Right! My untrained intuition still resists a bit; I should play with the numbers.
siclabomines
Karma: 57
Niice, it makes sense! Thanks!
So to recap, I was right in that riskier assets can have higher avg returns, but I was missing the usually bigger and opposing effect where as the assets gets riskier, the same avg returns rely more and more on lucky very big gains while doing worse more often (at least if they are sort of lognormal).
My second point I still think was correct, right? -- i.e., that if Scott believed ETH had some chance of total collapse (a mixture distribution), then this skews it to the other side and pushes the median below the mean, and gives some reason to think ETH is more likely to outperform BTC. Does this make sense?
If ETH is less risky than BTC then the median performance of ETH will outperform BTC and his probability could be consistent with EMH
Wait. Does this mean that EMH expects less risky investments to have higher performance on average? That sounds shocking enough that I must be confusing something here. Or is this some sort of median vs mean distinction that I’m not seeing
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About 17 and the EMH. Can’t Scott be just thinking that ETH is sufficiently more risky than BTC so it may have higher expected returns even with the EMH (the EMH allows this, right?). Or even that he might think ETH has some chance of total collapse (like an outlier at 0) so even with equal expected returns it’s much more probable that ETH outperforms BTC than the other way around (?)
What’s this supposed to be estimating or predicting with Bayes here? The thing you’ll end up doing? Something like this?:
Each of the 3 processes has a general prior about how often they “win” (that add up to 100%, or maybe the basal ganglia normalizes them). And a bayes factor, given the specific “sensory” inputs related to their specific process, while remaining agnostic about the options of the other process. For example, the reinforcer would be thinking: “I get my way 30% of the time. Also, this level of desire to play the game is 2 times more frequent when I end up getting my way than when I don’t (regardless of which of the other 2 won, let’s assume, or I don’t know how to keep this modular). Similarly, the first process would be looking at the level of laziness, and the last one at the strength of the arguments or sth.
Then, the basal ganglia does bayes to update the priors given the 3 pieces of evidence, and gets to a posterior probability distribution among the 3 options.
And finally you’ll end up doing what was estimated because, well, the brain does what minimizes the prediction error. Is this the weird sense in which the info is mixed with bayes and this is all bayesian stuff?
I must be missing something. If this interpretation was correct, e.g., what would increasing the dopamine e.g. in the frontal cortex be doing? Increasing the “unnormalized” prior for such process? (like, it falsely thinks it wins more often than it does, regardless of the evidence). Falsely bias the bayes factor? (like, it thinks it almost never happens that it feels this convinced of what should happen in the cases when it doesn’t end up winning.)
Whatever prevents the most infection, hospitalization and death is the right answer either way
I first read this sentence as suggesting that killing people is the best way to prevent infection.
Yeah, if R0 is held constant and also COVID-UK is going up in absolute numbers.
Israel’s deaths are dropping more slowly than I would have intuitively expected given the vaccinations; I now wonder if it’s because of longer duration of the new strains which means we may have to wait a little longer until most of the previous infections resolve. Anyone that’s been looking at detailed data (like strain prevalence, the ages of the people still dying, etc) has an opinion? (I just looked at the daily death and vaccination rate)
I haven’t read the papers so, please correct me if I guess wrong (most likely), anybody.
I’m guessing the UK strain was estimated from relative growth between strains when the UK cases were skyrocketing, and that gave around ~40% higher R0 than COVID-classic.
Now, say they were underestimating the duration of the UK strain. That would mean it is actually more transmissible than estimated—but it was masked by the long timescales (transmissibleness means R, right?). And that would mean that it’s that much harder to contain than we thought (yet it was contained in the UK, which is great and suggests I’m talking BS). And it also means that it comes to dominate COVID-classic that much faster when COVID is going down.> This means that we should expect the English strain to arrive in numbers somewhat slower than its level of infectiousness would otherwise indicate.
I’d instead guess that we should expect it to arrive faster since it’s would be more infectious than previously expected and the US seems to be mitigating much more decently than the UK at that time? Does this make any sense?
I think you get more points for earlier predictions.
So one should interpret the points as a measure of how useful you’ve been to the overall predictions in the platform, and not how good you should be expected to be on a specific question, right?
Yeah, I wasn’t trying to be tautological.
I am under the impression that you are thinking something like: “Bezos has ~100 billion to spend. If he spends 1 million in X, then he has 1 million less to spend on the rest. But he won’t even get to spend it in his lifetime, so that extra million in X doesn’t change how much he would spend in Y. Therefore, it’s wrong to say that Y will become more available because Bezos spent in X.”.
I don’t think that’s the right way to think about all this. (Warning: oversimplification coming):
Bezos earns some income, say, in a year. Almost all of it will be spent. Most will be invested and not consumed, so it will still increase his net worth, but that demand for stuff is still there, affecting the economy. Bezos is already probably spending about as much as he can, and what he is not spending he is saving which probably means transferring it to someone else who will spend it. So, if he spends USD 10 in X, it’s reasonable imho to “expect” the economy to get USD 10 less spending in non-X stuff (on avg)
I think I disagree a bit with both (but what do I know).
For someone like Jeff Bezos, an increase in spending on Item A probably just results in slightly less money spent by his great-grandchildren in 100 years.
This doens’t seem to me to be the right way to think about it. Short term, the more he spends on Item A will result in lower spending on Item B, or lower investment in his companies, a lower transfer of money from him to someone else (like through lower savings). Or more money being spent overall if he just uses up cash he had hidden in his pillow; which increases prices for everyone (but this will be made up for in some future).
If we want to make sure that the starving guy gets some of the food, can’t we just allocate the food to him directly, rather than having to give him enough money to win a bidding war with Jeff Bezos?
Who produces the food and can set the prices? If it’s private companies, then they wouldn’t sell it to the state for cheaper than to Bezos, so it would be as expensive to the state as giving that same money to the poor and let them outbid Bezos. If the state owns the stuff, then [insert standard anti-socialism arguments]. If the prices are fixed by the state, then its inefficient and there may not enough production for all. If the prices fixed by the state but depend on the person—or on how many of X you have bought this month or stuff like that—then that introduces whole new types of messes.
I doubt that kind of hidden information can affect PredictIt betting odds as it limits the amount each person can bet.
There is bias or Zvi is reaching wrong conclusions with the same info.
It’s the placebo effect, obviously; you can’t get sick if you zinc it works.
Do they really get higher expected returns from that?
I know they do when the market isn’t efficient (relative to the specific investor), but that doesn’t help me.
Why is it that riskier investments should give higher expected returns?
I ask not because I don’t get that the avg person would rather invest on something safe than something unsafe, all else being equal. I get that. I ask because I imagine that investors could bring their total risk down through diversification without harming the expected returns, so big money would prefer the higher expected returns even if they are risky, and in doing that, they’d bring down the extra returns from the riskier investments.
Is it because investments options are so correlated that diversification isn’t enough to bring the risk of a portfolio down to acceptable levels? Or some other reason?
I have the opposite impressions. Science should embrace causality more and do it better. And as a layman term it should be refined so that we stop talking about the causes of any event as a cake where each slice has a name and only one name.
I find it hard to summarize why, at least right now, but my view is sorta similar to Pearl’s (though I don’t totally like how he puts it). Hopefully later I’ll re-read this more attentively and comment something more productive (if no one has done a strictly better job already).
I meant hiding just the CWish posts. There’re enough non-CWish posts to attract people that value the way of thinking in general.
Also, it doesn’t sound that bad to attract users through 1 to 1 recommendations only. Or allow unlogged people to read all, but only little by little release the power for new users to interact with the content. Maybe release it all at once if a high karma user vouches for you (they lose it that person gets banned or something). Maybe instead of karma, there could be another value that better reflects how much you are likely to value proper manners and thinking (e.g., it could be obtained by summing karma from different topics
iin a way that overvalues breadth of interest ).I’m just thinking out loud in real time. My main point one can go a long way just by limiting the rate at which new users can invade and screw with the content.
Do you have a good explanation to Moderna’s market price drop?
Borrow less, invest less, or, as you say in your last line, focus on other ways of making money that don’t require innovation and IP?