Four of the most successful asset managers in the world, selected through eleven editions of the Asset Allocation Awards on the basis of their ex-ante positioning over a rolling 36-month period, agree on one thing: the Strait of Hormuz is the single most important macro variable of this moment. Where they diverge is on what comes next, and that divergence may be more telling than the consensus itself.

Hormuz as transmission mechanism

The Strait handles roughly 20% of global energy flows. Since late February, Brent crude has risen 58% and natural gas 65%. The immediate market response was mechanical: risk-off positioning, hard hits to European and Asian equities, and a sharp repricing of energy-intensive sectors.

The inflationary arithmetic is well established. UBP, winner of both the Asset Allocation Award and the Overall Award at the 11th Asset Allocation Awards, lays out the transmission in their March 2026 House View: a $10 oil move adds between 0.2 and 0.5 percentage points to inflation, and oil at $100 per barrel translates to approximately 1.4 additional percentage points. The growth side mirrors it: a 10% energy increase reduces output by around 0.35 percentage points, and oil at $100 shaves a full percentage point from growth.

That combination — inflation up, growth down — is the textbook definition of stagflation.

Where the consensus splits

The inflation outlook divides the field. Invesco, winner of the Equities Sectors Award and the asset manager most attuned to cross-asset transmission, argues in their March 2026 edition of Uncommon Truths that the shock is temporary. Historically, a 50% oil rise adds roughly one percentage point to CPI, and breakeven inflation expectations have barely moved, suggesting markets are not yet pricing in structural damage.

ING Investment Office, winner of the Equities Regional Award, takes a harder line in their April 2026 Monthly. That regional discipline shapes their Hormuz analysis directly. In a year when virtually every major allocator tilted toward the US, ING explicitly chose neutral on North America at two quarterly junctures. That same discipline now plays out in their energy read: Brent +40%, gas +65%, Europe and Asia hardest hit, sector by sector. Their stagflation framing is not abstract. It is regionally grounded.

UBP and ING agree: the stagflation risk is real and not automatically self-correcting. The key variable for both is whether Hormuz reopens. If it does not, Invesco’s temporary thesis collapses.

The credit blind spot

Here is what the inflation debate obscures. None of these three asset managers, with one exception, has translated the macro deterioration into explicit credit risk. The stagflation scenario implies lower growth, compressed margins, and rising input costs for leveraged companies. The logical endpoint is wider spreads and higher defaults. Yet that step is largely absent from the analysis.

Federated Hermes is the exception. It is no coincidence that they won the Fixed Income Award at the 11th Asset Allocation Awards, in a year when the rate environment showed more movement than the preceding three years combined. Their March 2026 edition of Where We Stand is already defensively positioned: underweight both high yield and investment grade, with an explicit flag on credit problems among speculative borrowers. That is not scenario analysis. That is a position.

In a credit cycle, the distance between diagnosing and positioning is rarely academic. The three asset managers that built the stagflation case most precisely are now the asset managers slowest to act on its credit implications. Federated did not build a framework. Federated acted. When the credit cycle turns, that timing advantage will not be subtle.

The market remains in the early phase of a credit cycle that has not yet turned. Spreads are technically tight. Default rates are not yet rising. But the conditions that precede credit deterioration are accumulating. Stagflation, margin pressure, and reduced earnings visibility are the three variables that historically precede a turn. Invesco’s counterweight, stable breakeven expectations, suggests systemic stress has not arrived. If Federated’s positioning proves premature, that signal will move first.

The question allocators should be asking

The Strait of Hormuz is the ignition point. Oil is the transmission mechanism. Equities have repriced. The question that remains underpriced is whether this macro shock runs long enough and deep enough to produce the credit cycle that current spread levels do not yet reflect. That is not a macro question. It is a positioning question.

Four asset managers read the same data. Only one acted on all of it.

This analysis is based on the March 2026 editions of each publication. Updated positioning from all four asset managers with April data will be incorporated in our May 1st review.

New to this? The Strait of Hormuz is a narrow waterway in the Middle East through which one-fifth of the world’s oil passes, and right now it is largely closed, which means higher energy prices, slower growth, and rising pressure on company finances across your portfolio.

The consensus of 72 asset managers remains broadly constructive. Equities are overweight, bonds underweight, and overall positioning still points toward growth. But beneath that stable surface, four signals are shifting simultaneously, and they all point in the same direction.

Cash as an early warning system

The most striking signal is not in what is being overweighted, but in what is quietly being built up. Cash positions are recovering sharply: the percentage of overweight positions doubles from 5.4% to 11.1%, while underweights decline from 54.1% to 50.0%. Cash remains formally the least popular asset class. But the move is unmistakable. A growing group of allocators is building liquidity buffers, not as a strategic choice, but as protection against uncertainty they cannot quantify.

Avoiding duration, hedging inflation

That uncertainty has a name: inflation. Within fixed income, Inflation Linked Bonds shift from neutral to overweight, while Government Bonds slide further. More than half of all asset managers, 50.9%, are now underweight government bonds. The reasoning is sharp: higher energy prices driven by geopolitical tensions fuel inflation expectations, forcing central banks into caution and delaying rate cuts. Long duration becomes a risk, not a buffer. Spreads over duration: that is the implicit choice embedded in this consensus.

Energy: the market doesn’t believe its own prices

Brent is above $112. The energy sector rose +12.54% in March and stands at +40.94% year-to-date in euros. Yet Energy shifts only from underweight to neutral in sector allocation. The explanation lies in the futures market: one-year forward delivery prices $94.8, three-year forward prices $75.7. The market expects current energy prices to be temporary, and the consensus follows that judgment. Betting heavily on energy now means betting against the forward curve.

America wins by standing still

The fourth shift is the quietest. America climbs from third to second in regional equity allocation, not because conviction on America increases, but because Japan and Pacific ex Japan give up overweight positions. Emerging Markets retains its lead with 63.6% overweight recommendations, but America benefits as a relative safe haven: less exposed to the oil shock, less vulnerable to the geopolitical turbulence hitting Asia and Europe harder.

One theme, four moves

Four signals, one conclusion: the consensus repositions without changing course. Equities remain the core, but the edges are being reinforced. Cash up. Duration out. Inflation hedged. Energy normalised. The portfolios still run on growth, but the hands are moving toward the emergency brake.

New to this? Large asset managers adjust their portfolios monthly based on what they expect markets to do, these four shifts signal that professionals worldwide are quietly getting more cautious, even if they’re not saying so yet.

I spent six weeks looking for an investment committee that made an allocation decision based on AI output. I did not find one.

The filter

The research window ran from 1 March to 15 April 2026. The criteria were strict and cumulative: AI had to be embedded in the allocation decision itself, not in the research preceding it. The decision had to be owned by a CIO, head of asset allocation, or investment committee. And the implementation had to be live in an existing mandate — no pilots, no proofs of concept. No single case met all three conditions.

This is the second research round. The first window ran from January to February 2026, applying identical criteria. The outcome was the same.

Two rounds. Identical method. Identical result. That is not a single observation. That is a pattern forming.Zero cases. A clean result.

The near misses

Several came close. A large pension fund embedded neural networks in scenario analysis and generated equity-buy signals during a stress period. A sovereign investor applied AI to improve predictive signals and tilt portfolios. A global asset owner used AI for risk monitoring and to support early divestment decisions.

These are not experiments. They are real implementations. But they sit one layer below allocation policy: they inform decisions, they do not make them.

Where AI is live

The contrast is sharpest in publicly listed strategies. Robeco launched the NextGen Global Small Cap ETF in March 2026, an active strategy using machine learning to detect non-linear relationships in return drivers and dynamically adjust signal weights at the level of individual stocks. M&G announced the Global Maxima Equity UCITS ETF in December 2025, built on a machine learning model trained on data from more than one thousand companies across twenty-five years.

Live portfolios. Trackable. Real. But they operate inside equity sleeves. They do not alter SAA frameworks. They do not revise capital market assumptions. They do not redefine allocation policy.

The decision boundary

AI is present in security selection, portfolio construction, and risk monitoring. Absent in allocation mandates, investment committee decisions, and strategic allocation frameworks. That boundary is not technical, it is institutional. An investment committee must be able to defend an allocation decision to a board, regulator, and client. That requires ownership: someone who puts their name to the answer. A model that autonomously determines what percentage goes to equities cannot provide that accountability. Until committees can delegate that responsibility, the decision remains human, regardless of the quality of the AI output.

The inputs are improving: better signals, sharper scenario analysis, more granular risk modelling. The decision itself has not yet shifted.

To change that, three things need to be visible: explicit AI integration in mandate language, adoption at investment committee level, and evidence of capital being reallocated as a direct result of AI output. None of these appeared in this window.

Result: no allocation impact found. Implementation expanding.

The boardroom is always last. In investment management, last is not a detail. Last is a decision.

New to this? Asset allocation is the decision that determines how much of a portfolio goes into equities, bonds, or other assets, and right now, that decision, the most consequential in the investment process, remains beyond the reach of AI.

41.2% overweight, 50.0% neutral, 8.8% underweight. The plurality was in the overweight column, and the thesis beneath it just broke.

Seventy-two reports. Commodities rank second in the investment consensus, directly behind equities. Sentiment has been more positive than this only 14.4% of the time since 2012. That consensus was built on an accelerating global economy: February 2026 PMI data showed the strongest global growth since May 2024, the best manufacturing figures since December 2021, and China growing at its fastest pace since May 2023.

Then the Strait of Hormuz closed.

Since February 28, 2026, the macro foundation beneath that consensus no longer exists. The Strait carried roughly 20 million barrels per day in 2025, approximately one fifth of global oil consumption and over a quarter of worldwide seaborne oil trade. That flow has now fallen to less than 10% of pre-conflict levels. Brent peaked at $126 on March 8 and was still trading around $107 on March 21, more than 50% above its pre-war level. The IEA described this as the largest supply disruption in the history of the global oil market. Gulf states have collectively curtailed more than 10 million barrels per day. This is not a geopolitical risk premium at the margin. This is a structural supply shock.

Three tension arcs, not two

Until Hormuz closed, the commodity story ran on two axes: dollar direction and Chinese growth momentum. A third arc has now emerged that overshadows both, for as long as the strait remains closed.

The first arc is Hormuz and shipping stress. This extends well beyond crude. Global LNG supply has fallen roughly 20% due to Gulf disruptions, with Qatar as the largest casualty. More than 30% of global urea trade and around 20% of ammonia trade normally transits the Strait. Maersk and Hapag-Lloyd have suspended their Middle East routes. The IEA launched the largest emergency reserve release in its history: 400 million barrels. A significant buffer, not a structural solution.

The second arc is the dollar. A rising DXY while oil prices climb creates an unusual regime: the dollar no longer brakes commodity prices, it signals flight to safety while supply-driven upward pressure runs independently. A weakening dollar from here becomes an additional tailwind on top of Hormuz.

The third arc is China PMI. Higher oil prices and disrupted supply chains weigh on industrial activity globally, and that pressure is now visible in the data. Copper fell 9.4% since the outbreak of the conflict, to $12,081 per metric ton on March 23. Global inventories surpassed one million metric tons for the first time since 2003. The strongest growth figures in years offered no protection once growth fears took over.

Two scenarios for energy

The bull case is straightforward: the supply shock persists, Brent stays structurally above $100, and gold moves in tandem as a geopolitical and stagflation hedge. Goldman Sachs projects an average Brent of $110 through Q2, with a worst-case of $135 if the Strait remains closed through June.

The bear case is de-escalation. A diplomatic opening or partial reopening quickly removes the risk premium from oil. At that point, DXY and China PMI reclaim dominance, and the story shifts back to structural metals and gold.

Three sleeves, three drivers

The commodity overweight is now a basket of conflicting micro-regimes. Three explicit sleeves are required.

The energy sleeve is driven by Hormuz, shipping stress, inventories, and production decisions in a disrupted market. The upside is substantial. The downside on de-escalation is equally abrupt. Futures implementation carries additional roll costs in a heavily backwardated market.

The metals sleeve tells a different story. Copper fell 9.4% in less than a month. Inventories sit at their highest since 2003. The bull case for industrial metals requires a stabilising China and falling energy prices. As long as Hormuz remains closed, both conditions are under pressure.

The gold sleeve has the strongest simultaneous support: geopolitical uncertainty, stagflation risk, central bank demand, and a dollar caught between two forces. Gold is currently the most coherent position within the commodity basket.

The question for an allocator is not “commodities or not.” It is which sleeve, in what proportion, and with what exit scenario, because the three drivers are now moving in three different directions at once.

The map was wrong. The positions are real.

Those who were overweight on electrification and mining underinvestment are now also long a geopolitical supply shock. Those are two different positions sitting in one sleeve, and the map that got them here will not get them out. The energy sleeve no longer rewards patience, it rewards timing. The metals sleeve needs China, not Hormuz. Gold does what gold always does when everything grinds at once: it works.

On April 1, the new Asset Allocation Consensus is published. The numbers will shift. More interesting is where the arguments move, which allocators have already repriced Hormuz, and who is still working from the old map. The strait opened this story. The data will tell us how many saw it coming.

how many saw it coming.

New to this? The Strait of Hormuz carries one fifth of the world’s oil, and right now it is largely closed. That single fact is now the dominant force behind every commodity in your portfolio, more than China, more than the dollar.

Seventy percent of the asset allocation reports published in 2025 did not need to be read. The question is which thirty percent was worth your time.

That is precisely the question Alpha Research began answering in 2016 with the first edition of the Asset Allocation Awards. This year, in the eleventh edition, we assessed a record 72 reports. Five winners remained.

How winners are determined: recommendations are assessed over a rolling 36-month period, alongside consistency of publication and argumentation, and breadth of asset classes covered. Scores are based on ex-ante positioning relative to ex-post market results. No subjective jury, no popularity vote.

Asset Allocation Award: UBP

UBP wins two awards simultaneously this year. It is the seventh time in eleven years, and five of those six previous occasions combined the Overall Award with the Asset Allocation Award. The pattern has become a defining characteristic. Their monthly House View runs to more than twenty pages and scored highest in the asset allocation category this year, ahead of strong competitors including J.P. Morgan Asset Management, Robeco and Northern Trust AM.

The distinguishing factor: UBP takes explicit positions across asset classes, with a clear time horizon per recommendation. There is no room for the strategic ambiguity that characterises many competing reports. That makes their recommendations testable. And the results speak for themselves.

Fixed Income Award: Federated Hermes

Six pages. That is all Federated Hermes needs to win the Fixed Income Award in a year when the rate environment showed more movement than the preceding three years combined.

The compactness is not a limitation. It is the product. No commentary requiring further commentary, no frameworks explaining other frameworks. The view is there, the position is alongside it, and the argumentation fits within a single read on a morning commute. For a time-pressed allocator, that is no small achievement: insights that are immediately actionable, without working through twenty pages first. Their coverage of Inflation Linked Bonds was accurately positioned in a quarter when the market significantly underweighted that segment. Precision, packaged in format.

Equities Regional Award: ING Investment Office

ING Investment Office ranks among the most consistent asset managers in the universe with 18 all-time nominations. But consistency is often confused with caution, and that is a misreading here.

A neutral recommendation sounds uneventful. In practice, it is one of the hardest positions to maintain. In a year when virtually every major allocator tilted toward the US, ING explicitly chose neutral on North America at two quarterly junctures. No underweight, no overweight. A deliberate refusal to move with the consensus. Both times, correctly. This is someone else’s money. Whoever understands that knows not losing is not a half-hearted strategy. It is discipline, and discipline has a price here.

Equities Sectors Award: Invesco

After six nominations, Invesco takes the award this year. Their publication Uncommon Truths combines sector views from the US and Europe into one consolidated global allocation, an approach most competing asset managers do not apply, as it requires additional position-taking per region.

That integration advantage proved decisive this year. Sector rotation in Europe played out differently from the US in 2025. Those analysing both markets separately missed the correlation. Invesco did not.

Overall Award: UBP

The Overall Award combines performance across asset allocation, regional equities and fixed income. UBP scored within the top five in all three categories this year. That breadth-and-depth profile has occurred only twice in eleven years of award history.

Monthly publication, explicit positions, demonstrable results. Three characteristics that rarely converge. This year, they did, at one asset manager.

Follow them

Five reports. Three criteria. Eleven years of data. The conclusion is the same every time: the asset manager who maintains independent judgment when consensus moves the other way does not win spectacularly, but does win. Consistency is not a style preference. It is a return driver, and this year, once again, the only one that counts.

New to this? Asset allocation is the decision that determines how an investor distributes capital across equities, fixed income and other categories, and that choice historically explains more than eighty percent of the performance difference between portfolios. These five reports are the best-documented guide to exactly that decision.

The asset allocation consensus for March 2026 barely moves. Just 51 view adjustments, down from 69 the month before. The only meaningful change: Corporate Bonds shifts from underweight to neutral. Otherwise: stillness.

That stillness is a good moment to hold the Consensus up against the ASR Asset Allocation Survey from February 2026, “Asset Allocators More Constructive: due to stronger, longer growth and benign monetary policy.” Two sources, different architecture. The Alpha Research Consensus aggregates the monthly TAA reports of 72 asset managers worldwide, from Amundi to Wellington, measuring each asset class on a scale from -1.00 to +1.00.

The ASR survey captures direct opinions from 284 CIOs and strategists at institutional investors, collectively responsible for $13.4 trillion in assets under management. To make both sources comparable on a single scale, the ASR implied probabilities have been transformed using the Alpha Research Consensus method: (Very Likely + Likely) minus (Unlikely + Very Unlikely), divided by 100. The result runs from -1.00 to +1.00, identical to the Consensus scale. The transformation is my own analytical step, the comparison is not a reproduction of ASR output.

The table below shows where they agree and where they diverge.

*ASR score based on Real Assets beat Treasuries and Treasuries beat Cash respectively. Scale runs from -1.00 to +1.00: above +0.20 overweight, below -0.20 underweight, in between neutral.

Where both sources agree

The areas of agreement are strong and broadly supported. Equities scores +0.75 at ASR against +0.655 in the Consensus: both sources point unambiguously to a risk-on baseline. Emerging Markets stands at +0.68 at ASR and +0.561 in the Consensus, the highest regional score on both sides. Commodities confirms the same directional signal: +0.61 versus +0.324. The arguments overlap: a weaker dollar, attractive valuations, stronger world trade.

Where the scores diverge

The first significant difference sits with America. ASR strategists score US outperformance versus non-US at -0.51: a pronounced negative conviction. The Consensus has America at +0.422, down from first to third place but still overweight. The direction is the same, the intensity differs sharply. Buy-side strategists are considerably more negative on the US than the TAA reports of asset managers suggest. The implication is direct: if buy-side conviction at -0.51 proves correct, current allocator positioning at +0.422 has further to fall.

The sharpest break sits in credit. ASR scores Corporate Bonds at +0.35 and Government Bonds at +0.35. The Consensus stands at -0.167 and -0.298 respectively. Those are opposing positions on the same scale. Buy-side strategists are constructive on investment grade credit and government bonds as carry instruments. TAA allocators are not. This is not a difference in tone. It is a measurable difference in position.

What the table does not show

What the table cannot show deserves a separate note. The ASR survey measures not only what professionals prefer, but also what they actively exclude. Recession risk scores -0.77. Higher Fed Funds -0.76. A stronger dollar -0.60. These are the strongest positions in the entire survey, and they sit at the bottom. The Consensus has no equivalent: TAA reports measure positive direction, not the active rejection of the bear case. Placing both sources side by side produces a fundamentally more complete picture of where professional capital is positioned and where it is deliberately not. For anyone building a macro view, that is the more valuable half of the information.

Conclusion

The Consensus measures what asset managers do. The ASR survey measures what strategists think. On equities and Emerging Markets the two track closely: scores of +0.75 versus +0.655 on equities, +0.68 versus +0.561 on EM. In credit they diverge, measurably and concretely. Corporate Bonds at +0.35 at ASR, -0.167 in the Consensus. Government Bonds at +0.35 at ASR, -0.298 in the Consensus. Two sources, the same scale, opposing positions. Strategists treating bonds as a carry instrument, allocators staying underweight: consistently inconsistent, until the market decides.

Two reports, the same direction. One credit market that still has to choose.

New to this? The asset allocation consensus aggregates the monthly recommendations of dozens of major asset managers worldwide to show where professional sentiment stands. Add a direct buy-side survey alongside it, and you see not only where the market is moving, but also what professionals are deliberately betting against.

Asset allocation is the boardroom at the top of the building. AI has entered through the front door, but it is still working its way up the floors.

Almost every recent article about AI in investing focuses on research, tools or workflow. Almost none address allocation itself. That gap is not accidental. It reflects how technology moves through investment organisations: first into instruments, then into process, and only later into policy. The boardroom is always last.

Governance first, models second

The CFA Institute report Explainable AI in Finance identifies a problem every allocator recognises immediately. AI models can be powerful, but investment committees will not use them if they cannot explain the output. Transparency is not a technical preference. It is a governance requirement.

For allocators this is not abstract. Strategic Asset Allocation, ALM and risk budgeting depend on models that must survive scrutiny from boards, regulators and clients. A model that cannot be explained will not survive an investment committee, regardless of its predictive accuracy. Explainability is the price of entry.

What AI cannot carry

The Human Advantage in an AI World (Asia Asset Management) argues that the real edge in an AI-driven world may still be human judgement. Not because humans process data better. They do not. But because investment decisions involve context, responsibility and accountability that cannot be cleanly delegated.

This is precisely where allocation differs from the rest of the investment process. Security selection can be automated. Rebalancing rules can be codified. But a policy decision about how much risk to take, against which liabilities, under which assumptions about the future, requires someone to own the answer. AI can inform that decision. It cannot carry it.

The risk hiding in the workflow

A Forbes piece by the Finance Council takes the broadest view: AI as both opportunity and threat. Firms are deploying AI for research, monitoring, portfolio analytics and client reporting. The same technology introduces model risk, operational risk and governance challenges.

For asset allocators, this tension is familiar. Every new model changes the workflow before it changes the portfolio. The danger is not that AI will get allocation wrong. The danger is that it reshapes the surrounding process so gradually that allocation assumptions go unexamined through an entire ALM cycle, across multiple policy reviews, before anyone notices the ground has shifted.

The door at the top

Taken together, the message is consistent and slightly uncomfortable.

AI adoption inside investment management is accelerating. The change is real, the tools are improving and the workflow is shifting. But allocation itself remains largely untouched. Not because it will stay that way, but because organisations move policy last: after the tools are proven, after the research is trusted, after the committees are ready.

Models move first. Processes follow. Policy waits.

AI has entered the building. It has improved the research, sharpened the tools and restructured the workflow. Floor by floor, it is working its way up. But the boardroom, where allocation policy is made, defended and owned, remains untouched. Not forever. Just last. And in investment management, last is not a detail. Last is a decision.

From reports to consensus

Each month, the Asset Allocation Consensus is built from the ground up. Before anything is aggregated into a model or ranking, the starting point is what strategists actually write.

This page brings together the 72 most recent asset allocation reports used for the February 2026 Consensus, published on 1 March 2026, representing EUR 65.8 trillion in assets under management. All reports are no older than six months, making this one of the broadest input sets since the start of the Consensus in 2012.

These documents are the primary sources, CIO views, house outlooks, tactical updates, and cross asset frameworks in their original form. The value is not any single report, but the patterns that emerge across them.

Fewer changes, weaker conviction

Compared with the previous month, changes were limited. In total, 51 recommendation changes were recorded, down from 69 in the prior update. Downgrades slightly outnumbered upgrades across asset classes, suggesting some cooling in conviction rather than a clear shift in regime.

Only one consensus change occurred at the asset class level. Corporate Bonds moved from Underweight back to Neutral.

Regional shifts below the surface

Within regions, rankings changed more than recommendations. Emerging Markets equities moved to the top position, Pacific ex Japan rose to second, while US equities dropped from first to third. Under the surface, the relative attractiveness of the US weakened, even though overall equity positioning remains positive.

Still risk on, but watching closely

At the total allocation level, the signal remains risk on. Equities and commodities stay overweight, while cash is at an all time low. Fixed income positioning is mixed, but not defensive.

These reports were written before the escalation in the Middle East in early March and before energy prices moved sharply higher. That makes the next update especially interesting, not only for the recommendation changes, but for how strategists adjust the arguments behind them.

Source reports

Below are the source documents used in this month’s Asset Allocation Consensus.

1. Aegon AM Global House View

2. AllianceBernstein Strategic Investment Outlook 2026

3. Allianz Global Investors Multi Asset Tactical View February 2026

4. Amundi Global Cross Asset Investment Strategy February 2026

5. Arab Bank Investment Strategy Q1/2026

6. Aviva Investors House View 2026 Outlook

7. AXA IM Multi-Asset Investments Views

8. Barclays Market Perspectives February 2026

9. Bendura Market Outlook February 2026

10. Berenberg Horizon Handout

11. BlackRock Weekly market commentary

12. BNP Paribas AM Monthly Market Viewpoint

13. BNY Investments Vantage Point

14. Candriam Monthly Coffee Break

15. Citibank GIC 2026 Q1 Macro Investment View

16. Columbia Threadneedle Tactical Asset Allocation Outlook

17. Degroof Petercam - Indosuez Monthly House View

18. DWS Investment Traffic Lights

19. Erste Group Global Strategy 1Q 2026

20. Federated Investors Where We Stand

21. Fidelity Global Asset Allocation Insights - February 2026

22. Fisch Asset Management Monthly Update - February 2026

23. Franklin Templeton Allocation Views February 2026

24. Generali Investments Market Compass February 2026

25. Hang Seng Bank 1Q Investment Outlook 2 Jan 2026

26. HSBC AM Investment Monthly February 2026

27. ING Investment Office Maandbericht Beleggen

28. Invesco Quarterly Global Asset Allocation 2026 Outlook

29. J. Safra Sarasin Cross-Asset Weekly February 2026

30. Janus Henderson Multi Asset Quarterly

31. JP Morgan Global Asset Allocation Views 1Q 2026

32. Kempen Asset allocation outlook overview February 2026

33. L&G IM Outlook

34. Mackenzie Investments Blue Book

35. Merrill Capital Market Outlook February 2026

36. MFS Global Market Pulse

37. Morgan Stanley The BEAT for Q1 2026

38. Neuberger Berman Asset Allocation Committee Outlook 1Q 2026

39. Ninety One Multi-Asset Strategy Quarterly

40. Northern Trust AM Investment Perspective

41. Nuveen Global Investment Committee

42. OFI Asset Management Panorama

43. Pictet AM Barometer Ferbuary 2026

44. PineBridge Investment Strategy Insights February 2026

45. Raiffeisen Anlageguide February 2026

46. RBC The Global Investment Outlook

47. Robeco Monthly Outlook Februari 2026

48. Russell Investments Asset Class Dashboard

49. Schroders Our Multi-Asset Investment Views

50. SEB House View

51. Societe Generale House Views February 2026

52. Standard Chartered Global Market Outlook February 2026

53. Sys Group Asset Allocation Insights February 2026

54. T. Rowe Price Global Asset Allocation February 2026

55. UBP House View February 2026

56. UBS Macro Monthly

57. UniCredit Monthly Outlook February 2026

58. UOB AM Quarterly Investment Strategy

59. Vontobel Investors’ Outlook February 2026

60. Voya Multi-Asset Perspectives February 2026

61. VP Bank Our View February 2026

62. Wellington Multi-Asset Outlook February 2026

63. Wells Fargo Asset Allocation Strategy February 2026

64. Wilmington Trust Capital Perspectives

The past weeks I spent more time reading AI research than allocation reports.
That contrast is becoming interesting.

New models appear every month.
Allocation frameworks adjust slowly.
Formal policy barely moves.

Over the past weeks I searched for work that could realistically influence allocation decisions.
Not trading models.
Not product marketing.
Research that could affect Tactical Asset Allocation (short-term tilts), Strategic Asset Allocation (long-term policy weights), Capital Market Assumptions (expected return models) and ALM (asset-liability management).

Scope of the search:
1 January 2026 – 12 March 2026.
Focus on models that change inputs used by allocators, not just execution.

Four findings stood out.

First, Amundi AIP (Dynamic asset allocation: its relevance and signals for 2026)
This is not a paper but a production allocation platform.
Machine learning is used to classify macro regimes, model correlations and generate scenario-based portfolio weights.
The system distinguishes multiple historical regimes going back more than a century and uses those classifications to bias portfolio construction toward or away from risk.
The important point is not the technology.
Allocation inputs are already partly model-driven before a committee ever meets.

Second, AQR 2026 Capital Market Assumptions.
Strategic allocation still depends on expected return estimates.
The latest update shows how valuation models, macro data and long-horizon statistics are combined in systematic frameworks rather than judgement alone.
The result is not a new allocation rule, but a different starting point.
Return expectations for traditional balanced portfolios remain well below long-term historical averages, which directly affects how much risk allocators can justify taking.

Third, LSTM-based risk budgeting research (Nature).
Neural networks were used to model time-varying risk across multiple asset classes.
Compared with static risk parity, the dynamic approach reduced drawdowns during stress periods without increasing turnover.
That matters because many Strategic Asset Allocation models still assume stable correlations that disappear exactly when risk rises.

Fourth, LightGBM tail risk modelling (SSRN).
This work focuses on predicting extreme losses instead of average volatility.
The models improved detection of regime shifts before large drawdowns, allowing earlier reduction of portfolio risk.
For allocators this is directly relevant to ALM, stress testing and downside control.
Better tail estimates can change how much risk a portfolio is allowed to carry.

Taken together, the pattern is clear.

AI is not rewriting allocation policy.
It is rewriting the inputs used to justify that policy.

The sequence is predictable:

• risk models change first,

• return assumptions next,

• tactical signals after that,

• and formal allocation policy last.

For practitioners this is familiar.
Mandates do not change because a model improves.
They change when the evidence becomes too strong to ignore.

The evidence is accumulating faster than committees are moving.

Research is moving.
Frameworks are evolving.
Policy is slow.

The next question is not whether AI can improve allocation inputs.
It already does.

The real question is which of these models will be the first to influence an actual allocation decision, and what it will take before a committee is willing to follow.

Every year the Asset Allocation Awards start with the same question: which asset managers have been the most consistent in their allocation recommendations?

This year, after analysing 72 asset allocation reports over a 36-month horizon, the shortlist is ready.

Across five categories, 25 nominations are awarded each year. Making the shortlist already places a report among the most consistent allocation frameworks in the market.

But the nominations tell a larger story, not just about this year, but about who has been consistently getting allocation decisions right over time.

A decade of nominations

Over the past ten years, 247 nominations have been awarded across the five categories.

Looking back over that period reveals something striking: a relatively small group of asset managers appears again and again.

Source: Alpha Research - Asset Allocation Awards

Together these 11 firms account for 60.3% of all nominations over the past decade.

For investors navigating dozens of strategy publications, this observation is useful. Following this relatively small group of asset managers already narrows the field considerably compared with analysing the entire universe of 72 reports.

But historical consistency does not guarantee future nominations, and every year the shortlist changes.

The 2026 shortlist

This year’s nominations highlight both continuity and change.

Several historically strong names appear again, but there are also shifts in momentum. Some long-time nomination leaders appear less frequently this year, while others move to the front of the shortlist.

Source: Alpha Research - Asset Allocation Awards

One name clearly stands out.

UBP leads this year’s shortlist with four nominations, appearing in almost every category. ING Investment Office and J.P. Morgan Asset Management follow with three nominations each.

The strong showing from ING Investment Office also moves the firm up to second place in the all-time nomination ranking, reinforcing its long-term consistency.

J.P. Morgan Asset Management, meanwhile, returns prominently to the shortlist after a period with fewer nominations.

Nominations by category

Asset Allocation

Nominees:

• UBP

• Federated Investors

• J.P. Morgan Asset Management

• Robeco

• Northern Trust AM

This category reflects the broadest allocation decisions across asset classes and often sets the tone for the overall positioning in multi-asset portfolios.

Fixed Income Allocation

Nominees:

• Federated Investors

• UBS

• Candriam

• Invesco

• Amundi

The shortlist combines established fixed income strategists with firms whose allocation views have recently ranked strongly in the model portfolios.

Equities Regional Allocation

Nominees:

• ING Investment Office

• T. Rowe Price

• J.P. Morgan Asset Management

• UBP

• L&G IM

Regional allocation remains one of the clearest ways strategists express macro views, from positioning between the US and Europe to shifts toward Japan or Emerging Markets.

Equity Sector Allocation

Nominees:

• Invesco

• UBP

• ING Investment Office

• Pictet AM

• Candriam

Sector allocation highlights how strategists position within equity markets themselves. The shortlist includes both global investment houses and managers known for strong thematic or sector-driven frameworks.

Overall

Nominees:

• UBP

• ING Investment Office

• UBS

• T. Rowe Price

• J.P. Morgan Asset Management

The Overall category rewards consistency across multiple allocation dimensions. Appearing here typically requires strong performance across several individual categories.

The final step

The shortlist now defines the contenders.

With four nominations across the five categories, UBP enters the final stage of the awards with the strongest position. Several other firms remain close behind, particularly ING Investment Office and J.P. Morgan Asset Management.

But nominations alone do not determine the outcome.

In the final article of this series, we will reveal which asset managers ultimately receive the Asset Allocation Awards.

When the first Asset Allocation Awards were presented, the idea behind them was already several years old. Investors had been asking me the same question long before that: who is actually the best asset allocator?

When Alpha Research started analysing asset allocation reports from asset managers in 2012, the first Asset Allocation Consensus quickly emerged. By combining the views of dozens of strategists, it provides an overview of how the market as a whole is positioned.

For many investment committees, this is valuable information. Comparing a portfolio with the market consensus immediately shows whether it is positioned more defensively or more aggressively than the broader market.

But almost immediately a second question followed: if we know the consensus, which asset managers actually make the best allocation decisions?

Answering that question turned out to be more complicated than expected.

Measuring forecasts is harder than it looks

An asset allocation recommendation is not a simple buy or sell signal. Strategists typically work with relative positions such as overweight, neutral, or underweight. In addition, recommendations are made across different categories such as regions, sectors, or fixed income segments.

For that reason, in the early years I had many discussions with investors, CIOs and quantitative specialists about how allocation recommendations could be measured in a fair and consistent way. The objective was to develop a methodology that would be as objective as possible while remaining practical to implement.

This process ultimately led to the first Asset Allocation Awards in 2016.

Since then, the Awards have become an annual moment to review the quality of allocation recommendations from asset managers.

A growing universe of reports

When Alpha Research started collecting asset allocation publications, around forty reports were followed. Over time that universe gradually expanded.

By 2020 the number had grown to around fifty publications. In 2024 it reached sixty. Today Alpha Research analyses 72 asset allocation reports from international asset managers.

For investment committees this represents a large amount of information. At the same time, it creates a practical challenge: which reports are the most valuable to follow?

The Asset Allocation Awards aim to help answer that question.

How the model works

To make allocation recommendations measurable, Alpha Research translates the recommendations from asset allocation reports into model portfolios.

Within each category, five sub-asset classes are used, which are equally weighted in a neutral situation. The neutral benchmark therefore consists of a portfolio in which each sub-asset class has a weight of 20%.

When an asset manager recommends an overweight position in a sub-asset class, the weight is increased to 25%. When a position is underweight, the weight is reduced to 15%.

The portfolio is then normalised so that the total allocation always equals 100%, ensuring that no leverage is introduced. In this way, the model portfolio reflects the relative allocation view of an asset manager.

The performance of these model portfolios is then ranked and compared with the neutral allocation.

Within each category, an equal-weighted structure is deliberately used. The goal of the analysis is not to replicate the structure of the market, but to measure whether relative allocation decisions add value.

In a market-weighted index such as the MSCI ACWI, the United States currently represents roughly 60% of the index. As a result, allocation decisions regarding the US can dominate overall outcomes.

Using an equal-weighted structure ensures that smaller regions such as Japan or Emerging Markets play an equally important role in the analysis. This makes it easier to observe whether allocation recommendations for these segments add value.

The exact composition of sub-asset classes differs by category. In Regional Equities, for example, regions such as the United States, Europe, Japan and Emerging Markets are used, while in Fixed Income segments such as government bonds, investment grade, high yield and emerging market debt are included.

For a fair comparison, reports must contain a sufficient number of recommendations. Therefore, only categories with at least four out of five sub-asset classes receiving a clear allocation recommendation are included in the analysis. If a report contains too few recommendations, that category is excluded from the ranking.

Time horizon and consistency of the universe

The analysis is conducted over a 36-month period.

Asset allocation decisions often take time to be reflected in market performance. In the data tracked by Alpha Research, rankings over shorter periods tend to fluctuate more strongly. A three-year horizon therefore provides a more stable view of the quality of allocation recommendations.

During this period, changes in the universe of reports are also taken into account. If an asset manager stops publishing a report for an extended period, that report may be removed from the analysis. Conversely, new reports are only included once sufficient historical observations are available to allow for a meaningful comparison.

This approach helps ensure that rankings are based on consistent and comparable data.

Award categories

The Asset Allocation Awards are presented in five categories:

• Asset Allocation

• Regional Equities

• Equity Sector Allocation

• Fixed Income Allocation

• Overall

The Equity Sector Allocation Award was introduced in 2017 and will be awarded for the tenth time this year. The other categories have now been running for eleven years.

Clarity and consistency of reports

In addition to performance, Alpha Research also evaluates the clarity and consistency of the reports themselves.

An allocation report must provide clear signals. Many asset managers use arrows, plus/minus signs or colour coding to indicate positions. This makes recommendations easy to interpret.

When recommendations are expressed only in text and require interpretation, it becomes more difficult to measure them consistently. In such cases a report may be excluded from the analysis.

The regularity of publication also matters. If a report does not appear for an extended period, its comparability with other publications may be affected.

From consensus to selection

The Asset Allocation Consensus shows how the market as a whole is positioned. That information is valuable, but it remains an average of many different views.

The Asset Allocation Awards add a second perspective. By measuring the quality of allocation recommendations over multiple years, a shortlist of asset managers with a demonstrated degree of consistency emerges.

For investors, this can help quickly identify which reports are worth following. In an environment where investment committees have access to dozens of strategy publications, this can result in a meaningful time saving. Instead of monitoring a large number of reports, investors can focus on a smaller group whose allocation recommendations have historically ranked well.

In the next article, we will look at which asset managers have been nominated for this year’s Asset Allocation Awards.

This week’s tactical asset allocation question

Four of the past five calendar years, High Yield delivered the strongest returns within fixed income. It outperformed government bonds, investment grade, and emerging market debt.

The recurring objection was simple, spreads were too tight.

In practice, the higher coupon compensated for valuation risk. Carry dominated caution.

The question now is whether that regime persists, or whether late cycle dynamics erode the income advantage.

Consensus positioning

Within the Asset Allocation Consensus, positioning remains broadly neutral. As of 1 March, 25.4 percent of strategists are overweight High Yield, 45.8 percent neutral, and 28.8 percent underweight.

The net positioning score, defined as overweight minus underweight, moved only marginally from -0.017 on 1 February to -0.034 on 1 March. In other words, the debate has intensified, but positioning has barely changed.

Within fixed income preferences, Emerging Market Debt (EMD) ranks as the most attractive segment, followed by Inflation Linked Bonds. High Yield shares third place with Corporate Bonds, while Government Bonds remain the least attractive.

Fixed income attractiveness ranking based on Asset Allocation Consensus

This distribution reflects the same tension visible in the data: attractive carry, but limited valuation buffer.

One regime, two outcomes: Carry dominates, until growth turns

In a resilient growth regime, attractive all in yields and contained defaults allow carry to compound. Spread compression is not required for acceptable returns.

In a late cycle regime, tight spreads offer limited protection. Rising real yields lift refinancing costs. Earnings cyclicality becomes the binding constraint.

The regime call, growth stability versus deceleration, determines whether High Yield behaves as income or equity beta.

At a glance

• US High Yield OAS 295 basis points, well below historical average
• Euro High Yield OAS estimated 310 to 340 basis points, also compressed
• US Purchasing Managers Index (PMI) expansion, but cooling momentum
• Eurozone PMI improving, led by Germany
• US default rate 3.7 to 4.8 percent, forecast 3.8 percent with wide uncertainty band

March 2026 Positioning Snapshot

1. Spreads

US ICE BofA High Yield OAS stands near 295 basis points. The 5 year average is around 350 basis points. The current level sits roughly 55 basis points below average and near the 300 basis point threshold widely viewed as very tight.

Euro High Yield spreads are estimated between 310 and 340 basis points, versus a 10 year average near 400 to 430 basis points. Valuations are compressed across both regions.

At these levels, the buffer against macro disappointment is thin.

2. Growth signal

US Institute for Supply Management (ISM) Manufacturing PMI rose to 52.6 in January, then eased to 51.2 in February. Services PMI declined to 52.3. Expansion continues, but momentum softens and tariff related pull forward may distort the signal.

Eurozone composite PMI reached 51.9, with manufacturing at 50.8. Germany returned to expansion. France remains marginally below 50.

No region signals contraction. The US shows cooling momentum, Europe shows tentative recovery.

3. Default structure

The trailing 12 month US High Yield bond default rate stands near 3.7 percent, versus a longer term average around 3.4 percent. Leveraged loan defaults remain higher near 5.9 percent. Moody’s baseline forecast projects speculative grade defaults near 3.8 percent by end 2026, with a wide range between 1.7 and 8.3 percent.

By rating bucket, BB defaults remain near 1 to 2 percent, B near 3 to 4 percent, and CCC materially higher. Stress concentrates in the weakest cohort, not the index core.

Defaults are elevated but not accelerating.

The key takeaway for allocators

Spreads are tight. Growth has not broken. Defaults are contained but uncertain.

That mix argues for discipline, not expansion.

High Yield

3 Supports, Why Carry Still Anchors Returns

All in yields remain attractive relative to recent history. Even without further spread tightening, yield to worst can support mid single digit total returns over a 6 to 18 month horizon.

Default rates remain near historical averages. Broad credit stress is absent.

Balance sheets improved during the refinancing window of prior years. Near term maturity walls remain manageable.

In a stable growth regime, time supports returns.

4 Constraints, Why Tight Spreads Limit Margin

High Yield OAS trades well below medium term averages. That leaves little cushion against volatility.

A sustained PMI decline below 50 would pressure leveraged issuers. Growth deceleration transmits quickly through earnings.

Higher real yields increase refinancing costs and tighten financial conditions.

The weakest rating bucket already shows stress. A broader spread would reprice quickly.

Carry versus Recession Risk

2 Conditions for the Bull Case, Why Income Dominates

If PMI stabilizes above 50 and real yields plateau, carry remains the primary driver of return. Default rates near baseline projections allow spreads to remain compressed without repricing.

Under that regime, High Yield functions as an income anchor.

3 Triggers for the Bear Case, Why the Cycle Overrides Yield

If PMI rolls below 50 and default rates trend higher, spreads must widen. At 295 basis points, repricing potential is asymmetric.

The critical interaction is rising defaults alongside tight spreads. That combination historically precedes abrupt spread widening.

Under that scenario, High Yield behaves like equity risk.

Allocation Stance: Neutral

Spreads near 295 basis points do not justify an overweight. Growth does not justify an underweight.

Carry compensates for current risk, but does not warrant risk expansion.

Position Neutral until spreads widen meaningfully or growth momentum reaccelerates.

Debate this in the comments

A → Carry still compensates

At 295 basis points, US High Yield still offers mid single digit return potential if defaults stabilize near 3.5 to 4 percent. PMI remains above 50. Stress is concentrated in the CCC bucket.

Under that scenario, carry offsets tight spreads. A modest overweight remains defensible.

B → Asymmetry dominates

295 basis points sits 55 basis points below the 5 year average. The margin for error is thin. If PMI weakens or defaults migrate from CCC into B, repricing will not be gradual.

Downside resembles equity risk. Upside remains limited by compressed spreads. Neutral may already assume too much stability.

The decisive question

Is 295 basis points adequate compensation for late cycle uncertainty, or does it only work if growth remains intact?

What indicator would make you move from Neutral to Overweight or Underweight?

1 January–27 February 2026: no new verifiable AI fund launches surfaced.
That absence matters.

If artificial intelligence (AI) is transforming asset management, it is not yet visible through new regulated products.

Three listed exchange-traded funds (ETFs) with documented AI-driven portfolio construction remain central:

• QRAFT AI-Enhanced U.S. Large Cap ETF (QRFT)

• QRAFT AI-Enhanced U.S. Large Cap Momentum ETF (AMOM)

• Amplify AI Powered Equity ETF (AIEQ)

In all three, AI determines security selection and portfolio weights.

That exceeds marketing language.

What Is Actually AI-Driven?

The QRAFT funds use deep neural networks to evaluate U.S. large caps across quality, size, value, momentum, and low volatility.
Rebalancing occurs monthly under systematic rules.

There is no discretionary override at the stock-selection level.

That qualifies as integrated portfolio construction.

AIEQ discloses its process in its Securities and Exchange Commission (SEC)-filed prospectus.
EquBot’s model, running on IBM Watson™, applies natural language processing to news, filings, sentiment data, and macro inputs.
Sector exposure emerges bottom-up from model signals.

Process transparency is high.
Alpha durability remains uncertain.

Does AI Deliver Verified Alpha?

QRFT has tracked close to its category over three years.
AMOM has outperformed since inception, with periods of recent strength.
AIEQ has lagged broad benchmarks over longer horizons.

Implementation alone does not produce structural outperformance.

At least not yet.

Product Innovation or Allocation Impact?

These vehicles operate within U.S. equity sleeves.
They do not alter strategic asset allocation (SAA) frameworks.

• No capital market assumption (CMA) methodology has shifted because of them

• No institutional mandate language has changed

• No allocation model references AI explicitly.

AI influences manager-level execution.
It does not yet shape capital allocation policy.

That distinction defines the current stage.

What Is Missing?

• Independent process audits

• Multi-cycle validation

• Institutional scale adoption

• Explicit AI references in allocation mandates

Without these elements, we observe product evolution rather than systemic capital reallocation.

The Weekly Search Continues

This review forms part of a structured weekly scan.

The objective is not to catalogue AI-branded products.
The objective is to detect when AI reshapes allocation frameworks.

For now, implementation appears measurable.
Allocation impact remains absent.

AI Allocation Watch: Week 1

Implementation observed. Allocation shift not yet visible.

This week’s Strategic Asset Allocation question

If expected returns keep drifting lower across asset classes, where does the long-term premium remain?

This year’s Expected Returns update shows 6.36% nominal for Global Equities over ten years. Private Equity stands at 9.75%.

The 3.39 percentage point gap looks compelling.

But does it reflect a durable liquidity premium or peak-cycle optimism?

One regime, two outcomes: Valuation pressure vs private market conviction

The 60 Capital Market Assumptions reports cluster around a 10-year horizon, average 11.1 years, nominal returns, mostly USD-based.

The direction is clear. Expected returns continue to compress, especially in public equities. Inflation supports nominal figures, yet elevated valuations constrain future premia.

Private Equity retains a meaningful premium in forward estimates. The consensus clusters around 9.8%, signaling conviction.

The regime remains consistent, slower growth, higher rates, tighter liquidity. Yet outcome expectations diverge.

At a glance

• 60 CMA reports, record sample size

• Average forecast horizon 11.1 years, median 10 years

• Global Equities 10-year nominal consensus 6.36%

• Private Equity 10-year nominal consensus 9.75%

• Implied Private Equity premium 3.39 percentage points

• EUR hedged adjustment about minus 1.10% annually over ten years

10-Year Nominal Expected Returns (USD)

Three observations matter.

First, consensus, median, and middle quintile align in both assets. The crowd shows internal coherence.

Second, dispersion in Private Equity exceeds that of public markets. The uncertainty band runs wider.

Third, the 3.39% premium surpasses long-term realized differentials.

The key takeaway for allocators

The consensus holds steady. The premium remains elevated. The uncertainty exceeds the headline figure.

In Strategic Asset Allocation (SAA) and Asset Liability Management (ALM) frameworks, dispersion and currency treatment may outweigh the point estimate.

Global Equities

6.36% Expected Return, 60 Managers, Why Valuations Cap the Upside

The 10-year nominal consensus for Global Equities stands at 6.36%. Median and middle quintile cluster near 6.45%.

This reflects a balanced building-block view. Inflation supports nominal returns, yet starting valuations limit forward premia. Recent quarters show continued downgrades, averaging minus 0.15 percentage points.

The assumption favors normalization over expansion. Lower multiples and moderate earnings growth shape the outlook.

3.22% Dispersion, Why Scenario Risk Dominates

The gap between the highest and lowest quintile reaches 3.22 percentage points. That spread influences ALM outcomes.

If inflation surprises upward or real yields remain elevated, valuation compression could persist. If productivity accelerates, multiples may stabilize. Path dependency defines the risk.

Private Equity

9.75% Expected Return, 3.39% Premium, Why the Liquidity Story Persists

Private Equity consensus stands at 9.75% nominal over ten years. Median and middle quintile align near 9.8%.

The implied premium over Global Equities equals 3.39 percentage points. In 2015, the gap measured 2.63%. It widened again in 2024 and remains elevated.

Supporters cite operational value creation, pricing power, and long-duration capital. Infrastructure and private markets also offer partial inflation linkage.

5.32% Dispersion, Why Liquidity Assumptions Deserve Scrutiny

The spread between the highest and lowest quintiles is 5.32 percentage points. This uncertainty points to uncertainty among strategists and CIOs when making capital market assumptions. Perhaps prompted by actual returns, the table below shows the difference between the MSCI ACWI and the S&P Listed Private Equity index over the past 20 years.

The 3.39% expected premium presumes orderly refinancing, stable leverage, and functioning exit markets. Recent cases such as Accell show that even experienced sponsors misjudge operating risk when growth stalls.

Stress rarely starts in liquid markets. It often surfaces first where pricing is opaque and transactions freeze. Redemption gates in private credit funds illustrate how promised liquidity can collide with illiquid underlying loans.

If exit multiples compress and refinancing costs remain elevated, the projected premium narrows quickly. The premium may be real. But it only holds if liquidity holds.

What this means for a strategic allocator

Private Equity does not serve Tactical Asset Allocation (TAA), yet its forward premium shapes strategic risk budgets. If the 3.39% differential compresses toward historical norms, portfolio efficiency assumptions weaken.

Debate this in the comments

A) The 3.39% Private Equity premium reflects structural compensation for illiquidity.
B) The premium will revert toward 1 to 1.5%, pressuring strategic return targets.

Which side do you support, and why?

This week’s Tactical Asset Allocation question

When nearly half of strategists underweight an asset class, does that make it wrong, or simply unloved?

Across 72 Tactical Asset Allocation (TAA) reports, Government Bonds rank last within Fixed Income. Yet 14% still hold an overweight. That minority is not random. It follows a distinct playbook across bonds and equities.

Source: Alpha Research - Asset Allocation Consensus February 2026

The real question is not whether Government Bonds are cheap. It is what role they play in a portfolio.

One regime, two outcomes: Hedge duration versus carry conviction

Fixed Income splits into two camps. The consensus prefers Emerging Markets Debt (EMD). It leans on carry, spread compression, and a weaker US dollar.

Source: Alpha Research - Asset Allocation Consensus February 2026

The Government Bonds minority sees a different regime. In their framework, duration regains value as ballast. Term premia and steeper curves offer carry and roll down. They also argue for selectivity, not broad exposure.

These views rarely coexist in one portfolio. This is not a bond debate. It is a portfolio design debate.

At a glance

• Sample: 72 active Tactical Asset Allocation (TAA) reports, data through 31 January 2026

• Government Bonds stance: 14.0% overweight, 36.8% neutral, 49.1% underweight

• Government Bonds are the least preferred Fixed Income segment in the sample

• 100% of Government Bond bulls are also overweight equities

• The consensus Fixed Income preference remains Emerging Markets Debt (EMD)

Government Bonds versus EMD: the Fixed Income split

Government Bonds sit at the bottom of the Fixed Income preference list. Emerging Markets Debt sits at the top. Inflation Linked Bonds and High Yield also rank ahead of Government Bonds in the consensus.

That ranking matters because the choice is rarely additive. In practice, a Government Bonds overweight often means less room for EMD.

The key takeaway (for allocators)

The Government Bonds bulls are not running a classic defensive book. They pair duration exposure with overweight equities. The disagreement is not about safety. It is about structure.

Government Bonds

4 drivers the bulls cite, why duration is back

The bull case rests on four pillars.

First, the hedge role. Treasuries and other developed market government bonds can still cushion downside growth shocks, according to UBS and BlackRock.

Second, compensation is improving. Wellington highlights term premia and steeper curves, which can deliver carry and roll down.

Third, they emphasize geography. BlackRock prefers developed market government bonds outside the US. Franklin Templeton and UBS see value in UK Gilts. Morgan Stanley points to opportunities in European peripherals.

Fourth, they treat duration as stabilizer, not a substitute. They keep equities overweight and use Government Bonds to shape drawdown behavior.

4 headwinds the bears stress, why fiscal risk dominates

The bear case is also coherent.

First, valuation looks thin. Nuveen and Schroders describe government bonds as offering little value.

Second, fiscal dynamics matter. Pictet, Invesco, SEB, and Société Générale warn that rising deficits and heavier issuance can push yields higher.

Third, rate cuts may not save duration. UniCredit and VP Bank flag scenarios where yields rise despite easing.

Fourth, core markets face specific skepticism. UBS is underweight Bunds, and Morgan Stanley is cautious on core government bonds.

Emerging Markets Debt (EMD)

5 reasons EMD leads the consensus, why carry wins

EMD remains the preferred bond segment in the consensus.

The case starts with yield. Several managers cite attractive carry as the base return engine, including Nuveen, T. Rowe Price, and UBP.

The second leg is currency. Franklin Templeton and UBP highlight a weaker US dollar as a tailwind for returns, especially in local markets.

Third, fundamentals look supportive. Franklin Templeton and Pictet point to disinflation and better growth dynamics across parts of emerging markets.

Fourth, spreads can help. JP Morgan, PineBridge, and Morgan Stanley argue that inflows and fundamentals can support tighter spreads.

Fifth, the allocation is selective. Morgan Stanley and UOB Asset Management (UOB AM) prefer hard currency exposure and higher quality sovereigns.

The bear case is muted, why neutrality still matters

Explicit underweight calls are scarce in this dataset. The main caution is a neutral stance on EM US dollar debt from BNY, framed as balance rather than conviction.

That silence does not remove risk. EMD can suffer if the US dollar strengthens, spreads widen, or geopolitics disrupt flows.

What this means for a tactical allocator

Start with intent. If you want Fixed Income to hedge macro downside, Government Bonds can fit. If you want Fixed Income to earn carry, EMD fits more naturally.

Then stress test the fiscal backdrop. If you expect deficits and issuance to keep term premia elevated, duration will behave differently than in prior cycles.

Finally, note the profile signal. The Government Bonds minority also runs overweight equities. They are not retreating from risk. They are building a portfolio with two engines and a stabilizer.

Debate this in the comments

A) Government Bonds are a renewed hedge inside an equity overweight portfolio
B) Government Bonds are structurally impaired under fiscal dominance

What single macro development would make you change your duration stance?

With Nuveen and Schroders jumping into the top 10 of the IPE Top 500 Asset Managers list, their tactical views appear to be surprisingly similar. There are only three measurable differences in equities, emerging market equities and investment grade bonds.

This week’s question

What changes for allocators when two top 30 asset managers merge to become a top 10 player?

Scale is important, distribution is important, and pressure on fees remains. The trend towards bigger, bigger and biggest is not over. Mergers and acquisitions in the asset management world are a given. And asset allocation remains the most important investment decision that every institution has to make, which raises the question of how much current asset allocation visions differ today.

Specifically for asset allocators, the question is: how big is the difference between Nuveen and Schroders today, before any harmonisation of commissions?

One regime, two outcomes: Scale is the strategy, TAA is the integration test

The strategic logic is simple. Consolidation helps protect margins in a competitive market, and the relevance of rankings remains important. Number 23 plus number 30 becomes number 9, and that status delivers distribution power, negotiating power and more shelf space.

But scale does not automatically lead to a single shared vision. Or does it?

For Nuveen, the quarterly update VIEWPOINTS FROM THE GLOBAL INVESTMENT COMMITTEE, 2026 OUTLOOK, is a report that paints a picture of solid but slowing growth, persistent inflation and a preference for selectivity given valuations and tight spreads.

For Schroders, the monthly update Our multi-asset investment views, January 2026, remains constructive on equities, but explicitly balances that view with gold and shorts in US government bonds and the US dollar to manage valuation and political risk.

The result: more agreement than you might expect, with three clear tactical differences that require a good discussion, but certainly not a culture war.

At a glance

• Global ranking math: #23 + #30 = #9

• Combined scale: about $2.5 trillion AUM

• 3 measurable TAA differences: equities, EM equities, investment grade credit

• Shared positives: US equities, EM debt

• Shared caution: duration risk, valuation discipline

3 Tactical Differences, 2 Big Agreements, 1 Open Question

Where they differ

1. Equities overall

• Schroders: overweight / positive

• Nuveen: broadly neutral overall, with selectivity.

  Schroders stays positive on equities, supported by earnings momentum, while acknowledging valuation and geopolitical risk.

2. Emerging Markets equities

• Schroders: neutral (Global EM), valuations favourable but China keeps them neutral.

• Nuveen: cautious given trade policy risks.

3. Investment Grade credit

• Schroders: neutral, tight valuations limit upside.

• Nuveen: highlights headwinds from extremely tight spreads and extended duration, prefers other credit sectors such as securitized assets and senior loans.

Where they agree

• US equities: Nuveen sees US large caps as still having room to run.

  Schroders also remains positive on US equities, supported by stabilising labour market conditions.

• Emerging Market Debt: Schroders upgrades EM local currency debt to positive, supported by weaker USD trends.

  Nuveen’s heat map shows EM debt as a more positive segment.

The key takeaway

Consolidation explains the shift to number 9, but TAA is where the merger becomes investable. Today, the differences are real but limited, and the similarities are clear and logical. It will be interesting to see whether the new combination will result in a single combined vision, or whether both teams will continue to exist side by side, as is often the case in a boutique structure.

What this means for a tactical allocator

If you use house views as an input, this merger is a live experiment. Watch the next 2 to 4 quarterly updates: do the three gaps narrow, stay stable, or widen? If they converge, you learn what the combined committee values most. If they coexist, you gain two perspectives under one roof, which can be useful for allocator debate and decision discipline.

At the same time, consolidation raises a broader question for the industry. Today Alpha Research tracks 72 published TAA reports. If the number of independent house views shrinks over time, does the value of TAA increase because it becomes scarcer, or decrease because decision-making shifts toward central CIO models and platform-level positioning?

Debate this in the comments

With industry consolidation accelerating and the number of published house views likely to decline, how important is TAA really for allocators going forward?

This week’s question

Cash is supposed to be the least interesting line in the portfolio, and right now it still is, but what are the contrarians thinking? Most CIOs and strategists see cash as the least attractive asset class, and the consensus percentages are clear. Yet a small minority chooses the opposite. So the real question is not whether cash is “good” or “bad”. This week’s question is: what kind of allocator goes Overweight Cash, and where does that profile diverge most sharply from the crowd?

One regime, two outcomes: Overweight Cash is not “less risk”, it is “different risk”

The analysis shows that allocators who are Overweight Cash do not suddenly turn bearish on equities. They keep equities firmly Overweight, in line with the consensus. The big divergence shows up elsewhere: bonds move from Underweight in the consensus to maximum Underweight in the contrarian profile. What does not go into duration stays liquid in cash. And within fixed income, the profile becomes more selective and more assertive: less government duration, more spread and EM carry. The end result looks like a barbell: safety via cash, return seeking via High Yield and Emerging Market Debt, while classic government bond duration is consciously avoided.

At a glance

• Cash positioning in the full sample: 13.2% OW, 29.0% Neutral, 57.9% UW

• The contrarian subgroup consists of 5 asset managers, all 100% OW Cash

• Their top level profile: OW Equities, heavy UW Bonds, OW Cash

• Within fixed income: UW Government Bonds (sharp), UW Inflation Linked, UW Corporate, but OW High Yield and OW Emerging Market Debt

• Regional equity tilts: more positive than the consensus on Japan and Emerging Markets

• Practical interpretation: this is primarily a duration avoidance stance, not a generic risk off posture

Cash: consensus percentages, plus the contrarian filter

1) Cash positioning in the full sample

2) Decision map: what the camps truly disagree on

Sources behind the contrarian cash profile

1. Franklin Templeton Allocation Views

2. Northern Trust AM Investment Perspective

3. Russell Investments Asset Class Dashboard

4. T. Rowe Price Global Asset Allocation

5. VP Bank Our View

The key takeaway for allocators

Overweight Cash is not “lazy parking”. In this dataset it is a structured duration decision: the contrarians diverge on bonds, not on equities. They keep equity risk, avoid government duration, and then hunt income via High Yield and Emerging Market Debt, while cash functions as ballast and optionality.

Cash

4 reasons why Cash works now: yield, defense, and dry powder

The pro cash case is about function. Cash is a shock absorber and keeps optionality alive when markets dislocate. With elevated short term rates, cash can feel like a rare “risk free” return stream, especially for allocators who want to avoid the volatility of longer duration bonds. Cash can also be framed as readiness: liquidity to seize opportunities when markets dislocate, rather than a strategic end state. In that view, Overweight Cash is not doing nothing, it is buying flexibility while still earning carry.

4 reasons why Cash may disappoint later: cuts, opportunity cost, and weak compounding

The anti cash case is simple and sharp. If policy eases, cash yield reprices down quickly. What looks attractive today can become a narrow return range that struggles to meet long term goals. Opportunity cost is the second hit: if intermediate duration and high quality fixed income offer a better entry point and a better risk adjusted return, then staying in cash becomes expensive. That is why several allocators push cash explicitly lower in their models, sometimes toward zero, forcing the portfolio to earn returns elsewhere.

Bonds (Fixed Income)

3 reasons why bonds are the real battleground: duration is the red flag (the OW Cash profile)

This Overweight Cash analysis shows that the main divergence is not in equities, but in duration. This contrarian subgroup agrees with the consensus that government bonds are unattractive, but with maximum conviction. There is also less appetite for inflation linked and corporate bonds, where the consensus is closer to neutral. This suggests these tactical allocators believe the portfolio is not being paid sufficiently for rate risk. Cash then becomes the alternative to duration, not a replacement for risk assets overall.

3 reasons why the barbell can still be fragile: credit and EM risk can bite hard (the same OW Cash profile)

The twist is that these allocators do not simply take less risk, they relocate it. By overweighting High Yield and Emerging Market Debt, they reintroduce cyclical and liquidity risk through spreads. In a regime where growth disappoints or spreads widen, HY and EMD can sell off sharply. Cash helps as a stabilizer, but it does not hedge spread blowouts. That is why the profile reads as a barbell: safety in cash, income and return seeking in HY and EMD, and minimal exposure to government duration in the middle.

What does this mean for a tactical allocator

See Overweight Cash as a signal about rates, not as a generic risk off label. In this dataset, the contrarian allocator says: keep equities, cut duration hard, hold cash, and earn carry via HY and EMD. If your base case is easing without a spread shock, that structure can work. If your risk case is widening spreads or EM stress, the barbell can wobble, even with a large cash anchor.

Debate this in the comments

A) Overweight Cash is the cleanest hedge against duration risk, and the HY plus EMD barbell is the right compromise.
B) Overweight Cash is a temporary illusion, if you fear duration, you should own high quality bonds, not replace bonds with cash.

Pick A or B and name one trigger that would make you switch sides (first cut, curve steepening, widening spreads, or an equity drawdown).

Each month, the Asset Allocation Consensus is built from the ground up. Before anything is aggregated into a model or distilled into a ranking, there is one essential layer: what strategists actually write.

This page brings together the 63 most recent asset allocation reports, published in January 2026, representing USD 65.5 trillion in assets under management, the broadest input set we have used since the start of the Consensus in 2012.

These documents are the primary sources: CIO views, house outlooks, tactical updates, and cross-asset frameworks in their original form. The value is not any single report, but the patterns that emerge across them. Notably, the year has started with more active repositioning: CIOs and strategists adjusted views far more than in December, with a clear pickup in underlying recommendation changes.

This month, those shifts translated into five consensus recommendation changes: three upgrades and two downgrades. Commodities moved from neutral to overweight, and Pacific ex Japan equities also shifted from neutral to overweight. Within fixed income, Corporate Bonds turned from neutral to underweight. In equity sectors, Industrials rose from neutral to overweight, while Communication Services slipped from overweight to neutral.

Beneath the surface, fixed income saw a noticeably positive tilt in revisions overall, not in corporate credit, but across other bond segments—reinforcing the theme of selective rotation rather than a wholesale risk-off move.

Taken together, the signal remains risk-on, now with sharper differentiation across regions, sectors, and bond categories.

Below you will find direct links to every source document used in this month’s Asset Allocation Consensus.

1. Aegon AM Global House View

2. AllianceBernstein Strategic Investment Outlook 2026

3. Allianz Global Investors Multi Asset Tactical View January 2026

4. Amundi Global Cross Asset Investment Strategy January 2026

5. Arab Bank Investment Strategy Q1/2026

6. Aviva Investors House View 2026 Outlook

7. AXA IM Multi-Asset Investments Views

8. Barclays Market Perspectives February 2026

9. Bendura Market Outlook January 2026

10. Berenberg Horizon Handout

11. BlackRock Weekly market commentary

12. BNP Paribas AM Monthly Market Viewpoint

13. BNY Investments Vantage Point

14. Candriam Monthly Coffee Break

15. Citibank GIC 2026 Q1 Macro Investment View

16. Columbia Threadneedle Tactical Asset Allocation Outlook

17. Degroof Petercam - Indosuez Monthly House View

18. DWS Investment Traffic Lights

19. Erste Group Global Strategy 1Q 2026

20. Federated Investors Where We Stand

21. Fidelity Global Asset Allocation Insights - February 2026

22. Fisch Asset Management Monthly Update

23. Franklin Templeton Allocation Views January 9, 2026

24. Generali Investments Market Compass January 2026

25. Hang Seng Bank 1Q Investment Outlook 2 Jan 2026

26. HSBC AM Investment Monthly 08 January 2026

27. ING Investment Office Maandbericht Beleggen

28. Invesco Quarterly Global Asset Allocation 2026 Outlook

29. J. Safra Sarasin Cross-Asset Weekly

30. Janus Henderson Multi Asset Quarterly

31. JP Morgan Global Asset Allocation Views 1Q 2026

32. Kempen Asset allocation outlook overview

33. L&G IM Outlook

34. Mackenzie Investments Blue Book

35. Merrill Capital Market Outlook

36. MFS Global Market Pulse

37. Morgan Stanley The BEAT for Q1 2026

38. Neuberger Berman Asset Allocation Committee Outlook 1Q 2026

39. Ninety One Multi-Asset Strategy Quarterly

40. Northern Trust AM Investment Perspective

41. Nuveen Global Investment Committee

42. OFI Asset Management Panorama

43. Pictet AM Barometer

44. PineBridge Investment Strategy Insights

45. Raiffeisen Anlageguide

46. RBC The Global Investment Outlook

47. Robeco Monthly Outlook

48. Russell Investments Asset Class Dashboard

49. Schroders Our Multi-Asset Investment Views

50. SEB House View

51. Societe Generale House Views

52. Standard Chartered Global Market Outlook

53. T. Rowe Price Global Asset Allocation

54. UBP House View

55. UBS Macro Monthly

56. UniCredit Monthly Outlook

57. UOB AM Quarterly Investment Strategy

58. Vontobel Investors’ Outlook

59. Voya Multi-Asset Perspectives

60. VP Bank Our View

61. Wellington Multi-Asset Outlook

62. Wells Fargo Asset Allocation Strategy

63. Wilmington Trust Capital Perspectives

For this interview, I sat down with Valentijn van Nieuwenhuijzen, author of the Substack Always Expect the Unexpected. Valentijn brings 25+ years of experience from senior roles at Goldman Sachs Asset Management, NN Investment Partners and ING Investment Management, spanning macro, multi-asset investing, portfolio construction and sustainability.

Our conversation builds on insights from the latest Asset Allocation Report by Alpha Research, which synthesises the tactical views of 60+ global asset managers. One result is particularly striking: Emerging Markets currently rank as the most attractive asset class across both equities and bonds, a rare combination.
In this interview, we work through the key building blocks behind this renewed EM tilt: what had to align for it to show up in both equities and bonds, why valuation supports the case but rarely times the entry, and how the USD, liquidity and flows can turn a strong thesis into a fragile trade.

Valentijn also shares his own reflections on the discussion on Always Expect the Unexpected, a great companion read to this piece.

Below, the full conversation is structured in 16 questions, moving from the “why now” signals to the practical portfolio questions: where EM is most vulnerable, what could change the view, and how to implement without turning it into one big EM bet.

1) The striking consensus

Eelco: What stood out to you when you saw that Emerging Markets came out as the most attractive asset class for both equities and bonds?

Valentijn: I found that very striking, because Emerging Markets have been somewhat out of favour with both institutional and retail investors in recent years. A strong dollar, weak commodity prices, rising interest rates in developed markets, and long-standing disappointments around corporate profitability in EM all created headwinds until about a year ago. That picture clearly started to turn over the course of 2025.

Why is this combination so rare right now, and what had to ‘come together’ for this outcome?

What really stands out to me is that EM equities have also become more popular again. EM debt has long been a structural overweight for many institutional investors, with a solid track record of delivering extra return and diversification in fixed-income portfolios. That has never really been the case for EM equities. Over the past 20 years, the asset class has largely failed to deliver on its promise. Despite higher economic growth in these regions, it has rarely translated into superior earnings growth or higher returns on equity than in the developed world.

2) What is the real driver: macro, valuation, or the USD?

Eelco: If you had to pick one factor pulling EM today - valuation, the USD, or financial conditions - which would it be?

Valentijn: If I really have to pick one factor, it wouldn’t be any of the three you mention. I would point instead to the broader search among investors for new sources of growth and return outside the US, triggered by Trump’s policy agenda.

What are the two signals that would make you say: ‘okay, this factor is now turning against EM’?

Many emerging markets are highly dependent on global trade. The trade restrictions and tariffs currently being rolled out by the US pose both direct and indirect risks, especially if other countries follow suit. That creates clear headwinds for EM.

3) Valuations: cheap, but cheap is not enough

Eelco: Many asset managers point to attractive valuations. When is ‘cheap’ a real buy signal for EM?

Valentijn: Cheap sounds attractive, but it is rarely a good entry signal. Often there are very good reasons, like structural problems, why assets are cheap. And just as often, markets are willing to keep buying “expensive” assets far longer than seems rational. For me, valuation is a supportive long-term argument, but almost never a trigger to enter a position.

Which valuation metric do you find most useful: P/E, P/B, risk premium versus DM, or something else?

There is no universal rule. It differs by asset class and by whether you are looking at equities, bonds, or commodities. Risk premia are probably the best metric for comparing asset classes, but even that breaks down for commodities, which generate no earnings or cash flows and therefore can’t be assessed using most traditional valuation measures.

4) The USD as a pivot point

Eelco: How important is USD stabilisation or weakness in your EM case?

Valentijn: The USD plays a major role. EM performance has always been highly sensitive to capital flows, across equities, debt, and FX. That sensitivity may be even greater now, because after years of US return exceptionalism, investors are genuinely searching for alternative sources of return. The USD weakened sharply in the first half of last year and is under pressure again this year, which clearly coincides with strong EM performance.

If the USD strengthens again, which EM segments are most resilient and which are most vulnerable?

So far, the weakest parts of EM have been China and then India. That’s striking, given they are by far the largest EM economies and therefore key focal points for the Trump administration. Escalating trade tensions with the US could weigh disproportionately on them. China also faces major domestic challenges, deflation, a housing market correction, and so on.

If the USD were to strengthen again, however, I would expect the most negative impact in EM segments that are highly dependent on capital flows, smaller economies in Southeast Asia, Latin America, and Africa.

5) Financial conditions and risk appetite

Eelco: Many analyses link EM performance to looser financial and monetary conditions. How does that transmission work in practice?

Valentijn: That ties directly back to EM’s sensitivity to capital flows. When financial conditions are loose and global risk appetite is high, capital flows toward riskier parts of the world. EM clearly falls into that category. These psychologically driven capital flows often dominate fundamentals, although the two can of course reinforce each other.

What do you actually watch: global liquidity, credit spreads, PMIs, central bank expectations, or flows?

You never look at just one indicator. Many of these variables are interconnected. Global liquidity is always a function of both the cost of credit - set by central banks like the Fed - and the willingness to use leverage, whether in corporate balance sheets or investment strategies such as hedge funds, leveraged ETFs, or private equity. Fed and ECB expectations, observed flows, and market-priced credit spreads each describe part of the broader liquidity and risk-appetite story.

6) China: the biggest source of noise, or still the key catalyst?

Eelco: In the bear case, China and tech weakness keep coming back. Is China still the EM factor for you?

Valentijn: China has clearly lost some relative importance for the EM region because of other supportive factors, but it remains crucial. Trade between China and the rest of EM is enormous and still growing. If China were to weaken significantly, that would eventually weigh more heavily on the rest of EM. The good news is that this sensitivity appears to be declining, and China is currently growing at a modest, but relatively stable pace.

If you take China out of the picture, which EM story still stands - India, LatAm, EM EMEA, ASEAN - and why?

ASEAN and India clearly have the strongest growth potential, driven by growing populations and high nominal GDP growth prospects. Politically, this part of Asia is relatively stable and benefits from comparatively well-functioning institutions. Other EM regions generally face lower growth potential and more political or institutional instability.

7) Trade tensions and tariffs: headlines or fundamentals?

Eelco: How do you assess trade tensions and tariff risks, mostly sentiment and headlines, or structurally damaging to margins and earnings?

Valentijn: There are many layers to this. At the core, Trump’s tariff policy undeniably creates structural uncertainty around economic policy. As long as he is in power, that uncertainty will periodically catch markets off guard. Trade with the US will become more difficult for almost everyone, negatively affecting margins and earnings growth.

The key question is: how much? At the same time, new trade routes are being explored and new trade agreements are being signed between other regions. That will at least partially offset the loss of frictionless trade with the US and reinforces the idea that future growth opportunities may increasingly lie outside the US.

Which EM regions or sectors are most exposed and where do you see potential beneficiaries?

China is actually a more important trading partner for EM than the US. It imports large amounts of agricultural products and commodities from other EM countries, especially in Latin America, while much of its technology and manufactured goods trade is concentrated within Asia. If China were to re-accelerate meaningfully, that could provide a major additional boost to the rest of EM.

8) EM equity: earnings breadth beyond the US

Eelco: There is an argument that growth and earnings breadth outside the US are improving. Do you see that and where?

Valentijn: Yes, that is happening, but with an important caveat. Technology and financials are the largest earnings-growth sectors globally. In many EM countries, banks and the broader financial sector play a role, but tech exposure is far more uneven. The US still dominates global tech and therefore retains a large share of global earnings growth. China is trying to challenge this, but mainly succeeds domestically, leaving US tech dominance in the rest of the World largely intact.

Is this a cyclical rotation, or a multi-year trend?

The broadening of earnings growth beyond the US is a structural trend. But the tech dimension remains crucial. A true acceleration will only occur once tech winners outside the US emerge, whether in EM, Europe, Japan, or Korea.

9) EM debt: carry is attractive, but what’s the risk?

Eelco: With EM debt, the story is often yield and carry. What is the ‘hidden cost’ of that carry?

Valentijn: There is no hidden cost if you recognise that yield or carry is simply a risk premium. It’s the compensation you receive for providing capital to an EM government or company. The higher the risk, the higher the yield. The hidden cost only appears if you expect that extra return without bearing the underlying risk.

Where does that cost usually show up - FX, drawdowns in risk-off, liquidity, or politics?

Those risks certainly exist. FX risk is the largest issue for local-currency debt and EM equities, while liquidity is a major risk across all EM assets. Political risk at the global level mostly comes from Trump and the Fed, given their impact on liquidity conditions. Local political risk exists too, but can largely be diversified away across countries.

10) Hard currency versus local currency

Eelco: If you had to choose today: hard currency or local currency EM debt and why?

Valentijn: Very clearly hard-currency EM debt. Historically, the performance difference has strongly favoured hard currency. In theory that gap should be smaller, but persistent EM currency underperformance versus DM currencies has meant that local-currency debt delivers diversification but also much higher volatility and structurally lower returns.

What macro development would make you switch?

A combination of credible policy frameworks across EM and clear evidence that EM currencies have entered a sustained upward trend versus DM currencies.

11) Spreads, flows, and positioning

Eelco: How important are flows and positioning in your EM decisions?

Valentijn: Very important. Behavioural analysis and psychology should be core tools for modern investors. If you want to understand market dynamics and actively manage entry points and outperformance, you have to incorporate these elements. Flow and positioning data help identify inflection points and areas of fragility, which often determine the size of drawdowns during unexpected risk-off shocks.

What would you consider an ‘overcrowded’ signal?

Broad signs of excessive optimism among professional and retail investors. There are many indicators: surveys, positioning data, volatility pricing, and AI-based sentiment analysis from media, research, and earnings calls. Asset-class-specific indicators also matter, and this is often where investors can really differentiate themselves.

12) Risks: politics, FX, and regulation - how do you actually manage them?

Eelco: EM is often framed as ‘political risk, FX risk, volatility’. How do you translate that into concrete risk limits?

Valentijn: It’s not fundamentally different from other asset classes. There is now ample historical data for EM equities, EM hard-currency debt, and EM local-currency debt to estimate correlations, volatility, drawdowns, and expected returns. That allows you to determine appropriate portfolio weights. Risk is ultimately a source of return, also in EM, but you need a solid analytical framework to understand the uncertainty that can never be fully modelled.

Do you use hedges, country caps, drawdown rules — or mainly diversification?

FX hedging has historically made sense, which is one reason EM hard-currency debt has performed so well. Beyond that, hedges, caps, and drawdown controls all matter, but the right mix depends heavily on portfolio specifics and whether you are dealing with EM equity, hard-currency debt, local-currency debt, or a combination.

13) Implementation: making EM portfolio-proof

Eelco: “If you’re constructive on EM equities and debt, how do you avoid it becoming one big EM bet?”

Valentijn: It starts with a reality check. Correlations within EM are high, especially in stress periods, so drawdown management is critical. You need to stay acutely aware of exposure to Fed policy, liquidity, and risk appetite. Allocating to more resilient EM segments helps. Exposure to precious metals and oil producers can provide some protection in stress scenarios. Over time, large economies like China and India may also become more domestically driven, improving diversification across Em assets.

Do you use target bands, phasing, or sequence debt before equity?

Short answer: no. Start with your optimal EM portfolio and stay adaptive. As Keynes said, “When the facts change, I change my mind.” That principle applies to EM just as much as to developed markets, perhaps even more so.

14) Scenarios: when are you right, and when not?

Eelco: What’s your base-case scenario in which EM surprises over the next 6–12 months?

Valentijn: A modest acceleration in global growth driven by fiscal and monetary stimulus in developed markets, combined with slightly less tariff chaos from Trump as he shifts focus to domestic politics ahead of the midterms. That would channel capital toward EM in the search for above-average growth and returns. Positioning is tactically overweight, but strategically still underweight among large institutions. So, there is still ample room for further inflows.

And what’s the scenario where you have to admit: ‘this isn’t working’?

A US recession. That would accelerate Fed easing but also amplify Trump’s policy chaos and sharply increase global risk aversion. Capital would exit EM and move toward the few remaining safe havens — gold, German Bunds, and the Swiss franc.

15) What would change your mind?

Eelco: Which two or three datapoints would push you from overweight EM to neutral or underweight?

Valentijn: Strongly negative US employment data, a collapse of the AI capex boom, or a US invasion of Greenland.

And what would make you more aggressive?

A strong rebound in China’s domestic growth, or another wave of new trade agreements among EM regions themselves or with Europe, the UK, Japan, and Canada.

16) Closing question: the 30-second pitch

Eelco: If you had to pitch this to an investment committee in 30 seconds: why is EM attractive in both equity and debt right now?

Valentijn: In a rapidly changing and ageing world, the search for new sources of growth and return is more urgent than ever. Emerging Markets offer renewed potential on both fronts and stand to benefit from deeper partnerships with parts of the developed world that are actively seeking alternatives to the US. The global energy transition also creates opportunities, both through commodity trade and by enabling EM economies to leapfrog directly to cleaner, more productive energy systems. For large parts of Asia, Africa, and Latin America, this represents a development opportunity Europe and the US never had.

And what’s the one sentence you must add to frame the risk honestly?

In periods of stress, correlations between all EM assets converge toward one. Don’t overestimate diversification benefits when they matter most!

Eelco: Thank you, Valentijn. This was a very valuable discussion, and it genuinely helped sharpen how I think about the signals in the Asset Allocation Report.
Readers interested in the broader data behind this conversation can find the full Asset Allocation Report on my Substack. Valentijn’s own reflections are published on Always Expect the Unexpected.

Valentijn: It was my pleasure. I really enjoyed the conversation, thank you for sharing the insights from the report, and for the great dialogue on EM assets.

This week’s question

Markets love a clean story, even when reality is messy. Emerging Markets rarely get one narrative that covers both equities and debt at the same time. Yet the Alpha Research CMA dataset, built from 60 long term reports, produces three unusually usable anchors. The uncomfortable question is simple: when the crowd converges, is that clarity, or complacency?

4 pillars, 3 assets, 1 regime: the USD and financial conditions do the heavy lifting

The common thread is straightforward: when the USD stabilises or weakens and financial conditions ease, EM assets often benefit together, across both risk and spread markets. That is why EM equities and EM debt can look attractive at the same time in long term assumptions. The twist sits in dispersion: EM debt forecasts cluster tightly around 6%, while EM equities show a much wider range across quintiles. In plain English, the crowd feels more confident about debt than about equity, even if both lean on the same macro regime.

At a glance

• Return definition: nominal, USD, unhedged, 10 year CMAs

• Source: Alpha Research, based on 60 CMA reports

• Equity index: MSCI Emerging Markets

• EMD hard index: Bloomberg Emerging Markets United States Dollar Aggregate USD

• EMD local index: Bloomberg Emerging Markets Local Currency Government USD

• Key hinge: USD direction, financial conditions, risk appetite

3 tables, 166 observations, and the shape of the crowd

Emerging Market Equities, quintiles (N=74)

Read-through: your 7.61% consensus sits close to the middle (Q3 7.76%, median 7.80%). The range is still wide, the crowd agrees on the centre, not on the path.

EMD Hard Currency, quintiles (N=63)

Read-through: this distribution is noticeably tighter than equities. The middle (median 6.00%, Q3 6.03%) supports your 5.98% consensus as a clean working proxy.

EMD Local Currency, quintiles (N=29)

• Consensus: 6.09% (USD)

• Median: 6.25%

• Q3: 6.10%

Read-through: local screens slightly higher than hard on both consensus and median. The “why” likely sits in FX assumptions, but your “keep it simple” approach is sensible for now.

The key takeaway for asset allocators

One sentence: the regime logic is shared, but confidence is not. EM debt looks like a tighter call than EM equities in the CMA crowd. That does not make debt safe, it makes forecast dispersion smaller, which is a different kind of comfort.

Emerging Market Equities

6 tailwinds, 1 shared driver, why EM equities keep resurfacing in CMAs

The bull case is valuation plus regime. Several houses highlight attractive EM valuations (Standard Chartered, Pictet). The bigger lever is macro: a stable or weaker USD is repeatedly framed as a tailwind (BNY, Fidelity, RBC), especially when paired with easier financial and monetary conditions that support risk appetite (AllianzGI, PineBridge). Add the growth angle, earnings breadth and growth outside the US, including EM (AllianzGI, UBS). Then the structural layer: reforms and productivity gains via AI and automation (Federated). Put together, EM equities look less like a single bet and more like a basket that works when the USD and global liquidity stop tightening.

4 frictions, 1 knife twist, why valuation rarely saves you

China and tech weakness can drag the EM label (Northern Trust AM). Political, FX, and regulatory risks can dominate fundamentals, and volatility remains structurally higher (Franklin Templeton, Nuveen risk framing). Trade tensions and tariff headlines remain a persistent uncertainty (PineBridge, RBC). There is also model driven caution, with downgrade signals in parts of the EM complex (PineBridge). The twist is that almost every pro argument flips if the USD strengthens and the regime turns risk-off.

Emerging Markets Debt

5 supports, 0 drama, why EMD keeps looking like a “6% asset”

The pro case is clear: carry. Multiple managers point to relatively high and attractive yields (Nuveen, T. Rowe Price, UBP). A weaker USD is again a meaningful tailwind (Franklin Templeton, UBP). Some link support to disinflation and improving fundamentals (Franklin Templeton, Pictet). Others emphasise that spreads can stay supported, or tighten further, if fundamentals and flows cooperate (J.P. Morgan, PineBridge, Morgan Stanley). Implementation matters: there is preference for specific segments, such as hard currency and IG sovereigns (Morgan Stanley, UOB AM). Your distribution reinforces the story, the centre clusters around 6%.

2 cautions, 1 practical reality, why neutral can be the right stance

You did not find explicit underweight calls within the allowed EMD terms, which itself signals how “consensus-friendly” this sleeve is right now. The main counterpoint is not bearishness, it is lack of conviction, a neutral, balance-position framing for EM USD debt (BNY). The practical reality is that EMD is not one thing, segment choice matters, and your index definitions underline that (USD aggregate versus local government). In a risk-off shock, spreads and FX can still hurt, even if long-run carry screens attractive.

What this means for an asset allocator

Use these figures as anchors, not promises. If your base case is stable-to-weaker USD and easing financial conditions, EM can be one coherent long-term allocation story across both equity and debt. Size it differently: EMD reads like the tighter forecast with a clearer carry logic, while EM equities are the higher-dispersion expression of the same regime. In a “less is more” framework: start with EM debt for carry discipline, add EM equity when you explicitly want pro-cyclical upside.

Debate this in the comments

A) Make EM Debt your core EM exposure (carry first, equity optional)
B) Go equity-led (valuation plus earnings breadth, debt as a satellite)

One sentence: which sleeve best matches your base case for USD and risk appetite over the next 6 to 12 months?