Infundly Perspectives

This week’s research brings together several developments with direct implications for professional fund selectors. New long-term capital market assumptions suggest higher prospective returns across traditional asset classes, while research into private credit, geopolitical fragmentation raises questions about how investment risks are transmitted and managed.

This week’s research offers a particularly useful combination of fund governance, manager behaviour, portfolio construction and financial stability. New academic evidence questions how private-equity managers communicate performance, Morningstar examines the gap between fund returns and investor outcomes, and the IMF highlights the growing systemic importance of hedge funds. Meanwhile, fresh research on gold, AI financing and asset allocation provides useful context for asses

This week’s strongest material centres on a common issue for allocators: whether portfolio assumptions still hold as the cost and availability of capital change. AI financing is moving rapidly from an equity story into credit markets, monetary policy has shifted again, while new long-run evidence provides a useful challenge to the way historical returns are used in strategic asset allocation.

This week’s Infundly Research Reads focuses on the constraints, assumptions and operating structures that can materially shape portfolio outcomes. The selected research looks at concentration limits in active funds, manager-level due diligence across European fund groups, contrasting interpretations of the sovereign-bond sell-off, the investment industry’s evolving AI operating model, and the trade-offs embedded in downside-protection strategies.

This week’s Infundly Research Reads focuses on how investment outcomes can be shaped by the processes and assumptions sitting behind the headline proposition. The selected research covers AI bias in investment workflows, benchmark-free portfolio construction, multi-asset allocation, structured-credit opportunities linked to AI infrastructure, and the limits of universal manager-selection signals, all with direct relevance for professional fund selectors and allocators.

This week’s Infundly Research Reads focuses on the forces shaping portfolio outcomes beyond headline market moves. The selected research examines the sources of inflation, the changing economics of AI exposure, conflicts and governance in private-market continuation vehicles, operational preparedness for T+1 settlement, and the wider cross-market backdrop for allocators.

This week’s Infundly Research Reads focuses on how investment outcomes are shaped not just by asset allocation, but by the structures, assumptions and decision frameworks behind it. The selected research covers active versus passive success rates, target-date glidepaths, AI-enabled investment processes, capital-market assumptions, fund flows and tactical asset allocation — all with direct relevance for professional fund selectors and allocators.

The selected papers and reports examine liquidity governance, active fund selection, performance measurement, systematic factor implementation, macro conditions and the evolving Japanese equity opportunity set. Together, they reinforce the need to test whether reported outcomes, stated investment edges and portfolio characteristics remain credible once differences in methodology, vehicle structure, implementation and market regime are taken into account.

This week’s Research Reads looks at the gap between investment narratives and the exposures, behaviours and governance structures that sit underneath them. The selected research spans macro regime change, factor-driven returns, investment-trust governance, portfolio disclosure and AI-related market concentration, with a common message for selectors: headline outcomes often reveal less than the underlying mechanics that produced them.

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.