The Power of Information in Venture Capitalism
Featuring Josh Wolfe and Michael Green
Published on: July 10th, 2019 • Duration: 16 minutesJosh Wolfe, CEO of Lux Capital, joins Michael Green of Thiel Macro to discuss the power of information asymmetry in venture capital markets. Institutions like SoftBank have been making big bets based on that information asymmetry, and appear to be cashing in for now. But Wolfe warns that the unprecedented levels of investment combined with the binary nature of success in venture capital markets could lead to unexpected losses. This clip is excerpted from a video published on Real Vision on March 15, 2019 entitled “Robotics Success and VC Madness.”
JOSH WOLFE: Does it really matter if we're negotiating here and quibbling over $1 billion or $2 billion? Well, of course, it does, but that I think induced a lot of growth investors to say, let's just try to speculate on some of these big unicorns.
Going back 7 years or so, Andreessen- who I think is a brilliant investor, a brilliant technologist- basically said, there's only 10 companies that matter in a given year. And statistically, that's probably true. Now knowing which 10 is very hard, but he said, you just basically want to be in those companies. And I that was a meme that really went very wide. And people said, okay, well, it doesn't matter if you invest in Facebook at $1 billion, or $5 billion, or $10 billion because we're going to be hundreds of billions.
And so does it really matter if we're negotiating here and quibbling over $1 billion or $2 billion? Well, of course, it does, but that I think induced a lot of growth investors to say, let's just try to speculate on some of these big unicorns. And you've got this phenomenon of companies that were pining to signal that they were going to be that next Facebook by attaining a billion-dollar valuation. And then you got a positive feedback effect where people were funding these things, and to get access, would write a $100 million check at a $900 million pre. And they would own 10% in a billion-dollar valuation.
And the problem for the early-stage investors and their limited partners is they were getting these huge markups. And on paper, it looked phenomenal. And then they would go out and raise their next fund and put it into more illiquid companies. But they weren't necessarily getting liquidity on that billion-dollar company. And you have started to see over the past 3 or 4 years, a lot of these unicorns not go from $1 billion to $800 million. They've gone from $1 billion or $2 billion to 0.
And so there's this liquidity trap that is natural in markets because people are basically taking massive amounts of capital, which in the venture world, there's a capital structure just like in the traditional public markets. And you have common equity, which sits on the bottom of the stack, and then preferred, and then debt on top. When you have preferred equity of a size that is so large, and with it, might have the classic Carl Icahn, your price, my terms. So
SoftBank would come in, for example- we could talk a bit about them- and say, sure, we'll give you $20 million, and we want to own 20% at a billion-dollar valuation, and we want a 2X or 3X liquidation preference. Now, you're talking about a payout where if they actually got sold for $1 billion, SoftBank is not getting 20% of that. They're getting $600 million. And so all the people below the stack, that might be okay because you're really actually getting your percentage of a $400 million distribution in a waterfall, but what if it's only $400 million or $500 million? You're getting nothing.
So the presence of SoftBank coming in and basically said, you know what? We're going to do this in a huge way. And combination of Saudi money, and others, and complex debt structure, started basically becoming in a relatively- not relatively- in an absolutely inefficient market, the top-tick price setter. And suddenly, they were writing these large checks, owning very large pieces of companies at extraordinary valuations, setting comps that other people would reference, while SoftBank just did that as though they would fund the other.
They would publicly come out and do these Solomonic baby splits, right? We're going to go to California and we're going to invest in either Lyft or Uber. Fight it out because we're going to king-make one. It's my view that- and this is a borderline tinfoil conspiracy theory- I think that part of what's going on is SoftBank is investing in companies that they know that they will be able to inflate the value of later on. You saw this with We Work. First investing at around $10 billion valuation, then $20- basically, pricing up the deal themselves.
And when you looked at the earnings release, either a quarter or two ago, most of the profits that SoftBank was able to show on paper were from the write-ups of their equity holdings. So I believe that a lot of the activity is done not just because they think they can make money- although I'm sure that's true- but because they believe that it will serve as collateral against a massively indebted mothership parent company. And so that has absolutely distorted the venture market. And we have warned our companies, unless you and we are getting liquidity in one of these monster rounds, you're basically taking the risk that you're going to be holding zombie shares. And I think that there will be a rude awakening for a lot of people that that's the case.
Now, it has attracted other people who are providing capital as alternatives to SoftBank. And so you have crossover funds and you have really smart groups. We have Tiger- who has absolutely killed it in a really smart way- Viking, and Coatue, and others that are writing $100 million plus checks. They do have the public market savviness and understand what the comps are. They are generally value-add. In the case of Auris, all those groups that came in were super helpful. But it's a very dangerous phenomenon where you have huge amounts of money coming in at huge valuations on what are still largely unprofitable binary outcomes.
MICHAEL GREEN: Well, so those companies hit on two separate issues. One is at minimum in a Minsky-type framework, they're speculative finance. They rely on the capital markets remaining open in order to cover their costs and service their existing levels of debt. At worst case scenario, they have Ponzi-like aspects, which is in order to keep going, they need to keep raising more money. The second component though that you're describing when you talk about these types of preference rates is you're creating waterfall characteristics similar to a securitized debt stack.
JOSH WOLFE: The structure of the payout.
MICHAEL GREEN: The structure of the payout is very different depending upon the underlying outcomes. And pricing that is really quite tricky. It's very unclear that anyone involved is actually making the type of calculated analysis that says, well, I have an option that suddenly has very different components.
JOSH WOLFE: I actually think that there is a very sophisticated step- there's just three steps. The first step is the finger in the air. The second is to the tongue, and then the third is to put it in the air.
MICHAEL GREEN: To put it up, yeah. Yeah, it's a highly efficient temperature gauge. I think that's right. And that would largely argue that most of the participants in the venture space are not by experience equipped to do that type of calculation- understanding the option components.
JOSH WOLFE: To be fair, Auris from a $20 million pre to a $5.75 billion exit-
MICHAEL GREEN: Oh, sure, pick on something that worked.
JOSH WOLFE: -I didn't look at a single spreadsheet- not a single one. We didn't model anything. It was literally we're backing a team. They're developing a technology. We think it's going to be relevant to this market. And if you would've told me that it would've been sold for $3 billion, or $8 billion, or $4 billion- like we had no conception of what that range could actually be.
MICHAEL GREEN: So that's traditional venture capital. And that's obviously meant as a compliment. But when you start making an observation about a historical distribution of payouts, and then change your behavior based on that historical distribution of payouts, what you're actually doing is changing the future distribution of payouts- i.e. Marc Andreessen's observation was correct as it described the history of venture capital. But by choosing to act on it and act on it as a scale enough agent- and SoftBank obviously is even larger in this context- but by acting on it as a scale agent, you've changed the future distribution. You won't know that until you observe the outcomes.
JOSH WOLFE: I think you've skewed the probabilities lower. Just by definition, the more people that are chasing things, the greater the competition. Now, if you have these layers in the public markets where there were pools of capital that were voracious to be buyers of IPOs, then you would see this flood of IPOs, like we saw in the late '90s and early 2000. You don't see that today. Now for a variety of reasons, the narrative is to stay private for longer, control.
But I think you're absolutely right that by making the observation that there's a handful of companies that mattered and the price that you paid didn't, it attracted a flood of capital. But that flood of capital, I believe is going to end up with a lot of donuts.
MICHAEL GREEN: I think that's correct. And I think the challenge is that there is a feedback loop as you go through that process. So exactly as you highlight with SoftBank, where they're able to write up their investments and show profits, that in turn is then it would be presented to investors and say, hey, look how stable this process is or how profitable it is.
JOSH WOLFE: Which induces more capital.
MICHAEL GREEN: Which induces more capital to come in.
JOSH WOLFE: It's very dangerous. It is, in a sense, like a Minsky cycle.
MICHAEL GREEN: It's absolutely a Minsky cycle. The challenge on all of this though is that in a world that is dominated by empirical finance, which is the historical returns are the only fact pattern, the future returns are your opinion and my opinion. Particularly in that process of migration where more pools of capital are coming in, raising the valuations, improving the returns, you can look like a fool- a complete Cassandra- arguing that this is bad in the future because the immediate history is going to tell you the exact opposite.
JOSH WOLFE: And the analogies between the history in public markets, which I try to study a lot- not anywhere near as well as you. I learn way more from you than I do from any of my venture brethren when it comes to capital markets. And you compare that to the venture world. There are really ends of ones in venture. Like looking at comparables, in 1997, you would have been an idiot- or '98- you would have been an idiot for saying, who the hell needs another search engine, only to miss Google. But then once you see the presence of Google, you would've been an idiot to try to fund the next 10 Lycoses or whatever it was.
And so it's very hard because you have these aberrant outcomes. They are total anomalies, and then people try to learn from these things. And it's just it's way different. And I would actually argue that the reason it's different is because you do not have the kind of information that is conveyed through price discovery in traditional markets. You do not have the number of really smart people that are looking at a security, analyzing its history, looking at the fundamentals, debating it, being long it, being short it. The absence of that kind of relative efficiency is totally missing in venture.
And so you also get, which you don't typically get in the public markets as much, massive dislocations between bids and ask in pricing events. So the step-ups that we see in seed stage round can be 10X into a Series A. Now, the scale of what you're talking, you might be putting a few $100,000, or a few million dollars in it, a few million dollar valuation, and then you might be raising $20 or $30 million at a $50 million valuation, then $100 million at $1 billion. The gaps- the discontinuities between those is huge.
Now, liquidity is one form of that- this sort of asymmetry of information, but it starts before conception or inception of a company. And there's information asymmetries all the way. And you could argue that they get reduced over time. But the first information asymmetry, like the maximum information asymmetry, is with the invention that a scientist has. And there's this quote from Linus Pauling, a Nobel Laureate, who said, I know something that nobody else in the world knows. And they won't know it until I tell them. That is the ultimate power in the world- to know a secret that soon, the rest of the world will know, but you're the only one that knows it. So that's maximum information asymmetry.
The next is, okay, now, the scientist has teamed with an entrepreneur. Now, the entrepreneur might have asymmetry because not a lot of other people know about it or they've befriended the scientist and they started the company. But then the entrepreneur has an asymmetry of both a false positive and maybe a true positive, which is their estimation of their ability. Almost all entrepreneurs believe that they are more valuable than the market thinks they are. Because if the market thought that they were-
MICHAEL GREEN: Most teenagers as well.
JOSH WOLFE: And by the way, the disposition are the same. They throw tantrums. They seem like they're drunk. You don't know if you should trust them with money. The entrepreneur, if they felt fairly valued by the market, would go and just join a consulting firm- a McKinsey. But they say, no, either because they were rejected, and they say, no, I'm going to go do it myself.
And so to do something entrepreneurial, in a sense, is to have an overestimation of the thing that you know or think you know that the rest of the world doesn't. Now 90% roughly, let's just say, failure means that 10% of those people are actually right or lucky. And maybe some of them are right and unlucky. So that's the next asymmetry- the entrepreneur who thinks that they know something or maybe does, in fact, know something the rest of the world doesn't.
Then the next stage is the investor. So now, we come along and we meet the engineer or the Fred Moll. And we think, okay, wait a second. We're early here. We've got something that nobody else knows. And so we jump on that. And that's really, it is the same phenomenon as the teenager who is discovering the band that nobody else knows about yet- the book, or the movie, or the artist that is going to impart on them social currency because they have discovered the thing that everybody else is going to celebrate later. There's no difference.
So for us, it isn't an Excel spreadsheet. It's not a model. It's like based on the market, and the understanding we have, and the marketability of this entrepreneur, and their ability to raise money, and recruit people and convince them to part with their jobs and move across the country and join them. Do we think that these guys and girls are going to be really valuable? It's a total qualitative psychological judgment.
So now, we're in the first few board meetings. And we know everything that's going on in the company, or let's say, 80% of what's going on in the company. And if you have a good relationship with the CEO, you know a lot more. And if you don't, then they hide things from you. But now, a new investor comes in. And so, let's say, we've invested in this case, like in Auris a $20 million pre, and then Peter Thiel comes in at 80 or whatever it is.
Does Peter know more than we do? Now, maybe he knows something about the market that we don't know or maybe he has an unfair access to be able to make introductions that are going to create value by reducing risk. But there's very improbable chance that a new investor knows more about what is happening in the company than an existing investor. So now, we have asymmetry of information.
And so it's very different than public markets where you might have different preferences in time, or liquidity, or expected return. The information asymmetry starting from that scientist to the entrepreneur to the first funders to the later funders is just enormous. Over time, I think it starts to reduce. And then ultimately, you're going to the public markets. And the public markets are saying, well, we demand to be able to look at the books, and understand, and how this compares to comps, and how it's going to be valued, and what are our estimation is and how other public market investors are going to value it.
And then you start to get more and more scrutiny. And scrutiny, I think ultimately creates liquidity and it creates markets because you have more information. So that information asymmetry is where most of the returns on venture come from, and being able to identify people early, develop a reputation so that you can attract the next entrepreneur who believes that they might be like your last entrepreneur, and have a reputation for being a good actor with other investors, and not being zero-sum knowing that this is a long game. And otherwise, I think it's an asset class that, frustratingly for us as insiders and definitively for outsiders, is really dominated by luck.