I would disagree with this. In general, the algorithms are well known and only need to be implemented once. Doing problem modeling to solve real problems is where the action is for optimization.
This is a good write-up but it's also missing huge other sections of quant finance like statistical arbitrate and factor investing. I guess you could put this under the 'market taking' section except everything he describes is still in the mode of single stock thinking while these strategies are more about portfolios. You typically estimate some factor model of the market and use a portfolio optimizer to create your trade baskets.
In these types of strategies you care about latency but on the order of milliseconds not microseconds. The challenge is in building multi-day predictive alpha models with low correlation to each other, getting good executions though brokers can do a reasonable job these days, and especially combining alphas into one book which requires sophisticated mathematical programming (conic programming etc)
I think you completely missed what I said...you are again pointing at numbers that compare averages and I am saying that the averages are irrelevant. If half the people do great and half do terrible, the avergage will look merely ok but the people doing great aren't irrational to want to continue to do great. How is that in any way in conflict with WHO metrics?
I think what people in Europe don't appreciate about American healthcare is that the quality of care is a bi-modal (or maybe even more than 2 modes) distribution where a very large fraction of the population does in fact have the best access and quality of care in the world. On the other hand, there is a significant fraction of the population that has a lower overall access and quality of care. It is not irrational for the 40% to 70% (the fractions are debatable) of the population to not want to reduce their quality of care to average European care, which is in fact a lower standard for them.
If it's strictly a linear program, it's probably fine. You can always find the global optimum. Seems more likely to me that it's non-linear, which then depends on how non-linear (quadratic only?), if it's just the objective or the constraints that are non-linear, is it convex at all, etc.
If you do your time, you are square with the state. That doesn't and shouldn't mean private business or individuals should be forced to accept you. Should we make a law that says your friends and family have to accept you once you do your time?
It's not really a "loophole", per se. It would be ludicrous to say that a bank should not be able to exclude someone from hiring if they have been convicted of a serious financial crime, or that a day care should not be able to exclude a convicted child molester.
Now, will other companies take advantage of this so that they defeat the spirit of the law? Perhaps. But the fact that they need to make an assessment means that might be subject to review at some point.
They are probably market neutral. For as many dollars they are long, they are short an equal amount. Therefore it doesn't matter what the market is doing. It matters that their longs outperform their shorts.
What the market is doing isn't really relevant to a market neutral strategy, and that is almost surely what they are running. The goal is to make money consistently, whether market is up or down.
The problem is that you think they went out and investigated this topic then wrote about the results of their investigation. In reality, they had a narrative and agenda they wanted to pitch and then went out to find confirmatory evidence, while largely discarding contradictory evidence.
Just buy shares of SPY. It tracks the S&P 500. Keep in mind, returns aren't everything. They have to be considered along with risk. The S&P 500 also has big downturns of 20% or more. A good measure of return to risk is the sharpe ratio. The S&P's isn't all that good. This is why people invest in hedge funds.
In the US most allow but not always. For instance, NYC recently passed a law forbidding it. Many companies will not report anything other than whether or not you were an employee and the dates of your employment, but that is by their choice to limit lawsuits, frivolous or otherwise.
On the other hand, if you can make an organization work with a lower grade of employees, you will scale much more easily and cheaply. Maybe its a pipe dream to accomplish this but I think it's probably somewhere in between. At the scale of a multinational corporation with hundreds of thousands of employees, it surely comes into play more.
Those are hypothetical causes but they don't actually line up with all the observations. For instances, poor people are fatter than rich people. Shouldn't rich people be fatter since they
1) don't have to work as much manual labor
2) have more access to food.
You can try complicate the explanations to account for this but the fact is that it shows that the 'obvious' reasons most people surmise are not so clear cut and need to be tested like any hypothesis. It's a hard problem to test and there are several other competing hypothesis. The best I can say for my own beliefs is that we need to have more studies that need to be done before I'm convinced of any of them.
Well, I don't think that is going to "solve" the underlying problem. It might help the government pay for things, but it's not going to solve the obesity epidemic. There are already huge intrinsic and extrinsic negative impacts to your life if you are obese. One more negative impact is not likely to suddenly make you thin. What we need to do is figure out why people are getting fatter despite how much they don't want to be fat.
I hear what your saying but can't you use the same logic with bathrooms? Sure, we could all get by with 1 bathroom. Hell, we can get by with just communal bathrooms. But it turns out it's nice to have the luxury of not sharing things, even with your family. It's nice to be able to customize things the way you want. I will buy the argument that people will give up personal car ownership when I start to see people give up having personal bathrooms.
The problem is people outside the field of whichever cert pile into them as a means to break in, so the median cert holder winds up being inexperienced and overall unqualified. The cert itself then becomes associated with that. You're not wrong that its silly to be biased against, in the larger context of someones qualifications, but only certs that are sufficiently exclusive will get any respect and that probably isn't going to change.
You're right that the existence and quantity of news does not necessarily indicate bias, however, bias is found not just in news that is reported but also in what news is reported versus what news is not reported. I personally find this to be where most of the egregious media bias is. For instance, if the media chooses to not cover left-wing initiated violence at a protest, but heavily cover right-wing initiated violence at a protest, that is still bias, even if the reporting about the right-wing violence is accurate.
It's a much more insidious bias too because its harder to point out. You will have to use non-mainstream sources as they are the only ones doing the covering, and the fact that they are not mainstream will be used to hand waive away the complaints.
I agree with that in general but having your monitoring system be dependent on the thing it monitors is a pretty big goof. It possible that the dependency was very non-obvious and many layers deep, which is more understandable, but still...its pretty fundamental.
The thing is that this is really only true for people in dense urban environments. For instance, parking is not an issue in suburbia. There are use cases, like getting from your home to the train station, but it's not nearly as universal as it is for people who can currently get by with no car at all.
Not disagreeing with your points about L1 but I want to point out that you can also do things to make L2 more robust to outliers (and have better empirical performace), such as winsorizing the data.