enable the systematic review of the quality of trade executions, and that promotes a continuous conversation/discussion with sell-side counterparties to optimise execution outcomes.

Ideally, tech-driven solutions should also help to optimise and simplify workflows and create a systematic approach that benefits counterparties and achieves the best possible execution outcome.

What sort of technologies are needed/exist to mutually benefit buy- and sell-side participants?

There are a number of useful tools available today. For example: Block-Crossing Network (BCNs) helps connect different counterparts and achieve the best possible price and at the same time minimise overall market impact; improved FIX versions help to exchange as much useful information as possible between different market participants; TCA solutions help achieve trade transparency, best execution controls, and at same time enable, continuous learning from the data created and improve the trading processes.

Technology enables trust building by promoting instant connectivity and transparency. Today, more data is available for all sides to analyse, discuss and optimise execution outcomes.

How do you pick and choose the right tech for your desk?

Our view is that the best way to pick and choose technology is to build it yourself – it ensures that it is built to your exact specifications, as we have done over the years with our own global OMS Bedrock. With the advent of AI that should be more easily done in the future but most firms don’t have that ability now and need to rely on traditional vendors. Engaging with software providers and keeping abreast of new modalities as well as getting client feedback on best in class trading technology is the way to gain knowledge to consider new trading software.

Does increased technology mean the buy-side relies on the traditional sell-side less?

Already electronic execution and direct market access has reduced the reliance on sales traders to source liquidity. AI will likely cause an increase in the use of sophisticated technology where trader’s jobs are supplemented by machines and trades will simply be monitored by human traders. The reliance of traders as we know is likely to reduce over time as one trader will be able to efficiently handle a large number of transactions.

What is the ideal structure for a trading team in today’s world?

A trading team needs to be cohesive across time zones and work together and not have a siloed approach. This is paramount. The global team increasingly needs to work 24 hours as exchanges are likely to be open for longer hours – there is a possibility for exchanges to open 7 days a week!

Although hours of trading per week will likely increase, as trading tools improve, trading decisions can be made by rules-based programs, leading to reduced number of traders involved. Having said that, human traders will still be needed although their focus will be titled towards monitoring.

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We’re very much looking forward to our launch on Monday (9 December) and are definitely optimistic. We have a good mix of clients – both international and German – who are ready to start from day one. 

Once we got approval from regulators on 28 November – who of course look into every detail which takes time when it comes to Q&As etc. – we allowed time for everyone to get prepared. 

The banks and proprietary trading firms who are ready to go have more than 40% of the market share on Xetra today, and we also have some more in the pipeline that are interested and in preparation. 

We will see how it goes on Monday and the first weeks after launch, but we have a good idea of how liquidity in the midpoint book will evolve. As you know we have two order types, the sweep orders and the midpoint orders. Midpoint orders stay in the midpoint book if they are not immediately executed while sweep orders go directly to the lit book in case they don’t get executed in the midpoint book at entry. We actually designed this in a way that makes it a pure upside to use the sweep option compared to a regular order that you would send directly to the lit book: it has no latency disadvantage and it costs you the same.

One step further, if you’re lucky, you can find a price improvement saving half the spread compared to the aggressive execution in the lit book. Therefore, we expect that sweep will be used heavily even if not at all times. It’s an interesting offer where you can use the sweep functionality with no disadvantage at all and then the midpoint orders that will be passively written in the book will not have to wait for long to get executed. 

In terms of the initial launch, we’re also starting with an attractive incentive programme for the midpoint orders to start with, just to ensure maximum efficacy. 

We’ve previously spoken about the idea of an integrated approach to dark trading, why is this important?

I think it’s very important because when we took the decision to enter that segment it’s not an entirely new thing. There are dark pools all over the place but being the reference market (source for reference prices) is unique and allows us to tailor in a way that others simply cannot. 

First of all, we have the real time midpoint prices that other venues also have to use so whenever an external dark pool offers trading in German equities they have to use those prices in order to calculate that midpoint and technically we have those prices without any delay.

This also means there’s no stale pricing, and thus there’s no risk that you have some players in our dark pool that have information advantages over others. This is different from external venues to which a latency arbitrageur could leverage a faster private connection in order to have information on changes in the reference price first transported to that venue before the reference price is even updated there. 

The midpoint book is hosted on the same machine as the lit and incoming order messages are being sequenced strictly across both those books and we can process the sweep order execution in one matcher transaction.

That means in the midpoint book where it might find some immediate execution there and then it goes to the central limit order book. Essentially, it’s only one transaction and only after all those things have happened the next order message is being processed by our matching engine. Therefore, there’s no overtaking. I think that’s compelling.

Can you tell us more about how this is a client-led development?

The idea was born back in Spring 2023 when some of my colleagues came back from a roundtable with some clients and debriefed that midpoint was something we should be looking into.

From there it was basically a joint brainstorming between some clients and us on how we could best leverage our position as reference market and importantly how we could do a complementary offering to others that already exist.

Following that comes finding a release time. We have many ideas and allocate our developer resources carefully at our company that it’s almost like an internal competition as well when it comes to what can be prioritised, but here with clients so involved of course we are focused here. At the end of the day, it’s a business case and when it comes to meeting client needs it’s a back and forth – inspired by an initial idea and then build upon. 

Following the roundtable, we continued bilaterally with those clients we felt were most interested and most committed to providing their insight, really digging into what exactly they wanted from this. 

What are the main technical challenges Deutsche Börse is prioritising when it comes to further enhancing dark trading? 

There were a couple of functionalities and features that we developed, guided by our clients, that we tailored especially for the special needs in midpoint trading. One of the priorities for example is that we have a minimum acceptable quantity (MAQ), something that when we consulted clients was flagged as essential.

Next thing, our clients were very specific on wanting dedicated MIC codes for the regulatory reporting. Essentially all the transactions from our midpoint book are reportable under a dedicated MIC only for this purpose. 

Third, it may seem like a small detail but also an interesting thing when it comes to user friendliness: We’ve learnt that clients, if they use the sweep order, want to do it without even looking at the specific situation or the specific instruments. The result is that on Xetra Midpoint you can use sweep orders even in instruments or at times where the midpoint book is currently not available, without getting an order reject – it will simply be routed to the lit book. 

Another focus is on self-match prevention, as exists in our lit books. Instead of re-using our existing functionality, we learned that actually it’s much more efficient in midpoint trading to use a “cancel passive” logic that allows a trader to switch from bid to ask by simply sending a new order that will automatically delete the older orders marked with the same ID on the other side while the new order is entirely sustained.

And last but not least, the matching algorithm that we use in our midpoint book is different from our central limit order book – optimised to maximise executable volume, reflect individual execution constraints such as MAQs, and checking for potential executions not only when new orders come in, but also if the reference price changes.

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Automation and electronification has brought a number of changes, one of which has been the large increase in volumes. There are various reasons for that – the obvious one being that you can do more with less when you apply computers to a problem like this. Trading desks have got smaller over the years, while volumes have gone up.

Another manifestation is that trading has become more widespread geographically. At one point, if you wanted to trade a German stock, you had to be in Germany and if you wanted to trade a Thai stock, you had to be in Thailand. Today, you can pretty much trade anything, anywhere. The electronification of the market has brought about that change as well, which has allowed money to flow around more broadly. 

The third evolution has been around different trading models. If you go way back, 30 years plus, trading – even on exchanges – was broadly manual. You basically phoned an order through onto the floor of the exchange and people negotiated prices and so on. Since then, central limit order books have come in, around 30 or so years ago. Electronic access to those came with it and we’ve seen evolution of market models ever since, because it’s relatively easy to program in software changes to these types of systems to give you periodic auctions and all these different ways of trading that simply wouldn’t have been possible by hand. 

What are some of the good things that we’ve lost and/or gained in the past three decades?

Starting with the gain, the obvious one is cost. This evolution has certainly helped facilitate dropping commission rates pretty much across the board, particularly in the more agency-style business because again, you could do more with less and new entrants coming in and competitive pressures and the rest of it. Ultimately, trading has become a lot cheaper.

There’s certainly been concerns raised over the years with certain types of trading. I think it’s safe to say that some of the high frequency markets had a bit of a bad reputation, perhaps in the press, for good reasons or bad. It’s certainly caused a lot of changes and people have had to adapt to that. The days when you could simply just put a large order directly on the market and the market would just deal with it, things have changed. You need to be a bit more careful and a bit more considerate about how you interact with the markets.

Of course, the flip side of that is that doing so is much easier because the technology around, and indeed the experience around to interact with the markets, in this new world, is there and is available for a large number of participants at good prices. So I think those things have changed and it’s also safe to say that the electronification of markets and indeed trading in general works best for liquid instruments.

Liquid listed derivatives, liquid shares and so on, they have really ridden the wave of this very effectively. When you get into other asset classes, it’s less obvious that electronification makes a material difference because there’s so much manual processing anyway. There are still advantages, not least of which being that you take away rekeying risk and things like the error rates of trading can come down, and indeed have come down. That’s a big boon as well. But whether you see the same sort of change in volumes and trading styles in some of these instruments or not, that’s yet to be seen. We haven’t seen an awful lot of change in a number of asset classes over the last few years. 

Alternatively, what are some of the bad things we’ve lost and/or gained over the same period?

I don’t know if there’s anything particularly that we’ve lost, however one thing which comes up in conversations every now and again is this slight worry about whether we are losing any skills in the industry. This is a general theme which crops up not just with the electrification of trading, but also with the younger generations coming to the markets in a much more technologically driven environment. Also, with artificial intelligence coming in and being able to take on some of the heavy lifting.

In a way we’re exposing ourselves to a potential risk that we have less experience and knowledge, particularly for dealing with tricky situations on the trading desks. That’s something which I think we as an industry need to make sure we’re very mindful of and act against. Not incidentally by not adopting these technologies or indeed hiring younger people, but by making sure that we have training and we keep the handing down of knowledge going. 

Looking forward, how do you expect the trading landscape to shift in the next 30 years?

We will see in some ways more of the same. There will continue to be evolution and innovation in the markets and people will try new things. AI of course is something everyone needs to keep an eye on as to what various types of AI will allow you to do or enable you to do in the world of trading. Even if it’s just supporting the process in terms of workflow management and pre-trade idea generation, or even if it doesn’t actually make it the trade process itself. We will see more of that coming through as well. It’s also safe to say that newer technology such as blockchain, distributed ledger technology and so on has yet to make a real impact in financial services. We’re probably going to see that becoming more mainstream in the near future, because of the possibilities that provides to simplify a lot of processes.

Beyond that, very hard to tell. I think it’d be very hard to tell 30 years ago where we would have ended up now. People probably predicted fewer traders – with some people even predicting no traders – and that turned out to be completely wrong and a good thing too. I wouldn’t want to say in 30 years’ time we’ll have no traders. We’ll probably see a continuation of what we’ve got today, wherein skill set and the role of traders changes over time – with this probably becoming more technology-based. But we’ll still have traders. We’ll still have trading. There are the larger scale changes that technology will help bring, not least of which being perhaps bringing more cross asset trading together, as the barriers between these asset classes breaks down and technology helps that. Also, with people becoming more adept at managing different types of asset classes as part of their day job. I can see that trend continuing.  

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