For nearly two years, the AI trade has been the single most powerful engine behind global equity returns. It has lifted indices, concentrated their leadership in a handful of mega-cap names, and left much of the rest of the market trading in its shadow.

For nearly two years, the AI trade has been the single most powerful engine behind global equity returns. It has lifted indices, concentrated their leadership in a handful of mega-cap names, and left much of the rest of the market trading in its shadow. The risk of that concentration became visible in July, when a brief unwind in AI-related names was enough to send a wave of panic through the broader markets. Investors were reminded, uncomfortably, how much of their portfolio’s fate now hinges on a single factor.

This is precisely why strategies capable of generating strong risk-adjusted returns without leaning on the AI trade deserve a closer look today. We believe that considering a systematic multi-strategy approach is a really interesting way to diversify the risk of a balanced portfolio: it can systematically adjust and neutralise exposure to specific factors while generating compelling performances across different market cycles.

In practice, we like combining four specific strategy families within such a vehicle: equity market neutral (EMN), quant macro, trend following, and short-term trading. Equity market neutral extracts alpha from stock selection while stripping out broad market exposure, making it a natural diversifier against a single dominant theme like AI. Quant macro trades systematically across rates, currencies, and commodities, positioning around regime shifts rather than any one asset class. Trend following captures sustained directional moves once they emerge. Short-term trading exploits faster, tactical dislocations, adding a different time horizon and low overlap with the other three. Blended together, the combination is built to perform across a wider range of environments than any single style could by itself.

Year-to-date in 2026, EMN has shown a correlation of -0.43 to the AI factor – the most negative of the four – with the broader portfolio also negative at -0.23. Quant macro sits near zero at -0.07, while trend following, unsurprisingly, carries a positive 0.27 given its tendency to ride crowded trends. Low or negative correlation to AI is rare today, offering investors genuine diversification rather than another disguised bet on the same handful of stocks.

Should the AI trade correct sharply, or rotate violently as in July, EMN looks well positioned. Its exposure to the AI theme is limited directionally, so its return should stay largely uncorrelated with an AI-driven drawdown, and July’s strong performance is evidence of that. Trend exposure within the blend is deliberately modest, and the portfolio is not cap-weighted, so the largest names driving broader market momentum carry no outsized influence.

Fixed income is another pillar of this case: due to low dispersion and low volatility the segment has had a tough time for the last three years, and, following a particularly difficult 18 months, yields are moving with more conviction, opening up a richer opportunity set, both directly and across the other asset classes these strategies trade. However, it should be remembered that across the decade prior to 2023 it was the strongest contributor among such strategies.

Currencies are quietly playing an important diversifying role too, absorbing much of the macro and geopolitical dispersion that rate markets have not. One real advantage of this approach is that it does not require a clear long-term bias to generate performance; in fact, capital can pivot to wherever dispersion shows up.

On rates specifically, the missing ingredient has been sustained directionality rather than simply volatility. This is likely to emerge once one narrative starts to dominate among the competing macro regimes at play, for example, an energy supply shock, fiscal expansion, and higher sovereign issuance. We observed a change in inflation expectations, and we saw all developed economies being forced to raise interest rates.

History offers a useful context on how long these ‘volatility collapse’ regimes last: US 10-year yields, for example, spent roughly a year (from April 2025 to March 2026) locked in an unusually tight range after a long period of consistent movement. Such regimes rarely persist indefinitely. We believe these systematic strategies that are backed by strong research and proven models are well equipped to weather what seems to be an interesting market environment regardless of whether or not the AI narrative continues to dictate market direction.

Taken together, the message for allocators is straightforward: the AI trade has been a powerful, narrow driver of returns, and that narrowness is itself a risk. A blend of EMN, quant macro, trend following, and short-term trading, alongside a fixed income opportunity set that is finally reopening, offers a credible way to diversify performance drivers without giving up strong, risk-adjusted returns. All of this needs to be combined with a strong risk-management process.

For Professional Investors in Switzerland or Professional Investors as defined by the relevant laws. Investments in hedge funds involve significant risks, including the risk of illiquidity, of loss of capital, strategy‑specific and leverage related-risks.

The opinions expressed herein are correct as at 25 September 2026 and are subject to change without notice. This information should not be relied upon by the reader as research or investment advice regarding any particular fund, strategy or security. Past performance is not a guide to current or future results. Any forecast, projection or target, where provided, is indicative only and is not guaranteed in any way.

The views and opinions expressed by fund managers (internal or external) may differ from the house view. They are shared for informational purposes and do not constitute investment advice or a recommendation.