Infundly Weekly Briefing — 24 July 2026
This week’s Infundly Research Reads highlights the growing gap between portfolio labels and real-world portfolio behaviour. The key theme is that allocators need to look beyond headline categories, bonds, private markets, AI-enabled research, quantitative credit and target-date design, and test the evidence, governance, implementation and liquidity assumptions behind each strategy.
What changed: The FCA’s latest package proposes simplifying AIFM-related requirements and introducing the Fund Reporting for Asset Management Entities framework. The regulator estimates the combined reforms could reduce annual industry costs by approximately £128 million while producing more consistent supervisory data.
Worth reading because: The direction of travel is highly relevant to allocator due diligence. Reporting quality, delegation, liquidity oversight and operational substance should increasingly be assessed as connected governance issues rather than separate compliance questions.
What changed: MSCI argues that access to capable AI models will become commonplace, shifting competitive advantage toward structured data, defensible methodologies, governance and human interpretation. It expects AI to automate more analysis and portfolio-construction work while leaving accountability and judgement with investment professionals.
Worth reading because: This is directly applicable to both manager assessment and Infundly’s own research tooling. Useful due-diligence questions include what data the manager permits AI to use, how claims are verified, who owns the output and whether decisions remain reconstructable after the event.
What changed: Investors are reconsidering whether traditional fixed income can reliably diversify equity risk amid persistent inflation, heavier government borrowing and less dependable stock–bond correlations. Some allocators are increasing exposure to commodities, infrastructure and other real assets instead.
Worth reading because: The important issue is not whether “60/40 is dead”, but whether portfolio assumptions remain evidence-based. Multi-asset managers should be asked which risks their bond allocation is intended to hedge, under what inflation regime that relationship may fail, and what substitutes introduce in liquidity, valuation and manager risk.
What changed: PitchBook data reported by The Wall Street Journal indicates that assets held in US private-equity funds at least ten years old and no longer investing reached a record $348.5 billion at the end of 2025. A further large pool sits in funds approaching that age, reflecting delayed exits and ageing portfolio companies.
Worth reading because: Private-market due diligence needs to distinguish reported valuation resilience from realised liquidity. Allocators should examine fund-extension practices, exit assumptions, continuation vehicles, distribution pacing, conflicts and whether a manager’s claimed holding discipline is partly imposed by an unreceptive market.
What changed: MSCI finds that alternative credit risk models produced broadly comparable realised volatility but materially different turnover and implementation costs. Factor-based modelling had its greatest benefit through reduced trading costs, particularly in leveraged long-short portfolios.
Worth reading because: It illustrates why assessing a systematic strategy solely through gross back-tested returns is inadequate. Manager research should test turnover assumptions, market-impact estimates, financing, leverage, capacity and whether the selected risk model improves investable outcomes rather than merely the optimisation output.
What changed: The paper proposes building target-date portfolios around an explicit required return and a declining conditional-value-at-risk constraint, rather than using preset age-based asset-allocation limits. Its application to Chile’s pension system suggests the point at which risk reduction begins is especially consequential, while insufficient contributions cannot be repaired through portfolio construction alone.
Worth reading because: The framework usefully connects portfolio risk to the outcome being funded. More broadly, it supports challenging managers and proposition providers whose risk bands or glidepaths are mechanically defined without demonstrating how they relate to required returns, contribution behaviour or the probability of meeting investor objectives.
Infundly takeaway
This week’s common theme is the gap between portfolio labels and portfolio behaviour. Bonds may not always diversify equities, private-market valuations may not translate into liquidity, quantitative models with similar headline risk can carry different implementation burdens, and AI output is only as defensible as its evidence and governance.
For selectors, that reinforces the need to assess the complete decision system: underlying economic exposure, data quality, implementation costs, liquidity, accountability and evidence that the strategy behaves as represented.
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