The key difference seems to be German private health insurance contracts are long-term affairs. Multi-year, or perhaps even lifetime? US health insurance contracts are typically a year at a time. So German companies have to reserve for costs projected to occur far in the future because they are liable for them, while US companies have no idea if their customer will still be around in 20 years.
My guess would be there's a healthy dollop of regulation pushing the German insurance market into that shape, otherwise you would probably see short-term insurers outcompeting long-term insurers since they wouldn't have to do old-age reserves and could therefore charge lower premiums. Consumers tend not to be nearly as good at rationally planning for long term expenditures as are actuaries.
There exist both types of health insurances in Germany:
"Krankenversicherung nach Art der Lebensversicherung" (health insurance in the form of life insurance) and "Krankenversicherung nach Art der Schadenversicherung" (health insurance in the form of indemnity insurance).
The first one is basically an alternative to the state-mandated health insurance, while the latter one is mostly intended for more specialized health services like for example dental replacement.
There is a regulation that once you are in a "Krankenversicherung nach Art der Lebensversicherung", the health insurance company is not allowed to cancel the contract with you, but on the other hand for this restriction the health insurance company is allowed to "adjust" premiums (nearly always that means "increase premiums") if the medical costs for the agreed treatments rise (which they commonly do).
Thus having a (near-certain) cashflow over the lifetime of the whole insured person (who can only under very special circumstances get out of the insurance treaty) is quite attractive for the insurance company.
> otherwise you would probably see short-term insurers outcompeting long-term insurers since they wouldn't have to do old-age reserves and could therefore charge lower premiums
You must not compare the current premiums, but the amount of premiums that you will pay over the whole lifetime. Here, the situation is completely different.
I think considering the huge amount of money (for premiums and medical costs) that is involved here, it can only be explained with stupidity to just compare current premiums in the young age: it is very well-known that the whole actuarial reserve that the insurance company built up from the premiums of a huge part of your lifetime will be spent for medical costs in just the last few years of your life.
It is thus a really macabre truth that if we would just let patients with cancer or another expensive disease die instead of giving them expensive treatments for just few additional years it would save an insane amount of money in the health system.
It mentions reduced spending on doctors. My thinking on the mechanism is that freeing doctors from noncompetes makes it easier for them to leave big practices and start small ones. Small practices have less bargaining power with insurance companies and will have to charge lower rates.
Big practices feel like patients should remain loyal to the practice, not the individual provider with which they have established a trusting relationship.
Doesn't make intuitive sense to me why you'd need a whole new airplane for this. Can you not rig something up to let one of these blades ride on top of an existing plane like the space shuttle transporter? Or would Sergey Brin's giant dirigible work? Or two helicopters flying in formation? Or just make the blades come in two pieces assembled on site?
Just seems very hard to believe a project as massive as a whole new airplane is the best solution to this problem.
For one thing, a 747 is only 250 feet long. So a 300-foot blade on top would trail significantly.
For another, the shuttle piggyback worked partly because of the shuttle’s aerodynamic profile. It’s designed to go straight forward into the wind. This means the 747 still handled well. A windmill blade, though, would present a very different cross section to the oncoming air, and seriously screw up the host’s aerodynamics.
So you could mask it and put fairings on it, and by the time you’ve done that 500 times you’ll wish you’d just built a special-purpose airplane to begin with.
The Boeing Dreamlifter is literally that. There's also the Airbus BelugaXL. Taking big cargo aircraft and putting bigger cargo fairings on it has been going on since the 60s.
None are capable of a 300' length, but they're also not far off. I'm not sure what Radias gameplan here is but I'm extremely doubtful they'll be able to spin up a bespoke airframe for this one market before Boeing/Airbus have built a FeverDreamlifter or BelugaXXL off an existing airframe.
Especially with A380s to be had rather on the cheap these days.
So I’m no expert, but I’m not sure I agree. For one thing, a Dreamlifter is 235 feet long. They’d have to add nearly 100 feet to that before it fit a 300-foot blade. I think that makes it a completely different airplane.
Also I wonder about density — turbine blades are really light, and this Radias seems not to have a huge wingspan. Perhaps it’s optimized specifically for long, low-density cargo. That’s not the market that Boeing or Airbus are going for with their craft.
I would love to deliver a TED talk on the costs and issues with developing new airframes vs adapting existing ones to new roles.
However I'll leave you with an analogy. If you were in the business of delivering mattresses, would you rather have a GMC cube van that is perhaps not aerodynamically optimal and has a weight capacity that exceeds your requirements but has parts available around the world and every mechanic and driver has seen before. Or would you rather develop a custom mattress delivery vehicle that no one knows what to do with, doesn't fit in normal parking lots and can only be maintained and driven by your own specially trained team of mattress delivery vehicle specialists. How many mattresses do you have to deliver in a year before that option makes sense? What happens when GMC sees this giant mattress delivery market and pulls the box off one of their larger pickups and attaches a mattress carrying unit?
I actually know someone at radia and asked them this exact question last year. Apparently the blades are also extremely fragile and couldn't withstand the forces of being mounted on an aircraft. The problem with lighter than air is that the wind farms tend to be in places with, well, a lot of wind. Not ideal places for lighter than air vehicles.
Helicopters just aren't efficient enough, would have the same issues with wind (especially when carrying a giant airfoil), and would damage the blade if they came out even a bit out of formation.
You're right it doesn't make intuitive sense, but the people doing this are pretty damn smart and actually did think of these things!
I really don't think they did, the problems that need to be solved to retrofit existing airframes to carry a lightweight 300' load pale in comparison to what's needed to design a whole new jumbo sized airframe. Especially since once they've designed an airframe that's only good for carrying large low density loads to rough fields, then that will be the only thing it's good for.
A large wide body airliner with a big-ass shell and gravel kit retrofitted is still a large widebody airliner. Just one that happens to have a decent amount of headroom.
> The problem with lighter than air is that the wind farms tend to be in places with, well, a lot of wind.
On the other hand, an airship doubles as a crane, so there would be no need to truck it from the airfield and then crane it into place. You can deliver it directly to the rotor hub.
Countering the wind with computer-controlled thrusters would seem to be the way to go. Also, there is a large tower already there that you could use as a stabilising mast.
I was curious on some of the details, so I did a little digging.
The town in question (Salisbury, MA) is built on a narrow strip of land between a marsh and the ocean. Mostly between 2 and 5 houses wide. Doesn't seem like you need a geology PhD to determine you're going to have some erosion problems here.
As best I could determine, the beach replenishment in question was from access points 5 - 11, which covers 1.6 miles and about 150 homes. If I'm right on that, they put down enough sand to extend the beach 3-7 feet[0]. So the first thing to note is that this was a very small beach replenishment project. The senator is probably right that they should go bigger next time.
The cost per home for that would have come out to about $3333.33. Honestly, even if you triple it and do it every year, I don't find that to be an unreasonable expense to impose on owners of $1-5 million houses built on a sand dune. These guys need to quit whining and raise their _local_ taxes the relatively modest amount necessary to preserve their town. Something like $5k/year for beachfront and $1k/year for the rest would get the job done.
[0] This is assuming a constant slope to the beach. The low end is extending at 3 feet above sea level, the high end is extending at 6 feet above sea level.
I don't have evidence for this, but my suspicion is that the sand was not supposed to be long-term, but just to look impressive for suckers while the owners dump their now worthless real estate.
Contractors pay self employment taxes in lieu of the social security and Medicare payroll tax, and as a result are eligible for both.
The health insurance situation is not great, but it's available through Obamacare. In my experience the actual cost is not much worse than employer provided, but the true cost is often subsidized, so employees don't always realize how much salary they are giving up for health insurance.
No eligibility for unemployment or workers comp though.
'motivate customers to visit' - Some people like cheap stuff. Some amount of people who are not willing to pay x for a meal at noon might be willing to pay 0.9x at 2 pm. Other people have money and tight and inflexible schedules. Some of them may be more willing to visit at noon and pay 1.1x than they would be to visit at noon, wait in a 10 minute line, and pay x.
'enhance customer and crew experience' - Neither customers nor crew like it when the restaurant is busy enough that the line gets long. By making it more expensive to eat at peak times and less expensive to eat at off peak times, they think they can smooth out the demand schedule. Of course whether that's a net positive to any given consumer depends on their relative preferences on meal time, wait time, and meal cost. But the potential is there at least. On the crew side, a smoother demand schedule means they can either schedule fewer people on longer shifts, or if they keep schedules the same reduce the amount of "crunch time" during each shift.
I think what this work does is establish a new, and lower, upper bound on the number of points that need to be explored in order to find an exact solution.
From some of your other replies it looks to me like you're confusing that with an improved bound on the value of the solution itself.
It's a little unclear to me whether this is even a new solution algorithm, or just a better bound on the run time of an existing algorithm.
I will say I agree with you that I don't buy the reason given for the lack of practical impact. If there was a breakthrough in practical solver performance people would migrate to a new solver over time. There's either no practical impact of this work, or the follow on work to turn the mathematical insights here into a working solver just haven't been done yet.
This method will work but will require a large grid and consequently be quite slow. And order of magnitude or two faster than this is possible if you are clever.
Given the exercise boundary, the American Option Price can be written exactly as a one-dimensional integral. That is the key insight to this superior method.
( I'm a fixed income quant, so I didn't look for it until now.) For a more advance model than Black-Scholes, e.g. local vol I don't expect it can be extended, and one would then need use some PDE based method.
Your intuition is quite correct. These methods (Leif et al) do not extend well to different boundary or intermediate conditions that are quite necessary in real life scenarios. AFAIK, there are a few teams on the Street that do fairly advanced numerical analysis, but most resort to Monte Carlo or some statistically-informed perturbation theory.
(I wish I could talk more, but yeah, legal obligations)
Monte Carlo might be ok to OTC derivatives, however for automatic market making of exchange traded option, which are mostly American, it would be too slow.
I go through academic literature on a regular basis, hoping that some kind of really major improvement might magically appear. Usually the ideas are great, but they don’t survive real life equities markets ( from dividends to non convex payoffs, local vol etc )
Crank-Nicolson is probably the least objectionable part of the method, but I prefer ADE.
There are two numerically painful parts of the problem: the advection term and the oscillation inducing terminal condition (because it has a discontiuous derivative). I like to deal with advection by transforming the equation to an advection free equation. I'm under NDA on the best solution to the oscillatory terminal condition so I can't give that one away unfortunately.
Indeed, a transformation (of some kind) is fairly standard, including the derivation for the standard analytic solution for European options.
AFAIK, discontinuous first derivative per se may act as a seed to an oscillation due to its high frequency content that are not captured by any finite resolution algorithm (n.b. Gibbs phenomenon). But it is Crank-Nicolson that characteristically creates these oscillatory problems -- in other words, there are algorithms that can gracefully handle the discontinuity without creating oscillation.
Yeah, the discretization interacts with the oscillation for sure. Full implicit is better than CN with regards to oscillation for instance, but I don't think would be a net win. Running a few implicit steps before switching to CN might help, though I've never tried it.
Real historical data might not cover current market state.
For example, option price among other params depends on the interest rate. For the last decade interest rate was around 0% in Europe and slightly higher in US. If you train on that data only, there is no chance to "learn" option prices in the high-interest-rate environment which we saw for the last few years. Hence, you need synthetic data to learn that region of the market space.
My guess would be there's a healthy dollop of regulation pushing the German insurance market into that shape, otherwise you would probably see short-term insurers outcompeting long-term insurers since they wouldn't have to do old-age reserves and could therefore charge lower premiums. Consumers tend not to be nearly as good at rationally planning for long term expenditures as are actuaries.