Investment Views
Strategy
Middle East Risks and AI Rewards
- Oil in storage provides a Middle East buffer
- AI revolution continues
- Earnings updates upgraded
April saw a strong recovery in global equity markets from the March sell-off driven by the conflict in the Middle East. This recovery has been driven by three factors: oil prices have risen less than feared, spending on building out the infrastructure to power AI has continued at breakneck pace, and corporate earnings estimates have been revised meaningfully higher.
Oil prices initially rose rapidly when the conflict broke out and the crucial Strait of Hormuz shipping lane effectively closed. There had been many alarming forecasts made around the risk of oil prices going to $150 or even $200 per barrel if the Strait remained effectively closed. Initially it was thought that the Strait would need to open by the end of April, but the timeframe on this has shifted. Brent oil has been fluctuating in a range of $90-$120, which is elevated but not debilitating for the global economy. Coming into the conflict, there was a lot of oil production and oil in storage. This buffer has helped keep the oil price under control, but as oil inventories fall, it is important that commodity flows from the Middle East resume to avoid more damaging price rises.
This is not to say that there haven’t been any market consequences to the Middle East conflict. Jet fuel has risen materially and we have seen some flight cancellations, aluminium prices have risen, fertiliser (important for food production) prices have risen, and helium (an input in the prediction of semiconductors) prices have risen. There is a sense that the Strait will either need to be opened by negotiation or by force, but in an era when warfare has changed due to drone technology, re-opening the Strait through negotiation is clearly the preferable outcome.
The AI theme has dominated financial markets in recent years, and recent months have been no different. Large technology companies are spending huge amounts of money to build out the infrastructure to power the AI revolution. Morgan Stanley estimates that the large tech companies spent around $450bn on capital expenditure last year, but that this year the number will rise to around $800bn. Not all of this spending boosts US economic growth, as some of it is imports, but for context, this spending is around 2.6% of the US economy. It has therefore been a huge boost to economic growth and to revenue for companies in the supply chain.
Nvidia CEO Jensen Huang has described AI as a “five-layer cake”. The five layers being energy, semiconductors, infrastructure, models, and applications. The first three layers in particular are well represented in global equity markets. This spans not just the traditional technology sector, but also industrials and utilities. Every dollar of capital spending is a dollar of revenue for another company. Nvidia was the earliest beneficiary of the spending on AI, but we have recently seen a broadening out of the beneficiaries. This is no longer just a US technology story, and we have seen strong performance from some of the Asian technology companies.
This AI spending also goes a long way in explaining the strength in corporate earnings. Profits for the first quarter came in ahead of expectations, and more importantly, estimates for profits over the coming quarters have been revised meaningfully higher. For the year 2026, estimates are for very healthy earnings growth in the US of 21% on revenue growth of 10.1%. Earnings growth has broadened out, but is still dominated by companies linked to AI.
These factors help to explain the apparent disconnect between strong equity markets and negative geopolitical news. The risks from the Middle East remain, and it is important that commodity flows resume before too long. We are already seeing the inflationary impacts of this, so this is something we continue to watch closely, along with monitoring the progress and monetisation of the AI revolution.
Fixed Income
The Calm Before the (Inflation) Pass-Through
- Long-term bond yields rose despite weaker global growth
- The inflation shock spread beyond oil into the real economy
- Credit markets rallied as investors looked through geopolitical risk
April was calmer for fixed income markets, but the usual link between weaker growth and lower bond yields remains disrupted. Global macro data softened, particularly in China and Europe, yet the Iran war and disruption around the Strait of Hormuz kept energy prices volatile and inflation uncertainty elevated. US Treasury yields moved marginally higher, with the 10-year ending the month at 4.37% and the 30-year at 4.97%. Longer maturity bonds remain under pressure, with 30-year real yields reaching their highest level since 2006, reflecting near-term inflation risk and a higher required return for holding long-duration assets amid fiscal pressure, geopolitical uncertainty and reduced confidence in central banks’ ability to quickly return inflation to target.
The Federal Reserve left rates unchanged at 3.50%–3.75% at its April meeting, and the tone was cautious rather than dovish. The Fed noted that activity was still expanding at a solid pace, while inflation remained elevated, partly reflecting higher global energy prices, and developments in the Middle East were adding to uncertainty. The Committee also stressed that it remained attentive to risks on both sides of its mandate. That language matters. The Fed has now missed its 2% inflation target for more than five years, so another energy shock risks becoming embedded in wage demands, price-setting behaviour and inflation expectations rather than being dismissed as temporary.
Inflation breakeven markets reflected this tension. Short-dated US breakevens fell over the month while longer-dated breakevens rose. The front end was pulled lower by the risk that higher fuel prices would damage real incomes and growth, while the long end rose as investors focused on the risk that energy costs feed into wages, prices and longer-term expectations. Rising transport costs are beginning to affect broader commodities, food and goods prices, as we transition from the initial oil shock into a more difficult pass-through phase.
Oil remained the central market variable, with headlines around the war and ceasefire negotiations driving swings in risk sentiment. US gasoline prices reached $4.39 per gallon, while jet fuel prices also surged, threatening the consumer ahead of the November mid-term elections. Higher energy and freight costs are no longer just a direct inflation issue; they are becoming a broader tax on consumption and corporate margins.
Global bond yields were mixed, with muted moves across most G10 markets, but Japan and the UK stood out. Japan’s 10-year yield rose to 2.52%, the largest move among major markets, as the Bank of Japan kept policy unchanged but lifted inflation forecasts. The UK 10-year gilt yield rose to 5.01%, reflecting energy vulnerability, sticky inflation and rising political risk. The Bank of England held rates at 3.75% but highlighted the risk that a persistent energy shock could require tighter policy if wage and price behaviour deteriorates.
Currency markets were mixed. The US dollar weakened as risk assets rallied despite the unresolved conflict and continued disruption. The Australian dollar rose more than 4% against the US dollar, supported by a positive terms-of-trade backdrop, expectations of the strongest nominal growth in the G10 in 2026 and relatively high real yields. Sterling was another winner, helped by the hawkish Bank of England and improved risk sentiment. However, the rally looks fragile, with several elections in May likely to pressure the Labour government and raise the risk of looser fiscal policy.
Credit markets remained resilient. As global equities rallied and FOMO (fear-of-missing-out) buying returned, volatility fell sharply and average US high yield spreads compressed by 49bps to around 268bps over duration-matched Treasuries. With only a limited risk-asset sell-off in March, there was not much weakness to reverse, and current spreads are not pricing recession. Although, they appear more consistent with US real growth closer to 1.3%, well below the 2.1% currently expected, leaving room for further compression if growth remains stable and defaults stay contained. The risk is complacency. Volatility has fallen, risk assets have rallied and spreads have tightened, but the war remains unresolved and growth effects are beginning to surface, especially in Europe and Asia.
Looking ahead, the outlook depends less on the initial oil shock and more on how long the pass-through lasts. If energy prices normalise quickly, fixed income markets can return to pricing in softer growth, attractive carry and eventual policy easing. If they do not, higher fuel and transport costs will continue to pressure consumers, margins and fiscal balances, particularly in energy-importing economies. Markets may have moved too quickly to price a benign outcome, with spreads tighter and volatility lower despite the unresolved geopolitical backdrop. Fixed income still offers value, but the opportunity set is more selective: favour income over excessive duration risk, quality over weak credit beta, and markets with stronger external balances over those exposed to energy and political stress.
Equities
AI Powered Rebound
- “Magnificent 7” no longer a useful term
- AI needs more memory than first thought
- Emerging Markets rally
The MSCI World index returned a healthy 9.6% in US dollar terms in April. This more than recovered the 6.4% sell-off in March and was the best monthly performance since November 2020, when markets rallied on news of the Covid vaccine. Emerging Markets led the way, returning 14.7%, with some particularly strong performance in South Korea up 31.5% and Taiwan up 26.0%. US equities also outperformed, returning 10.5%, while European and UK equities lagged, returning 7.7% and 5.2% respectively.
At a sector level, Information Technology was the best performing sector in April, returning 17.5%. Communication Services, Consumer Discretionary, and Industrials also outperformed. Energy stocks lagged after a very strong start to the year, while more defensive sectors such as Health Care and Consumer Staples lagged.
Many of the moves seen in equity markets can be explained by the AI factor. In recent years, market commentators have referred to the “Magnificent 7”, which are seven dominant US technology-focused companies: Alphabet, Amazon, Apple, Meta Platforms, Microsoft, NVIDIA, and Tesla. However, in recent quarters, framing markets or AI in terms of this group has been far less helpful. These companies account for the majority of the spending on building out AI infrastructure, but the recipients of this spending in the AI infrastructure supply chain have seen large price gains.
Companies selling memory hardware have performed particularly well. The thinking on how AI works and will be applied has changed a lot over the last year. Initially the thinking was that AI needs powerful processors (Nvidia semiconductors) and that “old fashioned” memory chips were not a key part of the process. However, running AI models in the real world requires constantly shuffling vast amounts of data back and forth at enormous speed.
This process, called inference, is far more memory-hungry than anyone initially anticipated. Early use cases were relatively simple, like “suggest a three-day itinerary for a new city I am visiting”, whereas now the use cases are far more complex. Models can understand the preferences of the user, they can remember previous conversations, they can check availability etc. This needs a lot more infrastructure in the background to run this process.
Many people are familiar with AI as they have used it as a consumer, but the growth in companies/enterprise has been a key pillar of the story in markets. Unlike a simple chatbot that answers one question at a time, companies are using “AI agents” that can autonomously plan, make decisions and complete multi-step tasks, for example analysing documents or writing code. This means that AI is essentially running inference continuously, which multiplies the demand for memory many times over.
Given the importance of AI to equity markets, a key question is whether all of this spending on AI can be implemented by real world companies to drive efficiencies and profitability. This is not just a story about AI replacing jobs, although that is likely, it is about humans being more productive. AI can allow companies to grow without needing to grow headcount to the same degree as previously. There is still a lot of uncertainty around how this will all play out, but we have seen revenues for AI model companies and cloud computing companies inflect higher.
Geopolitical risks continue to loom large, and a more material rise in the price of oil remains possible without a resolution in the Middle East. Beyond that, understanding AI is now crucial to understanding what is happening in equity markets. It is an area where we have spent a lot of time learning and trying to think though about the implications, and will continue to do so.