Those are fine. I would give them a 3⁄10 for comfort, 11⁄10 for efficacy, and 3⁄10 for price, since only the respirator part is reusable and you have to buy filters. A good choice if you in a very at risk demographic and don’t mind spending the extra money.
For comparison, I’d give the modified KN95 a 6.5/10 for comfort, 7⁄10 for efficacy, and 8⁄10 for price.
Like the idea of ear savers; might try them to see how they feel compared to the tight earloops.
I see. Upgrade price to 9⁄10 then
What kinds of vaccines did you guys have? Also how long ago? I hypothesize a lot of the difference in efficacy reported by the UK (88%) and Israel (64%, kind of close to the efficacy in your situation if we make the generous assumption that all 14 would have been infected without the vaccine) has to do with the fact that Israel started vaccinating earlier.
I was also surprised to read that because I was always under the impression that the SR of bonds is higher than that of stocks over a long time, and the SR of the stock market over a long time (much longer than 5 years) is about 0.5.
However, when I looked into the data more closely, the recent (1976-present) high sharpe ratio of bonds seems to be an extremely temporary phenomenon related to the large decline in interest rates during this time. The SR of bonds prior to 1976 is actually worse than stock index SR. So when looking at a very long timespan (on the order of about 100+ years), I actually agree with SimonM on this upper bound for assets now.
At the very least, I do not know of any asset classes with 100+ years of history that have SR over that period significantly greater than 0.5
I should perhaps clarify that I am talking about weak form efficiency. In a weak-form efficient market, active management through fundamental analysis can still produce excess returns. The three and five factor models attempt to find fundamental factors that can predict excess returns. This contradicts the stronger forms of EMH, but it stands just fine with the weak form. In addition, academic practitioners use the five factor model often in defense of weak EMH.
To your point, perhaps I should edit the original article though. Investopedia says of the FF model, “there is a lot of debate about whether the outperformance tendency is due to market efficiency or market inefficiency.”
The scatterplot in the middle is not risk adjusted.
It seems ad hoc to me because they continue to add “fundamental” factors to their model, instead of accepting that the risk-return paradox just existed. Why accept 5 fundamental factors when you could just accept one technical factor?
Suppose that in 20 years we discover that although currently in 2021 we are able to explain the risk-return paradox with 5 factors and transaction costs, the risk-return paradox still exists despite 5 factors in this new out of sample data from the future. What do we do then? Find 2 more factors? Or should we just conclude that the market for the period of time up until then was just not efficient in a weak-form sense?
I don’t think that gilch answered the question correctly. His two games A and B are both “additive” games (unless I’m misunderstanding him). The wagers are not a percent of bankroll but are instead a constant figure each time. His mention of the Kelly criterion is relevant to questions about the effect of leverage on returns, but is relevant neither to his example games nor to your question of why volatility is used as a “proxy” for risk.
I’d say that to a large extent you are right to be suspicious of this decision to use variance as a proxy for risk. The choice to use volatility as a risk proxy was definitely a mathematical convenience that works almost all of the time, except when it absolutely doesn’t. And when it doesn’t work out, it does so ways that can negate all the time that it does work out for. The most commonly used model of a stock’s movements is Geometric Brownian Motion, which only has two parameters, µ and σ. Since σ is the sole determinant of the standard deviation of the next minute/day/month/year’s move, it is used as the “risk” parameter since it determines the magnitude distribution for how much you can expect to make/lose.
But to get to the heart of the matter (i.e. why people accept and use this model despite it’s failure to take into account “real” risk), I refer you to this stackexchange post.
I think I would agree with you that if you could really find the “right” factors to care about because they capture predictable correlated variance in a sensible way, then we should accept those parts as “explainable”. I just find that these FF betas are too unstable and arbitrary for my liking, which is a sentiment you seem to understand.
I focus so much on the risk-return paradox because it is such a simple and consistent anomaly. Maybe one day that won’t be true anymore, but I’m just more willing to accept that this phenomenon just exists as a quirk of the marketplace than that FF explains “part of it, and the rest looks like inefficiency”. FF could just as easily be too bad a way to explain correlated variance to use in any meaningful way.
Thanks for this! Updated the post with more high quality screenshots.
11 days could be unusual based on the Hong Kong report:
Based on the report it seems that someone arriving Nov 11 had enough virus to test positive by Nov 13, and the person he infected had enough virus to test positive on Nov 18. Both were sent to the hospital but it is unclear whether this was part of a standard procedure or if they were ill enough to need to go.
Internet is a great place. Thanks for that info!
I asked Alex from RADVAC on reddit about antibody responses to the vaccine. He replied by saying 4 of the researchers saw a “positive antibody response.”
https://www.reddit.com/r/radvac/comments/ig2b1q/related_news_open_for_suggestions/
“Some of our core group started performing ELISA assays to determine the presence of anti-Spike antibodies, beginning back in May/June. Since only a handful of us had at that point been collecting samples rigorously, the sample size available to us was small, so although we saw a positive antibody response, we didn’t consider the (n=4) data credible as a data set.”
I dare not interpret the implications of this finding on how much we should expect out of these vaccines, but I thought that this would be important to discuss.