Quantifying the Meltdown
The complexity of quantitative analysis is accelerating financial turmoil.
Will Knight 09/18/2008
- 9 Comments
The chaos engulfing the world's financial markets is remarkable in its severity and complexity. The latest stage has seen the collapse of Lehman Brothers, the sale of Merrill Lynch, and the Fed stepping in to rescue insurance giant AIG with an $85 billion loan. Today, the world's central banks pumped in $180 billion in cash in an effort to resuscitate the global money markets.
As financial turmoil accelerates, it is worth rereading The Blow-Up (requires free registration), an article that we ran in November 2007 examining the way that quantitative analysis contributed to the credit crisis that has gradually deepened ever since.
Much of what's happening currently connects back to this: the application of incredibly complex mathematical and statistical techniques to financial markets. An article in yesterday's Financial Times highlights how the failure of mathematical modeling to accurately foresee market behavior is now exposing even seemingly safe institutions such as AIG to the wider credit mess:
On a wider level, AIG failed to see how the fate of supersenior [pools of debt previously considered safe] could be linked to behaviour in other parts of the financial world. For what has made the price falls so vicious this year is that all the institutions that had previously piled this "boring" supersenior on their books have needed to sell at once. Hence the development of a vicious, downward spiral.
These institutions can hardly be blamed. This morning I spoke with Jiang Wang, a professor at the Laboratory for Financial Engineering at MIT's Sloan School of Management. He says that the models used by big financial institutions simply aren't engineered to cope with the kind of severe conditions we are now seeing:
"Quantitative models/tools have served finance well at the micro level, such as valuation techniques, trading strategies, and specific risk analysis and product design. However, they are not at the level of capturing system wide risks and dynamics, and not intended to be. Much more work and data are needed here."
Unfortunately, as the situation worsens, it becomes even harder to predict what will happen next.



JoseSmith
2 Comments
Las Vegas vs High Finance
When I was taking my first finance 101 about a quarter century ago, I asked the professor what is the difference between going to Las Vegas and high finance (…after just having learned the risk and cost analysis equation and because, to me, it looked just like gambling).
Answer was something along the line of Las Vegas was pure statistical gambling (i.e game of chance) and, therefore, investing was better and safer because our Superb mind gets in the loop and therefore can make better educated decision.
Well, our mind may make better odds however, from all the human elements that contributed to this meltdown; I can see that our mind can really really screw up things order of magnitude worse, too.
Might have been much better for everyone involved if we were rolling dice, at least you know statistical gambling has known outcome over the long run.
Reply
billcockerill
1 Comment
Re: Las Vegas vs Hing Finance
Such mistakes made by finance are explained very entertainingly in Nassim Taleb's book Black Swan. Or for free this Edge article by Taleb is very good:
http://www.edge.org/3rd_culture/taleb08/taleb08_index.html
Reply
z0rr0
99 Comments
Re: Las Vegas vs High Finance
If wealth is created through work (which most of do) and the tranfer of wealth is through gambling (Vegas style or by financier wizardry), then is the $700 billion bail-out to re-bankroll the gamblers, by making us work harder? PS: where did the pot go in the first place?
Reply