Lee Ainslie - Founder of Maverick

Good afternoon and welcome to the thirty-seventh Pari Passu newsletter,

Hope you have had a slow end to this short week. Today, we are going to learn more about public equities, in particular, we will learn more from Lee Ainslie, founder of the Tiger Cub Maverick.

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Background

Like most professional investors, Lee developed an interest in stocks early on: he started trading stocks at 13. His professional career reflected that passion turned job. After attending the University of Virginia for an undergraduate degree and receiving an MBA from the University of North Carolina, Lee was hired at Tiger Management.

He talks, as expected, very highly of his experience. Julian Robertson had several talents besides picking stocks, and one of the most important ones was being able to identify talent, an essential skill for a small investment firm. Lee believes that Julian’s ability to pick great talent is what led a lot of the funds that spun off from Tiger to go on and achieve great track records. Regarding his experience at Tiger, Lee highlights two episodes:

The first one relates to the idea of emotional consistency. Lee wrote a memo that technology tends towards standards and he believed that in the database world, Oracle was becoming that standard, and a flywheel impact could have a very beneficial effect. As a result, in '91, Tiger bought a lot of Oracle. Unfortunately, in the next quarter, an earning miss made the stock drop from $11 to $6. There was such stress on the balance sheet, and the company’s ability to survive all of a sudden was brought into question. This led to a challenging discussion with Julian, but Lee did convince him this would be the absolutely wrong time to sell even though Lee felt management had not been fully forthright in certain issues. This turned out to be the right decision as it ended up being a very successful investment. Lee explains how one of the phrases they used to say is: “Hey, we're not playing football, we're playing chess”. Getting round-up and emotional is just really counterproductive.

The second one happened after being under Steve Mandel’s wing for the first few months on the job. Lee went into his year-end review thinking there was a decent chance he was probably about to be let go. But to his surprise, he was paid well beyond expectations. They doubled his percentage interest in the firm's profits and made it very clear, that this is all happening because of Steve's recommendation and indeed, they want me to take over a new sector altogether, technology. Despite being a competitive industry, he believes people are intellectually honest and Steve recommendation was probably in the firm’s interest.

Starting and running Maverick Capital

Lee founded Maverick in 1993 even though he was not looking to leave. Julian was treating him extremely well, both in terms of compensation and responsibility and he loved everybody he worked with.

Sam Wiley, a serial entrepreneur at the time was the CEO of two different public companies, recognized the attractiveness of the hedge fund model and wanted to start one. The management team of the two public companies knew Lee and recommended him and they connected. Lee enjoyed our conversations but made it clear he had absolutely no interest in leaving Tiger but Sam kept making the idea of leaving more and more and more attractive.

At the time, Lee was 28 years old and had only been at Tiger for 3 years. He realized that maybe later he would feel ready to start an investment firm but no one would want to invest in him and Sam was being very generous so Lee decided to leave Tiger. Looking back, he thinks that decision was naive as he did not fully understand the challenge he was getting himself into. Maverick launched with $38 million. The firm had some challenges raising additional capital but then performance took care of things as the firm posted great results from its founding in October ‘93 to ‘96.

Running an investment firm requires 3 jobs: 1) stock picking, 2) managing the portfolio / managing risk, and 3) building the business. Let’s focus on the stock picking part since most of our readers are not too involved with the other two skills (at least for now).

Stock Picking

His background in leading the tech effort at Tiger taught him the value of sustained growth and how challenging it is to sustain growth. As expected he learned from his colleagues at Tiger, in particular, he recalls how Steve was always super focused on the individual unit economics, so Lee developed a better appreciation of that.

It is also important to note that analyzing stocks has totally changed with the development of technology. To get a 10-Q in the ‘90, you would need to use the fax machine. Today, there are many sell-side reports. You could use the internet for days and days and days, there is a lot of discussion about stocks on TV, etc. Something in particular that Lee has done over the year is talking to several different members of management, looking for consistency in answers.

In terms of building a competitive advantage: Maverick typically only has 3/5 investment positions per investment professional, much less than what other funds usually do. This enables a level of due diligence that's quite unusual. In addition, Maverick has much longer holding periods than most long/short funds which allows one to know the management for longer periods of time. On the long side, we average 17 months, on the short side it's 13 months.

In addition, Lee shares what are some of the strategies Maverick has used to achieve the goal of “never be at an informational disadvantage to another public investor.“ One that a lot of readers might be aware of is counting cars in retailers parking lots. Maverick evolved from hiring people to go count to use satellite imagery, but the idea at its core remains the same. Another interesting one revolves around a successful short investment; Maverick ordered something from them once a week only so they could look at the PO number, which told us how many POs they processed in the past week. Talking about getting an edge.

Lee goes on to talk about great management teams and the idea of the fresh sheet of paper exercise. They have the philosophy that given this amount of money to invest today, what is the best way to invest it? If we didn't have any investments, have a fresh sheet of paper, what are we going to do? Okay? So why is the actual portfolio different than that? If that's the ideal portfolio, let's move the actual to the ideal. This is a recurring idea as I remember hearing Paul Enright (former Viking PM) share this same idea. He explained in a slightly different way but the concept is identical. His explanation was that if the portfolio were to be liquidated today and we need to re-buy it, would we buy it exactly how it is or in a different way? If not, why is my portfolio not in my ideal allocation?

Hedge Fund Returns and Interest Rates

We have all heard about arguments that hedge funds do not beat the market so it is interesting to get Lee’s take. Despite people arguing that higher rates favor hedge funds as short rebates are higher, Lee has a different take and he proves this by looking at the HFRI long-short index (the most comprehensive hedge fund index started in 1990) and interest rates.

Since 1990, the Fed funds rates went over 2.5%, 47% of the time. When rates are over 2.5% on average, hedge funds have outperformed the markets by 6.5%, driven by 12% alpha. Under 2.5%, they've underperformed by 4% on the back of less than 1% of alpha. So clearly, higher rates are a more productive environment, but rebates play a tiny role in that. What matters is that capital is very cheap and therefore it's harder to understand which company is making better decisions than the other because every use of capital is a good decision. In recent years, stocks were driven by what the Fed said, not by earnings, leading to a period with very little dispersion.

Software Investing vs Semiconductor / AI Investing

Software investing has dominated public markets over the last decade and Lee provides an interesting comparison with Semiconductors and AI Investing

1. Switching costs:

   1. Software: high; imagine telling your team you are moving from Excel to Google Documents

   2. Semis / AI: low; telling your team to switch from Chat GPT to another AI platform would cause much less problem

2. Capital Intensity:

   1. Software: low; ~90% labor and 10% infrastructure cost

   2. Semis / AI: high; ~10% labor and 90% infrastructure cost

3. Network effects:

   1. Software: high; you use social media because your friends do

   2. Semis / AI: low; you do not care if your friends use Chat GPT or another AI platform

Overall, it is clear that these are very different businesses and we are in front of a revolution that will create new large corporations and destroy some old ones.

Summary

These are some of my notes from Lee’s interview on Invest Like the Best, if you enjoyed this summary I would recommend you check the episode out.

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