David Kirkpatrick

December 8, 2008

The financial crisis and math

Yep, it’s a release dump day. For any regular reader who wonders why I’ll post a press release, sometimes without any real additional commentary — you’d be amazed at how much “reporting” at news websites and even print news outlets are nothing more than reworked press releases, often without any new information added.

Years ago when I did daily reporting for LocalBusiness.com as a freelancer I did nothing more than get a release from my editor, try and get an interview with a principal at the company putting the release out there and writing a story within a couple of hours at most.

If I couldn’t secure an interview I’d do the story purely off the release with maybe some info pulled from the company’s website for filler. Rough estimate would be 70% of my stories done for LocalBiz were of this variety.

This is why I present my blog readers unadulterated releases. I give you the entire story as presented by the source. Sure it’s been spun up by the PR writer, but you get the whole picture without me trying to un-spin anything or maybe leaving something out that you’d really enjoy.

With that in mind, here’s a release on this year’s ongoing financial crisis from the mathmatical perspective. Not sure if I totally agree with the first sentence there.

The release:

The crash of 2008: A mathematician’s view

Markets need regulation to stay stable. We have had thirty years of financial deregulation. Now we are seeing chickens coming home to roost. This is the key argument of Professor Nick Bingham, a mathematician at Imperial College London, in an article published today in Significance, the magazine of the Royal Statistical Society.

There is no such thing as laying off risk if no one is able to insure it. Big new risks were taken in extending mortgages to far more people than could handle them, in the search for new markets and new profits. Attempts to insure these by securitisation – aptly described in this case as putting good and bad risks into a blender and selling off the results to whoever would buy them – gave us toxic debt, in vast quantities.

“Once the scale of the problem was unmistakably clear from corporate failure of big names in the financial world, banks stopped lending to each other,” says Bingham. “They couldn’t quantify their own exposure to toxic debt – much of it off balance sheet – so couldn’t trust other banks to be able to quantify theirs. This led to a collapse of confidence, and the credit crunch, which turned a problem in the specialised world of exotic financial derivatives into a crisis in the real world. Once the problem became systemic, government had to step in to bail the system out with vast quantities of public money.”

Professor Bingham suggests that to learn more and predict financial future, we should look to our past, likening the current crisis to the ‘Tulip Mania’ in the Netherlands in 1636 where huge prices were paid for futures in tulips, which then turned out to be as worthless as sub-prime mortgages today.

Even Alan Greenspan, the long-serving former chairman of the US Federal Reserve, admits that mistakes were made in the past. To avoid repeating these mistakes, we need to learn from them. This needs a new mind-set, new policies, and much more proactive regulation.

Bankers complain that the risk models they used predicted problems as dramatic as today’s only every few centuries. “This is like talking about the details of how to steer a boat on a river,” says Bingham, “what matters there is whether or not the river is going to go over a waterfall, like the Niagara Falls.”

 

###

Leave a Comment »

No comments yet.

RSS feed for comments on this post. TrackBack URI

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: