In 1952, Harry Markowitz published “Portfolio Selection” in the Journal of Finance. It made a simple but important claim: that the proper unit of analysis for an investor was the portfolio rather than the individual security, and that the relevant quantities were expected return, variance, and the covariance between holdings. The mathematical framework required to define an efficient portfolio along these lines was set out in the article. The framework that would later be called modern portfolio theory was, in its essentials, complete.
The institutional investment community didn’t, broadly, adopt it. Through the 1950s and 1960s, many large institutions continued to allocate capital using methods that had little to do with mean-variance optimisation. Asset allocation was governed by tradition, by category-by-category prudence, by intuitions about what one ought to own. The portfolio-level thinking that Markowitz had formalised existed in academic finance but not in trustee meetings.
Sharpe built on the framework in 1964 in developing the capital asset pricing model. Markowitz and Sharpe were among the recipients of the 1990 Nobel Prize in Economic Sciences for foundational work in financial economics — thirty-eight years after the original paper. By the early 2000s, the language of mean-variance analysis, efficient portfolios, and optimisation had become embedded in institutional asset allocation, even where committees used constrained, liability-aware, or heuristic versions rather than textbook optimisation. The framework had finally crossed.
Half a century is a long time for an idea to traverse the gap between being formulated and being adopted in practice. The puzzle isn’t that the idea was wrong. The puzzle is what determined when, having been articulated, it finally became behaviour and practice.
What kind of problem is this?
The Markowitz story was not, fundamentally, about an idea waiting to be understood. It was about an understood idea waiting for the social conditions of its adoption. The information was available throughout. The logic was clear enough to reshape academic finance. What had not yet formed was the social structure through which the behaviour of using it could spread.
When an idea is widely known but not adopted, when the gap between awareness and behaviour cannot be closed by stating the case more clearly, when the diffusion of a practice depends not only on its merits, but also on the social structure around it — that is a specific shape of problem. And the discipline that has thought most rigorously about how behaviour spreads through networks of people is the sociology of social contagion, particularly the work of Damon Centola at the University of Pennsylvania.
So let’s borrow.
This is the multi-model move: recognise the shape of a problem, find the discipline that has thought rigorously about that shape, and import its frameworks deliberately rather than reinventing them from scratch.
Where the spread of a behaviour requires more than a single exposure, the structure of the network — not merely its connections, but the way they overlap — governs whether the behaviour can cross.
The starting point is a distinction. Some things spread once a single exposure occurs. Others require reinforcement from multiple independent sources before adoption follows. Sociologists call the first a simple contagion and the second a complex contagion. The defining feature is structural — how many independent sources of activation must converge on a person before they adopt — rather than a property of the thing being transmitted.
A virus is the canonical simple contagion. One infected source can be sufficient to transmit it; confirmation from multiple sources isn’t structurally required. Much information behaves the same way — a single trustworthy mention is generally enough to know a fact — though gossip and credibility-sensitive claims can themselves require reinforcement from several sources. Models that describe simple contagion treat the network as a set of pipes. What matters is connectivity. Shorter average path lengths and broader reach speed transmission.
Behaviours are typically complex contagions, with adoption thresholds that exceed a single exposure. Adopting a new practice, joining a movement, changing a professional routine — these usually require seeing the behaviour from multiple sources before adoption becomes plausible. The reasons combine. Social proof: I’m more confident the behaviour is reasonable when I see several people doing it. Risk reduction: the cost of being wrong is lower if others share the choice. Legitimacy: the behaviour feels institutionally sanctioned only when it appears across the social field. Learning: the practical know-how is typically distributed and requires more than one teacher.
This distinction has a network consequence that’s easy to miss. Mark Granovetter’s celebrated 1973 paper, “The Strength of Weak Ties,” showed that distant, weakly connected contacts were particularly valuable for information transmission. They connect otherwise separate clusters and so accelerate the diffusion of facts and opportunities. The result is famous, and for simple contagions it holds.
For complex contagions, the weak-tie result often reverses. A single weak tie can’t, by itself, transmit a high-threshold behaviour, because adoption requires reinforcement from multiple independent sources and a single tie supplies only one. What’s needed instead is what Centola and Michael Macy, in a 2007 paper, called a wide bridge: a connection between two communities that consists of several overlapping ties, rather than one. A wide bridge can carry behaviour across because it delivers the reinforcement that adoption requires. A bridge too narrow to deliver the required reinforcement can’t carry the behaviour across, however short the path it creates.
Centola’s empirical work made this concrete. In a 2010 study published in Science, he constructed online networks with identical numbers of nodes and ties but different topologies — some random, some clustered — and observed how a particular behaviour, registration with an online health forum, spread through each. The clustered networks, with their wide bridges and redundant exposures, propagated the behaviour faster than the random networks, even though the random networks had shorter average paths. For a simple information contagion, that result would have been backwards. For behaviour, it was exactly what the theory predicted.
Markowitz’s framework was one instance of a much broader pattern. The same distinction surfaces across markets day to day, but the unit of analysis matters. Headline-level repricing can occur quickly because it requires only marginal orders from actors already authorised to place them — a trader changing a quote, an algorithm rebalancing a book. Durable exploitation of a thesis is a different kind of behaviour. It requires capital commitments, mandate changes, the willingness to risk credibility on an unpopular position. That kind of behaviour propagates at the speed of reinforcement: often slowly until wide bridges form, and sometimes rapidly once they do.
Several familiar phenomena fall out of this framing.
An apparent inefficiency can sit visible for years if betting against it requires behaviour that the relevant network can’t easily transmit. The information is there. The behaviour doesn’t cross. This doesn’t replace the standard limits-to-arbitrage explanations — financing constraints, benchmark risk, career risk, short-sale frictions. It helps explain why the social and institutional willingness to bear those limits may itself diffuse slowly.
When the wide bridges finally form — through new intermediaries, new platforms, new regulatory frameworks, new generations of decision-makers, new vocabulary that becomes shorthand inside a profession — adoption can cascade rapidly. The window between “still lonely” and “fully crowded” can be much shorter than the window of persistent visibility before it.
Some practices become institutional defaults not because the underlying case is overwhelming but because the network achieved wide-bridge density inside the right professional clusters early. Other equally defensible practices remained marginal because they didn’t. The set of universal practices is shaped not only by analytical merit, but also by social topology.
Strategies based on widely discussed but not widely adopted ideas are the strategies whose practitioners spend long stretches looking wrong. The frustration is structural. Holding the position requires sitting on a narrow bridge while waiting for it to widen.
Centola’s framework does not give you a clock. It cannot, by itself, tell you when the bridges around an idea will widen, or whether the network involved is approaching the threshold where adoption becomes possible. What it gives you is a structural test, and the test is specific.
Picture what adoption would look like at scale — not one institution adopting a new approach, but several converging on a pattern: a portfolio framework like the Total Portfolio Approach taking hold across allocators, a new research practice for valuing private assets becoming standard, a shared methodology for assessing long-horizon risk, common analytics for factor exposure. Then trace the network through which that pattern would have to spread — who is connected to whom, which clusters reach which adopters. Then ask: how many independent sources are already moving, and how well do they reach the practitioners who would have to follow?
The same questions apply far beyond markets. In organisations, a practice held up by a single senior champion is on a narrow bridge — and it disappears with the champion. In scientific communities, an idea cited by one camp may be widely heard but nowhere adopted; an idea taken up across previously distinct sub-disciplines, each translating it into its own language, has already crossed. In professions, the moment a new approach appears at once in textbooks, conferences, regulators’ guidance, and peer practice, crossing to it no longer feels like a choice.
Recognising the structure does not give you a forecast. Bridge formation can take much longer than expected and then happen suddenly. And recognising the structure does not place you outside it: your own decisions are reinforcing some bridges and leaving others narrow. Knowing why your position is lonely does not make it less lonely; it only tells you not to mistake the loneliness for being wrong.
The discipline is in asking: are the bridges widening around this idea, or is it still resting on a single source?
References & Further Reading
How Behavior Spreads: The Science of Complex Contagions: Damon Centola
Complex Contagions and the Weakness of Long Ties: Damon Centola & Michael Macy
The Spread of Behavior in an Online Social Network Experiment: Damon Centola
The Strength of Weak Ties: Mark Granovetter
Portfolio Selection: Harry Markowitz
Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk: William Sharpe
Capital Ideas: The Improbable Origins of Modern Wall Street: Peter Bernstein
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