Lyft Inc. filed the prospectus for its initial public offering on Friday, and it reads like the standard prospectus for an initial public offering of a certain kind of modern technology company. The foundational text of this genre is probably Facebook Inc.’s IPO, when Mark Zuckerberg wrote a letter to shareholders that began “Facebook was not originally created to be a company. It was built to accomplish a social mission – to make the world more open and connected.”
Lyft, too, focuses on mission rather than business. The first page of Lyft’s prospectus is a big pink slide saying “Our mission: Improve people’s lives with the world’s best transportation.” Is there a letter from the founders? Oh boy is there a letter from the founders. Its headline is “Our Life’s Work,” and it begins “It’s time to redesign our cities around people, not cars,” a counterintuitive slogan for a company that, uh, sells car rides. “The Y in Lyft” is a section header: “The why in what Lyft is doing is most important to us, as well as the cities and communities we serve, and it will always be our company’s North Star.” That sort of thing.
Focusing on this stuff has a few obvious advantages. For one thing, it draws a contrast between Lyft and its main competitor (in the U.S. rideshare industry, and in the 2019 rideshare IPO race), Uber Technologies Inc. “Lyft Wants Investors to Know It’s the ‘Better Boyfriend,’” says Bloomberg News: Lyft has staked out a position as the nice and woke alternative to Uber, and it picked up market share in 2017 due to Uber’s string of scandals. “Consumers, especially millennials, are gravitating towards brands that value community engagement and embrace social and environmental responsibility,” says Lyft’s prospectus, making the business case for its broader-than-business focus.
For another thing, if your IPO is about improving people’s lives and redesigning cities, and not about selling car rides, then it’s easier to look past the fact that you don’t make money selling car rides. Lyft loses money every year, and as my Bloomberg Opinion colleague Shira Ovide notes, “This is a company that doesn’t have to spend to produce a physical product yet has the gross margins of a clothing retailer.” But it’s got a mission. I suppose it helps that Facebook went public declaring that it was driven by mission rather than business, and has been a gusher of money ever since.
It also helps justify Lyft’s dual-class share structure, in which the co-founders will have Class B shares with 20 votes, while the public buys Class A shares with one vote, ensuring that the founders can control Lyft until they die despite owning a minority of the economic interest. Dual-class structures make sense for companies that have social missions distinct from near-term shareholder value: If the company has to choose between redesigning cities around people and making more money selling car rides, the public shareholders will presumably want option B, and only the wisdom and concentrated voting power of the mission-driven founders will be able to preserve Lyft’s long-term vision. It’s all a little boring, honestly, and it mostly makes me look forward to Uber’s prospectus. Uber has become nicer under its new chief executive officer, and I suppose a certain amount of missionary guff is now mandatory in a big tech IPO prospectus, but still I hope that Uber’s IPO might strip a lot of this away. Uber does have a founding vision, but it’s not about cities or communities or people; it’s a vision of free-market absolutism with a lot of Ayn Rand. The symbol most identified with Lyft is a big pink mustache on the front of its cars; the symbol most identified with Uber is surge pricing during emergencies. Uber’s vision comes from its charismatic founder, but the company is not structured around perpetual founder control: It doesn’t have dual-class stock (now), and in fact it chucked out its founder in 2017 because he was getting in the way of his own vision. Oh sure Uber loses money, but that’s not because it is rebuilding cities around people or anything; if it ever has to choose between making more money for shareholders and pursuing some grand social goal, Uber will clearly go for the money. I hope its prospectus just says that. I hope it’s like “our mission is to build an app that connects drivers with passengers and takes a cut of the money, and our vision is to take a bigger cut of more money.” I hope instead of a founder letter it just reprints that Howard Roark courtroom speech.

Did Bill Gross generate alpha?

Well, and what if he didn’t? What is “alpha”? Often you read that alpha is an investment manager’s return above a benchmark—if the S&P 500 returns 10 percent and a stock manager returns 12 percent, he has added 2 percentage points of alpha—but academics and allocators tend to take a stricter view. If he just bought riskier stocks to get that extra return, that’s not really alpha; he’s not demonstrating any extra skill or “really” outperforming the market. One stricter approach goes something like this:
  1. Look at the manager’s returns over time, and get a rough sense of what he actually did to get those returns.
  2. Construct some smallish number of mechanical investing strategies that are sort of similar to what he actually did. These strategies could be as simple as “buy all the stocks in the S&P 500 index” or as complicated as “use an optimal trend-following strategy of buying lookback straddles”; they could involve a passive buy-and-hold approach or constant trading; but the point is that they can be totally specified in advance and a fairly simple robot could carry them out.
  3. See how much of the manager’s actual performance could be explained by those mechanical strategies: That is, if you had just replaced the manager with a handful of simple robots programmed to carry out straightforward strategies, how close would the robots have come to his actual performance?
  4. If the robots’ performance looks nothing like the manager’s, then you have just chosen the wrong strategies: If there is little correlation between the mechanical strategies and the manager’s results, then that means that the manager is doing something very different from what the robots are doing, and you have learned nothing.
  5. If the robots’ performance looks a lot like the manager’s—if the correlation is high—but the manager outperformed the robots, then he is adding alpha: He has demonstrated skill that your simple robots can’t match. His strategy is not as simple as “buy all the stocks” or “buy all the stocks with high book values” or “buy all the stocks that went up yesterday” or anything else that you can fully describe in a sentence; his strategy instead involves buying stocks that are good and not stocks that are bad, based on his own mystical intuition or hard work or whatever.
  6. If the robots’ performance looks a lot like the manager’s, but the robots outperformed him, then he has negative alpha. Perhaps this just means that he’s terrible and keeps losing money, but if you’ve come this far that is unlikely to be the explanation. Instead, what is more likely is that he has mostly made money, and has attracted investors and made a name for himself, but the way that he has made money is not primarily through mystical intuition about what stocks to buy. His intuition about what stocks to buy is mostly bad—worse than the robots’ mechanical selection—but his choice of strategies worked out fine.
Another thing that you often read is that alpha is a measure of an investor’s skill, but really it only measures one aspect of that skill. Making a big levered indiscriminate bet on stocks adds no alpha and arguably, in the narrow sense, requires no “skill,” since a simple robot could replicate it. But if you make a big levered indiscriminate bet on stocks right before a long bull market in stocks, you will get rich and your investors will get rich and it is all much better than the alternative. You could have made a big levered indiscriminate bet against stocks at the same time, and your alpha would be the same (zero), but that would be worse. Anyway here is a fun paper from (Bloomberg Opinion contributor) Aaron Brown and Richard Dewey about “Bill Gross’ Alpha: The King Versus the Oracle.” (It follows in the footsteps of a famous paper about Warren Buffett’s alpha.) They start from what recently retired “Bond King” Bill Gross actually said about his strategy:
Gross, like Buffett, often publicly discussed what he perceives as the drivers of his returns. At the Morningstar Conference in 2014 and in a 2005 paper titled “Consistent Alpha Generation Through Structure” Gross highlighted three factors behind his returns: more credit risk than his benchmark, more 5-year and less 30-year exposure and long mortgages and other securities with negative convexity.
And so Brown and Dewey break Gross’s strategy down into those three factors, plus an interest-rates factor, and find that they are highly correlated to Gross’s performance: A set of robots that bought 10-year Treasuries (for interest-rate exposure), a corporate bond index (for credit exposure), mortgage-backed securities (for negative convexity) and a 5s/30s steepener trade (long 5-year Treasuries and short 30-year Treasuries) would get pretty close to Gross’s returns. Correlated, but lower. Gross did significantly better than the robots: “The regression suggests Gross had annualized alpha of 0.84% after fees,” which, in bond investing, is pretty good. But the interest in the paper is maybe less in the measurement of Gross’s alpha than in the discussion of what it would mean if he didn’t have alpha. There is the theoretical answer: Some factors seem to represent genuine risk factors, meaning that Gross took greater risk to get greater returns. They write:
Two of the factors we will use to explain PIMCO TR return above benchmark are credit risk and short volatility. Most fixed-income investors care about these exposures. One reason is these factors usually give small positive returns, and inflict occasional large losses, typically at the most painful times, a return pattern investors dislike. Another reason is that it is hard to evaluate the amount of left-tail risk in these strategies. … If we find Gross has no alpha after adjusting for exposures to the market plus the first two factors, or perhaps all three factors, we would be saying his historical track record is not one most investors should find attractive.
“Just take a lot of credit risk” is not obviously good for investors; it got an above-market return during the period when Bill Gross ran Pimco’s Total Return fund, but it gets a higher return for a reason (it is riskier) and some investors might not like that. Nor does getting a higher return by taking higher risk necessarily demonstrate skill. (The third factor—the 5s/30s trade—is more ambiguous; they write that “the most likely reason for this strategy to carry a return premium is leverage aversion among investors,” and that “some investors might care that Gross achieved some of his returns by using leverage, others might not.” It might not actually add risk.)
But there are other things that go into investment-manager skill. Brown and Dewey note that Gross certainly had a lot of skills: “He acquired investors and leverage, he ran his fund efficiently, he stuck with his high-risk principles even when they were going through bad periods, and he communicated so that his investors not only stuck with him, but gave him the funds to build the largest bond fund in the world.” And:
We want to make clear that even if Gross’s performance can be explained in some, or even in large part by these factors, that this should not undermine his accomplishments as an investor. Gross’ ability to stick to these strategies, identify low cost and consistent sources of leverage and effectively communicate his strategy to a dedicated investor base is impressive.
It is easy to say, as an academic matter, that just leveraging up your fund to take more risk than the market doesn’t demonstrate skill. But try going out and selling that to investors! The point here is that, in evaluating the skills of an investment manager, you have to ask whose perspective you are taking. From the investor’s perspective, skill means something like “providing an above-market return without exposing me to risks I don’t want,” something similar to, though not necessarily identical with, alpha. From the manager’s perspective, though, skill is broader and more nebulous. If you are making investors happy—by providing alpha, or by providing above-market returns without alpha, or just by writing really good investor letters while losing money—then that is the skill you really need.


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