By Eugenia Mykuliak, Founder & Executive Director, B2PRIME Group
In the current global landscape marked by geopolitical tensions, stubborn inflation, and a fragile macroeconomic backdrop, liquidity has come into the spotlight. The Federal Reserve may not have formally shifted its policies, but its quiet liquidity injections are already reshaping markets. We’ve seen it in the wild swings of Treasury yields, and in Bitcoin’s $500 billion drop at the end of 2024, which underscored that digital assets are also sensitive to macroeconomic signals.
All of this is pushing all of us — asset managers, institutional investors, advisors, and everyone in-between — to ask the same question: how ready are we for the next liquidity crunch? Illiquidity is no longer a side risk, it’s a fundamental factor that deserves front-and-center attention when optimizing portfolio strategies and considering risk management.
When Liquidity Fails: The Lessons Are Loud
If 2023 and 2024 taught us anything, it’s that liquidity can disappear faster than most risk models anticipate.
Let’s recall the Silicon Valley Bank (SVB) situation, when a single day of digital panic wiped out what seemed like a solid institution. In March 2023, after the bank disclosed losses on its bond portfolio and a failed capital raise, tech startups and venture-backed firms immediately rushed to withdraw funds. Social media only fueled the panic further, and, as a result, nearly $42 billion in withdrawal requests hit the bank almost simultaneously. Unable to meet these demands, SVB went into a meltdown almost overnight.
A year before that, across the Atlantic, in the UK, margin calls on gilt positions during the LDI crisis forced pension funds into emergency bond sales. The situation was only salvaged by the Bank of England directly stepping in.
In crypto markets, the FTX crash of 2022 caused a cascade of failures, with stablecoins and major exchanges folding in a matter of hours. This showed clearly that even in digital markets, liquidity can vanish just when everyone needs it most.
Even U.S. Treasuries, long considered the most liquid asset in the world, have shown signs of stress in recent times. Hedge funds engaging in large-scale “basis trades” created a fragile dynamic, where volatility spikes triggered margin calls and fire sales.
We now live in a world where liquidity isn’t guaranteed even in the safest assets. Digital communication can turn fear into action in seconds, and waiting for a warning sign is no longer a viable strategy. As a result, real-time liquidity monitoring and scenario-based stress testing needs to become the new norm if the growing risks of illiquidity are to be avoided.
Institutional Shifts: How the Smart Money is Adapting
Given everything we’ve covered above, the smart institutions are already on the move, refusing to just sit and wait for another crisis to strike.
Hedge funds are learning to hold larger buffers of cash and repo-eligible assets. They’re dialing back leverage and using Liquidity-at-Risk (LaR) models to understand how much liquidity they can realistically access under stress.
An interesting thing to note is that regulators like the U.S. SEC have rolled out new measures to discourage short-term trading and strengthen fund liquidity protections. Among them is a rule permitting open-end funds to charge redemption fees of up to 2%, helping to cover the costs associated with frequent investor turnover. Additionally, the SEC now requires intermediaries to provide more detailed investor data, enabling funds to better track trading patterns and respond to potential redemption risks more effectively.
Meanwhile, quant funds are becoming increasingly sophisticated in how they manage liquidity risk, especially during volatile market conditions. They are embedding real-time liquidity signals directly into their trading algorithms so that the systems can assess when markets are becoming too thin to trade efficiently. When market depth drops or spreads widen beyond a certain threshold, the algorithms automatically reduce trade size, slow down execution, or pause trading altogether to avoid exacerbating price moves.
Some quant managers are also proactively building safeguards to address a newer threat of AI-induced selloffs. As more trading strategies rely on machine learning, there’s a risk that multiple models may interpret the same news events in similar ways, triggering large-scale, synchronized selling. To counter this, forward-thinking funds are stress-testing their models and introducing circuit breakers to prevent cascading reactions that could worsen market instability.
On the asset management side, portfolio segmentation is becoming the norm, as firms increasingly recognize the importance of aligning liquidity with investor expectations. Managers are now grouping assets by how quickly they can be liquidated — this allows for more accurate forecasting and helps avoid forced sales during market stress. Many funds are also adopting tools like swing pricing and redemption gates to further strengthen outflow management during periods of extreme volatility.
Beyond that, enterprise risk teams are actively developing detailed “liquidity playbooks” — predefined response protocols that guide real-time decision-making across credit, equity, and macro portfolios. These playbooks incorporate cross-asset signals and market depth analytics, ensuring that firms can respond swiftly and cohesively when liquidity conditions deteriorate.
Tools for the New Liquidity Era
We’re also seeing a shift in the tools used to manage liquidity, moving from reactive to proactive.
The previously mentioned Liquidity-at-Risk models simulate different redemption scenarios and identify fire-sale thresholds. AI-powered monitoring tools, meanwhile, scan markets for early signs of stress, including widening bid-ask spreads or rising funding rates.
Stress testing isn’t limited to interest rate shocks anymore — it now includes geopolitical events, cross-asset contagion, and mass redemptions. Yet another breakthrough comes in the form of network risk mapping — by identifying shared counterparties, repo dependencies, and exposure overlaps, institutions can spot choke points before they become systemic risks.
Liquidity as Alpha: A Strategy, Not a Reaction
Managing liquidity is a distinct competitive advantage now, and institutions that can act decisively in volatile conditions have a real edge. When prices move fast, the ability to move quickly and efficiently, without panicking, can be all the difference between gain and loss.
But in order to make it work, more firms need to start treating liquidity as a board-level issue. Every strategy should come with an exit plan: build buffers during calm periods, stress-test constantly, and assume zero warning in a digital-first world. Real-time dashboards and clear liquidity metrics can save precious seconds when it matters most.
In short, liquidity is no longer just a metric. It’s a mindset.
