Regarding new variants, what is the relevant metric to think about generation of relevant mutations?
Infected person days (somewhat weighted by severity since a person with a more severe infection has probably more cells getting infected)? But you probably often need multiple mutations that work well together, so depth of the phylogenetic tree probably matters as well (as opposed to width, which Omicron certainly generates a lot of).
In the end, the distance and especially the path to a new optimum are of course the important factors, but for this we’d could (as a first order approximation) use the difficulty going from “wild type” to Alpha.
I feel like estimating the breadth and depth of phylogenetic “search in the genomic space” lends itself so well to mathematical modelling that it should be a pretty well-covered topic. Given that (and current infection estimates), one should be able to get a good estimate of the likelihood per day that a new interesting variant occurs. That is of course unless Omega found a local optimum that is very hard to escape from.
So, sorry for what's probably a dumb-ass question if one is familiar with trading, but I am not, so here goes:
When you say you want to 'sell' any of these, it's clearly that means you think there's a lower chance of these things happening than the market prices imply, so if you were actually holding contracts that would yield $1 if they happened, you'd sell them at this price, and down to some lower price (either your sell-to or honest-guess price, depending on what you're up to). I get that. However, I do not currently own any such contracts, and it doesn't seem like you do either. So, when you say you want to 'sell' these, is that equivalent to saying you want to buy the no contracts at their current price and then up to whatever the mirror of your sell-to price for yes is?
This, to me, seems like it would be the case, but I wanted to check if there's some crucial distinction between selling yes and buying no that I'd failed to pick up on (likely something to do with how fees are going to work out, I'd guess, or maybe with what seeing the prices does to your estimates of the probability?)
I’m curious how that mask requirement question will resolve if it remains permanently in effect but with vague and unenforceable conditions like “everyone must wear a mask if they believe they have been exposed to an airborne illness in the last two weeks,” which seems like a plausible outcome to me.
While I agreed with your impression that France will likely stay above ES/IT/US, I think you jinxed it: https://imgur.com/a/0paoS6Y
The very top of the graph is the last data point available when when you published the post.
It reminds me of a french philosopher known for his work on the topic "COVID modelling doesn't work, forget about it".
Maybe the French gave up and stopped testing. Or it's really related to the graph with substructure model from Lemoine, with France having maybe sparser clusters but higher connectivity between them (why that would be the case I have no idea).
Regarding new variants, what is the relevant metric to think about generation of relevant mutations?
Infected person days (somewhat weighted by severity since a person with a more severe infection has probably more cells getting infected)? But you probably often need multiple mutations that work well together, so depth of the phylogenetic tree probably matters as well (as opposed to width, which Omicron certainly generates a lot of).
In the end, the distance and especially the path to a new optimum are of course the important factors, but for this we’d could (as a first order approximation) use the difficulty going from “wild type” to Alpha.
I feel like estimating the breadth and depth of phylogenetic “search in the genomic space” lends itself so well to mathematical modelling that it should be a pretty well-covered topic. Given that (and current infection estimates), one should be able to get a good estimate of the likelihood per day that a new interesting variant occurs. That is of course unless Omega found a local optimum that is very hard to escape from.
Also: I am too late and someone who agrees with you made all those trades :P
Given the poor liquidity, it probably only took a single person with some small k$s in funds for this to happen.
So, sorry for what's probably a dumb-ass question if one is familiar with trading, but I am not, so here goes:
When you say you want to 'sell' any of these, it's clearly that means you think there's a lower chance of these things happening than the market prices imply, so if you were actually holding contracts that would yield $1 if they happened, you'd sell them at this price, and down to some lower price (either your sell-to or honest-guess price, depending on what you're up to). I get that. However, I do not currently own any such contracts, and it doesn't seem like you do either. So, when you say you want to 'sell' these, is that equivalent to saying you want to buy the no contracts at their current price and then up to whatever the mirror of your sell-to price for yes is?
This, to me, seems like it would be the case, but I wanted to check if there's some crucial distinction between selling yes and buying no that I'd failed to pick up on (likely something to do with how fees are going to work out, I'd guess, or maybe with what seeing the prices does to your estimates of the probability?)
I’m curious how that mask requirement question will resolve if it remains permanently in effect but with vague and unenforceable conditions like “everyone must wear a mask if they believe they have been exposed to an airborne illness in the last two weeks,” which seems like a plausible outcome to me.
While I agreed with your impression that France will likely stay above ES/IT/US, I think you jinxed it: https://imgur.com/a/0paoS6Y
The very top of the graph is the last data point available when when you published the post.
It reminds me of a french philosopher known for his work on the topic "COVID modelling doesn't work, forget about it".
Maybe the French gave up and stopped testing. Or it's really related to the graph with substructure model from Lemoine, with France having maybe sparser clusters but higher connectivity between them (why that would be the case I have no idea).