- Recent S&P 500 sell-off driven in part by concerns over rising capex of technology companies
- Portfolio allocators shift weights to defensive plays to position for monetary easing
- Latest Tech sell-down on S&P 500 provide good entry for investors to jump onto AI bandwagon
- In CIO’s asset allocation model, maintain overweight exposure to US equities
From hero to zero – Tech-related sectors worst performers in S&P 500 in 3Q. The S&P 500 has been volatile of late and this came on the back of concerns on Tech valuations and Nvidia’s outlook. Indeed, since hitting a peak in July, US Tech has retraced c.10.9% amid rising concerns on capital expenditure (capex) by Tech companies on AI initiatives as investors question the monetisation potential of these investments.
On a QTD basis, US Tech-related sectors like technology and communications services lost 5.6% and 5.5% respectively (as of 4 Sep) while defensive and yield-sensitive plays like real estate and utilities outperformed (+14.0% and +12.8% respectively). Clearly, investors are rotating their portfolio allocation and shifting weights to sectors that will outperform when the Fed embarks on monetary easing.
As we have highlighted in a previous report titled “US Equities: Beneficiaries of Fed rate-cutting cycle”, sectors that tend to do well in past Fed easing cycles include utilities, consumer staples, and healthcare. This is part of the “market broadening” rally that we have been narrating this year.
US Tech capex concerns: Much ado about nothing. We believe that there are two reasons as to why the capex worries surrounding US Tech are unfounded. First, unlike the dot-com era of the 1990s, the AI revolution today is being funded by free cash flow rather than debt. Hyperscalers such as Alphabet, Amazon, Meta, and Microsoft are flushed with cash from their well-established profitable businesses. The free cash flow growth of these companies is projected to grow 142% from USD142.8bn in 2020 to USD345bn by 2026.
Secondly, Tech “hyperscalers” have maintained their capex to EBITDA ratio around their 10-year average of c.43%, suggesting a disciplined capital management approach which ensures that resources are not stretched too thin. This self-sustaining financial model ensures that these companies are not over-leveraged, making the AI trend far more resilient to economic fluctuations.
Stay overweight US market for its heavy Tech exposure. The latest Tech sell-down on S&P 500 presents opportunities for investors to jump onto the AI bandwagon. We maintain that the AI revolution is still in its infancy and holds immense growth potential. Listed below is the “AI value chain” which investors can explore:
- Layer I - AI infrastructure: This stage focuses on semiconductor companies that provide essential components for computational power and memory, including processors, GPUs, and advanced chips that enable AI algorithms to function.
- Layer II - Software Services: The next layer involves the development of AI algorithms and platforms. This includes machine learning frameworks as well as other software tools such as Large Language Models (LLMs). These software solutions provide the underlying tools and frameworks for AI development.
- Layer III - Applications: This layer explores the diverse AI applications across various industries and seeks out companies with innovative business models capable of monetising AI through product offerings, thereby driving real-world transformation.
While investors have primarily focused on semiconductor companies, the AI value chain extends far beyond this initial layer. As AI evolves, we anticipate significant opportunities in the software services and applications layers.
Source: Bloomberg, DBS
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