Kicking off this whistle-stop summary as the number one most impactful innovation in the industry is the order and/or execution management system (OEMS) – the beating heart of trading desks around the world. Brought to market in the early 2000s, the sometimes combined and sometimes separated systems were designed to enhance the previously manual processes associated with managing and executing orders. They offer a nifty alternative to the previous plethora of both written records and later, excel spreadsheets that traders were previously forced to grapple with each day to keep things in order.

These systems touch upon all elements of the trading lifecycle throughout the front-to-middle-to-back-office including execution, order, risk and portfolio management. Traders’ order blotters sit within these systems and trading teams use these systems to consolidate data sources and research in one place to increase efficiency and speed when going about day-to-day activities. They also use them to access the market, connecting directly to counterparties to access liquidity. An EMS overlays an OMS by enhancing connectivity, aggregating data and being more flexible as it solely pertains to execution needs.

The systems are constantly evolving to meet the needs of the industry with new third-party vendors integrating their offerings via API in order to gain access to clients using them. While adoption is widespread in equities other asset classes such as fixed income have been slower to adopt these systems given the nuances of the workflows and liquidity landscapes in these markets. For more information on the various providers in the EMS market, check out The TRADE’s annual survey.

2. Bloomberg Terminal

Up next and needing little introduction is the Bloomberg Terminal, Bloomberg’s data and proprietary trading platform. First brought to market in the early 80s the system has over the decades earned its title as the leading market data source and a must have for any financial institution looking to execute in the markets. This is reflected in its annual subscription now nearing $30,000. For this reason, the system is favoured by institutional investors as opposed to individual ones.

Its black background and computerised white text might seem a little out of date to individuals outside of the industry but its role in the financial markets has cemented this interface as a poster child for financial services. Home to Bloomberg’s central data services the interface offers users access to news, data, analytics, and multi-asset trading tools. Given its widespread adoption by institutions it’s also a people move source as users can see up to date contact details of peers. According to Bloomberg, it offers  sell-side and independent research from over 1,500 sources as well as proprietary research on various industries and markets.

3. CLS

Coming in at number three is the multi-currency settlement system, CLS. While perhaps not one of the most exciting aspects of the trade lifecycle, settlement is a central process that acts as a pillar for the capital markets. The settlement period relates to the space of time between the trade date and the settlement date when a trade is considered complete. Within this window both the buyer and seller must undertake any necessary actions to ensure the transaction can be completed.

Established in 2002, the CLS network is designed to minimise risk and offer operational efficiency to institutions within the settlement window by avoiding bilateral settlement that is more likely to fail.

The settlement window has found itself in the industry spotlight as of late thanks to the recent decision from regulators in the US to move North American markets to a T+1 settlement period, down from T+2.

4. Central limit order book (CLOB)

While it is easy to romanticise the sheer graft that went into trading a few decades ago, the introduction of central limit order books (CLOBs) and streamed pricing were much-needed innovations. The idea that in order to understand the changing price of an individual stock or security, one would have to study daily directories and newspapers is something that many of those starting out in the industry today will never understand. With no central directory of orders in the market, understanding pricing must have been a headache to say the least, leaving many individuals subject to arduous process of calling everyone in the phone book.

CLOBs allow for transparency of live orders that are prioritised by price and time. By seeing what is available on the order book, traders have an idea of how much volume can be executed at a specific price. Facilitated by exchanges, a CLOB allows buyers and sellers to submit their trading interests and then utilises a matching engine to match buy and sell orders based on specific requirements such as price time priority. Once a trade has been matched the buy and sell orders are removed from the order book and the bid and ask prices are updated accordingly to reflect the change.

CLOBs offer greater transparency and consolidated liquidity meaning participants have a greater chance of trading. They’re typically used in equities given that this asset class trades on exchange unlike fixed income and some foreign exchange assets. Thanks to huge leaps in technology, participants can hide their full amounts in what’s known as “iceberg orders” that replenish the order book once liquidity has been matched and removed from the book.

5. Algorithmic trading

Rounding out the top five of The TRADE’s rankings of the most influential innovations to come to trading are algorithms and the concept of executing algorithmically or automatically. Most common for low touch and ‘easy flow’ algorithms are often used for small orders in highly liquid markets. Algorithms are a computer programmed trading workflow that follows a defined set of parameters. These parameters could be anything from liquidity seeking to volume dependant or venue-specific such as dark seeking.

Algorithms often offer traders a quick and easy route to market. They remove the opportunity for human error by taking away any manual processes and offer a low latency solution that will often achieve best execution and avoid any unwanted price changes.

While this all sounds fantastic and you may be wondering why they aren’t used for all flow, there are some downsides. Unpredictable activity in the markets such as Black Swan events can render algorithms that rely on historical data useless and result in losses for firms. At the other end of the spectrum, a lack of human judgement and intervention can sometimes result in lesser results in nuanced situations that require human intuition.

Buy-side institutions will often use a broker’s algorithmic suite for execution, with many sell-side institutions vying for the interest of clients with the launch of new and innovative products with flashy names. Less common is the development of proprietary algorithms inhouse on the buy-side given the cost, time to implement, and the speed at which priorities evolve. For more information on algorithmic trading providers, check out The TRADE’s annual survey.

6. The FIX Protocol

Think of the FIX Protocol – or the Financial Information Exchange Protocol – as a universal language allowing institutions to communicate clearly when looking to execute in the market. Used by the buy- and sell-side as well as venues and regulators the FIX Protocol is an industry standard used to complete transactions. It was originally cooked up in the early 90s by Robert Lamoureux and Chris Morstatt in order to exchange equity information between their respective firms Fidelity Investments and Salomon Brothers.

The crux of the protocol isa language comprised of a series of messaging specifications to be used in trade communications. Each specification whether it be size or time or client type has a number or letter associated with it making trading intentions clearer and more clean-cut no matter where they have come from. The protocol was designed in an attempt to simplify workflows and reduce error by creating an industry standard to adopted by all.

The standard is non-proprietary and free. It is owned by the FIX Trading Community made up of buy and sell-side firms, vendors, industry associations and trading venues. While originally only focused on equity information, the FIX protocol began supporting straight through processing (STP) in the 90s and also later added indication of interest (IOI) capabilities to its roster.

7. Dark pools

Dark pools are trading venues where institutional investors can access liquidity without giving away any pre-trade information. Dating back to the 80s these private pools emerged in the US as a way of institutional investors executing without showing their hand to the market in a bid to limit market impact, later arriving in Europe. Given the proliferation of high frequency trading (HFT) several investment banks chose to launch these alternative trading systems (ATS) as a means of protecting institutional clients who are typically slower to execute.

They were originally designed to facilitate block trading but have since evolved to support trades of all sizes – something that has led to criticism from some corners of the market in recent years. Some regulators – in particular those in Europe – have begun exploring how to limit dark trading in recent years given its potential role in reducing volumes on the price forming lit order books hosted by exchanges.

Dark trading is a popular practice globally. While there are specific dark pool operators such as Liquidnet and Virtu, many of the incumbent exchanges also have dark pool offerings.

8. All-to-all trading

Next up is all-to-all trading – which does what it says on the tin. The protocol is a type of trading that allows buy-side institutions to provide liquidity and trade amongst each other. Historically trading has always involved a sell-side counterparty that will access the market and source liquidity on behalf of a buy-side client. The introduction of all-to-all trading has subverted this workflow and is an attempt from venues operating these liquidity pools to offer buy-side firms an alternative means of trading.

The protocol is heavily focused on the fixed income markets and has seen recent growth in the foreign exchange sphere. It has seen a boom in recent years as institutions have looked to diversify the way that they executed. Chief among the catalysts for its growth was the Covid-19 pandemic which began in 2020 and subsequently saw many traditional sell-side institutions reduce their balance sheet and withdraw from the market.

Tradeweb launched its all-to-all corporate bond trading functionality in 2017. Rival fixed income trading venue Bloomberg launched its global all-to-all bond trading service in 2022. However, first off the bat was MarketAxess which launched its Open Trading all-to-all trading environment in 2012.

9. Transaction cost analysis (TCA)

Transaction cost analysis (TCA) is perhaps one of the most heavily discussed industry topics as of late thanks to the plethora of data now needed to execute and to prove best execution to clients. The process is used by institutional investors to analyse data to evaluate their trade performance post-trade, ensuring they have achieved the most competitive pricing. The data is used to make decisions on which sell-side counterparties to keep on an algo wheel or ‘panel’.

While the process has historically been a post-trade one, in today’s trading environment many desks are now assessing how to feed this information into their processes pre-trade in order to ensure further efficiencies.

Today, buy-side trading desks are increasingly using new technology to evolve their TCA use towards something more proactive, utilising predictive analytics that enable participants to anticipate and mitigate execution risks, optimise trading strategies, and help to generate alpha. The data is increasingly being used as more than a simple measurement, but instead is being applied to make better informed trading decisions.

TCA can be done in-house but is also offered by third party providers.

10. Systematic internalisers (SIs)

Next up in The TRADE’s innovation rundown are systematic internalisers (SIs). Usually hosted by bulge bracket banks, SIs are an internalising mechanism that allow banks to execute flow over the counter or off exchange. They’re an alternative venue to the lit order books hosted by exchanges. Within SIs, banks can cross flow from their various business divisions using their central risk books without going out to the market to find the other side. Within these ecosystems they can cross client flow with each other or cross it with their own proprietary workflows.

As an alternative trading venue to the lit order books these venues have found themselves under scrutiny as of late from some that argue that SI volumes are harmful to wider market structure as they do not contribute to price formation and fragment liquidity. Flip the coin and many participants argue that if a trade achieves best execution, it doesn’t really matter where it was executed so long as it achieved the optimal outcome.

In Europe, the SI regulatory regime was introduced in 2007 as part of the Mifid I regulation. The quasi-dark venues properly took off in 2018 with the introduction of Mifid II and greater restrictions on dark trading.

11. Direct market access (DMA)

Many of the innovations in this lengthy list offer a new way for buyers and sellers to access the markets and direct market access (DMA) is no different. In years gone by, buy-side firms have placed orders via a sell-side broker to be traded on exchange. However, DMA is the process of directly connecting electronically to an exchange in order to trade on exchange securities without using a broker or intermediary.

These pipes require advanced technological capabilities and are usually developed by sell-side firms. Buy-side firms will often pay to integrate said pipes in order to gain direct access to the exchange without having to go through the sell-side counterparty. The process offers a disintermediation of the typical broker trading workflow and creates greater optionality for investors looking to access the markets.

12. Hight Frequency Trading (HFT)

High frequency trading (HFT) firms have extraordinary computing capabilities. Sometimes known as proprietary trading desks, these firms are famous for their high-speed connections to the markets that leverage co-locations at exchanges and enhanced proprietary data feeds to gather information. They capitalise on the information gathered in one location to trade ahead of slower institutional investors on other venues.

The process was first brought to the world’s attention in Michael Lewis’ 2014 novel ‘Flash Boys’ which unpacks the role of latency in trading in light of the shift to electronification. The crux of the story: electronification and the laying of fibre optic cables to access venues had opened the door for these faster and more predatory firms, able to nip in ahead of institutional investors.

Today, HFT firms will often use microwaves using satellite dishes at exchanges to gain greater speed still. Some venues, such as Aquis, banned HFT on their venues as part of their USP. Aquis, however, moved to lift this ban last year in order to expand its liquidity pool in a decision that had both supporters and critics.

13. Exchange traded funds (ETFs)

Exchange traded funds (ETFs) have seen a journey to dominance in the last ten years in the advent of more passive trading strategies as opposed to more active ones. ETFs offer investors a chance to buy and sell a basket of securities as if it were a single stock and transaction.

ETFs track and mirror how a pool of exchange traded securities is trading on exchange and price themselves accordingly. They can simply track an index or they can be made up of a custom basket of stocks. The first ETF to launch in the US was the SPDR S&P 500 ETF (SPY) in 1993. ETFs, among other index tracking investment vehicles, have become popular in the increasingly passive trading era where low risk index-based strategies offer greater returns for investors in exchange for half the fees charged by active investors. Given their low risk and low fee model they’re extremely popular with retail investors.

While these trading products are usually passive, active ETFs with an active manager picking and choosing what goes into them, have also seen a surge in popularity in recent years.

14. Periodic auctions

Coming in at number 14 are periodic auctions, an innovation which offer an alternative location for investors to trade instead of the lit order book. Like SIs, periodic auctions saw a boost in interest following the implementation of Mifid II regulation in 2018 and the restrictions it imposed on dark trading venues.

The core difference between a periodic auction and a CLOB is that periodic auctions are not continuous. Various models exist but at their core, periodic auctions collect buy and sell offers to determine a price and then triggers a call period whereby participants can see the indicative price and how many shares can be expected to be executed. Participants then have the option to submit firm orders into the auction. These built in inherent speed bumps favour slower investors and prevent them from being picked off as they might be in the lit books.

The venues have become increasingly popular in recent years because they help investors seek price improvement by prioritising order size over speed at the order allocation phase. They are price-forming rather than price-referencing and they introduce randomness in trade timing. Several alternative trading systems (ATS) being brought to market recently have built their offerings around the skeletal structure of a periodic auction.

15. The Cboe Volatility Index (VIX)

The Cboe Volatility Index (VIX), has become an increasingly essential tool for traders as of late and, given the current market dynamics it’s likely it’ll remain front and centre in traders’ minds for a while yet. Created by Cboe Global Markets in 1993, the original index was used to measure the market’s expectation of 30-day volatility suggested by at-the-money S&P 100 Index (OEX Index) option prices.

In 2003, the index was updated as part of a partnership with Goldman Sachs. Designed to reflect a new method of measuring volatility the index is now based on the S&P 500 Index (SPX) for US equities. It estimates volatility by consolidating the weighted prices of puts and calls on the SPX. It has become a priceless tool for participants looking to track market volatility and for those trying to understand investor sentiment in times of market stress.

The need for such tools has been exacerbated in the last few years thanks to several major unprecedented market events, not least the global pandemic and the new ‘black Monday’ seen on 9 March 2020.

16. Portfolio trading

Next up is portfolio trading. The concept is heavily linked to ETFs and is not dissimilar from program trading in that it allows for the trading of a basket of stocks. Portfolio trades allow traders to execute a basket of stocks in one single transaction, minimising costs and allowing traders to bundle less liquid or more difficult to trade instruments in with more liquid transactions. The concept has exploded in the last few years, egged on by market conditions and volatility brought on by the pandemic and other macroeconomic factors.

Electronically, it is a relatively new phenomenon to the last four to five years, and the protocol has gained momentum alongside other forms of electronic trading that differ from request for quote (RFQ) protocols on multi-dealer platforms, as participants look to minimise their market impact and avoid information leakage. Manually, however, the practice has existed for many decades using a laborious process involving excel spreadsheets and phone calls. Portfolio trades have historically helped many institutions to move big blocks of risk.

The protocol appeals to the sell-side for several reasons, namely the fact that they can take a basket of securities and use them in other trades, special purpose vehicles (SPV) or, importantly, the exchange traded fund (ETF) create and redeem process.

17. Axe trading

The next innovation on The TRADE’s list is axe trading, which is based on… you guessed it, axes. Coined from the phrase ‘an axe to grind’ an axe shows a trader’s interest in buying or selling a specific security. Shown as a grid these tools are used by participants to indicate to their counterparties what they want and need to get done in a certain security so that they might go off and set about getting it done for them in the markets.

Outside of a chosen list of counterparties, traders will usually keep axes private as they indicate potential future moves and this information could be used by someone looking to front-run them in the markets. The process was one typically associated with just bonds but it has since expanded into different securities. Several vendors and platform providers have sought to launch new and innovative solutions that integrate dealer axe data into workflows in a bid to streamline the trading process. The concept has given birth to new platforms and vendors in the market with axe-led quoting and execution management systems (QEMS) at their core.

18. Conditional orders

Conditional orders do what they say on the tin. Many different order types exist under the umbrella of the word conditional but the general premise is, they are orders that will only be actioned or executed if certain conditions are met. Unlike a typical market order where it is placed into the market and the price is not guaranteed, conditional orders set out the parameters on how they should be filled from the get-go. This sometimes means they never get executed as the conditions are not met. They are particularly popular with the buy-side as they allow firms to access liquidity without committing to a trade. Traders can represent orders on multiple venues without running the risk of being executed in multiple different places.

Some of the most common include the ‘limit’ order which will only be filled at a specified price or better, a ‘contingent’ order which simultaneously executes two or more transactions on the back of each other, or a ‘stop’ order which orders the buying or selling of a stock one it reaches a certain price.

19. Actionable indication of interests (IOI)

An indication of interest (IOI) is a conditional and non-binding indication of a buyer’s interest in a security that is still in the underwriting stage. It’s a way of participants gauging available liquidity in the market without committing to placing an order. Sell-side firms will often pitch IOI liquidity to clients as a way of offering a natural other side. An actionable IOI takes this one step further, firming up an indication and offering the liquidity up in a click to trade format.

IOIs can be executed via a variety of workflows. Firms can submit an IOI to a venue seeking liquidity as a non-actionable IOI. When a match is found they can then firm up said IOI to make it actionable. Some EMS providers have integrated this workflow into their technology to streamline it further. Participants can access actionable IOI liquidity straight from their trading blotter within their EMS.  

20. Request for quote (RFQ) and request for market (RFM)

Our final innovation on the list is request for quote (RFQ) and the request for market (RFM) protocols. Both have revolutionised the way fixed income, currencies and commodities (FICC) traders operate in recent years. Both sit under a similar umbrella but other slightly different iterations of each other’s offerings. At the core of both is the idea of allowing fixed income traders to access multiple liquidity providers at once.

Given how bilateral fixed income trading has historically been and how sparse liquidity can be in different markets, the protocols allow participants to maximise their chances of finding the other side by sending out requests to trade to multiple people.

RFQ allows buy-side firms to send out a request for a price to multiple firms at once for the purchase or sale of a security. RFM is a slightly different concept and offers firms the chance to request a price for both the buy and sell so as not to give away the direction they intend to trade in. The idea being that firms can protect themselves from market impact by concealing this information from the rest of the market.

These are the 20 innovations we at The TRADE believe have shaped our community’s landscape most heavily in the last few decades.

Our industry is continuously shifting and innovating. Every year new trends and phenomena come to market intended to disrupt and improve the way that traders go about executing in the market. With continuously growing data sets and the prospect of artificial intelligence and greater automation being used on the trading desk in the near future, it’s likely this list could look very different in a few years’ time.

For more TRADE 20 lists visit thetradenews.com

The post The 20 greatest trading innovations appeared first on The TRADE.

Algorithms, especially when developed and managed internally, can significantly enhance the front-office tech stack. They reduce costs, lower market impact, and increase execution transparency. While the primary perception is that algorithms help investors execute orders efficiently, there’s much more to it.

For instance, the additional data collected by algorithms offers endless possibilities. Storing order book updates received at millisecond intervals in a well-designed database enables high-level back testing. Additional data also provides accurate transaction cost analysis (TCA) and supports various data science and possible AI-driven applications to improve strategies and execution. 

Moreover, algorithms help better understand the market, providing investment managers with valuable information to make more informed decisions. Placing quants directly at the desk creates a high-performance, hybrid workspace that significantly speeds up implementation and optimisation. This setup ensures that both quants and investment managers learn from each other, potentially creating a new and more capable type of quantitative investment manager. 

Finally, using algorithms makes your organisation more attractive to top quants in the labour market. Talented young professionals are eager to work on challenging data and tech projects where they can develop their own innovative ideas.

Are in-house algorithmic execution platforms the way forward?

When I look at the current state of the market and see all the developments taking place, I believe this will be the way forward. In recent years, the possibilities for developing your own applications have increased enormously. Combined with the rise in tech-savvy talent, this creates the perfect environment for companies in the sector to develop their own in-house execution platforms.

Having the ability to manage, optimise, and implement your own algorithms allows organisations to retain all associated knowledge internally. This not only provides a significant advantage over peers but also prepares your organisation for the rapidly evolving digital future. An execution platform also grants direct market access to several liquidity providers. With the newly unlocked data from the execution platform, it becomes easy to determine where and with whom to execute transactions. Adding new trading venues or banks is quicker and more efficient compared to traditional methods.

Additionally, your organisation can respond swiftly to new market developments to stay ahead. Creating an in-house execution platform also enables you to establish a high-standard risk management and governance framework tailored to your organisation’s needs.

All in all, there are ample reasons and movements within the market to encourage this trend.

How can technology be leveraged in a way that allows traders to execute the same procedures for all FX instruments?

There are numerous ways and opportunities to leverage the vast pool of available technological applications to achieve this. Therefore, there isn’t a single, clear-cut answer to this question. Previously, there was a trend where many technological solutions were purchased by organisations due to a lack of skills and manpower to build them internally. Nowadays, more organisations employ talented and well-qualified individuals who can develop these solutions in-house.

This doesn’t mean that everyone in the sector is building their own applications and tools for all FX instruments. However, there is a noticeable trend of organisations starting to create their own direct market access and/or TCA tools, which shows promise for potentially serving all FX instruments and also the non-FX instruments.

The market still needs to take some steps to make this possible. For example, in the FX Swap market, we are seeing initial moves where parties are providing streaming prices, which could enable the buy-side to develop in-house algorithms for FX Swaps.

For now, technology can be leveraged mainly in the pre- and post-trade procedures to execute the same processes for all FX instruments. Post-trade data for all FX instruments is already widely available, if not already stored by your organisation. This data can be used to create in-house TCA tools or back testing engines for all FX instruments, helping to improve execution.

In short, the possibilities are endless, and it is up to your organisation to determine how to best utilise them.

What are the main barriers when it comes to reaching this goal?

First of all, the technology must be made available to your employees and easily accessible for them to work with. This involves addressing several risk management, security and architectural challenges. Therefore, having a reliable IT partner with a high service level is crucial. Once your IT landscape is in good order and set up according to the highest market standards, you need talented and well-equipped personnel. Fortunately, there has been an increase in tech talent interested in the financial sector, so this should not be too big of an issue.

A bigger challenge might be obtaining internal approvals and managing your in-house developed procedures, applications, and tools for all FX instruments. While creating and testing these technological improvements can be done quickly and easily, getting the business to actually start using them can be more difficult. This means you need to establish a robust and widely supported risk management and governance framework in collaboration with your internal risk management department.

The post In-house algorithmic execution platforms are the way forward appeared first on The TRADE.

Gil Guillaumey

The offering offers new methodology to conduct investment portfolio risk calculations and produce predictive analytics, based on advanced machine learning. As well as improving execution time, the offering will also reduce costs, said Nasdaq. 

Users of Calypso include: banks, insurers, and other global financial institutions looking to process front-to-back office treasury workflows, manage risk, and meet regulatory reporting obligations.   

Gil Guillaumey, senior vice president and head of capital markets technology at Nasdaq, said: “All financial institutions trading OTC derivatives are required to perform increasingly complex calculations to meet internal risk controls and regulatory mandates. Maintaining the necessary infrastructure and systems can be outrageously expensive, inefficient, and increasingly impractical regardless of cloud elasticity strategies.” 

Nasdaq combines its machine learning technology with a specific form of mathematical modelling – via its XVA Accelerator – which also “significantly” reduces the amount of physical infrastructure required to run the relevant calculations.    

With this technology, the Nasdaq Calypso risk analytics suite is able to rapidly adjust during times of heightened volatility and fluctuating interest rates. 

Guillaumey added: “The sheer scale of computing power required to meet the most demanding regulations, alongside the strategic benefits of more accurate real-time analytics, is driving a profound rethink about how we can leverage AI to reduce the cost of compliance.” 

The post Nasdaq to process risk calculations up to 100 times faster through integration of AI appeared first on The TRADE.

By using ALTO Investment, TMI will leverage a solution covering the entire front-to-back value chain.  

The ALTO platform consists of tools including analysis, data management, trading, cash management, investment compliance, performance contribution, reporting, and attribution.   

TMI will also benefit from a modular cloud-based system; data connectivity with connections to over 150 data providers; and open APIs for workflow automation, cloud security, and monitoring.     

“This strategic partnership is set to significantly enhance our operational efficiency and deliver superior service to our clients, with faster response times and more comprehensive reporting capabilities,” said Mark Moran, chief operating officer at TMI. 

 Amundi’s ALTO platform will provide real-time data access, improve workflow automation, and streamline middle-office operations. By leveraging Amundi’s expertise, we aim to optimise our operational processes, ensuring greater accuracy and efficiency.” 

Amundi Technology’s expertise in middle-office outsourcing will be leveraged by TMI and will be served by a dedicated team within the firm.  

Outsourcing middle-office operations to Amundi Technology will also allow the firm to focus more primarily on its core service proposition. 

“This new partnership in the UK further demonstrates our ability to serve a wide range of financial companies through our technology platform, helping them achieve their goals by leveraging the latest innovations,” said Olivier Bouteille, chief client officer at Amundi Technology.  

The post Amundi Technology selected by Thomas Miller Investment to bolster operational processes appeared first on The TRADE.

At a high level, I think that most teams are pretty excited about the prospects of AI and the opportunities that it presents. Certainly we see very good usage among our teams. Despite this, there are certain concerns, understandably, and hallucination is certainly a topic that people are aware of. But at the end of the day, before trust comes education. It’s about helping folks understand where these models can add value right now and where they can’t.    

A lot of the wariness also comes because AI models are known not to be good at certain tasks and this taints opinion when it comes to others. For example, AI models are not good at math – that’s just not what they’re trained to do. The key is to educate [our] internal users and explain that they shouldn’t get spooked because, when it comes to the analytical path, the potential is there.   

How is AI already having a positive effect on trading processes? 

The traditional ChatGPT system, similar to our design internally, is focused on quick questions and quick answers. It aims to save people 20 to 30 minutes, on average. The deep research system we are working on allows one to rigorously research complex questions for results that can potentially save people 3 to 5 days.

AI has the ability to unlock a lot of productivity for investment professionals, allowing those within capital markets to discover and digest information even faster than they were previously able to do.

You could either be the fastest or you can be best, and we all want to do both but there are a lot of factors to consider.

How are firms across the industry adapting their teams to be more AI-focused?

In the future, our firm, and others, will want every team to effectively be an AI enabled team. At this point in time, however, what is of most benefit to organisations is to take a centralised approach. We have a team that is dedicated to AI as a centre of innovation – with technical expertise, doing research and building tools, but as importantly, looking for opportunities within the firm.   

A lot of my role and the role of my team is connecting the dots and finding commonalities across teams at Balyasny. If something is working really well in one team or one vertical, it then becomes about translating that. It’s never a direct translation but taking the lessons about what’s working well somewhere and then adopting it somewhere else allows us to achieve more scale within the firm.

The post Fireside Friday with… Balyasny Asset Management’s Charlie Flanagan appeared first on The TRADE.

Panellists argued that automation can be applied in some instances such as rates, whereas in others ultimately clicks are just reduced with only certain functions of the trade automated. Automation was therefore described by the experts as being a spectrum.

“You have to understand that automation is not the same across various areas of fixed income,” said Ricky Goddard, head of credit trading at Schroders.

“In credit, automation effectively is just reducing the number of clicks on the trade. We’re not at the point where we’re going to have our OMS or EMS read for certain characteristics and then have them push orders forward. For rates that can happen, but for credit markets it will be an entirely different process.”

Some panellists did acknowledge that even on a high touch desk, high levels of automation can be achieved. This was noted as being useful particularly in times where smaller trades do not take precedence and pressure is on fulfilling larger trades.

“Even on a high touch desk, we can have a hybrid setup where we initially set a list of trades to be automated and the algo will look at whether it fills these conditions. If met, it will execute, otherwise it needs a human trader to interact,” said Anuj Thakur, lead, high touch fixed income trading at Nordea Asset Management.

Automation was described by some panellists as a “vicious cycle”, given that a lot of pre-trade data is a prerequisite to be able to automate.

Thakur added: “As automation has picked up on the sell-side, whether it’s algos, pricing, RFQs quite quickly or various other protocols, that generates more data, which gives confidence both to the buy- and sell-side on approximately where the mid is.”

With some benefits clear, panellists were hesitant to claim that full automation would be applicable in the fixed income context. However, some panellists noted that it’s best to never say never.

This was in part an acknowledgement to the already huge advancements of procedures through electronification, which previously may have not been believed to be possible.

“We do, however, need to get to the point where we’re able to really trust how we put that process in place and why we’re selecting the banks that we’re selecting. Also, are we putting certain trades that are automated all-to-all or some to a bespoke group of three to five brokers because the trade is potentially illiquid?” added Goddard.

“When I’ve looked at some of the automation protocols in place for products in the past, you can fully automate who you want to send certain products to because you have a fairly good idea of market share in those asset classes. You need to be able to tailor it and that all leads back to having good quality data.”

Goddard went on to add that he does not believe that we currently have the quality of data required to fully automate broker selection.

Still seeing the positives associated with automation in fixed income, Thakur added: “We want our traders to focus on those block trades. A lot of time can be saved if a lot of that flow gets automated where you’re automating 60-70% of the number of tickets which you’ve done manually. This will ultimately free up time to focus on block liquidity.”

Automation was a key discussion point in various panels at the conference, with many panellists highlighting the gains that new technologies are providing. As with any advancement though, it was agreed that adoption must rely of good data for gains to be actualised.

The post The challenges of automation in fixed income: ‘Credit is an entirely different process’ appeared first on The TRADE.

Idea generation, market research and market colour are gained from sell-side institutions, which are then fed back into the buy-side, said one panellist, something which is less achievable virtually.

During and post- the Covid pandemic, the emergence of virtual conferences has seen a significant uptick. But panellists argued this has had both pros and cons. Despite the benefits of these virtual interactions – most notably the frequency in which they can take place and the removal of travel barriers – panellists argued that they are not as effective as in person meetings.

“With a virtual meeting, you can find yourself multi-tasking and not fully engaged when compared to an in-person meeting. Human interactions are always better,” noted one panellist.

A second panellist echoed this, adding: “You don’t gain culture from an algo, you get it from speaking to people and hearing what they need.”

Read more: The evolution of the buy- and sell-side relationship

Another panellist noted: “In a tech driven world, transparency and consistency are needed to ensure counterparty relationships are managed correctly. It is important to know who we can count on. Commitment from our counterparties is needed to build long term partnerships.”

However, whether that is done virtually or via in person and with more human connection is something participants are now exploring.

With advancements in technology, the role of humans within counterparty dynamics has shifted. Panellists acknowledged the worth of direct human interactions, particularly in times of market stress.

“We strive for tech innovation, but we still have hundreds of people on our team. People are still relevant,” emphasised one panellist. “When volatility is stable, we use automation. When volatility increases, we need relationships and to talk to people.”

Another panellist echoed this sentiment, noting that the levels of volatility in a given moment dictate which route to take when it comes to choosing between tech versus human interactions.

“Data [and technology] is great, but we still need to talk to people,” they added.

For trust-based relationships to continue to thrive in a tech-driven landscape, candid conversations are needed, the panellists added.

“It is essential for us to know where banks are outperforming or underperforming,” said one panellist, explaining that having social engagements and human relationships can help drive success in this regard.

Another noted that in “crisis mode”, participants often go back to traditional ways of dealing, however they still use technology – adding that the new ways to relate to participants can be fruitful. Despite advancements in technology being useful, panellists agreed that finding the balance is critical.

The post The importance of human connectivity – ‘You don’t gain culture from an algo’ appeared first on The TRADE.

Data has increasingly become available for trading teams, however, as discussed among other panels at the conference, it is only beneficial if clean and appropriate. Access to data is key for the next stage of data integration and analysis to be truly actualised.

“We believe all our trading team should be able to consume data in its entirety from the get-go. We don’t believe in barriers to accessing the data. We try to democratise it as much as possible,” said Odin Costa, senior fixed income trader at Dimensional Fund Advisors.

“By giving people access to the data, this might create different ways of doing things. That’s quite a powerful story that we want to keep fostering.”  

Cloud has helped bolster this access while also providing additional ways in which data can be consumed and this has resulted in a complete change in the landscape, added Kevin Flood, head of trading and execution analytics at Royal London Asset Management.

“You now have the ability to build out team databases which you can work on, sandbox, and do some experimental stuff, without affecting other users,” he said. “You can share amongst teams, and you can really do some interesting prototypes with that kind of data.”

Data providers acknowledge that they recognise clients’ desire to consume data where it’s most efficient for them and most practical for them. In some cases, this means building a full API suite where they can interact with data and integrate it where they need to inside their own platforms.

“It also means delivering the full set of analytics in some cases, so that they can incorporate it into their own platforms that they have with whoever their cloud provider is,” said Kevin O’Connor, global head of analytics at Virtu Financial.

“In some cases, we’re still delivering large time series in file formats because it’s going to another platform that is going to combine it with many other data sources and it’s the most efficient way. There’s still plenty of file delivery going out there. We’d like to push everybody to an API infrastructure that we control but recognise that that is not how all people consume data.”

Echoing a similar sentiment, Costa added that they’re not fully there yet when it comes to data using the cloud, with legacy systems still taking precedence.

“We have more of a legacy system where all the data has to be ingested and integrated. We need to take care about how we provision it, how we rationalise it and then how do we manage all of the computing power which is done in house.

“Once you move to the next step into this cloud computing world, you reduce this problem. It’s definitely a better world to be in and something that we’re also looking forward to.”

Guido Galassi, head of domestic markets and data at MTS Markets, added that “the challenge is to upload huge data sets, clean them and make them usable, but it also brings benefit because it makes our data more distributable.”

Cloud adoption and its usage for data analysis and consumption does, however, continue to gain traction among trading desks, with many acknowledging the benefits that it provides.

“The cloud computing element now is a fundamental enabler for our data ideas on the desk. It allows size of data, speed and scalability. It also allows you to collaborate across teams,” added Flood. “It’s fundamentally what we need on the desk to build out trade ideas, liquidity ideas and getting through to the PMs.”

As with any technological advancement, benefits can be accessed if approached appropriately. The pairing of cloud and data has the power to democratise data access as panellists mentioned, alongside helping improve execution strategies based on these strategies.

The post The future trading desk is cloud-driven appeared first on The TRADE.

TCA is central to making automated execution more fruitful by supplying insights into processes pre-trade to inform decisions, noted speakers when exploring ways to implement the right tools and skillsets to future-proof the trading desk.

Data – particularly ‘clean’ data – was highlighted as of particular importance. Ultimately, without data to back up automated strategies and their efficiency, said strategies will not be adopted. 

“TCA is important for automation, but we need to know if those automated trades were executed well and whether the execution was better than if handled by a human trader,” highlighted one panellist.

Increases in automation on trading desks has meant that more real-time TCA is required, panellists emphasised, although it was noted that not all firms have the budget to build out this capability yet.

TCA should move past being more of a regulatory exercise, to something that can be practically used to improve execution, panellists noted. “Efficiency gains can be accessed through TCA; TCA helps ensure it is safe to execute in an automated manner.”

Read more: Conscious usage of TCA: Making trade analytics more actionable

When exploring automation more generally, panellists noted that with automation, some challenges do arise and there is no one size fits all solution. In larger firms with huge trading teams, one panellist argued that collaboration becomes increasingly difficult with automation.

Ensuring collaboration is efficient and that the teams are working towards the same goal as a group can be challenging, they noted.

Automation is not a one size fits all, echoed one panellist, who emphasised that automation needs to adjust on the workflow you are trying to achieve.

The panellist noted that on the private banking side for example, speed is essential and an area where automation can truly be useful. However, on the asset management side, there’s a little bit more room for execution to be slower – with automation in this instance being used differently.

“The whole value chain should be considered when automating,” said one panellist.

Scale and efficiency were labelled as the two biggest things that become available with greater automation on the trading desk.

“With the proliferation of ETFs, there’s a greater number of smaller sized tickets that need to be executed, especially in and around the benchmark points of time – whether that is 12:00, 15:00 or market on close. So being able to get those and get them executed efficiently at those benchmarks, with little slippage in time, that’s a huge advantage.”

The panellist continued to say that as a firm increases its assets under management, there’s more trades to execute which can either be done through hiring more people or through more efficient execution.

Panellists went on the acknowledge that over the past five to eight years, there has been a massive influx in the ability to automate individual bonds, allowing for improved scale and efficiency.

With growing advancements in technology and an ever-increasing amount of data becoming readily available to the trading desk, panellists concluded that automation paired with TCA will be able to help future proof fixed income execution in the coming years.

The post Automation and TCA must go hand in hand appeared first on The TRADE.

Nigam Saraiya

Specifically, the tool addresses a major issue facing the buy-side, wherein higher slippage occurs when sending multiple parent orders for the same instrument when they arrive at different times. 

The Order Aggregation feature sits within BestEx Research’s execution algorithms for equities and futures and allows traders to consolidate new orders with existing ones in real time, treating them as a single parent order.

Nigam Saraiya, chief product officer at BestEx Research, said: “An algorithm trading multiple orders for the same symbol can add to overall expected slippage. The more information an algorithm has – in this case, awareness and control of the total size being traded – the better it can decide on order placement and execution speed.” 

Through this approach, high execution speeds are reduced, liquidity seeking is optimised, and trading costs are lowered.

The tool has been designed with the aim of fitting into existing workflows with minimal disruption, explained BestEx Research.

“Traders simply opt in, and fills are allocated on a pro-rata basis back to the original parent orders—no need for additional customisations within their OMS. While it’s not a silver bullet, it’s a significant step forward in making algorithms more intelligent and effective in handling the nuances of multi-order trading.” 

Order Aggregation is particularly well-suited for trading desks that deal with large, complex orders, BestEx Research confirmed, wherein fair allocation without disrupting compliance workflows is key.

The new tool was developed in response to a request from Nordea Asset Management, a BestEx Research client, The TRADE understands – one of the first to put the new functionality into action. 

Speaking to the impact of the offering, Eugene Seo, head of equity trading at Nordea AM, asserted: “It is necessary that multiple orders in the same security do not compete against each other but instead are aggregated and represented as a singular order in the market. Aggregating them helps us reduce signaling risk and ensures fair volume distribution across working orders. 

“It ensures volumes are distributed on a pro-rata basis, so our investment teams are represented fairly […] Given our large average order size, our reliance is on conditional order types to achieve volume through larger and less predictable fills.”

The post BestEx Research launches new aggregation functionality for execution algorithms appeared first on The TRADE.