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US High Yield: Finding cover in the gathering storm

Peter Khan - Portfolio Manager

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As markets navigate geopolitical tensions, US high yield indices have posted small negative returns year-to-date, much more supressed than other asset classes that have had bigger drawdowns (past performance is not a reliable indicator for future returns). Supportive factors such as meaningful energy exposure, which has benefited from higher oil prices, and limited vulnerability to AI disruption compared with other parts of leveraged finance, have supported performance. Thus in this environment, the asset class may help generate alpha against a challenging market backdrop.

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A sectoral hedge

Geopolitical escalation in the Middle East means the US high yield market's significant energy sector weighting has transformed from a historical volatility source into a strategic advantage. With US-Iran tensions showing no sign of easing, energy prices have adjusted to higher levels, aiding the considerable portion of the high yield universe tied to oil and gas producers. As crude prices respond to supply concerns, energy issuers are likely to see improved cash flows and enhanced ability to service debt, supporting spreads and total returns in the asset class. This sector concentration within US high yield provides a natural hedge against geopolitical risk relative to other credit markets such as investment grade or even other regional high yield markets (see Chart 1 below) where energy exposure is smaller. That is not say that US high yield market is immune to the volatility, as elevated oil prices introduce another layer of uncertainty for risk assets, particularly if higher energy costs begin to weigh on consumption and corporate margins.

Dodging the AI bullet

Prior to the latest Middle East developments, the conversation across markets was dominated by AI and its potential impacts. That said, US high yield has largely sidestepped the AI disruption fears that have challenged other spaces such as the leveraged loan market in recent months. The heavy concentration in software services in the latter has made it particularly vulnerable to concerns about AI leaving traditional business models obsolete (see Chart 2). This became apparent to investors in February 2026, when leveraged loans suffered their worst monthly performance since 2022, driven primarily by software sector weakness. In contrast, the sector composition of high yield markets skews relatively more towards traditional industries, including energy, telecommunications, healthcare, and basic materials, that are less immediately threatened by AI disruption. While it may be premature to say any sector is entirely immune to technological change, it appears high yield issuers face a longer runway before AI structurally changes sector dynamics for the asset class.

At the same time, the rapid evolution of AI is introducing new competitive pressures across parts of the software ecosystem, particularly SaaS business models. In some cases, AI-driven disruption is raising questions around the durability of business models that previously benefited from strong growth expectations and elevated equity valuations. While this does not necessarily imply widespread solvency concerns, it has made certain technology investments appear less compelling and increased scrutiny around earnings resilience across software-related issuers.

Beyond the macro backdrop, signs of stress are emerging across parts of the leveraged finance ecosystem, particularly within segments of the private credit market. Years of strong investor demand for uncorrelated yield encouraged aggressive lending and rapid loan growth among non-bank lenders. However, a growing number of individual credit events and rising pressure on weaker borrowers highlight the need for greater selectivity across leveraged finance. Against this backdrop, the transparency and liquidity of the public high yield market may offer an advantage, with US high yield comparing favourably to other segments where structural vulnerabilities appear more pronounced.

Past performance is not a reliable indicator of future results.

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