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Would this be a concrete example of the above:

We have two states S=0, S=1 as inputs, channel k1 given by the identity matrix, i.e. it gives us all information about the original, and k2 which loses all information about the initial states (i.e. it always returns S=1 as the output, regardless of the input ). Then k1 strictly dominates k2, however if we preprocess the inputs by mapping them both to S=1, then both channels convey no information, and as such there is no strict domination anymore. Is this so?

More generally, any k1>k2 can lose the strict domination property by a pregarbling where all information is destroyed, rendering both channels useless.

Have I missed anything?

My main argument in favour of risk profiles is to think in terms of the frequency in which events go wrong. It is true that me not getting Covid yesterday should not impact my decisions today, however making choices that yield a probability of a bad event of p over the next month means I'll have that bad event happen once every 1/p months, on average. Due to loss aversion I might want to cap that frequency, even at the cost of reduced expected utility, hence I'll give myself a risk profile. This goes into the psychological effects of loss, which tend to overweight positive outcomes. Any thoughts?

I have a personal belief that a lot of low hanging fruit does not get picked because of we have masses where each benefits a little vs smaller entities with a lot to lose, such as drug companies wanting smaller enforcement. As such the invested minority can outlast the majority in terms of preventing these changes from becoming law.
Do you see other factors having more significance? Further, can we avoid these impasses?

They can profit without this sort of Ponzi scheme. The best analogy I have seen is as follows:

Suppose you have 5 phones on the market, and by law short sellers have to buy 10 phones. Since the demand will always be higher than supply ( the legal requirement forces short sellers to buy ), then the price will go off to infinity by natural supply/demand mechanics.

The only way to break this is by increasing supply, ie if long stock holders decide to sell they shares as you recommended when you say get out. This would not be maximally beneficial for the long holders. Once supply surpasses demand the overpricing immediately breaks, but that doesn’t need to happen. Since short sellers owe something like 120% of the stock ( I’m not sure of the exact value), long holders could theoretically agree to sell only 1% of their stock each at a million a share, and this would still work and benefit all long holders.

This was only possible because short sellers overbought their side. The interesting issue here is that even though there is a way for ALL long holders to profit immensely, it would fail if enough of them get scared into selling, so it becomes a real life coordination problem. Do you think they can pull it off?

PS: I’ve worked in finance and found this very interesting, both due to the unusual short squeeze it is, and to the behavioural side of the situation. I’d like to hear opposing thoughts and questions if my writing isn’t as clear as it should be. Exciting times!

First of all thank you for your post, it’s very thorough :)

While I want to reread it in case I missed any arguments for this, the main issue I usually have with these trust webs is the propensity for the creation of echo chambers: by relying only on those you trust and who they trust, you might filter out others opinions not because they are less valid, but because you disagree on some fundamental axioms. Have you given any thought on how to avoid echo chambers in these webs of trust?

Best, Miguel

Lovely idea.

Minor point: it feels to me the average bet isn’t the usual average but instead the harmonic mean of all bets taken. The difference might be small and more importantly there’s no reason why the arithmetic average is fairer than the harmonic average, but it was just a small thing I noticed 😜

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