I'd rather use a more powerful EMH-focused definition: a bubble is large price increase which represents an inefficiency in the market which is predictable in advance (not in hindsight), exploitable, and worth exploiting.
I'm happy with that definition. EMH (Efficient Market Hypothesis) for those of you following along at home.
In my case I had amassed a small fortune by October of 1999 by simply holding the stock options I had been granted on taking the job 4 years earlier. They were up more than 10X at that point. Actionable? My very intelligent college roommate owned his own financial advising firm. He spent two weeks on the phone with me convincing me that it would be gigantically more sensible to cash out these options and give them to him to invest "in case, in the future, people get up in the morning, put their clothes on, and go outside instead of sitting in front of their PCs all day ordering stuff off the internet." He sent me books to read including this one first published in 1841. This describes witch hunts as well as South Sea, Tulip and other financial bubbles. Jim, my roommate, had been referring to tech as a bubble for a year or two before I talked to him in October of 1999. The action he was taking with his other clients was to simply not get in to tech. This was a horribly unsatisfying strategy until about the middle of 2000 when tech was well into its slide from the top.
By the time I cashed out and handed him the money in about december 1999, the stock had more than doubled again. The human in me wanted to hold on to it because, obviously, this was a stock which kept on doubling. He explained to the rationalist in me that whatever the case for investing that money in something else was at half the price, the case was TWICE as good at twice the price, unless we had learned something quite important and positive about the business in the last two months. Which we hadn't of course. What we had learned is that there was no shortage of "greater fools" willing to buy in AFTER all that price appreciation had already happened on old information that was not changing nearly as fast as the price.
Over the next three years the stock I had sold in December 1999 gave back about 75% of its price gains. Meanwhile, my friend invested my money in REITs, Berkshire Hathaway, banks, and a bunch of other asset classes not even dreamed about by most of my fellow techies. The money I had given him grew by 40% more or less, I don't remember exactly, while the nearly half of my original stock grant I had kept in my employers stock contracted to 20% of its peak value.
So yes, to me the internet bubble appears to have been actionable before it burst. The "investors" who stayed with the bubble, myself included with what started out as nearly half of my fortune and ended as about a tenth of it. The shift of 60% of my money out of the bubble preserved my wealth at a level that may well have been unique among my peers at this company.
I realize you can't get a drug approved with this kind of evidence. But you realize that most of what we "know" is the best model we can come up with in the absence of double blind studies. I've detailed the one best example in my life. I agree it is HARD to act on bubbles, shorting them is scary and fraught with risk, you are betting you can stay solvent longer than the market can stay stupid, which is quite a bet indeed. So bubbles, so spectacularly obvious in retrospect, may be no more reliably useful for making money than is any mispricing, even smaller more temporary ones.
Out of curiousity, are you enough of an EMH'er that you don't believe in mispricings? Or at least not in publicly traded financial securities markets? Do you think it is just a roll of the dice that 9 students of Ben Graham all ran funds which had long term returns above market averages? I think a bubble is just a particular kind of mispricing, a particular kind of inefficiency. It may be no easier to exploit than the other kinds of mispricings, but it is probably not harder to exploit. And shorting is not the only way to exploit bubbles or mispricings, just sticking with a discipline which on average avoids them appears to work for a broad range of investors, including such low-entropy categories of investors as former students of one professor who espoused value investing.
Actionable? My very intelligent college roommate owned his own financial advising firm. He spent two weeks on the phone with me convincing me that it would be gigantically more sensible to cash out these options and give them to him to invest "in case, in the future, people get up in the morning, put their clothes on, and go outside instead of sitting in front of their PCs all day ordering stuff off the internet."
This actionable advice is also 100% justifiable without recourse to claims of superior perception simply by the high value of divers...
In an unrelated thread, one thing led to another and we got onto the subject of overpopulation and carrying capacity. I think this topic needs a post of its own.
TLDR mathy version:
let f(m,t) be the population that can be supported using the fraction of Earth's theoretical resource limit m we can exploit at technology level t
let t = k(x) be the technology level at year x
let p(x) be population at year x
What conditions must constant m and functions f(m,k(x)), k(x), and p(x) satisfy in order to insure that p(x) - f(m,t) > 0 for all x > today()? What empirical data are relevant to estimating the probability that these conditions are all satisfied?
Long version:
Here I would like to explore the evidence for and against the possibility that the following assertions are true:
Please note: I'm not proposing that the above assertions must be true, only that they have a high enough probability of being correct that they should be taken as seriously as, for example, grey goo:
Predictions about the dangers of nanotech made in the 1980's shown no signs of coming true. Yet, there is no known logical or physical reason why they can't come true, so we don't ignore it. We calibrate how much effort should be put into mitigating the risks of nanotechnology by asking what observations should make us update the likelihood we assign to a grey-goo scenario. We approach mitigation strategies from an engineering mindset rather than a political one.
Shouldn't we hold ourselves to the same standard when discussing population growth and overshoot? Substitute in some other existential risks you take seriously. Which of them have an expectation2 of occuring before a Malthusian Crunch? Which of them have an expectation of occuring after?
Footnotes:
1: By carrying capacity, I mean finite resources such as easily extractable ores, water, air, EM spectrum, and land area. Certain very slowly replenishing resources such as fossil fuels and biodiversity also behave like finite resources on a human timescale. I also include non-finite resources that expand or replenish at a finite rate such as useful plants and animals, potable water, arable land, and breathable air. Technology expands carrying capacity by allowing us to exploit all resource more efficiently (paperless offices, telecommuting, fuel efficiency), open up reserves that were previously not economically feasible to exploit (shale oil, methane clathrates, high-rise buildings, seasteading), and accelerate the renewal of non-finite resources (agriculture, land reclamation projects, toxic waste remediation, desalinization plants).
2: This is a hard question. I'm not asking which catastrophe is the mostly likely to happen ever while holding everything else constant (the possible ones will be tied for 1 and the impossible ones will be tied for 0). I'm asking you to mentally (or physically) draw a set of survival curves, one for each catastrophe, with the x-axis representing time and the y-axis representing fraction of Everett branches where that catastrophe has not yet occured. Now, which curves are the upper bound on the curve representing Malthusian Crunch, and which curves are the lower bound? This is how, in my opinioon (as an aging researcher and biostatistician for whatever that's worth) you think about hazard functions, including those for existential hazards. Keep in mind that some hazard functions change over time because they are conditioned on other events or because they are cyclic in nature. This means that the thing most likely to wipe us out in the next 50 years is not necessarily the same as the thing most likely to wipe us out in the 50 years after that. I don't have a formal answer for how to transform that into optimal allocation of resources between mitigation efforts but that would be the next step.