Roko Karanusic
Sir Humphrey Appleby: Didn’t you read the Financial Times this morning?Sir Desmond Glazebrook: Never do.
Sir Humphrey Appleby: Well, you’re a banker. Surely you read the Financial Times?
Sir Desmond Glazebrook: Can’t understand it. Full of economic theory.
Sir Humphrey Appleby: Why do you buy it?
Sir Desmond Glazebrook: Oh, you know, it’s part of the uniform. Took me thirty years to understand Keynes’ economics. Then when I’d just cottoned on, everyone started getting hooked on these new monetarist ideas, you know, “I Want To Be Free” by Milton Shulman.
Sir Humphrey Appleby: Milton Friedman.
Sir Desmond Glazebrook: Why are they all called Milton? Anyway, I’ve only got as far as Milton Keynes.
Sir Humphrey Appleby: Maynard Keynes.
Sir Desmond Glazebrook: I’m sure there’s a Milton Keynes.
Sir Humphrey Appleby: Yes, there is, but it’s...
[Humphrey gives up]
as chronicled in “Yes, Minister”, Series 2, Episode 6: "The Quality of Life":
TL;DR
John Maynard Keynes learned the hard way that markets do not reward objective truth as neatly as economists like to think. Prices move not just on facts, but on how people think other people will react to those facts. His “beauty contest” analogy captures the logic well: success comes not from picking what is best, but from picking what others will choose. Venture capital works the same way, often even more so than public markets. VCs may praise contrarianism, but most allocate based on lagging indicators: social proof, visible traction, brand-name co-investors, and categories the market already understands. That is not necessarily because they lack imagination, but because VC is shaped by incentives. The game is not only about returns, but also reputation and fundraising. In that structure, lagging indicators become rational: they help investors coordinate, reduce career risk, satisfy LPs, and mobilise networks. Venture may celebrate originality in theory, but in practice it often rewards what is already legible.
⏱️ 16:31 Est. Reading Time
The Beauty Contest of 1936
For a good while, one had thought that if the facts were clear, if the bigger (macro) picture was understood, and if one excelled at reading the forces shaping the economy better than anyone else, then good investing should follow. And if one was equipped for that kind of investing, it was him. The one in question is John Maynard Keynes, one of the great economic minds of his age, who then was managing an endowment fund for King’s College in Cambridge. Yet, the markets did not award brilliance in the way he expected. In his early years as an investor, his results were respectable at best. From 1924 until 1932, he only slightly outperformed a quite weak UK stock market, a particularity that made the lesson so severe. He undoubtedly had the intellect, information, and a command of macroeconomics that almost nobody on earth could match, and still the markets refused to behave.
So, he realised then, markets were not simply mechanisms for processing only facts, but also machines for processing human behaviour. Prices did not move because reality had been properly understood. They moved because people, in all their fear, greed, excitement, doubt, and imitation, decided to buy or sell. It was the conviction of the masses from the each side of the trade that carried the true force, not the “truth”. A phenomena he coined the term “animal spirits” for; by which he meant the emotional and psychological energy that drives human action, especially under uncertainty. Investors, prone to all the human vices, do not move in straight lines from facts to price.
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Once Keynes comprehended this, his investing changed. After 1932, he moved away from trying to read the world mainly through grand macroeconomic conclusions and became far more interested in individual assets, in value, and above all in how other people were likely to judge value. He no longer treated the market as a machine that should eventually subjugate itself to the facts, but as a social game in which expectations about expectations matter more than the reality itself. His record after that point improved dramatically.
To explain this logic metaphorically, Keynes described the old newspaper beauty contests in which readers were asked to choose the prettiest faces from a large group of photographs. The winner was not the person who picked the faces they personally found the most beautiful. The winner was the one whose choices best matched the choices of the crowd. So, to invest well, you are not simply asking what an asset is worth (or what it could be worth), but you are also asking what others think it is worth (or what it could be worth), and how that chain of perception will turn into action.1
“It is not a case of choosing those (faces) which, to the best of one’s judgment, are really the prettiest, nor even those which average opinions genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be.” — John Maynard Keynes
The same analogy appears, even more clearly, in venture capital and other private markets. Despite venture capitalists being, undoubtedly, better informed and more skilled at allocating resources than the broad masses, they still need to pick the face they think others will choose, not the one they personally found the prettiest. Read: they are not in the game of funding companies with the strongest fundamentals, but the companies most likely to raise the next round, because that is what determines their markup and returns.
Even more so, you could argue that in public markets — where prices eventually do converge to fundamentals due to continuous price discovery, short selling, liquidity, and other factors — the beauty contest is somewhat temporary, while in venture there is no such corrective mechanism. Rounds are infrequent, there’s no shorting, valuations are set by a few negotiators in opaque negotiations, and that “price” is quite literally just whatever the last investor agreed to pay.
By now, one might conclude either that venture capitalists have failed to understand this, or that the industry is populated by semi-independent actors simply deferring to collective consensus. Both conclusions miss the point. Most VCs allocate based on lagging indicators not because they lack the ability to identify leading ones, but because the incentive architecture of venture capital makes backward-looking allocation the individually rational strategy across multiple reinforcing dimensions. The purpose of this article, however, is not to argue that independent thinkers in venture have the wrong strategy (probably the opposite), but to explain why most VCs are simply not structured to behave like them.
Table of Contents
1. Lagging Indicators
2. Consensus Bets Reduce Reputational Risk
3. Network Effects & Coordination Games
4. FOMO & Information Asymmetry
5. Waiting as a Strategy When Downside Is Convex
1. Lagging Indicators
Ever since Peter Thiel’s Zero to One was published in 2014, the venture world has been fascinated by contrarianism: the strategy of investing against prevailing market consensus, betting on unpopular or overlooked ideas that hold the potential for massive, non-linear returns.
It was a direct challenge to the dominant venture habit of pattern-matching, which is inherently backward-looking. Thiel’s point, one I fully agree with, was simple: there is no new Airbnb. There is no new Uber. Those companies did not become iconic by resembling what came before them, but by building something genuinely new.
And yet, despite paying tribute to originality in theory, venture still tends to reason through analogy. You hear it all the time: “This is Uber for X.” “This market looks like SaaS in 2012.” “She reminds me of a young [successful founder].” Every such judgment is, by definition, a comparison to something that has already happened. Pattern-matching can identify companies that resemble past winners. What it cannot reliably identify are the truly novel ones, which is where the outsized, infamous power-law returns tend to come from.
That is why some of the best seed investors are often thesis-driven rather than purely pattern-driven. They start with a structural shift, technical, regulatory, cultural, or behavioral, and then look for founders building into that shift before it becomes obvious. That is a leading-indicator framework. It tries to identify where the world is moving, rather than merely recognise what has already worked. In venture, by contrast, lagging indicators are the signals that appear only after a startup has already been partially de-risked by market validation, customer traction, institutional attention, or early adoption. If investors rely too heavily on those signals, they should, in theory, arrive too late to the real source of alpha.
So why, then, do most VCs still rely on lagging indicators?
2. Consensus Bets Reduce Reputational Risk
Despite what people often assume, venture capitalists arguably have one of the hardest tasks out there: they are paid to make judgments about a future that does not yet exist. But their job is not to predict the future in the abstract. Their job is to manage other people’s capital responsibly and generate credible returns over the life of a fund.
A VC then, as the agent, ends up optimizing for what the LP, as principal, can actually observe and evaluate:
• recognisable co-investors • clean step-ups • visible market validation • exposure to categories the broader market already understands (i.e. consensus)
These are legible signals. They may not capture the deepest truth about a company, but they make an investment easier to explain, easier to defend, and easier to present as progress. The principal-agent structure of VC makes lagging indicators the rational choice for many individual partners. It creates asymmetric career risk: losing money on a consensus deal is survivable; losing money on an unconventional one is much harder to justify. Venture, after all, is now a highly institutionalised asset class. Once investing frameworks spread across the industry, sameness followed naturally. Everyone began looking at deals through roughly the same lens, tracking the same trends from the same data sources and platforms, and consuming the same intellectual diet. The result is predictable: people start thinking alike, and eventually investing alike.
And yet, despite data being increasingly commoditised and differentiated conviction mattering more than ever, relationship-based investing still works in hot markets, at least in the short term. Keynes’s logic applies here too. If enough credible investors believe others will continue to believe, the cycle sustains itself. Firms validate one another through participation, mark one another up across rounds, and if strong exits eventually materialise, the process can still be defended as sound stewardship of LP capital. In colder markets, however, it becomes a drag on performance, because venture is no longer rewarded for staying close to consensus, but for being right before consensus arrives. That is especially visible today outside the most crowded parts of software and the B2B AI application layer, where true conviction is needed to fund the technology of tomorrow (robotic, precision manufacturing, etc.).
But even when a VC knows that leading indicators matter more than lagging ones, the cost of acting on that knowledge is high. It requires speed, deep networks, serious technical diligence, and the conviction to take meaningful ownership before the market has made the company legible. Which brings us to the next major reason VCs largely follow lagging indicators.
“You ever wonder why fund managers can’t beat the S&P500? Because they’re sheep — and sheep get slaughtered! Most these Harvard MBA-types, they don’t add up to dog sh*t. Give me guys that are poor, smart and hungry — and no feelings.” — Gordon Gekko, “Wall Street” (1987)
Read the full article by visiting our Substack via the button above. In it, we break down network effects, coordination games, FOMO & information asymmetry, and explaining why waiting is a sort of strategy in itself.
Best regards, Roko
