41–50 of 176 posts
When everyone uses AI to study the same indicators and figures out how the prices move with those indicators they all start investing at the same time and the prices move together. AI silently gets everyone on the same page.
A 2010 entry by the same author: Markets are efficient if and only if P = NP https://arxiv.org/abs/1002.2284 :)
So markets can only be (perfectly) efficient or competitive, not both at the same time. Largely theoretical but it tracks common sense!
Keeping in mind the mistake in the HN title (should be "P != NP"), the interesting part of the abstract is this: > Combined with Maymin (2011), who proved that market efficiency requires P = NP, this yields a fundamental impossibility: markets can be informationally efficient or competitive, but not both. (Note that Maymin is the author of both papers.)
Yet neither paper seems to eliminate the case of markets being neither. So both titles are incorrect.
> the collusion detection problem is computationally infeasible for markets satisfying a natural instance-hardness condition on their demand structure, rendering punishment threats non-credible and collusion unstable. And yet we’ve clearly observed stable price fixing cartels. Maybe the word “unstable” means too much or the game theory model used doesn’t describe the real world accurately. When theory is contradicted…
Game theory here is applied to two fundamental market theorems. It’s a way to analyze the validity of those assumptions, rather than to build a new model. Empirical evidence to the contrary is expected given mutually inconsistent premises, which is what the author’s results predict. The author has simply used game theory math to disprove economist math.
A lot of things are only true if P != NP but says nothing about P being within epsilon of NP.
If P!=NP then it is arbitrarily smaller, for the same reason that e^x > Cx^N for any constants C and N, as long as x grows big enough. There is no epsilon in that can overcome that, no matter how big you make it, because x will eventually dominate the equation.
There are a lot of cases where pragmatically x remains small enough that it doesn't matter, and a P algorithm will give you an answer more quickly. (For the same reason I only ever write bubble sorts: I would only write my own at all if I knew that the list would never be bigger than 10. Even then it's only when using the library is too much trouble for some reason.)
But we care about P and NP when the number can potentially be very, very large.
Very interesting. The author claims to have proved that markets can be informationally efficient or competitive, but not both. The implications for policy and regulation are significant. The author looks credible: https://philipmaymin.com/about-philip Thank you for sharing this on HN. -- To the mods: The title needs to be edited to replace the equal sign with not-equal.
The actual paper's title is "Markets are competitive if and only if P != NP" Seems that HN's auto-headline rewriting in this case has made a critical error :) >Artificial intelligence, by expanding firms' computational capabilities, is pushing markets from the competitive regime toward the collusive regime, explaining the empirical emergence of algorithmic collusion without explicit coordination. I have to dig more i…
or maybe compute allows simulating a lot of possible cooperation strategies, and arriving at the one maximizing profits for the colluding parties
The actual paper's title is "Markets are competitive if and only if P != NP" Seems that HN's auto-headline rewriting in this case has made a critical error :) >Artificial intelligence, by expanding firms' computational capabilities, is pushing markets from the competitive regime toward the collusive regime, explaining the empirical emergence of algorithmic collusion without explicit coordination. I have to dig more i…