Systematic Equity Outlook: Decoding Upside and Downside Risks

The act of reshoring, or bringing production, supply chains, and other business operations back to domestic locations, is one way that companies are adapting to a more fragmented world. Figure 2 shows the steady long-term rise in company announcements related to reshoring jobs which reached around 350,000 for 2023, along with Google search traffic revealing growing attention to the topic.

In identifying companies engaging in or benefitting from reshoring activities across industries, we employ a large language model (LLM) supplemented with granular text analysis and alternative data to help build a comprehensive basket of exposures. At a high level, this analysis reflects a positive view towards domestic industrials, raw materials suppliers, and real estate companies, and a relatively more negative view towards internationally exposed manufacturers and logistics firms.

Where innovation meets geopolitics

The technology sector has been a key area of focus around this topic given its highly global presence, with US tech companies generating nearly 60% of revenues overseas.¹ This puts the tech sector at the intersection of two prominent mega forces—AI and geopolitical fragmentation—with the potential to drive a wide range of stock-specific outcomes. Recent US executive actions, such as doubling semiconductor tariffs to 50% underscores potential headwinds to firms with global exposure.² Meanwhile, supportive legislation such as the CHIPS and Science Act of 2022 represents a nearly $53 billion investment in US semiconductor manufacturing, research, and development.³ This reflects the US government’s commitment to tech leadership which is likely to remain an area of political consensus, potentially creating a supportive backdrop for companies who are fostering US-centric technological innovation and production.

The right tail: more room for markets to price a soft landing

Soft inflationary data spurred the start of the recent rotation as investors adjusted expectations for monetary easing. As we look ahead, the potential for a right tail “FOMO” scenario could drive a more persistent rebound across segments of the market that lagged amid steady thematic and factor trends earlier in the year.

The two charts in Figure 3 show our alternative inflation indicators including web-scraped product prices and wage growth from online job postings which increasingly suggest that inflation is easing in real-time. Taken together with our estimated recession probability which remains below consensus estimates, hopes for a soft-landing have the potential to gain further traction in markets as these timely measures translate to official data releases.

Assuming this “right tail” macro narrative continues, the question becomes how much economic optimism is already priced? We explore this in Figure 4 by measuring how many companies across the US high cap universe are trading at a forward price-to-earnings (P/E) ratio that is below their average forward P/E ratio during previous recessionary periods. The chart shows that even after the strong market run of the past few months, there are still ~480 stocks trading below levels consistent with a recession, comprising more than one-third of the total universe. Recession-consistent pricing is concentrated within the most cyclical segments of the market, including airlines, construction, and housing, creating opportunities to exploit mispricings if data continues to point towards the economy avoiding a recession.

AI sentiment slipping, but still not DotCom 2.0

As the risks of both left and right tail outcomes increase, investors may choose to reallocate capital concentrated in established positions that have significantly outperformed year to date, most notably the AI trade.

Investor sentiment towards the AI theme has waned recently in response to high growth in capital expenditure spending, particularly among the hyperscalers in this space, amid concerns that the returns on this investment may not be as high as initially expected. Analysts are increasingly questioning whether sales and earnings will be able to keep pace with these large investments over the coming years. This weakening sentiment is reflected in measures of analyst expectations shown in Figure 5 below.

But more broadly, the current environment continues to look significantly different from the early-2000s tech bubble as illustrated in the series of charts in Figure 6. The first chart shows the z-scores of ~500 features for the Nasdaq 100 Index today versus at the start of the DotCom bubble burst—revealing very little similarity between the two periods, particularly along the dimensions of quality and volatility. The subsequent charts illustrate these differences with the time series of average aggregated feature scores across earnings quality, capital efficiency, and volatility buckets.

These dynamics have helped keep our confidence in the AI opportunity intact. However, the slight detachment in sentiment underscores the need for investment insights capable of looking beyond first-order effects.

For example, we’ve taken a deeper look at the long-run risks of business models being replaced by AI technologies. There is some nuance to this as companies facing redundancy risks could also be reaping the benefits of these technologies near-term. In this way, initial market excitement in response to AI-driven efficiencies and cost savings could eventually turn to skepticism over time. This is becoming more relevant as the eagerness to reward companies based on broad associations with the theme appears to be fading.

To explore potential redundancies, we analyzed ~2,000 unique revenue sources across the economy, using a large language model (LLM) to score their exposure to replacement risks (1: lowest risk of being replaced by AI – 5: highest risk). The histogram in Figure 7 shows the economy-wide distribution of scores, revealing that replacement risks are relatively low overall.

Figure 8 applies this analysis at the sector level. Materials and consumer staples appear the least vulnerable despite often being perceived as relative losers of the AI era given limited potential to benefit from these technologies. They are viewed positively in this context because demand for products is unlikely to be impacted by the progression of AI. In contrast, segments of information technology including software reflect a higher level of risk given AI’s potential to replicate certain tasks. While this is just one of several lenses we apply to the AI theme, it offers a unique perspective as investors focus on companies positioned to deliver tangible long-term results.

Conclusion

The first half of 2024 was characterized by strong equity market returns, muted volatility, and persistent market themes. Now, equity investors are faced with a range of new risks across geopolitics, macroeconomic developments, and weakening AI sentiment.

While we remain net long the AI theme, we have reallocated somewhat in favor of higher duration, more cyclical macro expressions, supported by our dovish duration and inflation outlooks and compelling signs that the equity market has yet to fully price these encouraging developments.

In navigating these evolving dynamics, our diversity of research competencies and breadth of alternative data sources helps us remain nimble and harness new opportunities amid greater uncertainty.

¹ Source: BlackRock as of 4/30/2024.
² Tariff Announcements 2024.
³ White House CHIPS and Science Act Press Release One Year After 2023.

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