Whaling & VC, A Common Misunderstanding
Something is often misunderstood regarding the VC and Growth industries. And nothing’s more effective to resolve it than the old case of the whaling industry (to be honest, there may be other comparables perfectly working, but they are way less exotic and fun).
Whaling became a commercial industry in the 16th century as the main operators, from Spain and Iceland, operated around sixty vessels annually. The dominant became the Dutch until the second half of the 18th when the leadership switched to Britain, before the emergence of the United States in the 19th. Tom Nicholas, author of VC an American History explains that “[b]y 1850, almost 75% of the nine hundred whaling ships worldwide were American registered.“
Their advantage came essentially from three factors: a technological advantage, with the redesign of vessels, human capital (with experienced agents, captains and crews) and a new financial mechanism, which consisted basically to give equity to whalemen.
However, the industry was still facing a structural challenge: it was very difficult to predict the likelihood of success. “Consider the famous voyage of the Essex, which inspired Herman Melville’s 1851 fictional masterpiece Moby-Dick. With a track record of success and a reputation as a “lucky ship“, the Essex set sail from Nantucket Island in Massachusetts in August 1819 for the Pacific Ocean on what was expected to be a lucrative whale-hunting venture. In November 1820, on an otherwise uneventful day, an eighty-five-foot sperm whale rammed the ship’s port side when the crew targeted a whale pod. The 238-ton whaleship capsized and sank, leaving the crew members scrambling into three whaleboats with provisions collected from the wreckage. In December 1820, the crew arrived at a deserted island. Some stayed while others headed for the coast of South America, almost three thousand miles away. Those who survived the ravages of the ocean were rescued two months later by whale-hunting ships operating off the coast of Chile.“ Imagine if that wouldn’t be a lucky ship.
Even if entrepreneurs today do not face carry lethal risks faced by whalemen, there are numerous similarities between whaling and tech entrepreneurship, including:
- the structural uncertainty regarding the success of the venture, but also,
- the importance of technology and talents,
- the duration implied (it’s not a short term, liquid bet — one voyage of the whaleship Nile, which set sail from New London in 1859 returned home only eleven years later, a fourteen-months expedition would be considered short, most whaling expeditions lasting more than three years),
- the high upside potential,
- the players (composed of captains/entrepreneurs, whaling agents/VCs, sailors/tech talents, wealthy individuals/LPs)
- the incentives between them (whaling agents/VCs, captains/entrepreneurs & crews/tech talents are all incentivized to the successes by having equity or equivalent).
But let’s get back to our misunderstanding.
Whaling, like venture capital, implies a high level of incertitude indeed. JT Brown in his opus The whalemen, vessels and boats, apparatus and methods of the whale fishery stated that “the profits of the whalemen have for many years been uncertain.“ Faced with the difficulty to predict the outcome of different ventures, the best behaviour is often to transfer a setup of randomness into a setup of plurality. Basically, you do exactly what insurance does. There is an individual risk that is very hard to handle on the individual level, but by aggregating a large number of people, you can predict and manage these risks.
The thing is regarding whaling and venture capital, it’s unclear if that’s a good idea. If you look at aggravated outcomes, the distribution of performance of both the different voyages in whaling and startups within venture capital portfolios looks like a long tail.
It’s very well summarized by Alexander Starbucks, who studied the American whale fishery stated: “While some vessels on their voyage have made but poor returns, even bringing, in numerous cases positive and at time damaging loss to their owners, others have done extraordinarily well, and brought in fortunes to those investing in them.“ Roughly the same comment can be borrowed by Peter Thiel about the heavily skewed distribution of a modern VC: “a small handful of companies radically outperform all others.“ But let’s look at complementary data. If you look at the venture capital returns in the US it’s pretty clear that the asset class is in itself interesting:
What’s happening is that the risks are well handled by the intermediaries (VCs) as a whole, as they shift the individual risk of startups (the heavily skewed distribution shows that even professionals cannot fully remove the risk of failure at the individual level, and this skewed distribution is also observed in Europe) into a situation of plurality within their portfolio.
If we look at more granular data you can see that the distribution of returns at the VC level (comparing this time not the startups but the portfolios), we find once again a very skewed distribution.
The median is lower than the average, implying the same type of skewness coupled with a high standard deviation of performances.
And here comes our misunderstanding.
This long-tail distribution, found in both whaling and VC, leads to two counter-intuitive attributes:
1/ Since the returns of VCs are facing a high standard deviation and its distribution of returns are something very close to a power low, there is a lack of homogeneity in the so-called asset class. This is the reason why, unlike many other financial endeavours investors should not try to diversify their risk too much between several funds because allocating numerous small tickets would lead to a regression to the mean, which will be way lower than the returns from the top tier funds.
2/ Even if the arithmetic means would be negative or just lower than alternative asset classes, it could still make sense to invest in VC and growth. The reason is that you are not betting on average (our previous point) but selecting the best managers. People tend to think that if the expected returns are negative, it would be foolish to play. But what’s true in a situation of pure randomness (if your expected return is below zero you should not play an infinite number of times because you will lose), is not necessarily true when luck isn’t the sole driver — and given the relative stability of returns for the best performing VC & Growth companies (there are continuously new entrants into the cool kids club, but on average the best performing funds tend to do it vintage after vintage, suggesting that the effect of luck is limited).
This is especially true when the distribution of performances is skewed (without entering in technical discussions, option pricing can show you situations where it can make sense to invest in ventures even when the expected utility using a DCF model would advocate staying out of the project). For the sake of fairness, a case has to be made for the opposite situation: it can be a bad idea to play a game where the expected utility is high but where the individual outcome can be undesirable (eg: it might not be a good idea to play a tempting game that statistically makes you rich if the first negative outcome can lead you to personal bankruptcy).
Maybe the thing to keep in mind (remember that these conclusions are selected in a very impartial, almost scientific manner) is that it makes a lot of sense to:
- invest in promising funds (hello!),
- avoid putting one’s eggs in the same basket generally but in the case of VC or whaling to favour putting most eggs in a small number of baskets (hello again!),
And that as investors in funds are a bit the successors of the sponsors of captains of whaleships and VC are a bit like captains successors. That could be a theme evening…
Disclaimer: we are not in any kind favourable to hunting whales
