Europe has a complex market structure with multiple exchanges, clearing houses (CCPs) and central securities depositories (CSDs) – each with different operating models and regulations. Unlike the US where DTCC provides a centralised clearing and settlement system, Europe’s diverse infrastructure makes coordination more complex. Many European trades involve multiple currencies and jurisdictions, requiring FX transactions – the shorter settlement time reduces the time to arrange funding and collateral.

The Central Securities Depositories (CSDR) in Europe includes a mandatory buy-in regime which is not present in US. Differences in regulatory frameworks across EU Member states could create inconsistencies in T+1 adoption. Coordination between ESMA, national regulators and industry bodies will be essential. 

How important is global cohesion?

The misalignment of settlement cycles between countries that adopt T+1 and other jurisdictions could present some operational challenges. This is a key catalyst for other markets to optimise operational frameworks and ultimately accelerate settlement cycles to a T+1 global standard. 

Improving global securities markets remains challenging as broad industry coordination is required to address related operational topics. In Europe, the trading and settlement infrastructure is more complex than in the US, spanning several jurisdictions, with 41 trading exchanges and 31 central securities depositories.

To make T+1 feasible on the continent, any adjustments to post-trade infrastructure, updates to technology systems, or further automation of trade processing would need to be synchronised across these constituents, as would the timing of cross-currency transactions.

Is preparedness an issue in APAC/Australia – will there need to be major changes made to comply?

Preparedness is key, and as with markets that have transitioned there will need to be changes. However, the progression towards T+1 is increasingly a well-trodden path. 

This transition is not a competition but a matter of readiness and evolution in operating models. The choice of settlement cycle depends upon market segment, asset class and transaction nature. Markets that leverage this change can reap immense benefits such as advanced operational efficiency, faster settlement and reduced risks associated with market exposure.

The move for India towards T+0 settlement is driven by retail investors and the pre-funded, pre-delivered market structure, contrasting with the intermediated institutional market in the West.

When APAC countries also move to T+1, what are the potential issues which could arise?

Some of the challenges and concerns associated with T+1 include operational challenges, most notably a shorter processing time. This increases the need for automation to streamline post-trade processes. Global investors and cross-border transactions may struggle to meet the accelerated timeline.

A specific point for AU/NZ Managers is that for any AU/NZ clients currently doing processes early on T+1 local time to cover US market close, it will be pretty much impossible to meet the UK/EU timelines which are two to three hrs earlier. This further promotes the need for either a global footprint, or to outsource to firms who have one and can meet regional cut-offs.

It’s also important to note liquidity and funding issues – investors who need to convert currencies may struggle to do so within the day. The shorter cycle may also require firms to post margin or collateral more quickly.

There is also the topic of impacts on international investors to APAC markets with a narrower window to process trades, as well as lending of securities potentially needing to be called earlier if selling a stock that has been lent out, and the risk of more frequent trade breaks with less time to correct errors. Firms settling trades will need to do so in a timely manner to avoid possible regulatory imposed penalties.

What is the impact of fragmentation, both across APAC – including Australia, and Europe?

Fragmentation poses a number of risks, most notably cross-border settlement risks with markets on different settlement cycles – foreign investors may struggle with liquidity and funding mismatches. Also, FX and liquidity management wherein shortened settlement cycles puts pressure on FX funding, as most markets still remain on T+2. Here there may be a need for pre-funding certain trades. In addition, market participants, custodians, brokers and managers need to adjust their processes to ensure reconciliations across the various settlement timelines.

It’s also important to note that differences in countries’ regulatory frameworks may exacerbate fragmentation, most notably reporting and compliance frameworks. 

What’s the best way for managers to mitigate risks as the world increasingly shifts to T+1?  
 
No single asset managers operating model is the same, every one is nuanced so the response to T+1 needs to be tailored.

We have been encouraging our clients to scrutinise the entire life cycle of the trade, as well as anything manual, every process and every exception. Data hygiene is imperative – analyse and clean static data and maintain regular reviews to reduce the chance of trade breaks.

Automation and STP is becoming an absolute pre-requisite, and if you can’t resource for it an option is to outsource it. At Northern Trust Securities we have seen a marked increase in component outsourcing, i.e. the outsourcing of a region where you don’t have presence, or you find it challenging. We have seen an increase in offshore managers outsourcing their US flow in response to the tightened settlement, trade matching and settlement, and trade related FX. 

The post Fireside Friday with… Northern Trust’s Rob Arnott appeared first on The TRADE.

Market structure changes, particularly regulatory reforms like Mifid I and, more specifically for ETFs, Mifid II, have significantly reshaped the European ETF trading landscape. Mifid II disrupted the dominance of traditional stock exchanges by opening the door for alternative trading venues, increasing competition, and expanding investor choice. However, this democratisation has also led to market fragmentation, with ETF trading now spread across multiple platforms and exchanges.

In Europe, multilateral trading facilities (MTFs) have emerged as key players. These MTFs can make execution quicker, potentially more efficient, and transparent, giving liquidity providers access to streamlined trading and offering clients pre-trade pricing transparency. At the same time, the emphasis on ‘best execution’ has driven more complex and fragmented market structures, with many algorithms now ready to help capture fair value trading via all lit, dark exchange executing venues. All aiming to ensure investors fully leverage the ETF wrapper’s trading characteristics for better trading outcomes wherever they choose to execute.

What’s next for the ETF landscape, particularly in fixed income?

The ETF market continues to expand at a rapid rate, and there are some exciting trends shaping its future. One of the most significant growth areas is within fixed income. For me this is where the ETF wrapper has created real structural change. Unlike stock markets, which have well-known centralised exchanges (e.g., LSE, NYSE, NASDAQ, etc.), the bond market operates differently. There is no single centralised exchange for bonds. Instead, bond trading occurs primarily in decentralised, over the counter (OTC) markets.

ETFs have indirectly evolved this market structure, taking an opaque over the counter market and successfully placing this on the same well-known exchanges around the world. ETFs’ success in evolving this market structure has created more price discovery within the fixed income asset class that has become evident after recent stressed market periods. This price discovery and execution transparency for fund assets is something only possible with the ETF wrapper. For this and more we believe the ETF wrapper will become mainstream for both passive and active fixed income pooled investment.

How does ETF activity differ between the US and the UK, and how do they interact?

In the US, about 70% of ETF trading happens on exchanges, while 30% is over the counter. In Europe, including the UK, it’s the opposite: 70% of trading is OTC, and only 30% is on exchanges. The US is the global leader in ETFs, with around 4,000 ETFs and about $10 trillion in assets, making up 70% of the global total. Europe, including the UK, has about 3,800 ETFs with $2.4 trillion in assets, which accounts for 16% of the global total. The US dominates ETF trading volume, handling over 80% of total global ETF trades, while Europe accounts for just 6%.

However, European ETFs grew faster than the US market in 2024, with a 33% increase in assets under management compared to a slower growth rate in the US. Despite this, ETFs still make up a smaller part of the retail investment market in Europe compared to the US, where retail investors play a more active role in ETF trading.

What are the nuances of how ETFs are, and will be, traded?

There are a few different strategies for trading ETFs, each with its own pros and cons. You’ve got NAV trading, risk trading, and agency/algorithmic trading. Some key tips for trading ETFs include knowing the best time to trade, considering your trade objective, choosing the right order type, and making sure ETF is trading close to its fair value.

ETFs can be traded on various venues, directly with brokers, or OTC via the MTFs mentioned earlier. This trading and liquidity flexibility is again a key catalyst for further investor ETF adoption, as many traders and investors continue to look for differentiating approaches to portfolio construction, execution and risk management.

How does ETF liquidity perform during times of market stress?

During periods of market stress, ETF liquidity can be a critical lifeline for investors. The structure of ETFs, which allows for continuous trading and relies on market makers to maintain liquidity, enables them to function even when underlying markets face pressure.

A prime example of this occurred during the pandemic in March 2020, when global markets experienced significant turmoil. While underlying bond markets became illiquid, fixed-income ETFs continued to trade actively on secondary markets, despite trading at record discounts to their net asset values (NAVs). This demonstrated the resilience of ETFs, as they provided investors with access to liquidity and price discovery when traditional markets froze.

The role of market makers and the ability of ETFs to aggregate liquidity across a basket of securities were key factors in their ability to remain functional during the crisis, solidifying their importance as a reliable tool for navigating market uncertainty.

The post Fireside Friday with… Franklin Templeton Investments’ Jason Xavier appeared first on The TRADE.

Futures and options are among the world’s most liquid markets, where traders, investors, producers, banks and institutions turn to discover prices, pursue opportunities and manage risk on everything from interest rates, equities, foreign exchange, and commodities. 

For our clients, this is a time of unparalleled uncertainty where risk is widespread – everything from constant macro-economic shifts to rapid geopolitical change and extreme weather events. Exchange-traded derivatives play a vital role in helping institutions worldwide manage these risks in regulated markets.    

As the head of EMEA for CME Group, I’m focused on our diverse client base in the region where use of our products is expanding rapidly as clients respond to global and regional risks. In February, we saw 7 million contracts traded daily from this region, a 17% increase from last year. Clients here face a more complex interest rate environment. As a result, we’re seeing increased participation, particularly from hedge funds and asset managers. 

With increased market volatility, how can traders and institutions effectively use derivatives to hedge risks?  

Futures and options are designed to help clients efficiently manage risk in any market scenario, but they’re particularly critical in volatile markets. This year, market participants have been active across all asset classes. US Treasury volumes have surged as market participants assess inflation and US debt issuance. FX futures and options volumes have risen with significant dollar movements against major currencies, and open interest has hit record highs.   

Traders and institutions need products that trade around the clock, around the world, as it allows them to respond to news and manage risk in real time no matter their location. For example, after the US election results, we saw over 865,000 equity index options traded before the US equity markets opened as investors responded to the results. Similarly, on 27 January, during a tech stock sell-off, over 750,000 contracts traded outside of US market hours. 

Given the growth of digital asset derivatives, what do you expect the future of regulated crypto futures and options to look? 

Digital assets are evolving into a more mature and resilient asset class. We see increased institutional trading in our products and the deployment of sophisticated trading strategies. Exchange-traded derivatives are now an essential component of price discovery, providing a regulated and transparent market with standardised reference rates. 

February was a record month for CME’s cryptocurrency products, with an average of 221,000 contracts traded each day, up over 200% year on year. Looking ahead, we’re excited to be expanding our offering beyond Bitcoin and Ether with the launch of Solana futures this month. 

What key advancements are being implemented in the derivatives space to enhance market efficiency? 

Futures and options are highly efficient instruments, which is why they are so widely used across the trading ecosystem. However, all our clients face significant capital constraints driven by regulatory requirements or the need to deliver risk-adjusted returns in highly uncertain times.  

It is a significant benefit for clients to be able to offset related positions when calculating margin requirements. We’ve expanded the range of savings available, for example by expanding our cross-margining programme with the FICC to enable more buy-side market participants trading US Treasury futures to benefit directly from these natural offsets. 

We also see clients transitioning positions from OTC to exchange listed products because of the ever-changing regulatory treatment of capital – from SA-CCR to uncleared margin rules, to the recent changes in the G-SIB calculations. This has led to increased usage of products that help clients move positions easily between OTC and listed products. 

The post Fireside Friday with… CME Group’s Serge Marston appeared first on The TRADE.

The accelerating growth of automation in fixed income markets presents unique challenges and opportunities compared to other asset classes. Equities markets – which have long benefited from electronic trading and automation – are highly transparent, largely trading on order books and on an agency basis. Fixed income, by comparison, has historically been far more dependent on risk warehousing, is more opaque, and uses request-for-quote (RFQ) as the dominant execution protocol. 

These factors, paired with voice trading remaining prevalent, have resulted in slower adoption of automation. However, in recent years, the rise of passive, low-cost/low-margin investment products, and shrinking bid/ask spreads make the demand for efficiency in fixed income as significant as other markets. This has led to considerable innovation in fixed income automation and rapid growth in adoption, particularly in areas such as price making/liquidity provision and order execution.  

A key catalyst of this progress has been the rise of predictive pricing models – such as MarketAxess’ AI powered pricing tool, CP+. This solution delivers the same functionality as a ‘top-of-book’ price feed in equities, providing a reliable benchmark of the best available price that enables market participants to automate their decision-making processes. 

How has buy-side sentiment shifted towards automated solutions recently?   

There is a growing sense of confidence and optimism towards automated solutions on the buy-side with demand increasing year-on-year. Large asset managers and private banks have been the quickest adopters, with the majority of client orders now executed using automation. Until recently, however, their focus has been liquidity taking via RFQ workflows using our rules-based automation solution, Auto-X RFQ.  

We are now seeing increasing appetite for more sophisticated automation workflows that include smart order routing, liquidity provision and aggregation. 

How far could trading automation realistically go? Is there a point at which it becomes unfeasible or is the sky the limit?  

I don’t think it’s really a question of feasibility anymore – it’s a question of how fast the transition will happen. 

At MarketAxess, we believe technology can have a positive impact on the entire trade lifecycle by allowing traders to focus on spotting opportunity, solving problems and managing risk. In that sense, I do feel ‘the sky is the limit’ when it comes to trading automation, but I don’t think that is necessarily a single protocol or workflow. 

We often talk about the ‘last 50%’ to refer to voice trading still happening in US and EU IG credit. I think it is inevitable that electronification will shrink that number over the next few years, but I also think workflows are likely to be more nuanced and may require different approaches. For example, in some cases, this might involve using automation to break up blocks of liquid bonds and trade throughout the day, taking advantage of the increased turnover generated by the ETF ecosystem. In other instances, it may be about smartly sweeping up natural liquidity in the form of dealer axes or buy-side matching.  

Markets outside of IG are also experiencing a shift. For example, in 2024, we saw an 8% increase in automated emerging market trading volumes compared to 2023, showing increased adoption. This momentum is set to continue, particularly as investors look beyond traditional bond markets for new growth opportunities. 

What should be front of mind for the industry when adopting increasingly automated solutions? 

Automation creates incredible potential for operational scale but that scale carries increased risks that need to be carefully managed. Helping clients do this is front and centre in our product design approach. We focus on providing automated and manual risk controls, observability, transparency and process auditability. This ensures the user is always in control, even during periods of high volatility.  

Quality of data is also paramount: automation outcomes are only as good as the quality and reliability of the data you use for decision making. Machine learning can play an important role here in making sense of the vast amount of fragmented data in fixed income markets, but this needs to be underpinned by a large, well-cleansed data set and robust model validation. These models take time and experience to get right. 

I think the potential for increased efficiency in fixed income is immense, but it’s all about choosing the right technology and data partners to help you on the journey.

The post Fireside Friday with… MarketAxess’ Gareth Coltman appeared first on The TRADE.

Fixed income encompasses a complex set of financial instruments with great breadth, depth and diversity. When you look at how this asset class is moving into the automated trading space, there is a high degree of fragmentation. While almost 50% of corporate bonds are trading electronically, other areas of the asset class are still marked by manual workflows and are at the more initial stages of automation. 

Fixed income also has a high degree of diversity within the sub-asset classes, which are each marked by unique characteristics and challenges. Speaking of fixed income as one asset class almost does not do justice to the complexities that are faced in the space.  

However, some areas of fixed income are growing very fast. If we look at the rise of ETFs, these vehicles are providing bond fund managers much more flexibility to be able to access and work in the space. Pricing data has also become much more available for investors to jump in and out of corporate bond positions. Players in the space are working to keep up with these changes, while also maintaining the legacy systems and complex workflows that are in place.  

What role does real-time data play in helping combat these issues?  

Real-time data enables more automated signals in fixed income – especially critical is API access to multiple signals simultaneously. Looking at the growth in the primary issuance space, where we see year-on-year volumes growing rapidly, the timelines on the first day of issuance are really condensing. This compression has made the space much more efficient, but it has also raised the stakes, making data accuracy and integrity key.  

To address this, Bloomberg’s New Issues Feed provides real-time updates on all of the different stages of bond issuance as they happen programmatically to enable users to make decisions in real-time, accurately and with confidence. Being able to do this in a cost-effective way across different asset classes – such as corporate bonds, treasuries and loans –  solves historic workflow pain points around data integrity and operational risk which were previously addressed with ‘dummy instruments.’ Firms previously needed to manage a huge clean up exercise as well to maintain the integrity of their data and make sure that they were confident with any trades that were executed in this space. With real-time data, firms can ensure data integrity in compressed timelines in ways they weren’t able to before. 

What are the key factors driving this compression of the fixed income trade lifecycle?  

The increased number of players in fixed income is driving greater automation and the use of API trading. The SEC’s approved rule changes to require most fixed income and municipal trades to be reported within one minute of execution, tightening the current 15-minute reporting standard, is also an evolutionary change for anybody in this space. 

In light of these shifts, industry participants would be wise to reassess the entire workflow as it relates to fixed income, identifying all manual and back-office processes and working to automate them as much as possible to drive faster decision-making. Real-time data consumed via API can provide a consistent view of multiple data points concurrently. As an example, in the New Issues workflow, if a bond is announced and a firm has interest, they can programmatically subscribe to an intraday pricing service like IBVAL and receive a price indicator for that bond within 15 minutes. This allows for much more confidence in the trading decision. Real-time solutions provide the API framework to tie together all parts of the fixed income trade lifecycle – from new issuance into trading, back into execution, and finally for reporting back to relevant agencies – eliminating fragmentation between different stages of a trade.    

How can those in the market adapt to more in a much shorter period of time? 

Taking pricing data as an example, historically this type of data consisted largely of voice transactions. But today, we see a lot of clients using Bloomberg’s MSG1 tool, which brings together IB, email and pricing information and provides a real-time feed of this data across a customer’s firm to give group-wide internal transparency on where the pricing is. This can then be aligned with broker pricing and data from reporting feeds to provide even greater value.   

Broadly, industry participants must be able to bring together disparate pieces of information, whether that’s a model price like IBVAL, a price indicator price (PIP), pricing internal to a firm, or trade reporting feeds like MSRB or SDR. Then, eliminating manual consolidation and reconciliation of these prices and enabling programmatic processing is essential for efficiently operating within today’s increasingly compressed fixed income trade lifecycle. 

The post Fireside Friday with… Bloomberg’s Colette Garcia appeared first on The TRADE.

The first thing which comes to mind is regulation. Post global financial crisis, regulators were obviously focused on the financial stability of the global banking system. Much work has been done to increase capital requirements, enhance risk management, improve liquidity, reduce leverage, and improve oversight. Regulators today are shifting more towards market resilience and infrastructure. Whilst mandatory clearing may reduce risk – and some may debate that – it does bring a host of post-trade operational efficiencies.

Shorter settlement cycles reduce overall risk and, if executed properly and automated, speed up the movement of collateral and capital. Fail penalties, like CSDR and TMPG, are blunt tools in forcing operational efficiency. With the levels of government debt exploding, the need for efficient financial markets and operational efficiency is clearly at the forefront of regulator minds, globally.

Secondly, cost awareness – highly correlated to operational efficiency is the higher cost of being inefficient. We can debate where inflation will settle, but most folks would agree that the days of 0% interest rates are not coming back anytime soon. Unsecured borrowing costs, as a result of operational inefficiency, is exponentially more expensive and global financial institutions are wrestling with this for the first time in decades.

Third is the need for scalability. As trading merges with computational ability and auto execution, the volume of trades in the global marketplace is only going one way – dramatically higher. The ability of the post-trade architecture to keep pace with this growth will be challenged. Antiquated systems and processes will be severely tested. Firms should be taking a hard look at their whole post-trade operations and taking the steps today to deal with the markets of tomorrow. 

How important is data in pre-trade and across the full lifecycle of the trading process? 

The importance of data and analytics for large financial institutions cannot be overstated. It’s simply crucial for those wanting to succeed and grow in the medium to long term.

To exploit hugely powerful tech like AI and blockchain, financial institutions have to collect, manipulate and analyse data across their front- to back-office, as well as across their divisional structures – within information barriers/ethical walls and regulatory requirements, of course. But it’s more than that, because this sort of efficiency, transparency and reporting capability – which we offer – is increasingly being demanded by regulators.

What’s front of mind when it comes to T+1 developments across Europe?

UK alignment with the EU and Switzerland on T+1 is unsurprising and natural, especially given the shift in North America last year. The trend is set, T+1 is going global. Next stop, T+0. However, even though vendors like us are ready for it, arguably much of the industry isn’t. The direction of travel is clear, and securities finance will follow the same evolution to real-time processes as many other sectors already have. 

T+1 is also reducing counterparty risk, this makes markets more efficient and improves liquidity but comes at the cost of a raft of operational challenges. Desks can choose to build their own solutions or engage vendors like us. 

In view of these three trends – increasing regulation, cost awareness and the need for scalability – enterprise data, flowing in real time across the full trade lifecycle can offer an entirely new level of operational and strategic intelligence and capability. True cost of trade, enterprise intelligence, operational efficiency, etc. Exciting!

The post Fireside Friday with… Pirum’s Jon Ford appeared first on The TRADE.

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.