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
    1, 23  - View Full Page