FlexPREDICTS 2026

As 2026 progresses, electronification of streaming FX swaps is set to take-off. While FX spot trading is largely automated, sell-side firms will begin offering streaming swap liquidity through the EMS and venues offering pricing via APIs. This will enable mid-market trading and better data analysis through the ability to build out customized curves for liquidity analysis. The shift to electronification will improve data and pave the way for algorithmic trading in FX swaps, reflecting the buy side’s demand for automation.

Automation of FX trading will advance with more sophisticated tools for analyzing spread and historical data. Supporting the move toward dynamic, real-time decision making, the buy side will have the tools to compare past, present and future FX trades. To simplify adoption, all the data will be moved into the UI to make trade comparisons easier to run.

On the execution side, expect an uptick in forward fixing platforms from large asset managers. Additionally, buy-side clients are expanding into emerging market currencies from smaller, less liquid countries. With pressure on the banks to expand their market making capabilities, this trend will broaden new revenue opportunities in emerging markets.

In the digital assets space, we see Traditional Finance (TradFI) firms adding crypto into their portfolios. With changes to SAB121 policy, some Banks have begun offering custody services, and we expect more to follow suit. With Hedge Funds leading the charge, we support them with a robust OEMS platform that provides crypto exchange and market-maker pricing, along with trading capabilities, alongside all other asset classes. It allows crypto to be traded in the same fashion you would other assets, such as FX.

Finally, 2026 will see further integration of transaction cost analysis (TCA) with AI chatbots. Traders can already interact with TCA data using FlexAI to query top performing banks or find best-performing execution styles for currency pairs. Partnerships with third-party TCA providers are underway for clients to add AI-driven data and MCP [model context protocol] servers.

2025 was a landmark year in the options trading space, with volumes rising 20% compared to 2024, reaching the highest levels we’ve seen in nearly three decades that FlexTrade has been in business. The record highs, primarily driven by the buy side, and retail investors, also saw a newer segment known as “Protail” which refers to professional retail customers utilizing institutional technology, enter the fray.

The majority of the liquidity and volume sits among the top fifty names, with SPX and VIX showing significant increases, half in the form of front month, weekly, and 0DTE short term option expirations. We’ve also seen a sharp increase in volumes for complex orders and flex options specifically.

As we head into 2026, we anticipate that options volumes will continue to grow. Currently, 18 options exchanges operate in the U.S., with two more set to launch in the next 12 months. In addition, ongoing economic uncertainty, inflation, and an unpredictable geopolitical landscape will make it impossible to escape volatility.

To navigate the rise in volumes, exchanges, and volatility, the need for financial institutions to adopt enterprise technology that can quickly process large volumes of data to make sense of a dynamic market and react in real time, becomes more pressing. Traders need to be able to price, trade, and hedge options in the same place—which includes hedging across asset classes and automatically. And in the face of mounting volatility, the ability to manage risk in real time will be imperative.

Of course, Gen AI and LLMs will undoubtedly play a role in devising new strategies for trading and putting capital to use. For options, this can mean improvements such as streamlining the placement of spreads across multiple underlyings by dynamically predicting correlations and optimizing contract ratios and execution timings.

The coming year will mark a turning point for fixed income markets. Over the past 12 months, we’ve continued to see new credit and rates venues across EMEA and North America, leading to increased fragmentation. At the same time, institutional clients are demanding greater access to direct dealer connectivity and diverse liquidity sources, reshaping how traders engage with liquidity and therefore the need for trading workflows to be reimagined.

Adding to this complexity is the introduction of the consolidated tape—a high-profile data set that promises transparency but also challenges firms to integrate and act on new information quickly. These developments make one thing clear: fixed income trading desks need scalable technology to keep pace.

In 2026, success will hinge on consolidating fragmented workflows within an advanced EMS. By unifying connectivity, liquidity, and data, firms can streamline operations, improve decision-making, and unlock efficiency at scale. Those who invest now will gain a long-term competitive edge, while those who hesitate risk falling behind in an increasingly complex market.

In 2026, I expect cost pressure, market uncertainty, and the possibility of a correction to prompt sell-side firms to rethink how they structure and invest in their trading technology. In these environments, budgets tighten, and firms are typically forced to decide which components they should truly own and where they should partner.

Across the industry, we are seeing a clear shift toward taking more control over the technology that defines a firm’s intellectual property while simultaneously simplifying the broader architecture and reducing legacy complexity. Many Tier-1 brokers are internalizing the pieces that add the most value, such as their fast gateways, ultra-high-frequency market making infrastructure, and client-facing components, while outsourcing commoditized and regulatory-heavy workflows to trusted partners.

At the same time, we have engaged multiple large firms seeking simplification. Instead of managing five or six different systems across desks and asset classes, banks are increasingly looking for one strategic partner who can support multi-asset trading, reduce vendor sprawl, and still give them the flexibility to build around the parts that define their edge.

In the upcoming year, I believe cost pressure and possible market correction will accelerate banks towards this model. They will need to discern which components are truly differentiators that should be built in-house and evaluate whether they have the right technology partner to support the rest of their workflow and act as an extension of their own development team.

With a pro-crypto mindset in the White House and a regulatory shift toward policies that support innovation in crypto and digital assets, we predict that tokenization will be a major theme for 2026. Despite years of regulatory uncertainty, regulators are moving quickly to develop a framework that distinguishes between crypto securities, digital currencies, and commodities.

Industry leaders such as Blackrock, have publicly spoken about tokenization of equities and ETFs while major banks including BNY, Citi, and JPMorgan have launched tokenization initiatives. Now, exchanges such as Nasdaq and LSE have proposed tokenization plans for individual stocks. Meanwhile, Robinhood has already tokenized 800 TradFi instruments in the EU and will continue to expand to the US.

There are compelling reasons for moving legacy rails onto blockchain such as de-risking the financial system via instantaneous settlement, moving collateral, and better aligning infrastructure with the evolution of 24-hour trading. Secondly, there is a mandate to advance US capital markets and lead the charge in this technology to maintain a competitive advantage.

However, brokers, market makers, and industry bodies have raised concerns about whether the SEC should grant broad exemptions for tokenized securities, from the regulatory safeguards, investor protection rules and other guardrails that are required in TradFI. SIFMA warned about “parallel, but unequal trading ecosystems with weaker safeguards, fragmented liquidity, potentially inconsistent pricing, and competitive disparities.”

Nevertheless, we expect that legislative efforts and US investor demand for digital assets, will push tokenization next year.

We expect global sell-side trading desks to accelerate their expansion into a wider range of asset classes in 2026. Beyond equities, options, futures, and FX spot, firms are increasingly requesting the ability to handle fixed-income RFQs, FX swaps, and crypto RFQ workflows as client demand broadens. At the same time, we’ve seen increased interest in AI integration for smart trader queries, real-time Transaction Analysis Reports, dark pool connectivity, and a renewed focus on compliance and auditing capabilities.

As trading volumes continue to rise across markets, it’s become apparent that firms are not looking to increase headcount but rather expand the capacity and capabilities of their OMS. To support this, firms will need an OMS with a consolidated global view across regions and desks, enabling better visibility into client orders and more unified risk management.

In 2026, the sell side will prioritize platforms that can handle higher volumes, more asset classes, and additional venue connectivity in a single, centralized view. The ability to scale workflows without increasing headcount will become a key requirement for OMS platforms. Systems that unify cross-asset trading, provide real-time insights, and streamline monitoring and risk oversight will be essential for desks looking to scale efficiently in the year ahead.

In 2026, I expect APAC Tier-1 brokers to continue accelerating their shift away from monolithic, single-vendor trading platforms and towards modular, bank-owned architectures, as firms look to improve straight-through processing and reduce operational friction across the trade lifecycle.

Asian markets are inherently complex because they are highly fragmented across countries, venues, rules, and workflows. Each market has distinct microstructure nuances—tick sizes, lot sizes, trading calendars, closing auctions, currencies, and languages—which forces brokers to maintain market-specific connectivity, risk checks, and post-trade processes.

The result is a landscape where internalization, multi-vendor interoperability, and customization are as critical as speed. Hence, firms are adopting a “buy-and-build” approach to their technology spend rather than relying on a single vendor to control the entire trading stack.

This flexibility gives firms greater control over how orders move through each stage of execution and post-trade processing.

To make this model work, firms require technology partners that can support the full sell-side ecosystem across multiple asset classes and desks, spanning key components such as FIX connectivity, OMS, risk management, IOIs, middle office, exchange connectivity, smart order routing, pairs trading, market making, and algos (DSA). A key differentiator is the ability to deploy independent microservices with all services underpinned by industry-leading APIs and analytics.

Next year, I predict APAC sell-side firms will seek partners that can provide every component of the ecosystem while allowing them to adopt only the modules they need. Empowering firms to optimize STP across APAC’s fragmented markets while scaling operations to meet diverse regulatory and liquidity demands.

In recent times, the sheer volume of risk, trading, and downstream data available at the hedge fund front office desk has grown exponentially in size, richness, frequency, and complexity. To make informed decisions, traders and portfolio managers (PMs) need timely access to this data in an aggregated format. In most current setups, this often requires switching between different views and applications to gather the necessary information. The process can be time-consuming and require significant manual effort—impacting speed, agility, and the ability to execute strategy effectively.

Today, cloud-based data warehouse (DWH) solutions can deliver Traders and PMs historical position, risk, and trade data, seamlessly embedded into their workflows. At a minimum, a modern DWH can deliver user-defined snapshots of key data points like portfolio exposures, PNL, and pro forma, say up to every 10 seconds, and make it available within the order blotter to make split-second decisions.

Moreover, with clean trade and position data sets aggregated in one place, trading institutions can unlock deeper value. For example, to view specific moments within a day to analyze portfolio performance and identify the contributing factors, such as movements in the underlying factors and trading activity.

AI will enable additional capabilities. For instance, natural-language queries of historical data on the fly, as well as custom reports and dashboards embedded straight into the order blotter. As on-demand accessibility continues to develop, expect “anytime, anywhere” access to historical and intraday data and analytics via a responsive mobile app to become the norm.