Is that one article really the best, solidest, most convincing criticism of EMH you can come up with, which you think will persuade people reading this conversation that EMH is to a meaningful degree false and markets are often beatable - some cherrypicked questionable examples from the dawn of time?
In its way, yes it is. You get a guy who has impeccable credentials, a massive public record who thinks he has been investing intelligently for decades, who if he IS performing randomly is a few sigma out on the positive side of the random distribution. You get to see what he has to say about what he thought he was doing, how it fits with what a whole bunch of other people were doing, a cogent description for why it might work, and a bunch of numbers about how it does indeed seem to work. Buffett understands the idea that he could just be lucky and he addresses it.
If you think the best explanation of Buffett's life and results are that he has been fooled by randomness, then you are a very different judge of character and information than me or millions of others like me.
If the EMH was "the markets are really really efficient, it is hard to produce alpha (outperformance), hard to know when you have alpha, and easy to fool yourself because of human biases" then who would argue with that? Not me. But that step from "really hard" to "impossible" is unreasonable. It is not impossible to be a great baseball player. It is not impossible to consistently beat other players at poker, even though everybody playing has the same information, on average across all the hands. It is not impossible to understand 10 languages, even though to most of us most of them sound like noise.
If EMH was right, wouldn't the smartest, most quantitative participants in the market have figured that out? Wouldn't Renaissance Technologies have 1) failed, and 2) figured out that their failure was consistent with randomness where they thought there was order?
EMH is the hypothesis that because bunches of smart people all work to figure out what the best investment is, there can be no excess returns available to the smart people who all work hard to figure out what the best investment is. Well if there are not excess returns available to them, why do they do it?
Isn't EMH the hypothesis that, for EVERYBODY in the market, it would be more efficient to free ride and use your intelligence on something where you can actually produce a return?
Isn't EMH ultimately a big floppy tent held up by a tent pole which the EMH'ers deny exists?
...In its way, yes it is. You get a guy who has impeccable credentials, a massive public record who thinks he has been investing intelligently for decades, who if he IS performing randomly is a few sigma out on the positive side of the random distribution. You get to see what he has to say about what he thought he was doing, how it fits with what a whole bunch of other people were doing, a cogent description for why it might work, and a bunch of numbers about how it does indeed seem to work. Buffett understands the idea that he could just be lucky and he add
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.