The New Alpha Playbook: How hedge fund CIOs are rebuilding portfolios for an uncertain world

JUNE 2026

HOW HEDGE FUND CIOS ARE REBUILDING PORTFOLIOS FOR AN UNCERTAIN WORLD

The macro environment in 2026 offers hedge fund chief investment officers little stable ground. Persistent volatility, geopolitical disruption and a succession of regime shifts have made the question of where uncorrelated alpha comes from, and how to access it, the defining one of the year.

This report surveys senior investment professionals on how their portfolios, asset class allocations and investment processes are evolving, and what infrastructure they need to keep pace. The picture that emerges runs against the prevailing narrative. The expansion into new asset classes, illiquids included, is being led from the platform end of the industry and driven by conviction rather than allocator pressure or compressed liquid-market returns. CIOs are choosing this path on its merits.

The operational story is less settled. Managers describe their front office technology as adequate, then upgrade it anyway, particularly once expansion is underway. What emerges is an industry quietly retooling itself for a more complex investment process, with infrastructure capacity emerging as the gating factor on portfolio ambition.

Part I examines where alpha sits in 2026, what is driving the reshaping of portfolios, and the concentrated move into illiquid assets. Part II turns to the operational consequences of that expansion: the challenges of running fundamentally different asset types within one book, and the front office technology that increasingly separates the funds that can execute from those that cannot. With data-driven findings and contributions from industry leaders, this report offers a view of how the 2026 CIO is rebuilding for an uncertain world.

MANAS PRATAP SINGH

The key source of data in this report is Hedgeweek’s Q2 2026 Hedge Fund Manager Survey. Respondents were spread across the major global domiciles, AUM size category and flagship strategy type. Further insights were gathered through interviews with named and unnamed hedge fund sources, alongside additional third-party research and intelligence. Allocator preference data is drawn from Hedgeweek’s H2 2025 and H1 2026 Allocator Surveys, conducted in partnership with AIMA, allowing this report to set manager behaviour against the shifting strategy preferences of the allocators who back them.

1

Conviction, not pressure

Among funds that have changed their portfolio approach in the past year, 42% cite the pursuit of uncorrelated alpha as the primary driver. Allocator demand registers at just 4% and compressed liquid-market returns at zero. This is a conviction-led repositioning, and it intensifies with scale: 67% of managers above $1bn name uncorrelated alpha as their primary driver.

KEY FINDINGS

2

Platforms lead the illiquid move

The shift into illiquids is concentrated, not broadbased. 33% of multi-strategy respondents have increased illiquid allocations over the past three years, against just 8% of equity long/short managers. The platform end of the industry, with the scale and operational depth to absorb the complexity, is doing the expanding.

3

Infrastructure is the gating factor

Execution and market access are the biggest asset expansion challenges, cited by 28% of respondents. But the infrastructure cluster of risk aggregation, data sourcing and accounting, valuation and reporting collectively accounts for 44% of primary challenges. Execution gets a fund into a new asset class; infrastructure determines whether the portfolio can be run coherently afterwards.

4

Adequate is a moving target

96% of managers rate their front office technology as either fully adequate (44%) or adequate with limitations (52%). Yet 28% have upgraded in the past 12 months, and a further 16% recognise the need to. The operational reality of multi-asset investing is forcing infrastructure decisions even where managers do not initially describe their technology as inadequate.

PART I: WHERE IS ALPHA IN 2026?

What is driving the reshaping of hedge fund portfolios, and is the move into new asset classes led by conviction or by hedging?

The starting point for any conversation about portfolio construction in 2026 is a simple shift in what CIOs are looking for. The industry is not running from beta. It is running toward differentiated return streams. That distinction reframes the entire diversification story away from making changes to the portfolio as a defence and but toward opportunity.

In our surveys of allocators over the last two quarters, a theme has emerged. Allocators want maximum diversification and are open to managers expanding into new asset classes for best risk adjusted returns. So how is it impacting managers and their portfolios?

We asked managers if their asset class mix had changed over the past year. Among funds that said that they have changed their portfolio approach over the past year, 42% cite the pursuit of uncorrelated alpha as the primary driver (chart 1.1), by some distance the most cited factor. Market volatility and regime change follows at 12% and risk management at 8%. Allocator demand for diversified exposure registers at just 4%. The diversification under way is conviction-led, not demand-led. CIOs are selecting this path, not being pushed onto it.

“Managers, much like top chefs, almost never choose to change their secret sauce based on the customer,” a Paris-based hedge fund CEO told Hedgeweek. “When we add any new ingredient or asset to our portfolio it is always based on our own research. If an investor would rather want something more than we have to offer, they can go to the shop next door.”

The conviction deepens with size. Among the largest managers, those running more than $1bn, 67% cite the pursuit of uncorrelated alpha as their primary driver, against 42% across the full sample. The funds with the greatest operational depth are also the most conviction-led, a pattern that recurs throughout this report. Scale does not dampen ambition. It concentrates it.

That instinct is echoed by practitioners across strategy types. Naruhisa Nakagawa, founder and CIO of Caygan Capital, a multi-asset fund specialising in convertibles and equitylinked securities, says his firm expands not because asset classes are new but because inefficiencies still exist within them and because its existing analytical edge can be transferred. When markets become crowded and alpha gets arbitraged away in one area, the natural move is toward adjacent spaces where competition is lower.

Zulfiqar Ali, CIO of ZAMS Asset Management, points to a live example of that dynamic. His energy commodities book has found alpha in inter-commodity spreads, with the situation in Iran creating dislocations that his strategy has been positioned to monetise. Neither manager describes allocator demand as a meaningful input to that process. Investors care about riskadjusted returns and diversification, Nakagawa says, but are generally agnostic about the precise instrument used to generate them.

The allocator side of the market reinforces the picture from a different angle. Across two waves of our allocator survey (chart 1.1a), strategy preferences have reordered in a way

consistent with a flight to differentiation rather than to safety. In H2 2025, allocators ranked their preferred strategies as macro first, then long/short equity, market neutral and credit, with multi-strategy, which had reportedly overtaken long/short equity in AUM terms, sitting fifth. By H1 2026, long/short equity had moved to the top, macro to second, market neutral holding third, multi-strategy climbing to fourth and credit slipping to fifth.

The headline movement, long/short equity and macro trading the top two positions, reflects

a reweighting toward strategies that promise dispersion and directional conviction in a volatile regime. The quieter signal is multistrategy’s steady climb. Allocator preference is catching up to where the asset has already gone, and to where, as the manager survey shows, the most significant portfolio reshaping is taking place.

PART 1A: THE RISE OF ILLIQUID

INVESTING

If the move into new asset classes is conviction-led, the move into illiquids is concentrated. This is not broad-based drift. It is a structural shift led by a specific cohort: the multi-strategy platforms with the scale and operational depth to absorb the complexity.

Across the full sample, 16% of managers (chart 1.2) have increased their illiquid allocations over the past three years, while 63% do not allocate to illiquid assets at all. The headline figure understates what is happening at the platform end. 33% of multi-strategy

respondents have increased illiquid allocations, more than four times the equity long/short rate of 8%, and ahead of event driven at 25%, relative value or arbitrage at 20% and fixed income or credit at 18%. The platforms are doing the expanding.

Recent expansion tells the same story from the other direction. Looking at how the asset class mix has changed over the past 12 months, equity long/short managers are the most likely to have added one or two new areas of exposure, at 67%, with multi-strategy funds

close behind at 44%. The appetite to broaden the book is widespread; the capacity to carry genuinely illiquid exposure is not.

The question of who can actually execute that expansion is one Nakagawa addresses directly. Scale helps, he argues, because large platforms can spread infrastructure costs across many investment teams and justify dedicated technology, data and operations resource. But size alone is not sufficient and specialist managers often have an advantage in focus and adaptability. His own view is that the key question is not whether a firm can support every asset class but whether it can support a specific new one to institutional standards. The most successful expansions, in his experience, are those where operational complexity grows more slowly than the investment opportunity set. Expanding from convertibles into warrants is a very different proposition from moving into an entirely unrelated asset class.

The rationale, once again, is opportunity rather than pressure. Higher risk-adjusted returns dominate as the reason for moving into illiquids, cited by 35% of the sample (chart 1.3), well ahead of a natural extension of existing expertise at 12%. Competitive pressure and allocator demand each register at just 4%. The pattern is one of managers identifying genuine opportunity sets, not positioning defensively or following the crowd.

The conclusion for Part I is clear. The expansion is deliberate, it is led by the pod shops, and it is justified on return grounds rather than defensive ones. The harder questions begin the moment a fund actually has the new exposure on its books.

PONTUS ERIKSSON

Head of Strategy, FIS

Our survey finds the move into new asset classes is conviction-led, with 42% of managers citing uncorrelated alpha as their primary driver. Where has alpha actually moved in 2026?

What has changed is not simply that alpha has moved. It is that beta has become less scarce, while differentiated access, information and implementation have become more valuable. In the low-rate, QE-heavy era, broad market exposure did a lot of the work. In today’s regime of higher rates, more dispersion, greater geopolitical fragmentation and more frequent policy shocks, alpha is more often found in relative value, security selection, complexity premia and less efficiently intermediated parts of markets. In practical terms: structured and specialty credit, private credit, event-driven situations, volatility and dispersion trading and selected private market niches.

CIOs are rebuilding portfolios because the old architecture is less reliable. Public equity and fixed income diversification has been less dependable, correlations have shifted and the boundary between public and private markets is blurring. Managers that can combine liquidity buckets, implementation flexibility and specialist sourcing are better placed to access wholeportfolio alpha. Alpha lives where markets are fragmented, information is uneven, execution is hard and balance sheets are scarce. CIOs increasingly believe diversification now requires not just more managers, but more capability sets.

Multi-strategy funds are the clear leaders in moving into illiquids. Is the platform model the future template for the industry, or a distinct operating model?

The survey result suggests the multi-

strategy platform is evolving from a riskbalanced collection of liquid trading pools into something closer to a capital allocation and infrastructure model that can absorb a wider range of opportunity sets. Large platforms increasingly win not just because they have talented portfolio managers, but because they can provide the data, financing, controls, treasury, governance and investor credibility needed to enter more complex markets. The platform model is likely to become more influential as more firms understand the benefits, setting the benchmark for institutional robustness: integrated risk, strong treasury, centralised data, flexible middle office and scalable governance. But there will still be room for specialist firms that win on deep domain expertise rather than breadth. The platform model is becoming the reference architecture for scale, but not the only viable form of hedge fund organisation.

When a fund decides to expand into a new asset class, what is the realistic operational journey from decision to first allocation?

The journey is usually much longer and less linear than people expect. The investment decision is only the starting point. From there, firms typically move through target operating model design, market-access decisions, data and pricing architecture, legal and fund-structure work, accounting and valuation set-up, risk model extension and controls, and only then pilot trading or initial allocations.

The two areas managers most often underestimate are data and operating model redesign. On data, the challenge is rarely just getting a feed in place. The harder problem is building trusted goldensource data for instruments, positions,

PONTUS ERIKSSON

Head of Strategy, FIS

valuations, cashflows and legal terms, often from messy, fragmented and partially unstructured sources. On the operating model, managers often assume they can bolt a new asset class onto an existing listed-markets chassis. In practice it frequently means redesigning valuation committees, booking models, liquidity frameworks and investor reporting. The industry often thinks in terms of trade readiness. The real question is operating readiness. The first allocation should come only once the firm can support the asset class through its full lifecycle.

What does best-in-class operational design look like for a hedge fund running genuinely multi-asset portfolios across the liquidity spectrum?

Best-in-class design starts with one principle: do not force illiquid assets to masquerade as liquid ones. A hedge fund

can run across the liquidity spectrum, but only if it explicitly separates what must be common across the platform from what must be asset-class-specific. The common layer covers enterprise data governance, portfolio views, exposure aggregation, treasury, compliance and risk oversight. The differentiated layer covers valuation, lifecycle processing, liquidity treatment and investor communications appropriate to the underlying assets. The strongest models have a central investment book of record integrated with front-office workflows, risk systems and finance, rather than a fragmented architecture of spreadsheets and asset-class silos. Best-in-class is not about building one giant generic stack. It is about a federated but controlled operating model: one platform, one governance philosophy, one data spine, with different lifecycle treatments for different asset classes.

If you were advising a CIO today on building a front office stack for multiasset investing over the next five years, what would you prioritise, and what is the most common mistake?

Three things above all else. First, a strong data foundation: not just market data, but a normalised, governed data model across instruments, positions, valuations, counterparties and lifecycle events. Poor data architecture becomes the hidden tax on every future decision. Second, cross-asset interoperability: the stack should support a genuinely multi-asset process across research, order generation, execution, risk, P&L and post-trade controls with a clear source of truth and minimal manual reconciliation. Third, extensibility over perfection. Given the likelihood of further public-private convergence, more hybrid vehicles and AI-assisted workflows, an architecture that can evolve through

APIs and modular services is preferable to one that looks comprehensive on day one but proves difficult to adapt.

The most common mistake is choosing technology based on today’s dominant strategy, not the future operating model the firm is trying to become. Managers optimise for current execution or PM workflow and underinvest in data lineage, risk aggregation, valuation governance and operational scalability. That is manageable when the portfolio is narrow. It becomes a major constraint the moment the firm tries to add private credit, structured products or hybrid public/private exposures. The short version: build for cross-asset truth, not just cross-asset trading. That is the difference between a stack that supports expansion and one that breaks under it.

PART II: PORTFOLIO COMPLEXITY AND THE INFRASTRUCTURE CHALLENGE

What happens operationally when a fund expands into new asset classes, and how CIOs treat their technology stack as edge or constraint.

Adding an asset class is one decision. Running it coherently alongside everything else is a series of much harder ones. The survey points to a clear sequence in how those challenges arrive, mapping neatly onto the journey from intention to execution to integration.

Execution and market access is the single biggest expansion challenge, cited by 28% of respondents (chart 2.1) as their primary obstacle. It sits ahead of risk aggregation across asset types at 20%, talent with crossasset expertise at 16% and data sourcing and accounting, valuation and reporting at 12% each. Getting into a new asset class is the first hurdle. Making operational sense of what you have acquired, and resourcing it, comes next.

The challenge profile changes with scale, and revealingly so. Among the largest managers, those above $1bn, talent with cross-asset expertise becomes the single biggest obstacle, cited by 33%, against 16% overall and zero among sub-$250m funds. Once a large platform has solved execution, the binding constraint is no longer access to the market but access to people who can run unfamiliar asset types. For smaller funds, execution and raw market access remain the dominant concern.

For those who have lived through the process, the friction rarely stays in one place. Igor Yelnik, CIO and CEO of London-based Alphidence Capital, says challenges can cascade across every layer of the operating model simultaneously, spanning legal set-up, trade allocation frameworks, execution platforms, risk systems and back-office processing, with each

revealing its inadequacy at a different stage of the journey.

His view is that expansion has to be treated as an enterprise decision from the outset, with the right people involved before the first trade is placed, not after. Taken together, the infrastructure cluster dominates the challenge stack. Risk aggregation, data sourcing and accounting, valuation and reporting collectively account for 44% of respondents’ primary challenges. Execution gets a fund into a new asset class. Infrastructure determines whether the resulting portfolio can be run coherently afterwards. The first is a transaction. The second is a capability.

This is why the operational question cannot be deferred until after the investment decision. For the funds in our sample, the constraint on portfolio ambition is rarely the availability of opportunity or even capital. It is whether the operating model can carry the added complexity of fundamentally different asset types sitting within a single book, each with its own valuation cadence, risk profile and reporting demands.

Data integrity is the part managers most often underestimate. Yelnik argues that the quality problem is worse than most people assume, even when data is sourced from wellestablished providers. Time series tend to be short, inconsistent and riddled with errors and a single bad data point can propagate through an entire system and produce unintended risk exposures. The day-to-day demands also vary sharply with trading frequency and data type: the discipline required to work with quarterly

 Fully supports our needs

 Adequate but with limitations

 Significant gaps we are working to address

 Yes, significantly  Yes, in targeted areas  No, but we recognise the need to

No, existing systems have been adequate

GDP figures is a qualitatively different challenge from managing high-frequency data streams. In both cases the lesson is the same. Data infrastructure is the classic known-unknown of new asset class expansion, manageable in theory and demanding in practice, and its true weight only becomes visible once a fund is actually operating in the new space.

PART 2B: THE TECHNOLOGY EDGE

Nowhere is the gap between stated comfort and revealed behaviour wider than in how CIOs talk about their front office technology. Asked to rate it, managers are reassuring. 96% describe their stack as either fully supporting their needs (chart 2.2), at 44%, or adequate with limitations, at 52%. Only 4% report significant gaps. On the surface, this is an industry content with its tooling.

The behaviour tells a different story. 28% of respondents (chart 2.3) have upgraded their front office technology in the past 12 months, 8% significantly and 20% in targeted areas, with a further 16% acknowledging the need to do so. Adequate, it turns out, is a moving target. It describes a stack sufficient for last year’s portfolio but not necessarily fit for this year’s. As the investment process grows more complex, the definition of adequate quietly ratchets upward, and managers act on that even as they describe their position in comfortable terms.

For some managers the front office stack is unambiguously the former. Yelnik says that Alphidence has built its modelling system entirely in-house and treats it as a distinct competitive advantage, not a cost centre.

That conviction does not translate into complacency. He is clear that there is no finish line: however powerful or resilient the system is at any given point, there are always ways to make it stronger and more efficient. Adequate, in his view, is simply a description of where you are today, not a destination.

The improvements that matter most are not always the headline ones. Jeffrey Sexton, founder and CIO of Demeter Tactical Investments, points to execution infrastructure at the daily close as the area where technology gains have been most consequential for his firm. Demeter evaluates price-based signals across major equity indices and US Treasuries each market day, and the ability to act on those signals systematically, free from emotion and within predefined risk, leverage and liquidity parameters, depends entirely on execution quality at that specific point. A decade of improvements in direct market access, real-time monitoring and post-trade confirmation have, in his view, been genuinely operationally significant for a strategy built around that structure.

The quality of price-based data has also mattered. Sexton says the improvement in real-time data availability has supported the continuous refinement of his firm’s model through live performance validation, allowing its hedging techniques to adapt to changing volatility regimes while keeping its core strategy constant. The tooling that makes that refinement rigorous rather than discretionary is, in his words, a genuine operational advancement. A third thread runs through his answer: transparency infrastructure. The ability to give investors full visibility into positioning, risk and performance on an ongoing basis reflects improvements in reporting technology that

he regards as equally important to execution capability for a firm committed to institutional governance.

The link to expansion is direct. The managers reshaping their books are precisely the ones acting on technology, even when their stated comfort with their existing stack would not predict it. Taken with the 16% who recognise the need without yet having acted, a substantial share of the active expanders have either upgraded their technology or know they must. The operational reality of multi-asset investing is forcing infrastructure decisions across the industry.

This is the technology edge in practice. It is not about a single transformative platform. It is about whether a fund’s front office stack can keep pace with the ambition of its investment process.

Zulfiqar Ali is direct about where his firm stands. ZAMS has built its analytics and infrastructure from scratch to reflect the particular characteristics of commodity markets, where assets expire, rolls create complexity and historic analysis has to account for delivery dynamics that continuous-asset managers rarely encounter. He regards the result as a competitive moat that will allow the firm to scale. For the platforms leading the expansion into new asset classes, technology has stopped being a back-office cost line and become a determinant of how far the portfolio can stretch. The managers who treat adequate as a finish line will find their ambition capped by their operating model. Those who treat it as a moving target are building the capacity to keep expanding.

CONCLUSION

CAPACITY AS THE NEW CONSTRAINT

The 2026 alpha playbook is being written by conviction, not necessity. CIOs are expanding into new asset classes because they see differentiated return streams worth pursuing, and the conviction is strongest among the largest managers. The platforms with scale are leading the way into illiquids on the strength of risk-adjusted returns, not allocator pressure or defensive positioning.

But conviction is the easy part. The survey’s central lesson is that the binding constraint on portfolio ambition has shifted from the investment side to the operational side. Execution gets a fund into a new asset class. Infrastructure, risk aggregation, data integrity, cross-asset talent and a front office technology stack that keeps pace determines whether it can stay there and run the position coherently.

The funds best placed to keep rewriting the playbook are those that understand this. They treat adequate technology as a moving target rather than a settled state, they resource the operational side ahead of the investment ambition rather than behind it, and they recognise that in a market defined by volatility and regime change, the capacity to run complexity is itself a source of edge. As the macro environment continues to shift, that capacity, more than any single allocation decision, is what will separate the funds that expand successfully from those that simply expand.

CONTRIBUTORS:

Manas Pratap Singh Head of Hedge Fund Research manas.singh@globalfundmedia.com FOR SPONSORSHIP & COMMERCIAL ENQUIRIES: Please contact sales@globalfundmedia.com