One signature feature of a bubble is that it grows rapidly, with the rate of buying activity increasing over time. Bubbles often feature what’s known as ‘super-exponential’ growth;[25] not only does the buying activity accelerate, the acceleration itself accelerates. With every increase in price, even more investors join in, driving the price higher. And like an infection, the faster a bubble grows, the faster it will burn through the population of susceptible people.
Unfortunately, it can be difficult to know how many people out there are still susceptible. This is a common problem when analysing an outbreak: during the initial growth phase, it’s hard to work out how far through we are. For infectious disease outbreaks, a lot depends on how many infections show up as cases. Suppose most infections go unreported. This means that for every case we see, there will be a lot of other new infections out there, reducing the number of people who are still susceptible. In contrast, if the majority of infections are reported, there could still be a lot of people at risk of infection. One way around this problem is to collect and test blood samples from a population. If most people have already been infected and developed immunity to the disease, it’s unlikely the outbreak can continue for much longer. Of course, it’s not always possible to collect a large number of samples in a short space of time. Even so, we can still say something about the maximum possible outbreak size. By definition, it’s impossible to have more infections than there are people in the population.
Things aren’t so simple for financial bubbles. People can leverage their trades, borrowing money to cover additional investments. This makes it much harder to estimate how much susceptibility there is, and hence what phase of the bubble we’re in. Still, it is sometimes possible to spot the signals of unsustainable growth. As the dot-com bubble grew in the late 1990s, a common justification for rising prices was the claim that internet traffic was doubling every 100 days. This explained why infrastructure companies were being valued at hundreds of billions of dollars and investors were pouring money into internet providers like WorldCom. But the claim was nonsense. In 1998, Andrew Odlyzko, then a researcher at AT&T labs, realised the internet was growing at a much slower rate, taking about a year to double in size.[26] In one press release, WorldCom had claimed that user demand was growing by 10 per cent every week. For this growth to be sustainable, it would mean that within a year or so, everyone in the world would have had to be active online for twenty-four hours a day.[27] There were simply not enough susceptible people out there.
Arguably the greatest bubble of recent years has been Bitcoin, which uses a shared public transaction record with strong encryption to create a decentralised digital currency. Or as comedian John Oliver described it: ‘everything you don’t understand about money combined with everything you don’t understand about computers.’[28] The price of one Bitcoin climbed to almost $20,000 in December 2017, before dropping to less than a fifth of this value a year later.[29] It was the latest in a series of mini-bubbles; Bitcoin prices had risen and crashed several times since the currency emerged in 2009. (Prices would start to rise again in mid-2019.)
Each Bitcoin bubble involved a larger group of susceptible people, like an outbreak gradually making its way from a village into a town and finally into a city. At first, a small group of early investors got involved; they understood the Bitcoin technology and believed in its underlying value. Then a wider range of investors joined in, bringing more money and higher prices. Finally, Bitcoin hit the mass-market, with coverage on the front pages of newspapers and adverts on public transport. The delay between each of the historical Bitcoin peaks suggests that the idea didn’t spread very efficiently between these different groups. If susceptible populations are strongly connected, an epidemic will generally peak around the same time, rather than as a series of smaller outbreaks.
According to Jean-Paul Rodrigue, there is a dramatic shift during the main growth phase of a bubble. The amount of money available increases, while the average knowledge base decreases. ‘The market gradually becomes more exuberant as “paper fortunes” are made from regular “investors” and greed sets in,’ he suggested.[30] Economist Charles Kindleberger, who wrote the landmark book Manias, Panics, and Crashes in 1978, along with Robert Aliber, emphasised the role of social contagion during this phase of a bubble: ‘There is nothing so disturbing to one’s well being and judgment as to see a friend get rich’.[31] Investors’ desire to be part of a growing trend can even cause warnings about a bubble to backfire. During the British Railway Mania in the 1840s, newspapers like The Times argued that railway investment was growing too fast, potentially putting other parts of the economy at risk. But this only encouraged investors, who saw it as evidence that railway company stock prices would continue rising.[32]
In the later stages of a bubble, fear can spread in much the same way as enthusiasm. The first ripple in the 2008 mortgage bubble appeared as early as April 2006, when US house prices peaked.[33] It sparked the idea that mortgage investments were much riskier than people had thought, an idea that would spread through the industry, eventually bringing down entire banks in the process. Lehman Brothers would collapse on 15 September 2008, a week or so after I finished my internship in Canary
