Reading an article Black-Scholes: The maths formula linked to the financial crash on the BBC website today, the oft-mentioned link between prosperity and global temperature came to mind (from William Herschel’s 1801 observation that when there were fewer spots, wheat prices were higher to, at a stretch, links with the Dow Jones here).
The article describes how the development of an equation and models that provided the financial world with a way out to calculate value of future options and all kinds of other financial assets led to over-reliance on such methods. Replace the terminology in places with that of climate science and you’ll get what I mean:
Stewart says the lessons from Long-Term Capital Management were obvious. “It showed the danger of this kind of algorithmically-based trading if you don’t keep an eye on some of the indicators that the more conventional people would use,” he says. “They [Long-Term Capital Management] were committed, pretty much, to just ploughing ahead with the system they had. And it went wrong.”
“It was abuse of their equation that caused trouble, and I don’t think you can blame the inventors of an equation if somebody else comes along and uses it badly,” he says.
For “more conventional people” read skeptics. And the trouble with climate models…
Predictions of the IPCC’s First Assessment Report in 1990, compared to the subsequent temperatures as measured by NASA satellites (UAH Data). Graph by Dr David Evans, reposted from Jo Nova.
…but it’s not just models.
“And it wasn’t just that equation. It was a whole generation of other mathematical models and all sorts of other techniques that followed on its heels. But it was one of the major discoveries that opened the door to all this.”
When you try to use mathematics in the service of elucidating a very complex problem, one where you have poor actual data, and you put too much reliance on the answer you get, you have a problem. Here, the issue of surface temperatures, metadata and UHI comes to mind.
The results described in the article include the collapse of a hedge fund.
But for Ian Stewart, the story of Black-Scholes – and of Long-Term Capital Management – is a kind of morality tale. “It’s very tempting to see the financial crisis and various things which led up to it as sort of the classic Greek tragedy of hubris begets nemesis,” he says.
“You try to fly, you fly too close to the sun, the wax holding your wings on melts and you fall down to the ground. My personal view is that it’s not just tempting to do that but there is actually a certain amount of truth in that way of thinking. I think the bankers’ hubris did indeed beget nemesis. But the big problem is that it wasn’t the bankers on whom the nemesis descended – it was the rest of us.”
And that’s just it with climate projections and CAGW predictions too – it is all of us who are being asked to pay the price. The difference is that a collapse of AGW predictive capability should ease the burden of tax and regulation, however it is likely that the controls enabled by ‘sustainability’ are too delicious for governments to let go.
Theres a PJTV video too (Best. Sentence. Ever.) that comments on WM Briggs’ modern aphorism “The love of theory is the root of all evil”. Starting with Steve Zwieck, it criticises CAGW supporters, and those who prefer to perfect theories and models rather than deal with the complexity of the real world. It is really worth watching.
It’s not really the theory that people love — it’s the wealth and power they can grab by exploiting the theory.
Exactly.
Digging in the Clay 
Reblogged this on Climate Ponderings and commented:
Hot Air comments:
It’s not really the theory that people love — it’s the wealth and power they can grab by exploiting the theory.
There are people who have committed themselves so strongly to the cagw theory that nothing, not even an ice age. would convince them that they could be wrong. They should be thinking more along the lines from the old adage, When you’ve dug yourself into a hole, stop digging.
That’s the trouble with gambling.
If I invent an effective model to predict – say – the results of horse racing, it only works if I don’t tell everybody about it.
If I do, and everybody starts using it, it will go wrong.
Especially if they’re all using money they’ve borrowed from other people.
As for people who purport to believe the output of computer models of open-ended non-linear chaotic systems, well….
There’s a derisible article on ABC News (where else), which in a nutshell is saying “deniers claim there’s been no warming over the last decade – that’s easily debunked by not actually looking at the last decade….” which has become a standard technique recently. The last refuge of the intellectually barren – avoid the question, confuse the issue with irrelevancies and long-term graphs which shrink the last decade to a tiny tick in the top right-hand corner, and talk about something else entirely, mostly appeals to consensus.
Climate Canard No. 2: ‘Warming Has Stopped’ — A Very Temporary Duck – ABC News
http://abcnews.go.com/blogs/technology/2012/04/climate-canard-no-2-warming-has-stopped-a-very-temporary-duck/
[Reply – That is the worst…. Verity]
The science of prediction used to be based on studying the entrails of goats.
While we laugh about such things today are we any better than the ancients when we make forecasts based on non-science (= nonsense)?
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