Vuk Magdelinic

Speaking to The TRADE, Vuk Magdelinic, chief executive of Overbond, explained: “A lot of buy-side firms, depending on their portfolios of course, look to Neptune basically to discover price and size most efficiently. This service is augmented now with a systematic integration of Neptune real time data and an algorithm that can then do deeper comparison both in real time and historical, digesting more data and bringing the insights to buy-side desk faster and in a more robust way. It’s essentially a levelling up of the Neptune benefits.”

The move will enhance client-specific analytics for corporate trading execution as well as providing Neptune Networks, a fixed-income pre-trade market utility, with the latest in AI size-adjusted pricing and liquidity discovery.

Byron Cooper-Fogarty, chief operating officer at Neptune, said: “Neptune has always responded to buy-side demand for connectivity to core workflow and analytical tools. The integration with Overbond is the latest step in that process.” 

In addition, Overbond is also set to expand the securities covered by its analytics and trading algorithms through the incorporation of Neptune data into each single-tenant client environment, on request. 

While sell-side fixed income desks have distributed axes to clients to signal which securities they are most interested in buying and/or selling for some time, buy-siders instead use this information to execute large trades, optimise order allocation and source liquidity for less liquid securities. 

Read more: Bond traders increasingly managing execution rather than partaking

“This is at the end of the day data integration. Obviously, the Overbond product on its own already has capability to aggregate different data sources to produce recommendations on size, routing, and obviously liquidity profile and market price per security, but the Neptune data inclusion for buy-side shops makes the dealer quotes and execution component of that aggregation more robust and extends the coverage and precision and relevance of the signals for particular buy-side desks. It’s a client-specific solution.” Magdelinic said to The TRADE.

Following this integration, Overbond AI is set to utilise axe data provided by Neptune to enhance its size-adjusted pricing, with plans for this to be included in its analytics and trade automation suite.

Read more: Overbond unveils new artificial intelligence-based smart order routing system

Last September, Overbond unveiled its smart order routing (SOR) algorithm, aimed at addressing the time-consuming and challenging process of allocating trades via the best execution route.

Specifically, it uses historical information alongside current dealer axes, unique to clients, to determine the optimal dealer to engage for a specific security, given current market conditions. The live axe data from Neptune will further enhance the precision of the Overbond SOR algorithm, according to the business.

Speaking to future plans, Magdelinic told The TRADE: “I think with increased buy-side adoption we will look to deploy our next generation smarter order router, which helps buy-side desks with recommendation of where to route – not just amongst the dealer inventory choices, but also with regards to the venues and protocols they’re connected to.”

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The integration of ESG factors into the fixed income market has been one of the most notable trends. With climate change becoming a pressing issue globally, there has been a surge in the issuance of ESG-centric bonds, including green, social, and sustainability bonds. These all serve as a means for issuers to raise capital for projects aligned with ESG objectives, while catering to the growing demand from investors who seek to align their investments with sustainability goals.

In addition to this, fixed income issuers have increasingly embraced innovation by structuring bonds tailored to specific investor needs. Structured bonds, with features such as adjustable coupon rates or embedded options, allow investors to better manage risk and exposure to the ever-fluctuating interest rate adjustments we have all experienced in recent times.

Lastly, exchange traded funds (ETFs) in the fixed income space have also continued to proliferate, as they provide exposure to niche fixed income segments such as emerging markets, high yield, and municipal bonds. These ETFs offer investors a convenient way to access a diversified portfolio of bonds while benefiting from intraday trading and transparency.

Aside from the above trends, the value of alternative data sources within the fixed income market are also worth noting. Over the past few years, market participants have started incorporating non-traditional data like satellite imagery, social media sentiment, supply chain data sentiment and online transaction data into their analysis. These alternative datasets offer unique insights into credit risk, issuer performance, and macroeconomic trends, enabling investors to make more informed decisions. Deutsche Börse has thrown its hat into the ring in this regard and developed datasets in partnership with Clearstream who are a leading International central securities depository that has unique visibility into security holdings and transactional data.  Clearstream Bond Liquidity provides unique post-trade settlement and transaction data by shining a light on the Eurobond market on a T+1 basis. The data feed can be used to fairly value fixed income assets and portfolios as well as generate unique liquidity scores in addition to measuring liquidity and systemic risk of bond issuers.

On top of alternative data sources, the application of machine learning and AI in the fixed income market has also gained traction. Financial institutions are leveraging these technologies to analyse large volumes of data and extract actionable insights. AI-driven tools have the potential to enhance trading strategies and risk management and it is for this reason that Deutsche Börse has partnered with Overbond to leverage their AI technology. Through the partnership with Deutsche Börse and Clearstream, Overbond’ s customers can gain access to settlement-level fixed-income transaction data derived from the 170 million transactions that Clearstream processes annually across 100 currencies and 60 domestic markets.

Regulatory changes have also played a pivotal role in shaping the fixed income landscape in recent years. Evolving regulations such as Mifid II in Europe and SEC reporting requirements in the US have placed greater emphasis on transparency, reporting, and investor protection. These reforms have driven market participants to adopt advanced technologies for compliance and reporting.

Another important factor influencing the fixed income market has been the intensity of efforts to standardise and consolidate data as it has historically suffered from fragmentation and lack of uniformity. Initiatives, such as the plan to build a consolidated tape in Europe, aims to address these issues by creating a centralised source of bond trade data. The European Union aims to enhance price discovery, enable better analysis of liquidity, and facilitate post-trade reporting. Moreover, the EU is intent on levelling the playing field for all market participants, from institutional investors to retail traders. The tape would aggregate data from various trading venues, providing easier monitoring of market trends, assessing market depth, and evaluating the true cost of trading.

Lastly, a predominant factor shaping the market has been the digital transformation of fixed income processes in recent years. Market participants are embracing electronic trading platforms, primary issuance workflow tools, automation tools, and digital settlement processes. These advancements streamline trade execution, reduce operational risks, and enhance efficiency throughout the trade lifecycle. A recent example of this at Deutsche Börse was when KfW launched the first digital fixed income bond in the form of a central register security on the German Electronic Securities Act (eWpG). The issue was carried out by Clearstream on Deutsche Börse’s D7 digital post-trade platform.

In conclusion, the fixed income market has undergone a significant transformation in product offerings and the utilisation of data-driven insights over the past two years. The integration of ESG considerations, the expansion of innovative bond structures, and the growing importance of alternative data sources reflect the market’s responsiveness to evolving investor preferences. Additionally, advancements in data analytics, AI, and machine learning have empowered investors and market participants with more sophisticated tools for analysis and decision-making. With ongoing regulatory changes and the continuous push for digitalisation, the fixed income market is poised for further evolution in the coming years, catering to the changing demands of investors and the broader financial ecosystem.

For further information on Deutsche Börse’s fixed income analytics offerings, please visit: https://www.mds.deutsche-boerse.com/mds-en/analytics or email analytics@deutsche-boerse.com

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The buy-side can utilise the automated process of SOR for online trading specifically, working for best execution through allocating based on price and liquidity. The algorithm also, when needed, has the capacity to determine optimal methods of breaking up (or chunking) a trade.

In the development of its offering, Overbond worked with both buy- and sell-side partners. Specifically, the system is an AI-enhanced routing logic to provide traders with a complete view of order break downs. 

Speaking in an announcement, the business highlighted that AI-driven tools are “critical for achieving no-touch end-to-end bond trading automation and may contribute to the continuing increase in automated trading of fixed income”.

Read more: Overbond expands automated bond trading service with Deutsche Börse European fixed income data

Overbond’s developed analytics auto-adapt to trade size and direction, which allows traders to view data across hundreds of thousands of fixed income securities.

Traders can view implied liquidity and confidence scores which have been sourced from volatility and bid-ask spread components. Overbond employs a three-tier system, dependent on liquidity and pricing confidence relative to the universe of bonds with the same currency.

Vuk Magdelinic, chief executive of Overbond, explained: “Gauging liquidity and routing orders are pivotal steps in the trading process and enhancing them with AI can help traders manage their workflow more efficiently, automate more trades and improve profitability. At Overbond we have a strong team of data scientists and developers who are working hard to innovate and push the boundaries of what AI can do in the fixed income markets.”

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Over recent months, historical Level 3 data provider BMLL has seen a surge in activity as it continues to expand its equities and ETF data coverage. Its products now include data from the Hong Kong Stock Exchange (HKEX), Cboe Europe Indices, and more recently this month, the Shenzhen Stock Exchange.

Speaking to The TRADE last week, Paul Humphrey, chief executive of BMLL, explained that these recent moves had come in response to client demand for enhanced coverage.

“Our clients and market participants overall are demanding increasingly comprehensive, high quality data sets to understand market behaviour and we are delighted to provide them with the insights they need to make more informed trading decisions.”

Data from the added exchanges are available to BMLL users across the buy- and sell-side, as well as global exchange groups. Other inclusions earlier this year include: Cboe Japan, Japannext, and Singapore Exchange.

In other exchange news, the Johannesburg stock exchange launched a joint venture with big xyt in a bid to offer greater accessibility to data analytics to international trading venues and firms of all sizes.

The JV – big xyt ecosystems – is set to offer the Trade Explorer data platform, recently launched in South Africa, to financial centres globally.

Speaking at the time, Leila Fourie, chief executive of JSE Group, said: “All trading venues understand the need for a market data business adjacent to the core mission of providing high quality markets.”

There has also been notable movement in bonds offerings, which included updates from Overbond, Mizuho EMEA, and Intercontinental Exchange (ICE).

In May, Overbond entered into an agreement to integrate European fixed-income transaction data from Deutsche Börse into its AI-aggregated data feeds and automated bond trading.

With this move, Overbond plans to “generate a robust European fixed-income trading data set,” aimed at plugging the gap in the fixed income markets in Europe that continue to be challenges for traders. The firm said its combination with Clearstream transaction data would create “the most robust European AI training data set available for the benefit of a better informed fixed income in Europe”.

The following month, Mizuho EMEA joined Neptune network as axe dealer for bonds in a move linked to a desire from the buy-side to access higher quality data from liquidity providers.

Byron Cooper-Fogarty, chief operating officer at Neptune, at the time highlighted that “this has been a client driven addition, as buy-side traders and portfolio managers continue to ask for high quality data from liquidity providers such as Mizuho.”

More recently, ICE made some updates to its corporate bond offering, relaunching its sweeps protocol – ICE RMA – in response to market demand.

Peter Borstelmann, president of ICE Bonds, highlighted that there was a notable demand for improvement in the space and the development of a product superior to that already in the market.

Speaking to The TRADE, he explained: “We heard from our partners that they wanted a strong competitor in this space and nobody had yet been able to step [into] that capacity.  We saw this as an opportunity to invest in something that we were the initial creators of and would be a nice complement to our existing ATS liquidity network […] we invested in both human capital and technology to bring an intuitive and easy product to market and the initial adoption and activity validates this investment.”

Also launched into the market in recent months were updates to FX offerings from several players. Earlier this month, August, Bloomberg announced that it had added a new suite of FX pricing quality tools in a bid to enhance RFQ pricing requests.

The tools – available to clients of its premier multi-bank FX trading platform (FXGO), through MISX, Bloomberg’s multi-asset reporting tool for electronic trading – allow price markers to more quickly identify where and why opportunities to price are being missed.

Tod Van Name, global head of foreign exchange electronic trading at Bloomberg highlighted the importance of this enhanced tool and the transparency and availability of real time information that it provides to their clients for trading operations.

“These new pricing quality analytics in MISX provide both buy- and sell-side market participants with unparalleled breadth and depth of analysis and output, that can help them make more informed trading decisions and achieve better outcomes.”

Guillaume Carreno, global head of electronic client connectivity at Crédit Agricole CIB, added: “The additional information, especially the “Best Alternative” data, has enabled us to identify areas where we can further improve the pricing quality for our clients. The productivity efficiency we gain with this new feature is an important added value.”

Similarly, Trading Technologies (TT) has been making a move to establish itself in FX, launching a new business line in June following its entry into the fixed income market for the first time in March with its acquisition of AxeTrading.

In August, TT acquired Abel Noser’s buy-side TCA subsidiary, building on its continued multi-asset data and analytics expansion.

“This acquisition enhances our appeal to the buy-side with an offering that spans multiple asset classes which we can fortify with the wealth of anonymised data harnessed through our platform,” said Trading Technologies chief executive officer Keith Todd.

Elsewhere, players have made enhancements aimed at assisting traders with their operational needs, seeking to optimise, secure, and streamline processes.

In June, futures industry technology provider FIA Tech enhanced its Trade Data Network (TDN) to support the operational resiliency demands of clearing firms utilising the platform. 

From now, users of TDN are able to securely replicate and store all trading activity at any exchange connected to the network, resulting in speedier recovery in the event of a systemic outage. 

Additionally, the following month, FlexTrade and TRAction announced a new integration aimed at alleviating the “operational burden” of transaction reporting on the buy-side trading desk.

Its system users can use this update in daily transaction reporting processes, by automatically reporting their data through the TRAction platform in the appropriate format. (Spark EMS users can also use TRAction for Emir, Mifir, ASIC, MAS and Canadian reporting).

At the time, the pair claimed that this direct integrated approach “removes formerly manual tasks, reducing errors and improving quality”.

More recently, MarketAxess announced plans to acquire multi-asset algorithmic trading provider Pragma, betting on this move as a sure way to enhance its clients’ workflows.

“Our acquisition of Pragma underscores MarketAxess’ commitment to innovating, integrating, and providing our clients with quantitative, AI-powered technology solutions powered by proprietary data designed to simplify and enhance their workflows,” said Chris Concannon, chief executive officer of MarketAxess. 

David Mechner, founder and chief executive of Pragma, added: “Pragma and MarketAxess share a common mission of using technology and automation to improve trader efficiency and generate superior trading outcomes for investors.”

These recent surge in activity, across various sectors and asset classes, makes clear how seriously firms are taking demands from the market. Providers are demonstrably taking note of the market’s call for better and more accessible data, acutely aware that falling behind the client demand curve now will be increasingly detrimental to business in the long run.

Whether it be through acquisitions to “plug gaps,” joint ventures to share expertise, or straightforward investment in technological updates, what is clear is that providers across the board know where priorities need to lie as the market undergoes significant change. 

Driven by mounting regulatory pressures, increased globalisation, and general uncertainty as regards future trading rules, the need for better data is clear. It’s do or die.

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The discussion delved into the key impacts of automation within fixed income, in particular, how it could shape the future role of traders themselves.

Among the panellists was Adrian Dacruz, vice president, strategic market development capital markets at Deutsche Börse who touched on the positive correlation between automated solutions and individuals being freed up to focus on higher value tasks, such as strategy and building client relationships – “working on managing the execution process rather than partaking in it”.

He added that, “Automation allows us to reduce the biases that exist in the investment sphere because of us as humans. Day to day behaviours, like herd behaviour, bias, and over confidence is reduced with an automated strategy. Humans act on emotion, but a system acts on what it’s told to do, which is a key factor.”

Andrew Kovacs, director of product management EMEA at Charles River Development agreed, suggesting that, “There is a need for technical expertise to evaluate the resulting trades that have been processed through this automation process”.

If everything is done manually, said Kovacs, “You have a very deep understanding of every trade you’ve actually executed as opposed to when you pass things through a machine. Looking for ways to improve or optimise the process on the trading desk requires new skills to make sure the quality of the trades remain high.”

He went on to say: “The skills that traders have today may not lend themselves particularly well to this exercise, so trade desks may have to bring in talent to complement the process.”

Other speakers included Lu Fu, managing director, head of eSales and digital transformation EMEA at Mizuho and James Bunting, global head of partnerships at Finsemble.

Interoperability is essential

The panel established that automation is a multi-faceted, dynamic problem to solve. A large portion of the discussion centred around interoperability, which the speakers agreed is vital to the future of the space.

Bunting said ensuring applications and services were working together cohesively was essential “even though they’ve never been designed to.”

For Fu, one of the most important considerations from a trading desk perspective was to ensure that users have a say in how they want their workspace to look and operate in order to increase efficiency.

“We need to upgrade the trading desk skill set in a way people feel comfortable in knowing how the systems work together now […] the majority of the time end-users struggle to see how systems interact. It’s a long journey and as Andrew pointed out a lot of time is [spent] training on the desk, and hiring more diverse types of talent on the desk to help with this,” Fu said.

Panellists also discussed what credit trade workflow could look like in the next two years, with Kovacs highlighting how the line between traders and PM roles is becoming increasingly blurred as the traders’ realm opens up.

“Years ago, traders had control over all the data related to trading activity, but now PMs have insight into a lot of information such as liquidity and pricing and they might use that to help inform their security selection process,” he noted. “Now more than ever, PMs are helping make decisions about which trades to automate” – a situation which he stated will only continue to be more prevalent as automation increases.

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The agreement specifically relates to Deutsche Börse and Clearstream’s recently co-developed new fixed income data service, Bond Liquidity Data.

Through this partnership, Overbond customers will be able to access settlement-level fixed-income transaction data derived from the 170 million transactions that Clearstream processes annually. This covers 60 domestic markets and includes 100 currencies.

With this move, Overbond AI plans to “generate a robust European fixed-income trading data set,” aimed at plugging the gap in the fixed income markets in Europe that continue to be challenges for traders.

Overbond uses six months of historical data to train its AI model. The firm said its combination with Clearstream transaction data would create “the most robust European AI training data set available for the benefit of a better informed fixed income in Europe”.

The fixed income markets have typically been heavily over the counter and manual in past years and for this reason the space lacks transparency. While Europe is on the cusp of implementing a consolidated tape for bonds, until regulators do so the industry remains reliant on data aggregation services such as these.

Vuk Magdelinic, chief executive of Overbond, said: “Complete and accurate data is a foundational tool for achieving consistent profitability in the bond markets. Incorporating Clearstream data into the training set for Overbond AI is a game-changer. It allows us to create a great tool for traders of European debt and enables them to automate up to 40% of their trades using Overbond.”

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As best execution has become front and centre, electronic trading offers a means of quantifiably measuring and thereby holding accountable the institutions guarding the purse strings. And that is a good thing. The developed listed equities space has paved the way for other asset classes in this regard, with an increasingly large portion of volumes in this market now accounted for by trading engine to trading engine activity. Smart order routers sit downstream of algorithms that interact with one another on an order book in real time.

Artificial intelligence is playing an increasingly important role in almost all aspects of life – even journalists are cautiously eyeing ChatGPT, feeling a prickle of sweat every time someone shares another flawlessly written article – but when it comes to buy- or sell-side traders taking their hands off the wheel completely and allowing orders to auto-execute with no supervision through zero or no touch trading, the financial industry is not yet ready or willing. Not least due to the volatile market conditions witnessed in the last few years thanks to unpredictable events such as the pandemic and the Russian invasion of Ukraine. You might be fine cruising in auto pilot for most of the flight, but when your plane hits turbulence, you want a pilot to take over.

It boils down to risk 

For much of the traditional long-only buy-side in particular, zero touch trading increases risk for very little return. Unlike proprietary trading firms, asset managers are accountable to their portfolio managers and ultimately their end investors. In today’s increasingly transparent and TCA driven environment letting technology have full control without any oversight, is a fool’s game. Instead, most favour a one or two touch approach. One for an extremely liquid stock or perhaps if an order is generated off the back of another.

“Start with two and when you get confident you go to one. I wouldn’t sleep well at night in my job going to zero,” says head of trading at Bluebay Asset Management, Stuart Campbell. “If you had tight enough controls you could have zero touch but you’re opening yourself up to a lot of risk you don’t need to take.”

The reality is, a completely zero touch system with no checks or monitoring in place is ladened with risk that buy-side firms just can’t afford to take. It’s reliant on airtight data – something still on the wish list of the buy-side, particularly in fixed income – and processes in place to deal with any outliers or unexpected activity in the market. What’s more, the larger a firm is on the spectrum of assets under management across its business, the more careful it has to be with ensuring it’s got good internal policies in place around aggregating and crossing orders to ensure there’s no conflicts. Technology is a tool to be used by traders to reduce clicks but not to withdraw all together.

“There’s no such thing as no touch right now and I don’t think there ever will be,” says senior analyst, risk and financial markets regulation at Coalition Greenwich, Audrey Blater. “Let’s say you’re an investor and want to put your money in a fund, I don’t think it sounds like a good risk practice to say we have zero touch trading.”

Ongoing squeezes on supply chains thanks to Covid and the Ukraine crisis have left most countries around the world on the precipice of recession. Cost reduction now more than ever is at the forefront of the minds of those overseeing budgets bringing to the fore new discussions around outsourcing either via outsourced desks or, technology. Some institutions are happy to pay as little as 0.1 basis points for an extremely low touch service, however, in exchange for this low fee how much risk are they agreeing to take on?

Value add

If the market were to reach a point where trading involved no touch or eyes from either the buy- or sell-side firm, it also brings into question what investors are paying for when they part ways with their cash in exchange for their services. With the prospect of outsourced trading looming, all parties must prove their value add to the trading process. Looking at it in the most morbid sense, a key driver for high client fees is that a human service offers firms someone to hold accountable when something goes wrong. This knowledge allows firms to entrust huge amounts of capital.

“One touch gives clients security that you have a set of eyes on it. It’s imperative that it’s still a decision made by you and orders are grouped accordingly by you,” said one buy-side head of desk.  “There is always an element of value to be added, I can’t see how people can be fully automated because of the diverse nature of clients’ needs; mandates, funds and individual rules of the IMA and prospectuses. There are too many nuances to completely automate away this risk. The fund management industry has multiple parties to respect and important regulations which must be adhered to.”

On the sell-side, amid flat volumes in Europe, particularly in equities where competition is high and commissions are low, market conditions have meant client offerings must now offer value add around a growing list of factors to prove their worth over their peers: including customisation to specific limits or types of liquidity, managing market impact and handling around connectivity or market outage issues. Despite an order being automated to the point that no trader has touched it, most firms will agree there is always some level of involvement. Monitoring orders for outliers is essential and there is always a kill switch. 

“We have people now that are completely dedicated to algo wheel monitoring and performance enhancement,” says head of EMEA electronic and program trading at Jefferies, Ben Springett. “Often it’s the outliers that you observe in real time that give you information about how you maybe adapt that strategy to avoid those occurrences repeating in future, and you need to be fast. Often you have just a quarter of measurement that determines whether you stay on the list, do you get smaller allocation or bigger allocation?”

As the markets become increasingly complex around regulation, reporting and fragmentation and as algorithms too have become more advanced, the role of the sales trader and trader has advanced as well. Historically a client might send an order into a liquidity seeking algorithm in a process that to the naked eye might seem simple, but Europe for example is now pushing almost 30 venues. What’s more, as strategies have become more complex, firms feel more confident in sending larger orders into automated strategies and this has increased the need for a hands-on approach from sell-side counterparties.

“Coverage is involved during the life of a trade and post-trade. It is about how those algos performed, how can we do better, what we should be looking to build and how we can continue to innovate. This side of the business has become ever more complex, we need people who are both technical and personable,” says Bianca Gould, head of electronic execution at RBC. “There is an expectation that we are overseeing orders. I don’t think zero touch can truly exist. Clients expect us to add value. We have an AI product where the algorithm takes ownership of that order effectively but that doesn’t negate the need for interaction and for coverage to be very much on hand.”

Naked Direct Market Access (DMA) is available to the buy-side, sidestepping the role of the sales trader and instead allowing the firm to utilise a broker’s pipes and infrastructure to directly access an exchange. However, most brokers would argue that this model alone often leaves buy-side firms vulnerable to fat finger – market impact – and that DMA should be overlaid with algo suites to avoid being subject to market moves against an order that hasn’t been properly placed in the market.

There’s always a touch somewhere 

The role of the trader and sales trader has evolved significantly. Whichever way you look at it they have become more hands on as opposed to less, in particular in the post-trade process thanks to the TCA-driven environment the market has morphed into. The intensive process of monitoring performance has replaced the formerly manual process of trading. 

Trading is without a doubt far less touch nowadays in terms the actual physical process. The pandemic was the final nail in the coffin for voice trading and for the most liquid stocks it is a thing of the past. Up to a third of Jefferies’ volumes are accounted for by so-called “black box” trading whereby a firm will have no individual trade inputs by a human being on either idea creation or on the subsequent order that’s generated or its execution. To another degree firms can code investor strategies that are then given a license to execute against that investment thesis on a fully automated basis. 

Further levels of automation vary across algo wheels whereby an order goes into a wheel that selects the appropriate pre-defined broker algorithm and executes it without touching the desk. No human has touched that order since making the decision to generate it and send it there. 

“If a broker is algo pricing my enquiry then that could be zero touch. For me to generate a ticket on my side I use controls, checks, balances, integrated mandate rules etc. It’s one touch for the buy-side and zero touch algorithmic on the sell-side,” adds Campbell. “I want to check a trade before it executes automatically. Most buy-side shops are doing the one or two stop checking process. On the sell-side if someone enquires about buying a stock and they have it on their book and their algo sees it and knows it can do the best price and gives it, they don’t touch that.”

Systematic and program trading firms that use the speed of their proprietary algorithms to gain efficiencies in the market are the most advanced when it comes to automation. But again, it must be stressed, someone, a human someone, has to understand the trade, understand its counterparty limits and what’s happening in the wider market. 

“That’s [program trading] a speed game, machines are faster than people but they only make the decisions that people programme into them. Somebody has to be watching and they are,” explains Blater.

In the listed equities space, the most outsize returns have accrued to those people that were first on board with digitisation and automation. A growing portion of what the largest institutions execute is done via black box methods of trading. Consolidation and economies of scale have meant the largest firms have continued to get larger. 

These are the firms that benefit most from zero touch trading, explains MarketAxess’ global head of trading automation, Gareth Coltman.

According to him, demand from the largest institutions for zero touch trading services has continued to grow in the last 12 months, as a means of easing the pressure off of desks that have a growing workload and a shrinking headcount.

“That isn’t to say there isn’t a trader supervising that process, finding that workflow, helping to define those rule sets and dealing with exceptions and orders that don’t fit into that workflow,” he says. “Having the ability to use a tool like this when the desk is very busy is very appealing. For some firms it’ll be something they use every day or for others when they’re particularly pressed for time. Every desk has to assess how much benefit and added efficiency they get from an automation solution and that benefit is likely to correlate with volume of activity.”

MarketAxess recently launched its Adaptive Auto-X service which aims to make plugging into fragmented liquidity pools easier for users by taking MarketAxess’ liquidity pools and placing them alongside its data and analytics offering, allowing them to set up more complex automated workflows.

Various other firms have come to market as of late with products advertised as zero touch including fixed income artificial intelligence quantitative analytics provider, Overbond, which announced a new integrated AI-driven margin optimisation model in October that should allow for end-to-end zero touch automated trading. But, exciting as it might sound, these systems are not acting alone.

“Sophisticated investment firms react to exceptions and enhance strategies and have clever quants to constantly make calibration changes to the way the machine is modelled,” says Andrew Morgan, president and chief revenue officer at TS Imagine. “To that end, these businesses are hands on and high touch.”

The argument can be made that the further you go downstream in a trade the more no touch it becomes. VWAP strategies executing an order over a period of time will slice it into smaller micro-orders that AI micro traders will then distribute to various liquidity pools or strategies. However, step back to examine the larger order and you’ll find a person has parameterised that VWAP algorithm. As trading stands today, there is a person (if not three) involved somewhere in the lifecycle of a trade, including its execution. Automation is at its most powerful when it is augmented with the human trader. 

“It’s nice to say “no touch” but I think it’s a misnomer. It’s not that no one’s touching it they’re just touching it less,” says Blater. “I don’t think zero touch is a realistic goal. I think some firms use interesting marketing language around automated features and rules-based trading but really that’s just a technology to enhance what the human being is doing. I don’t think the goal is to reach no touch.”

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

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

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

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

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

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

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Overbon

An AI quantitative analytics provider for institutional fixed income capital markets, Overbond provides data aggregation solutions and AI algorithms for bond pricing, bond buyer matching, pre-trade signals and market surveillance. 

“Happy to announce have started at Overbond,” said Hack in a social media post. “Would like to thank [CEO] Vuk Magdelinic for the opportunity and looking forward to European expansion for the company.”  

Read More – TRADE CALLS: Overbond – Automation in fixed income markets  

Hack was previously director of business development at Coremont for just under a year, and for Coremont Digital for eight months before that. He was formerly with cybersecurity firm QOMPLX from May 2020 in a variety of roles. 

He first came to the UK in January 2014 as managing director of EMEA business for investment management software firm Enfusion, for whom he set up the firm’s first London office. He started his career in derivatives at JP Morgan, where he worked for six years.  
 

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Vuk Magdelinic, chief executive officer, Overbond:

Steve Toland, co-founder, TransFICC: Over the past few years many people have predicted that the fixed income market would consolidate. In fact, the opposite is true, with more than 170 fixed income electronic trading venues currently live (an increase of approximately 20 in the past year). In 2023 we predict that market fragmentation will increase, with the launch of more e-trading venues. Also, as dealers seek to manage trading costs, direct connectivity will increase, where dealers provide direct streamed prices as an alternative source of data and direct trading. Modular technology will drive the market forward, and we expect to see opensource technologies become used more widely in fixed income, as firms accept they do not need to build all the applications in their technology stack. Cloud adoption is another key trend. In the past two years there has been more acceptance that the Cloud offers the benefits of scalability, efficiency, and reduced costs, and that it can be used for trading asset classes that are less sensitive to latency. With increased efficiency a key requirement for all trading firms, modular technology solutions, built in the Cloud for maximum scalability to meet evolving functionality, will be essential to the evolution of the Fixed Income market during 2023.

Raj Paranandi, chief operating officer, MarketAxess EMEA and APAC: The last 12 months have resulted in some of the most volatile and challenging liquidity conditions the bond market has faced in recent memory. Recent periods of volatility have created a greater desire from market participants to innovate and adapt to new approaches in the market. In fixed income this has continued to drive electronification and the use of data to enable transparency in decision making. We continue to believe that all-to-all trading is an essential mechanism to allow investors to navigate stressed market conditions, where there may otherwise be liquidity shortages.

Stefano Dallavalle, fixed income product manager, EMEA, FlexTrade Systems: The adoption of EMS technology will continue to grow into 2023, with the streamlining of execution workflow driving efficiency in fixed income emerging as key drivers for the buy-side. The next 12 months will build upon existing automation to see additional protocols and destinations made available to smart order router (SOR) strategies to deliver improved choice and flexibility of execution to the buy-side. Additionally, bilateral dealer connectivity via EMSs will offer a disruptive alternative to the established RFQ workflow of many desks and will continue to grow into 2023. The EMS’s ability to combine these connections with other data points available to the buy-side and to offer a consolidated pre-trade view of the market while providing intelligent automation capabilities will become crucial in 2023. As a result, I predict that fixed income EMS solutions will emerge into mainstream use and become a mission-critical tool for bond desks, similar to their use in other asset classes.

Alex Nowak, head of Continental European FICC e-Sales, JP Morgan: Since more than one-third of the institutional clients we surveyed in JP Morgan’s FICC e-Trading Survey at the end of last year suggested liquidity availability and price transparency were their key concerns entering 2022, we focused on enhancing the tools provided to clients to navigate these markets and to reinforce cross asset systematic trading capabilities. Due to the benefits clients received from real-time monitoring tools in FX spot and how it impacted their usage of orders versus risk-transfer, we see rising demand for more functionality and interactive capabilities in FX and at the same time greater pre- and post-trade transaction cost analytics in fixed income and commodity markets in 2023. These solutions will come via bank-specific and third-party channels to enrich the execution decision process and address the increasing data needs of traders and portfolio managers alike as well as the data scientists who support those trading efficiencies. Algos are set to continue to grow by volume in FX due to sophisticated decision-making processes supporting best execution requirements and new demand will arise for these orders in areas like US Treasuries, which are starting to see new solutions developed. Government bond trading will broadly witness changes to trading protocols aided by improved streaming pricing, similar to FX Spot, helping clients with price discovery, reduce information leakage and serve as a steppingstone towards more algorithmic trading solutions.

Chris Bruner, chief product officer, Tradeweb : The electronification of the credit market is truly taking shape and we’re seeing a unique change beginning in that space. In 2023, expect to see more focus on large-scale risk transfer in credit as opposed to single security trading. As the tools and analytics needed to make this kind of trading more efficient becomes available, expect to see more portfolio managers adopting this approach. Large-scale risk transfer will represent a fundamental shift in the structure of the credit market as traders increasingly view it as transferring baskets of risk with a desired set of characteristics. Packaging up trades provides investors with greater certainty that trades will be executed and when you combine this with the rise of automation, we know we’ll be seeing a lot more of this kind of trading in 2023. 

Jim Kwiatkowski, CEO, LTX (a Broadridge company):

The capital markets industry experienced a particularly volatile 2H 2022 as investors grappled with a looming recession and peak inflation. This year will be remembered as the year when market participants were forced to adjust to a drastically different environment due to a hawkish approach from the Fed, the war in Ukraine and persistent supply chain issues altering the trading landscape. The US corporate bond market was not unscathed by these challenges, which will continue to have ripple effects well into 2023.

We expect the Fed’s tightening of monetary policy to continue, with the process ending in the first half of 2023 and interest rates and inflation remaining relatively high throughout the year. We expect high rates and recessionary concerns to continue to hold back the new issue market. Amidst these conditions, the availability of secondary market liquidity will be a key challenge that market participants will continue to solve for in 2023. We expect to see electronic bond trading reach record levels with the employment of innovative artificial intelligence (AI) and technology that increase transparency while minimizing information leakage. We also anticipate the further adoption of advanced trading tools for more efficient e-trading of large orders.

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