Joe Zidle: Optimism and Uncertainty on the Menu
We recently wrapped up one of my favorite annual traditions: the summer Benchmark Lunch series started by my late colleague Byron Wien. Forty years ago, he launched the annual gathering of investors, philanthropists, and policymakers in eastern Long Island. I am humbled and grateful to continue this tradition, now renamed the Byron Wien Memorial Benchmark Lunch series. This year, I moderated three lunches attended by a total of approximately 100 people from July 19 to August 2. This year’s participants included private equity leaders, hedge fund managers, real estate titans, journalists, former government officials, academics, and high-tech venture capitalists.
Inspired by one of Byron’s life lessons, “When you take a new job or responsibility, don’t try to be better… be different,” I added a charitable component to the lunches, raising funds for two charities that were especially important to Byron.
Thank you to my hosts and everyone who attended. As usual, the discussions were insightful and thought-provoking, helping us all to stretch our thinking about topics including the economy, the market, and potential opportunities ahead.
Soft Landing Hopes
There was a sense of optimism about the economy, but that was before the weak jobs report for July triggered the stock market correction. That said, most participants believed that the US economy would avoid a recession in the next 12 months. “The US is the best house in a bad neighborhood” was one memorable quote. The US has enviable economic clout with the largest stock market, deepest pools of capital, a relatively healthy demographic and productivity growth. While they acknowledged slowing growth, many participants cited offsetting positives such as easing financial conditions, the Fed’s commitment to lower rates, and new fiscal stimulus expected in 2025. The recent rise in distressed companies was viewed as idiosyncratic and not systemically important, with defaults remaining below levels consistent with a recession.
By the last lunch, the Sahm Rule Recession Indicator had been triggered. Those optimistic about the economy noted that the rising unemployment rate was due to over 1 million people entering the labor force this year. They pointed out that historically the Sahm Indicator trips due to peak employment. Although the pace of hiring slowed, layoffs outside the tech sector remained very low.
Flat Markets
The group’s outlook on markets was subdued. When asked whether the S&P 500 would be higher or lower in the next 12 months, responses were mixed. The most common answer was unchanged from current levels with half of the attendees thinking the market would be down 0–10%, and the other half thinking it would be up 0–10%. In recent years, the dispersion of responses was wider and generally more bearish, particularly during the COVID years.
The last lunch occurred during the violent pullback from August 2–5, when global markets fell sharply and the Magnificent 7 collectively shed $944 billion in market cap, greater than the market cap of Denmark.1 Despite the selloff, the group was not any more bearish than participants from the two prior lunches. Small caps and value stocks remained out of favor, while large caps and growth stocks were preferred. Concerns about companies thriving in an environment where they finance growth at higher rates drove the preference, as large-cap and growth stocks have higher margins, stronger growth prospects, and less debt.
Most Compelling Opportunities
Some of the more adventurous bottom-up stock pickers in the group saw generational opportunities among out-of-favor small and mid-caps. Valuations outside of the Mag 7 are at attractive levels, with the S&P Small Cap 600 Index trailing P/E currently at the 17th percentile of observations since its inception in 1994, and flows remain almost non-existent.2 Interestingly, few identified Japanese equities or European companies as opportunities, perhaps representing a contrarian sign.
Private credit remains attractive as higher-quality companies benefited from earnings growth and deleveraging. While non-accruals have increased from their low of 0.9% to 1.5%, they remain well below their long-term average of 2.2%.3 Though viewed as a relatively “new” asset class, participants pointed out how direct lending existed within banks for years before the industry was spun out; it is an asset class that has been tested throughout different cycles.
The recent sale of Midtown Manhattan office building 135 W. 50th was highlighted by some participants as evidence that a clearing price is being formed in commercial office in selected markets. Built in 1963, the 23-story building with a 35% occupancy rate, one of the lowest in Manhattan for its size, sold at a deep discount to its last sale price.4 Several participants thought that transaction activity would pick up.
AI’s Evolution
Our lunches featured experts in the AI space, conversations that had attendees mesmerized. AI is progressing, though not as quickly as anticipated a year ago. Participants were careful to separate stock prices from the benefits that AI can deliver. The analogy that resonated most was the 1990s tech boom. From 1996–1999, the Nasdaq rallied by a significant 287% before the enthusiasm for tech stocks morphed into a bubble.5 Although the internet’s transformative potential was clear, it took longer to realize. The 90s tech boom needed a catalyst, which finally arrived with the 2006 introduction of the iPhone, which brought the internet to people’s fingertips.
Will history repeat? In some ways, it could. OpenAI has seen the fastest adoption of any modern technology, but for most people AI is still a curiosity.6 For AI to reach ubiquity requires unprecedented investment in its related infrastructure. One attendee quoted Google CEO Sundar Picchai who insightfully noted that “the risk of under investment is much higher than the risk of over investment.” Another participant likened it to building the railroad or electricity networks. A key difference between today’s infrastructure investment and the pioneering tech companies of the 90s is profits. In 1999, the largest tech companies by market cap were valued based on eyeballs and clicks, not profits. Today, real cash flow and profits are the basis for these companies’ valuation. The ten largest tech companies currently exhibit a return on equity (ROE) three times higher than their counterparts at the height of the tech bubble.7
We had a mix of public and private investors weighing in on AI opportunities. Data centers and their ecosystems, including power, services, and maintenance, were the most discussed opportunities. Participants highlighted the commodity-intensive nature of AI, which is expected to drive a secondary bull market for metals heavily used in data center components and semiconductor chips, such as copper. Seen as an enabling technology, companies that can deploy AI to boost productivity can outperform their peers lacking a plan. The bigger public players benefit from massive economies of scale.
Also, experts highlighted the convergence of AI, biotechnology, and life sciences as one of the most promising fields for innovation. AI will be able to significantly narrow down potential solutions and outcomes, allowing scientists to conduct research with greater efficiency and accuracy.
The Election and Fiscal Policy
The winds changed quickly on the election. We asked the group who they think will win, not who they want to win. Participants at the first lunch, which occurred while President Biden was still running for re-election, picked former President Trump to win unanimously. The second lunch took place after Vice President Harris became the presumptive nominee, and participants by a 2–1 margin predicted a Trump win. By the third lunch, after Trump’s interview at the National Association of Black Journalists convention, the group was split 50/50 between Trump and Harris.
Participants expressed concern about the fiscal deficit and that the US is on an unsustainable spending path. How long the market tolerates this irresponsible behavior is in question. Yes, the US has a structural advantage with its position as a reserve currency and the depth and liquidity of the treasury market. But prudent fiscal and economic policy matters for economic growth and competitive advantage.
Experienced tech venture capitalists provided AI as an example. Just a few years ago, the US lagged behind China in AI development. However, the US fostered a culture of creativity and innovation, leading American tech companies to leverage human input to enhance AI capabilities. ChatGPT is a notable example. As tech founders ramped up capex, the US swiftly transitioned from being perceived as losers to winners in the AI race.
Adding It Up
I’m often asked, “How accurate are the group’s predictions at the lunches?” Here, I would say the track record is mixed. On long-range issues, the conversations are incredibly insightful. For example, we’ve been discussing the potential of AI to revolutionize various parts of the economy for several years now, with life sciences, drug development, and healthcare viewed as the tip of AI the spear. I’m convinced that the group will be right. But the accuracy on the direction of the market or the 10-year Treasury yield in the next 12 months? Historically, successful short-term predictions are a bit more difficult to come by.
In 1934’s “Security Analysis”, famed investor Benjamin Graham writes, “In the short run, the market is a voting machine, wherein countless individuals register choices which are partly of reason and partly of emotion…but in the long run, it is a weighing machine.” Graham perfectly illustrates the tension between cyclical volatility and secular fundamentals. While I wouldn’t bet against any of the attendees in the long run, the collective behavior of markets in the short term can outweigh even the most principled investor.
- Bloomberg, as of August 6, 2024. Based on the change in market cap of the Bloomberg Magnificent Seven Index from close of August 1 to August 5, 2024.
- Standard & Poor’s, Bloomberg, as of August 6, 2024.
- New York Times, as of August 1, 2024.
- Cliffwater, as of December 31, 2023. Non-accruals represent Cliffwater Direct Lending Index, as of December 31, 2023. Non-accruals reached a low on March 31, 2022. Long-term average non-accrual rate spans 16.5 years since Cliffwater has calculated this data.
- Nasdaq, based on annual price returns from December 31, 1995 to December 31, 1999.
- Digital Information World, as of January 17, 2023. Based on time to acquire 1 million users.
- Bloomberg, Standard & Poor’s, as of August 6, 2024. Based on the top ten “tech” companies (information technology and communication services GICS sectors) of the S&P 500 annual filings in 1999 and 2023.
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