But I still think it's important to point out that the behavioral recommendations of Kelly do not violate the VNM axioms in any way, so the incompatibility is not as great as it may seem.
I think the interesting question is what to do when you expect many more, but only finitely many rounds. It seems like Kelly should somehow gradually transition, until it recommends normal utility maximization in the case of only a single round happening ever. Log utility doesn't do this. I'm not sure I have anything that does though, so maybe it's unfair to ask it from you, but still it seems like a core part of the idea, that the Kelly strategy comes from the compounding, is lost.
And yet it doesn't violate VNM, which means the classic argument for maximizing expected utility goes through. How can this paradox be resolved? By noting that utility is just whatever quantity expectation maximization does go through for, "by definition".
This is the sort of argument you want to be very suspicious of if youre confused, as I suspect we are. For example, you can now just apply all the arguments that made Kelly seem compelling again, but this time with respect to the new, logarithmic utility function. Do they actually seem less compelling now? A little bit, yes, because I think we really are sublinear in money, and the intuitions related to that went away. But no matter what the utility function, we can always construct bets that are compounding in utility, and then bettors which are Kelly with respect to that utility function will come to dominate the market. So if you do this reverse-inference of utility, the utility function of Kelly bettors will seems to change based on the bets offered.
I'm curious if you're taking a side, here, wrt which limit one should take.
Not really, I think we're to confused to say yet. I do think I understand decisions with bounded utility (all the classical foundations imply bounded utilities, including VNM. This doesn't seem to be well known here). Bounded utility makes maximization a lot more Kelly: it means that the maximizers can no longer have the arbitrarily high pay-offs that are needed to balance the near-certainty of elimination. I also think it should make it not matter which limit you take first, but I don't think that leads to Kelly, either, because the betting structure that leads to Kelly assumes unbounded utility. Perhaps it would end up as a local approximation somewhere.
Now I also think that bounded decision theory is inadequate. I think a decision theory should be able to implement a paperclip maximizer, and it should work in worlds that last infinitely long. But I don't have something that fulfills that. I think theres a good chance the solution doesn't look like utility at all: A theorem that needs its problem to be finite propably won't do well in embedded problems.
1. Money wants to be linear, but wants even more to be logarithmic.
2. Money wants to go negative, but can't.