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May 4, 2026
Ronald Ratcliffe, PhD, Head Strategist for Portfolio Analysis for Aladdin
Alisha Sewdass, Head of Americas Solutions Engineering, Aladdin Client Business
In a structurally more volatile environment, risk management is shifting from a periodic exercise to a continuous workflow, reshaping how institutional investors approach portfolio visibility, stress testing, and liquidity analysis across public and private markets.
A scenario-based approach to the evolving landscape of risk and market volatility
Volatility is no longer a single event or episode to navigate. For the CIOs and CROs that I work with at some of the world’s largest asset managers, pension funds, and leading insurance companies, it has become a permanent workflow condition to solve.
The institutions that are adapting well are not simply building bigger risk teams. They are rethinking how decisions get made, how portfolios get stress-tested, and how data and analytics sit inside that process—continuously, not periodically.
In 2026 year-to-date we are clearly in a higher-volatility regime. And there are structural reasons for that; namely, a confluence of technological disruption, including AI, layered on top of deepening geopolitical fragmentation. You don't have to resolve the debate about how different this period is from previous ones to accept that clients are preparing for it very differently. One way they're doing that is through scenarios. In more stable times, you'd really have to work hard to identify a couple of meaningful alternative outcomes. Now, clients want to know about half a dozen different outcomes and that's become the baseline expectation, not the exception.
1. Know your exposures. Know what you own. Know what it is worth. This is where everything starts. You cannot manage what you cannot see, and in volatile markets, visibility is the first thing that slips.
2. Be aware of what can change. A colleague of mine is fond of saying: “chance favors the prepared mind.” He is right. This is not about predicting outcomes. It is about understanding which assumptions your portfolio is most sensitive to so that when conditions shift, you are already thinking clearly.
3. Stress test your models. Look at your model. Then look at it again when the environment moves. Keep asking: is there something I would change, something I am not capturing, something I am missing? In the Aladdin platform, for example, Market‑Driven Scenarios (MDS) provide a way to assess how alternative market environments translate into portfolio P&L.
The willingness to adapt your model to reflect current reality is not a sign of weakness, it is the whole point. There is no such thing as a perfect model. Perfect volatility preparedness in 2026 is a model that gets better every time the world forces you to look at it again.
Liquidity, commitment risk, and the race for real-time data
Stress testing used to be a monthly exercise. Now it's a daily practice. And that shift isn't only about what markets are doing—it's about what clients are holding. Portfolios have become structurally more complex. The types of assets and structures that institutions are investing in have gotten way more complicated, which means that during a sell-off, understanding where your exposures actually sit has become a major analytical challenge in itself.
And really the workflow has to start there: with exposure. Not the stress test—with what you own. Ideally that means having all positions modeled accurately, with real-time cash and position-level data across both public and private assets, on a single platform. This is particularly critical for complex structures such as private credit, where it’s not enough to understand aggregate exposure—you need visibility into which positions are PIKing, increasing long‑term exposure while deferring near‑term cash interest, and therefore creating hidden liquidity and concentration risk.
The second major challenge our clients face is the pricing gap. Public markets reprice in real time. Private assets don't—there's typically a quarter's lag before they are formally marked. That gap between what you're seeing in public markets and what you can actually see on the private side is precisely where risk officers are asking the hardest questions right now.
Liquidity is where it becomes structural. When markets sell off, GPs see opportunity and call capital—at the exact moment that asset owners are already absorbing losses on the public side. That dual pressure, hit on the asset side and hit on commitments simultaneously, is a liquidity burden that can be supported with a near-real-time view of cash flows, income, and commitment risk across the whole portfolio.
Once you know what you own–only then–comes forward-looking stress testing. Instead of re‑running historical scenarios, today’s stress testing should take a forward‑looking, multidisciplinary approach that connects near‑term market risk with longer‑term credit migration and structural liquidity risk.
The institutions adapting well are building these components into a single, continuous workflow rather than an ad hoc exercise.
1. Measure how long it takes to understand your exposures: end to end. Pressure‑test the full chain: market move, data ingestion, aggregation, exposure insight. Determine if it takes minutes (or days) to aggregate positions and understand underlying exposures. Volatility compresses decision windows so time to action matters more.
2. Review the organization’s ability to surface integrated credit, liquidity, and market risk insights in a timely manner.
3. Establish a timely, forward‑looking liquidity view across public and private assets, incorporating cashflows, unfunded commitments, delayed cash income, and stress‑driven cash needs so liquidity risk is understood by cash flow behavior and timing, not asset classifications.
A structural regime of elevated uncertainty—not a single shock, but a persistent condition that demands continuous risk management. It is driven by the convergence of technological disruption and geopolitical fragmentation.
It means having a clear, real-time view of what you own, across every asset class, sector, geography, and counterparty—before making any risk or allocation decision.
Stress testing is the application of adverse hypothetical conditions to a portfolio to measure vulnerability and resilience. Post-2008, it has moved from a periodic governance exercise to a continuous, primary risk management tool.
Continuously stress test and question your risk models as conditions evolve—rather than treating them as fixed. The goal is a model that improves every time changes in the market force you to look at it again.
Continuously stress testing and questioning your risk models as conditions evolve—not treating them as fixed. The goal is a model that improves every time changes in the market force you to look at it again.
A forward-looking risk technique that models portfolio performance under a range of plausible – not just historical – macroeconomic, geopolitical, or policy conditions.
Public assets are liquid and frequently priced; private assets are not. Applying consistent risk analytics across both requires structured modeling, data standardization, and look-through capability into underlying holdings. Why is this needed? Average institutional alternatives allocations rose from 15.7% in 2020 to 19.6% in 2024 according to Preqin data—making cross-asset risk analytics a core operational requirement, not an optional enhancement (Preqin is a part of BlackRock).
A whole portfolio approach means managing public and private investments as one integrated system, rather than as a collection of separate asset‑class silos. Whole Portfolio by Aladdin was the industry's first end-to-end solution for managing public and private assets on a single platform. It is a connected ecosystem that gives institutional investors an enterprise-wide view across all asset classes—including both direct and indirect investments in private markets—enabling unified risk, exposure, and performance analysis.
Aladdin Risk is a market-tested analytics engine—available as a standalone offering or as part of the broader Aladdin platform. It combines sophisticated risk analytics, quality-controlled data, and highly scalable processing to give institutions a single, holistic view of risk and returns across their entire portfolio.
It solves three core problems:
Visibility: ‘Know what you own across the portfolio’, with flexibility to choose the most appropriate risk factors and models for each institution's specific circumstances. The Aladdin platform reviews 300+ risk and exposure metrics daily to support institutional portfolio oversight.
Identification: decompose risk by portfolio, risk factor, sector, or security; build and perform stress tests, what-if analyses, and optimizations
Decision support: perform a wide range of portfolio modeling exercises and conduct customized risk analyses by viewing and changing a variety of assumptions.
Aladdin Risk monitors 5,000+ multi-asset risk factors and reviews 300 risk and exposure metrics daily.