The S&P 500 has experienced a volatile, sluggish start to 2026, driven by an "early cycle dynamic" supported by positive economic data and healthy corporate earnings, particularly for value and cyclical stocks. However, intense scrutiny on the AI trade has triggered a sharp rotation from growth to value, with widespread selling across perceived "disrupted" industries. UBS Asset Management advocates for a selective, balanced portfolio approach, identifying companies with strong moats while capitalizing on broader cyclical recovery and durable AI capital spending.
Summarized by Podsumo
Despite a flat S&P 500, the market shows signs of an early cycle dynamic, supported by positive soft and hard economic data, and strong Q4 earnings growth (9% revenue, 12% earnings) benefiting value and cyclical stocks.
Intense debate around AI's disruptive potential has caused "multiple standard deviation stock moves" and indiscriminate selling across tech and non-tech sectors, leading to a significant rotation from growth to value stocks and into small/mid-caps.
Proving the non-disruption of incumbents is difficult, even as their fundamentals remain sound. Concerns focus on future growth, business model changes, and potential repricing of seat-based software models.
Hyperscalers are projected to spend nearly **$700 billion** on CAPEX this year for AI infrastructure, yet their free cash flow is flat, raising questions about incremental return on invested capital despite benefiting the supply chain.
UBS emphasizes a "barbell" approach, balancing durable AI capital spending opportunities with cyclical growth in financials, industrials, and semiconductors, advocating for a more balanced portfolio construction between value and growth.
"The S&P 500 has faced a sluggish start in 2026."
"The way that we see the market has continued to demonstrate signs of an early cycle dynamic trend that we saw exiting last year."
— Ed Tran
"The most challenging part about this AI disruption theme... is that we can have very high conviction on why the risk is overblown... but the burden of proof is trying to disprove the bear case."
— Ed Tran