What if the next major market event exposed a hidden weakness in your trading infrastructure – one that cost your firm real opportunities, not because of your strategy, but because your systems couldn’t keep up? In today’s markets, the pace and pattern of volatility have changed so fundamentally that many legacy systems are increasingly unfit for purpose.
The first quarter of 2026 has provided many warning signs about the importance of robust trading infrastructure and systems capable of processing large volumes of market data. The Iran-driven volatility spike in Q1 2026 highlighted a hidden risk in that legacy trading systems, originally built for lower volumes and predictable trading windows, are coming under strain as markets shift to distributed and continuous price formation in a volatile world. Firms that don’t invest in platform modernisation will increasingly find themselves unable to keep up with volatility and ever-increasing volumes.
In January, we published the 2026 State of Trading Infrastructure report in partnership with Exegy. The report found that firms are not just facing challenges from rising volumes, but also shrinking time-to-opportunity and increasing difficulty maintaining performance under stress.
In this blog, we take a closer look at how volatility is changing and why emerging drivers such as prediction markets are reshaping the demands on front-office infrastructure.
Volatility no longer behaves the way systems expect
Volatility remains a central challenge for quant trading firms, but not just because of its level. The real shift is that it is no longer linear. The market performance around the US and Israeli attacks on Iran in Q1 2026 provides a clear example of this shift in action.
The unpredictability of events meant that markets did not adjust gradually; instead, activity compressed into short, intense bursts around key events, impacting the energy markets and triggering rapid repricing across asset classes. Positions were adjusted in real time and automated strategies reacted instantly. But those moments triggered sudden surges in data, liquidity demand and execution pressure, all within seconds.
This market behaviour is becoming the norm. Market data traffic spikes are much higher during periods of stress, rather than increasing smoothly over time. The Acuiti study, conducted before the recent volatility, found that during high-volatility events, nearly three-quarters of firms experienced issues with their market data infrastructure.
The consequences are significant. Systems that perform well under normal conditions can become unstable when faced with sudden increases in load. This directly impacts outcomes – only 3% of firms reported being able to capture ‘all’ available opportunities during periods of volatility.
There’s a growing disconnect between legacy infrastructure and current market structure. Historically, trading systems were built around centralised liquidity and predictable windows, with activity concentrated for set hours.
As trading has extended market hours and enabled continuous price formation, firms that remain tied to legacy assumptions are increasingly likely to miss opportunities. This is not because they lack access, but because their systems cannot keep pace.
In this environment, average performance is no longer a useful benchmark. What matters is how systems behave at the extremes.
New drivers of volatility: Prediction markets
An increasingly important driver of this new volatility profile has been the growth of prediction markets. These markets introduce a fundamentally different trading dynamic. Prediction markets are uniquely positioned to isolate individual events, with activity directly tied to specific real-world events.
As in traditional markets, prediction market volume is sharply concentrated around moments of uncertainty, such as political developments or geopolitical escalation. This creates a feedback loop in which events, pricing and trading activity reinforce one another in real time.
Prediction markets do not solely reflect volatility; they are also shaping it. As new information enters the system, it’s priced, traded and transmitted across markets in real time, contributing to the same bursts of activity seen in traditional asset classes but fragmenting trading activity across a new asset class.
If you fail to prepare
As markets become more complex and unpredictable, maintaining performance under pressure is becoming critical. Fewer than a third of firms in the Acuiti survey said their current front office infrastructure to be able to process the market data volumes by 2030 without further investment, highlighting a growing gap between market demands and system capability.
Firms are increasingly missing opportunities not because of strategy limitations, but because their infrastructure cannot absorb current volumes – let alone future growth and complexity.
Market data processing is emerging as a key constraint. As volumes rise and activity becomes more irregular, it becomes an increasingly limiting factor in maintaining performance and reliability. When systems cannot process data quickly or maintain stable latency, execution quality drops, signals become less reliable and opportunities are lost.
To stay ahead, quant firms must rethink their front-office infrastructure, invest in scalable market data handling and systems for extremes – not just averages. The winners will be those who anticipate the next wave of volatility, adapt quickly and turn infrastructure into a competitive edge. The rest risk becoming obsolete in a market that never waits.
Download the paper for more information via the link here