murbard2
In theory you can claim it back, but it's a major pain in the ass. Some ETF issued outside the US and holding US stocks will do it.
Other strategies to avoid this annoyance include:
1. selling on the ex-dividend date and buying the next day.
2. buying a long-date call and selling a put instead of holding the stock
3. simpler version of 2: buy a deep in the money long-dated call, you won't be paying all that much for the convexity, and you don't have to think about dividends.
Dividends are silly in a world where you can achieve the same result and save everyone 20% tax by doing stock buybacks instead. It's also silly to strongly differentiate between dividend paying stocks and non dividend paying stocks as opposed to focusing on the business' cash flow, unless you're purposely avoiding dividend paying stocks because they suck from a tax perspective.
Yet, dividends are entrenched in many investor's psyche. Even official regulatory training in the US teaches registered representative that it's a good idea to recommend dividend bearing stocks to people who want "income" from their investments, which is a fallacy. Large mutual funds also have special categories for stocks providing high dividend yields.
It's sad to see them focus on confused investors as opposed to leveraging the incredible opportunity they have from their fabs.
Whoever is backing him is taking on the risk of SBF jumping bail (and I'd assume the house is under surveillance and he's wearing ankle monitors), in exchange for either silence or valuable goodwill on the tiny off-chance he gets out of this.
It's almost never the case that spam issues on popular social networks can be alleviated with some easy fixes, because obviously if they could they would already have done that. Twitter is a very weird exception.
If you pick 2 directions at each pass, one of them could be the direction of the last update and the other a random one, allowing for some kind of momentum.
1. pick a random direction
2. compute the derivative along that direction using forward-mode differentiation
3. update the parameters along that direction based on the derivative
The idea being that this gives an unbiased (albeit noisy) approximation of the actual gradient. You thus need a smaller learning rate, but you also need less memory and computation and, net net, they argue it's a win. Is this correct?
Microwave frequencies used in ovens would be dangerous because they can penetrate deep in the body and heat internal tissues, but in the EHF range microwave heating could be safe. See for instance https://en.wikipedia.org/wiki/Active_Denial_System
With all that said, what I had in mind is in the far less scary and far more prosaic near-infrared range.
With any luck he's got the source already.
He who unleashed it tarnished it.
While this is technically true, it obscures the reality of the matter. I doubt that woman woke up that day and decided in earnest she wanted to sue Kellogs over a poptart.
What likely happened is that Sheehan & Associates decided they wanted to try their hand at a class action lawsuit on the matter.
They need an actual plaintiff for doing that, just one person who, they will argue in court, is representative of anyone who ever bought a pop tart. They're not allowed to just solicit that person directly, so what they'll do is claim that they are "investigating the lack of strawberries in pop tart" and advertise heavily asking for help in their "investigation".
Once they get someone in their office or on the phone, it's easy to lead them towards the filing of a lawsuit (for which they can get paid).
The article does an unusually good job at showing scepticism over what is clearly lawyer-led and not plaintiff-led litigation, down to the title: "law firm sues".