As Rates, Policies Diverge, Asset Allocators Must Adapt – Brown Shipley

Tom Burroughes

15 December 2025

Countries’ macroeconomic paths are diverging – requiring wealth managers to reshuffle clients’ assets to obtain optimum results, for example in the fixed income space.

With interest rates varying, , sees opportunities for investors to move in and out of specific bond markets.

The firm has other views and it notably isn’t – at least yet – buying into the narrative of AI and Big Tech valuations being dangerously overheated, presaging a sharp correction.

Switching around
The firm is buying UK gilts and selling Japanese JGB bonds, taking the view that the stimulative macroeconomic policy of the new government in Japan will tend to weigh on fixed income, while the UK government’s recent tax hikes point (hopefully) to a falling budget deficit, with the added benefit of lower interest rates.

Monetary policy interest rate one-year expectations show Japanese rates rising to nearly 8 per cent, while those in the UK are seen falling below 4 per cent. The general government balance as a share of GDP is higher in Japan than in the UK, although the Japanese figure is expected to fall towards 2030, while Quintet has the figure rising in the UK towards that date.

In the US, the US Federal Reserve has started to cut rates – as happened last week with a 25 bps reduction.

“After decades of US-centric globalisation, the world continues to shift towards a more multipolar landscape,” Daniele Antonucci, Quintet Private Bank’s chief investment officer, said.

AI capex and valuations – no need to freak out
Artificial intelligence capital expenditure (capex) is accelerating – a reason why US and rest-of-world economic growth will be relatively robust. That said, AI’s overall impact is not as large as previous tech revolutions, the firm told journalists at a media briefing.

For example, UK railways in the 1860s loomed larger as a GDP booster. Railways achieved a peak historical investment pulse, as a share of GDP (about 4.5 per cent), and about 3.5 per cent for the US railroad boom of the 1880s. US automobile infrastructure was just above 2 pr cent; US electric motors were also around that percentage. US IT hardware of the 1990s came in at around 1.5 per cent and US telecoms were about 1.3 per cent.

The largest AI players, such as Microsoft’s Azure, are booking billions in revenues, using this cash to finance spending. For the largest corporates, they are paying for this capex from profits and cashflows, and not with debt, Boryana Perfanova, chief investment strategist at Brown Shipley, said at the briefing. She said there is more room for concern about smaller AI companies and their greater use in relative terms of debt.

At the end of the dotcom bubble, the average price-to-earnings ratio of the top seven tech companies was 81 times earnings (firms such as Cisco, Sun Microsystems, Lucent Technologies, IBM, Oracle, Microsoft and Intel); today, with the “Magnificent Seven” (Broadcom, Apple, Amazon, Meta, Nvidia, Microsoft and Alphabet), the average PE ratio is 36 times.

Beyond AI
Looking at sectors outside strict AI – albeit with linkages – Brown Shipley has its eyes on themes such as the need for new infrastructure (power connectors, improved roads, transport, etc), “future health” (innovative ideas in health and medicine); “aspiring economy” (the idea of an expanding middle class in certain parts of the world), defence (concerns about geopolitics), and cybersecurity.

The firm is more optimistic on GDP growth than previously, expecting global real GDP growth to reach 3.4 per cent in 2027, revised up from 3.2 per cent.