In public investing, I have argued that this plays out in whether you choose to play the value game (invest in assets where the price < value and hope that the market corrects) or the pricing game (where you trade assets, buying at a lower price and hoping to sell at a higher).  I would be glad to be offered evidence to the contrary but based upon the many VC “valuations” that I have seen, VCs almost always play the pricing game, when attaching numbers to companies, and there are four ways in which they seem to do it:

  1. Recent pricing of the same company: In the most limited version of this game, a prospective investor in a private business looks at what investors in prior rounds have priced the company to gauge whether they are getting a reasonable price. Thus, for an Uber, this would imply that a pricing close to the $62.5 billion that the Saudi Sovereign fund priced the company at, when it invested $3.5 billion in June 2016, will become your benchmark for a reasonable price, if you are investing close to that date. The dangers in doing this are numerous and include not only the possibility of a pricing mistake spiraling up or down but also the problems with extrapolating to the value of a company from a VC investment in it.
  2. Pricing of “similar” private companies: In a slightly more expanded version of this process, you would look at what investors are paying for similar companies in the “same space” (with all of the subjective judgments of what comprises “similar” and “same space”), scale this price to revenues, or lacking that, a common metric for that space, and price your company. Staying in the ride sharing space, you could price Lyft, based upon the most recent Uber transaction, by scaling the pricing of the company to its revenues (relative to Uber) or to rides or number of cities served.
  3. Pricing of public companies, with post-value adjustments: In the rare cases where a private business has enough operating substance today, in the form of revenues or even earnings, in a space where there are public companies, you could use the pricing of public companies as your basis for pricing private businesses. Thus, if your private business is in the gaming business and has $100 million in revenues and publicly traded companies in that business trade at 2.5 times revenues, your estimated value would be $250 million. That value, though, assumes that you are liquid (as publicly companies tend to be) and held by investors who can spread their risks (across portfolios). Consequently, a discount for lack of liquidity and perhaps diversification is applied, though the magnitude (20%, 30% or more) is one of the tougher numbers to estimate and justify in practice.
  4. Forward pricing: The problem with young start-ups is that operating metrics (even raw ones like riders, users or downloads) are often either non-existent or too small to be base a pricing. To get numbers of any substance, you often have to forecast out the metrics two, three or five years out and then apply a pricing multiple to these numbers. The forecasted metric can be earnings, or if that still is ephermal, it can be revenues, and the pricing multiple can be obtained not just from private transactions but from the public market (by looking at companies that have gone public). That forward value has to be brought back to today and to do so, venture capitalists use a target rate of return. While this target rate of return plays the same mechanical role that a discount rate in a DCF does, that is where the resemblance ends. Unlike a discount rate, a number designed to incorporate the risk in the expected cash flows for a going concern, a target rate of return incorporates not just conventional going-concern risk but also survival risk (since many young companies don’t make it) and the fear of dilution (a logical consequence of the cash burn at young companies) and becomes a negotiating tool. Even the occasional VC intrinsic value (taking the form of a DCF) is a forward pricing in disguise, with the terminal value being estimated using a multiple on that year’s earnings or revenues.
    At the time of a VC investment, the VC wants to push today’s pricing for the company lower, so that he or she can get a greater share of the equity for a given investment in the company. Subsequent to the investment, the VC will want the pricing to go higher for two reasons. First, it makes the unrealized returns on the VC portfolio a much more attractive number. Second, it also means that any subsequent equity capital raised will dilute the VC’s ownership stake less. If you reading this as a criticism of how venture capitalists attach numbers to companies, you are misreading it because I think that this is exactly what venture capitalists should be doing, given how success is measured in the business. This is a business where you are measured less on the quality of the companies that you build (in terms of the cash flows and profits they generate) and more on the price you paid to get into the business and the price at which you exit this business, with that exit coming from either an IPO or a sale. Consequently, how much you are willing to pay for something becomes a process of judging what you will get when you exit and working backwards.
But Venture Capitalists have a data problem
It is not just venture capitalists who play the pricing game. As I have argued before, most investors in public markets (including many who call themselves value investors) are also in the pricing game, though they use pricing metrics of longer standing (from PE to EV/EBITDA) and have larger samples of public traded firms as comparable firms. The challenges with adapting this pricing game to venture capital investments are primarily statistical:
  1. Small Samples: If your pricing is based upon other private company investments, your sample sizes will tend to be much smaller, if you are a VC than if you a public company investor. Thus, as an investor in a publicly traded oil company, I can draw on 351 publicly traded firms in the US or even the 1029 publicly traded companies globally, when making relative value or pricing judgments. A VC investor pricing a ride sharing company is drawing on a sample of less than ten ride sharing firms globally.
  2. With Infrequent Updating: The small sample problem is exacerbated by the fact that unlike public companies, where trading is frequent and prices get updated for most of the companies in my sample almost continuously, private company transactions are few and far between. In many ways, the VC pricing problem is closer to the real estate pricing than conventional stock pricing, where you have to price a property based upon similar properties that have sold in the recent past.
  3. And Opaque transactions: There is a third problem that makes VC pricing complicated. Unlike public equities, where a share of stock is (for the most part) like any other share of stock and the total market value is the share price times number of shares outstanding, extrapolating from a VC investment for a share in a company to the overall value of equity can be and often is complicated. Why? As I noted in an earlier post on unicorn valuations, the VC investment at each stage of capital-raising is structured differently, with a myriad of options embedded in it, some designed for protection (against dilution and future equity rounds) and some for opportunity (allowing future investments at favorable prices). As I noted in that post, a start-up with a “true” value of $750 million can structure an investment, where the VC pays $50 million (instead of $37.5 million) for 5% of the company, by adding enough optionality to the investment. I may be misreading Scott’s section on using option pricing to price VC investments, but if I am reading it right, I think Scott is saying that Andreessen uses option pricing models to clean up for the add-on options in VC investments to get to the fair value. Put differently, Andreessen would put a value of $750 million on this company rather than the $1 billion that you would get from extrapolating from the $50 million for 5%.
I am sure that nothing that I have said here is new to venture capitalists, founders and those close to the VC process, but it is the subtle differences that throw off those whose primary experience is in the public markets. That is one reason that public investors should take the numbers that are often bandied about as valuations of private companies (like Palantir, Uber and Airbnb) with a grain of salt.  It is also why I think that public investors like mutual funds and university endowment funds should either tread lightly or not all in the space. Even within the VC business, it is sometimes easy, especially in buoyant times to forget how much the entire pricing edifice rests as much on momentum and mood, as it does on the underlying fundamentals.
With Predictable Consequences
So, let’s see. VCs price companies and that pricing is often based upon really small samples with infrequently updated and tough-to-read data. The consequences are predictable.
  1. The pricing estimates will have more noise (error) attached to them. The pricing that I obtain for Lyft, based upon the pricing of Uber, Didi Chuxing and GrabTaxi, will have a larger band around the estimate and there is a greater chance that I will eb wrong.
  2. The pricing will be more subjective, since you have the freedom to choose your comparable firms and often can use discretion to adjust for the infrequent data updating and the complexity of equity investments. While that may seem to just be a restatement of the first critique, there is also a much greater potential for bias to enter into the process. Not surprisingly, therefore, not all VC returns are created equal, especially when it comes to the unrealized portion, with more aggressive VCs reporting “higher” returns than less aggressive VCs. That is perhaps the point being made by Scott about realized versus unrealized returns.
  3. The pricing will lag the market: It is a well-established fact that the capital coming into the VC business ebbs and flows across time, with the number of transactions increasing in up market and dropping in down markets. When there is a severe correction (think 2000 or 2009), transactions can come to a standstill, making repricing difficult, if not impossible. If VCs hold off on full repricing until transactions pick up again, there can be a significant lag between when prices drop at young companies and those price drops getting reflected in returns at VC firms.
  4. There is a price feedback loop: Since VC pricing is based upon small samples with infrequent transactions, it is susceptible to feedback loops, where one badly priced transaction (in either direction) can trigger many more badly priced transactions.
  5. And a time horizon issue: The lack of liquidity and small samples that get in the way of pricing holdings also introduce a constraint into the pricing game. Unlike public market investors, where the pricing game can be played in minutes or even fractions of a minute on liquid stocks, private market pricing requires patience and more of it, the younger a company is. Put differently, winning at the VC pricing game may require that you take a position in a young start up and bide your time until you build it up and find someone who will find it attractive enough to offer you a much higher price for it. This is perhaps what Scott was talking about, in his response, when he talked about this being VC investing being a “long” game.

There is one final point that also needs to be made. Much as we like to talk about the VC market and the public market as separate, populated by different species, they are linked at the hip. To the extent that a venture capitalist has to plot an exit, either in an initial public offering or by selling to a publicity traded company, if the public market catches a cold, the venture capital market will get pneumonia.

The VC Edge
If I were to summarize the entire post in a couple of sentences, here is what it would say. Venture capitalists price the companies they invest in, base that pricing on small samples of opaque transactions and the pricing is therefore more likely to be wrong and lag reality. That sounds pretty damning, but I think that it works to their advantage. That may sound contradictory, but here is my basis for making that statement.

  1. On average: Both VC and public market investors play the pricing game, with the latter having the advantage of more and better data, but over time, venture capitalists seem to deliver better results than public market investors, as seen in the graph below. These are raw returns and I do realize that you have to adjust for risk, but some of the biggest risks in venture capital (failure risk) have already been incorporated into long term returns.
    Source: Cambridge Associates
  2. The Elite: The most successful VCs not only earn higher returns than the top decile of public market investors but that there seems to be more consistency in the VC business, insofar as the best of the VCs are able to generate higher returns across longer time periods. That would suggest that they bring more durable competitive advantages to the investing game than public market investors.
How do I reconcile my argument that the VC pricing game is inherently more error-prone and noisy with the fact that VCs seem to make money at it? I think that the very factors that make it so difficult to price and profit of a VC investment are what allow VCs collectively to earn excess returns and the very best VCs to set themselves apart from the rest. In particular, the best in the business set themselves apart from the rest on three dimensions:

  1. They are better pricers (relatively): As Scott notes in his piece, the price that you can attach to a VC investment can vary widely across investors and he uses the example of how Andreessen’s option pricing approach can yield a lower pricing for the same company than an alternative approach. While all of these prices are undoubtedly wrong (because they are estimates), some of them are less wrong than others. Repeating a statement that I have made before, you don’t have to be right to make money, you just have to be less wrong than everyone else and the chances of you doing that are greater in the VC pricing game.
  2. They can influence the pricing game: Unlike public market investors, who for the most part can observe company metrics but not change them, venture capitalists can take a more active role in the companies that they invest in, from informally advising managers to more formal roles as board members, helping them to decide what metrics to focus on, how to improve these metrics and to cash in on them (from an IPO or a sale).
  3. They have better timing: The pricing game is all about timing, and the VC pricing game is more emphatically so. To be successful, you not only have to time your entry into a business right but even more critically, time your exit from it.

If you are an investor in a VC fund, therefore, you should of course look at both realized returns and unrealized returns, but you should also look at how the fund measures its unrealized returns and how it has generated its returns. A realized return that comes primarily from one big hit is clearly less indicative of skill than a return that reflects multiple hits over longer time periods. After all, if separating luck from skill is difficult in the public marketplace, it can become even more so in the venture capital business.

[drizzle][/drizzle]