FlexPREDICTS 2025

Market structure across asset classes has started to cross-pollinate increasingly, with workflows widespread in one asset class now cropping up as “innovations” in others. The overriding theme that will develop significantly in 2025 is the desire to connect liquidity providers with consumers in as direct a manner as possible.

We’ve already seen the first signs emerging in 2024 with the rise of direct-to-buy-side connectivity, where liquidity providers of various types create private, curated price streams for the buy side, who can then engage at their discretion. For some providers, notably those born in the deeply interconnected world of FX, this is nothing new, and they come with the native ability to widen spreads in response to various factors. For others, disclosing closely held liquidity is a more uncomfortable proposition, which is where technology providers will need to step up in 2025. Reducing the information asymmetry between liquidity provider and consumer will be critical to enabling both sides to engage willingly.

As this trend evolves, having a single entry point to the market – regardless of asset class – will become crucial. Lessons learned from one asset class can be ported to others without reinventing the (algo!) wheel. A flexible automation framework capable of operating across asset classes while observing the nuances of each will enable firms to transition to the long-anticipated model of a “true” multi-asset trader.

Portfolio Trading (PT) in fixed income has gone from zero to sixty over the past few years. Estimates suggest PT volumes will have doubled in 2024, with some asset managers now trading a massive portion of their fixed-income orders via PT.

Key use cases highlight its effectiveness. For example, PT facilitates the negotiation of large baskets of trades between the buy and sell side, minimizing market leakage and enabling more efficient pricing. Bond ETF use has increased in stressed or volatile markets, allowing asset managers to hedge their custom baskets within the overall beta. Baskets can then be iterated to resemble a liquid ETF as closely as possible. Similarly, liquid and illiquid bonds can be combined, leading to better execution outcomes than trading illiquid bonds individually. From a risk transfer perspective, PT can be more efficient than trading bonds line by line as portfolios can be rebalanced to achieve overall objectives, such as duration.

Currently, the PT process is very manual on both the buy and sell sides across workflow steps, such as initial portfolio selection, inclusion/exclusion, negotiation, pricing, execution, and managing exhaust. However, with PT volume expected to rise again in 2025, attention is turning to how an EMS can optimize increased activity from a flow efficiency standpoint.

In 2025, solutions will emerge addressing friction points to build efficiency around the overall PT workflow process. For instance, the management of “PT Exhaust,” where items not included in the negotiated PT still need to be handled manually. Using an EMS, traders can work both PT and the exhaust on the blotter. Regarding analytics, expect to see EMS integrations with providers such as ICE that can build the PT blotter by bringing in DV01 at the portfolio level to assist the iterations undertaken with the sell side.

Finally, PT effectively allows for “outsourced liquidity aggregation,” as dealers quoting on the portfolio could be sourcing liquidity through various means. For instance, one item in a portfolio might be very liquid, allowing the dealer to fill it from the market; another could be sourced from their inventory, while a third might be illiquid, necessitating sourcing from different locations and sizes. Over the next 12 months and beyond, an EMS will play a significant part in optimizing this process.

In the treasury space, interest rates cash trading will see significant advancements regarding EMS technology in 2025. The progress will be centered across five key areas where critical emerging functionalities will revolutionize Rates traders’ operations.

Seamless Liquidity Access:
Through an EMS, rates traders will access pre-trade, API-based tradeable firm liquidity, allowing the buy-side to make quantitatively informed, automated execution decisions.

The Buy-Side Leverages Sell-Side Functionality:
The buy side will leverage the same features and functionalities as the sell side, including reduced tick increments and spreads, firm liquidity, brokerage-free executions, and access to central limit order books.

Intelligent Automation:
The continued usage of smart order routing capabilities will allow the buy side to automate execution decisions cross-broker and inter-platform on a single trade.

Sophisticated Data and Analytics:
2025 will see continued advancement in data collection & querying abilities for broker & platform selection and a push for more advanced TCA.

Extended use of Execution Algos:
Finally, via the EMS, I expect to see growth in use of available execution algos, particularly by benchmark-driven portfolio managers looking to improve trading costs against the status quo.

As buy-side firms manage their foreign exchange trading activities in 2025, we see ongoing demand for bringing FX data and analytics into the EMS to further optimize electronic trading and improve results. The pre-trade data space will evolve further in FX over the coming year, with more peer-to-peer Transaction Cost Analysis (TCA) solutions emerging. Tying TCA to order and execution to deliver intra-day analytics will create value for asset managers and hedge funds by helping to guide and recommend execution.

We will also see buy-side firms seize control and extend the value of their data sets overall by crunching the numbers themselves. Large asset managers have recently become more sophisticated, building and leveraging their own cloud infrastructure to take in various data feeds that can directly or indirectly affect their trading. The outcome is that they can undertake bespoke in-house quant analysis of the full data set available to them. In turn, this will increase API order flow adoption – a direct result of the increase of in-house data analytics – essentially creating a feedback loop into their trading applications through an API connection.

From a cross-asset workflow perspective, clients will maximize their use of multi-asset technology by combining workflows currently executed independently to gain trading efficiencies.
 

A few months ago, I predicted that the SEC equity market structure rules on decreasing the minimum tick-size increments on certain stocks (Reg 612) and lowering the access-fee caps (Reg 610) for NMS stocks, would have the largest impact of any regulations on the sell side in 2025.

These reforms would have wide-ranging implications for the industry, from tighter spreads to how markets are made. In addition, they would increase the burden on vendors and other market participants in terms of making changes to their technology.

However, with the nomination of Paul Atkins as the new SEC Chair on Dec. 4, and legal challenges from the CBOE and Nasdaq on lowering the access fee caps, there is uncertainty on whether both the tick-size and the rule to lower access-fee caps will proceed or get postponed from their effective date of November 2025, if not completely shelved. On Dec. 12, the SEC decided to “stay” the rules pending completion of the judicial review process. Due to Atkins’ long-standing pro-industry, pro-business, and pro-capital formation stance on market structure, stay tuned for more twists and turns.

It’s even possible the SEC Chair will look to revisit Reg NMS in addition to seriously reconsidering these tick-size and access-fee rule changes. As has been the case for so many years regulatory and compliance will be the most impactful themes affecting our industry in 2025. However, for the first time in many years, we may see a regulatory environment geared towards a more industry participant-friendly approach, with a preference towards efficiency and innovation.

In 2024, the sell side has continued to experience increased demands from buy-side clients regarding service quality, access to liquidity, and, importantly, innovation. While collaborating with the buy side to meet these needs, the sell side has been forced to do so against a backdrop of reduced budgets and headcount due to tighter margins. With cost-to-income ratios likely to be under further scrutiny in a predicted challenging environment, increasing STP rates and, in turn, reducing the need for manpower around flow will be intrinsic to controlling costs and will remain an ongoing challenge into 2025.

Over the next year, I believe that the sell side will increasingly look to address these challenges by adopting solutions that can automate and scale as their business requirements evolve and have the optionality to add new asset classes or strategies as the market or their client demand dictates. For instance, from a technology perspective, they will look to adopt solutions to ensure whether they are trading fixed income, futures, or equities, they can do this with their current headcount through solutions that offer sophisticated automation tools – across all asset classes. Adopting this approach from a business and technology perspective can help manage costs while maintaining the agility and innovation necessary to deliver exceptional services.

In recent years, client and market demands have significantly challenged in-house and legacy trading technologies to operate beyond their original design to rapidly deliver an evolving set of functionalities and features required by the business.

Looking ahead to 2025 and beyond, I anticipate that trading teams will increasingly turn to external solutions that can offer cutting-edge capabilities and are underpinned with optimized delivery and deployment that empower them more effectively with regular drops of new functionality. While not a trivial task, strides are being made for it to happen. For example, automated testing, which enables continuous software testing to enhance both the quality and speed of the delivery cycle—from the initial requirements gathering to deployment—without sacrificing quality, will be a key focus.

This shift allows sell-side firms and their technology partners to move away from traditional monolithic upgrades, and adopt a strategy of smaller, more frequent updates. This approach facilitates the rapid delivery of features that positively impact clients, and when combined with continuous automated testing, it ensures timely and secure delivery.

Additionally, as the capabilities of technology and technologists continue to advance, sell-side firms will focus even more on automated trading – slicing and dicing customer orders, placing slices into algorithmic layers using next-generation liquidity search tools rather than relying on linear algorithms. Expect the next generation of traders to be less “wheelers and dealers” and more aviators at the controls of a jet airplane, setting the destination and dialling the controls up and down as they look for an edge. Increasingly, the machine will take care of the timing of the flow of orders and executions!

We expect the trend toward 24/5 trading to accelerate as more U.S.-based broker-dealers tap demand from retail investors for extended trading hours, driving more brokers and venues to jump in.
The major catalyst has been the demand for trading US stocks and ETFs in Asia Pacific. We were among the first to integrate our sell-side OEMSs with the Blue Ocean ATS. The motivation is that U.S. brokerage clients are routing order flow from retail investors in Asia Pacific to Blue Ocean’s ATS, which operates from 8:00 pm to 4:00 a.m. Eastern time.

We’ve seen very strong growth in those volumes and think it’s going to continue. A lot of retail investors overseas are sending orders inbound with order flow overnight, which occurs during APAC’s daytime trading hours. We don’t see that letting up, and it will require robust and scalable OEMS technology. With the New York Stock Exchange’s plans to extend its hours 22/5, and startup 24 National Exchange receiving SEC approval to operate 23/5, subject to changes in the Equity Data Plans (SIP) operating overnight, we expect to see more competitors enter the field. We think 24/7 trading is inevitable over the next 5 to 7 years.

In 2024, APAC has seen a surge in interest in new launches of all sizes and strategies. While smaller funds have often sought lighter, standardized solutions, most large single Portfolio Manager and Multi Strat funds have identified sophisticated, high-performance tech with robust, flexible APIs and advanced trading capabilities within a tightly integrated OMS and EMS solution. Additionally, they want open integrations with third parties to allow them to customize their workflows to suit their unique trading strategies.

In 2025, we expect these requirements to continue to grow, with increased asset class coverage and sophisticated cross-asset trading functionalities with a data and API-driven approach. TCA, Automation, AI, and mobile platforms remain emerging themes. Across an increasingly complex and volatile global market landscape, we are seeing an uptick in funds tracking index and model baskets, meaning solutions with baskets benchmarking and batch processing capabilities are coming to the fore as “must-have functionalities ” for the OEMS.

Finally, many regional desks will expand to trade more with the US, meaning global multi-asset technology solutions underpinned by superior client support across time zones will be crucial to delivering the operational agility to compete.

With the growth of multi-strategy hedge funds, many shops have diversified into various pair trading strategies, such as risk arbitrage and/or cross-border relative value arbitrage, handled by different pods.

In 2025, we expect to see demand for global, multi-asset pairs trading to continue, along with heightened interest in relative value fixed-income and cross-asset, cross-region pairs trading strategies.

However, the workflows associated with multi-asset pairs trading — executing linked securities trades, arranging short locates, running compliance and allocations — are complex and can pose challenges if undertaken on separate systems. The future is about simplifying workflows and driving efficiencies. Many hedge funds are turning to the OEMS to lead that charge.

The multi-asset, multi-strategy nature of hedge fund operations, combined with the rapid movement required to capitalize on market opportunities, has evolved how teams need to interact with their Order and Execution Management Systems (OEMS). Today, specific strategies, pods, asset classes, and workflows demand specific functional and oversight access to the OEMS across various trading, portfolio managers, operations, compliance, IT, and business functions.

In 2025, we expect to see firms demanding multi-faceted ways of interacting with their OEMS, such as:

The Main OEMS UI: Funds will expect constant enhancement and development to cater to their multi-asset / multi-strategy trading requirements and deep cross-asset class specialization in one single user interface view. From this seamlessly integrated view, which incorporates and aggregates data providers, liquidity venues, market makers, ELPs, and third-party execution services, users can access liquidity and data from multiple sources in one OEMS framework to drive decision-making and execution.

API: Today, almost all desks have direct development exposure or oversee development resource allocations. In 2025, expect more data analysis, automation, and streamlining workflows, which are only possible with modern, robust APIs and workflow tools. All clients will look to use APIs in various shapes and forms, including signal and order generation, custom data, automation, integration with third-party data, running compliance, and more.

Flexible Access via Devices: The increasingly global nature of hedge fund trading will require a more flexible “on the road” way of interacting with the OEMS. We envision further uptake and adoption of native mobile app access to cater to various workflows, including portfolio manager order entry, real-time PnL monitoring, and compliance monitoring and overrides.

The adoption of GenAI-driven assistants in the past 18 months has been truly fascinating, and the potential for change they can bring is accelerating rapidly. In 2024 alone, multiple clients successfully deployed our AI assistants across applications in FlexTrade’s solutions suite. They’re now actively using them to extract information and operationalize their trading data and their chosen trusted third-party sources to make quicker actions and decisions on their blotter—crucially, with fewer errors.

So, in a rapidly evolving area, where next in 2025? AI assistants will likely take the next jump over the next 12 months to evolve from ‘assist and learn’ functions toward ‘alert and warn’ capabilities. Combining GenAI with Machine Learning, trained on users’ behavior data, will enable intelligent and proactive guides, allowing traders to work more efficiently and reduce errors. Could we soon be at the point where the AI guide can proactively “co-pilot” a trader and suggest – ‘It’s Thursday at 7:30 pm, and you still have 30 Orders to complete. Should I order your dinner?’”.

In 2025, we could also see GenAI provide value in other areas. For instance, from an interoperability perspective, connecting applications controlled by an AI core, allowing users to have a complete suite of functionality across their selected providers to create a seamless ‘best of breed’ solution, is possible.

As we look across the multi-asset landscape, desks seek scale, so new liquidity workflows will develop for equities, fixed income, and other asset classes. AI bots can handle these workflows to help manage the increased trading activity. Additionally, algorithms and trading wheels will be enhanced with machine learning to improve execution. The overarching theme, though, is that efficiency is crucial; users need to be able to manage more with less effort.

With exponential increases in data from electronic trading, analytics will continue to leverage advances in Machine Learning and AI in 2025 through EMS technology. Buy-side trading desks will most likely demand the ability to digest granular and overarching information about their flows quickly. This will extend to analytics, where we see it becoming commonplace to offer natural language queries about key what-ifs and the context of a trade over its life cycle.

In addition to seeking answers from their datasets, we anticipate that standard trade analytics and TCA evaluation will give way to quantifying the value of automation to a portfolio manager. The rich data streams that inform trade analysis can also help trading desks demonstrate their value. Specifically, traders will turn to analytics to measure alpha capture, execute investment ideas, and quantify the PM’s time and opportunity cost in justifying automation efforts.

While digital assets have been a hot topic over the past few years, will 2025 see them finally move from being considered a fringe asset class to being more widely adopted by retail and institutional investors as a legitimate asset class?

With BlackRock being among the first household names to offer exchange-traded funds in cryptocurrencies, initially focused on SEC-approved ETFs in bitcoin and Ethereum, there are signs that support for digital assets has hit the mainstream in TradFi. Other factors like support from the new incoming U.S. government and a more crypto-friendly SEC chair, could lead to legislation from Congress and less regulatory uncertainty over the coming year.

If widespread adoption accelerates with hedge funds and asset managers allocating to digital asset classes, this raises the need for institutional-grade trading platforms and other infrastructure, such as smart order routers and algorithms through an OEMS, to source liquidity across various crypto exchanges and venues.

In that case, the question is how well the industry is ready to support a rapid increase in trading volumes as desks look to get in and out of positions. Indeed, trading technology improvements will be required, with spreadsheets likely to be unsuitable in the long term. Additionally, outside of trading, the supporting infrastructure for downstream processes, such as real-time settlement on blockchain, independent custodians, and data security, will need to be industrialized to handle the new increased scale.

In algorithmic trading, continuous improvement frameworks are expected to gain attention next year. This enables market participants, including investment groups, trading desks, brokers, and venues, to adjust their tactics to “reset” their understanding of strategy, algo, and venue behavior. We expect the industry to shift away from merely asking questions about which are their best brokers or how their algos perform and move towards examining the methodology that’s used to set up automation so that it gives clear, ongoing answers to key business questions.

As 2025 unfolds, we anticipate that trading desks will demand more tailored analytics, where they seek answers about how analytics directly bear on the particulars of trading flow. In the past, clients would accept a general cost model trained on the entirety of a similar set of orders. Now, the buy side wants to consume analytics capable of considering their firm’s particulars and its PMs and traders. The crucial tradeoff here is how to measure and frame the robustness associated with the adaptability of an analytic.

In 2024, our survey with Coalition Greenwich found that a quarter of respondents highlighted “automated trading tools” as the desired functionality within a fixed income EMS to solve their challenges. In 2025, we expect automation to continue to be a central theme for the fixed income EMS conversations in the market across a few distinct areas.

From a venue perspective, the trading platforms have offered more automation functionality. Over the next year, we expect to see more firms using an EMS to enrich, not replace, that venue automation with additional layers of customization.

Incorporating “algorithmic automation” alongside “workflow automation” will also be an emerging theme to keep an eye on. We’re already seeing the early adopters of algorithmic automation in fixed income markets give up some discretion to the algo, while, of course, maintaining the usual trader-specified directives and guardrails. Is the quantitative assessment of execution performance reaching new heights?

Watching buy-side firms leverage the power of a fixed income EMS for automation, informed by aggregated, cleansed, and actionable data, will be very exciting in 2025.