Tech continued to escape the brunt of the financial collapse, despite extensive business with Wall Street where some financial firms have gone belly up or are severely cutting back on spending. U.S. unemployment rates for computer and math-related professions rose from 2.8 percent in 2008 to 5.4 percent in 2009. Likewise, unemployment for architecture and engineering occupations rose from 2.3 percent in 2008 to 5.4 percent in 2009.
“It is still a very low level,” said Jed Kolko, an economist with the Public Policy Institute of California. “People in most industries and most occupations would be thrilled if their unemployment rate was 5.4 percent.”
The Texas Board of Education will vote this week on a new science curriculum designed to challenge the guiding principle of evolution, a step that could influence what is taught in biology classes across the nation.
The proposed curriculum change would prompt teachers to raise doubts that all life on Earth is descended from common ancestry. Texas is such a huge textbook market that many publishers write to the states standards, then market those books nationwide.
“This is the most specific assault Ive seen against evolution and modern science,” said Steven Newton, a project director at the National Center for Science Education, which promotes teaching of evolution.
The documentary, My Father, My Brother, and Me, is all about Parkinson’s Disease, but from a very personal perspective. Dave’s father died of Parkinson’s, his brother contracted the disease, and Dave himself was diagnosed with Parkinson’s a few years ago. It seems that Dave’s family is one of the minority of Parkinson’s patients with a hereditary form of the disease.
In the documentary, he explores the latest research on the disease, its environmental and genetic links. He talks about some promising treatments, as well as the political controversy around stem cell research. And he shows the positive benefits of exercise and dance for those coping with the disease.
You can watch the entire program on Frontline’s website, which also links to PD resources on the web.
What led to the current situation were numerous legislative, ideological, and business decisions that worked together to create a systemic failure. Consider each of the following:
- The Commodities Futures Modernization Act 2000 allowed unregulated derivatives to run wild.
- The repeal of Glass-Steagall 1999 allowed depository banks to become far more intertwined with Wall Street.
- From 2001-03, Fed Chair Alan Greenspan took rates down to unprecedented levels, causing 1 a mad scramble for yield and 2 an enormous housing boom.
- In 2004 the SEC allowed the five big investment banks to leverage up from 12-to-1 to 35-to-1 or more.
After the sub-prime mortgage meltdown and subsequent collapse of the financial system, a lot of people wondered how the credit ratings agencies got things so horribly wrong. After Wall Street firms scraped some toxic waste from the bottom of the barrel and packaged it as a new investment product, the rating agencies still gave it a AAA rating. It’s as good as a Treasury Bill!
Clearly there was a conflict of interest, and a lot of pressure to rate their favored client’s products favorably. But they were also using some really bad math from the Quants in the back room. Formulas that the traders really didn’t understand. Hey, but it’s all good, as long as everyone’s still making money, right?
The Wired magazine article: Recipe for Disaster: The Formula That Killed Wall Street shows what how things went horribly wrong. They tracked down the source of those optimistic ratings to one formula, developed by David X. Li at JP Morgan Chase. In 2000, he published the formula in a paper: “On Default Correlation: A Copula Function Approach.”
Li’s formula tried to compute the joint probability that any two instruments will both default. And it did not require any historical data – just the spot prices of credit default swaps. That speed and simplicity meant that soon everyone was using the formula.
For five years, Li’s formula, known as a Gaussian copula function, looked like an unambiguously positive breakthrough, a piece of financial technology that allowed hugely complex risks to be modeled with more ease and accuracy than ever before. With his brilliant spark of mathematical legerdemain, Li made it possible for traders to sell vast quantities of new securities, expanding financial markets to unimaginable levels.
The effect on the securitization market was electric. Armed with Li’s formula, Wall Street’s quants saw a new world of possibilities. And the first thing they did was start creating a huge number of brand-new triple-A securities. Using Li’s copula approach meant that ratings agencies like Moody’s—or anybody wanting to model the risk of a tranche—no longer needed to puzzle over the underlying securities. All they needed was that correlation number, and out would come a rating telling them how safe or risky the tranche was.
As a result, just about anything could be bundled and turned into a triple-A bond—corporate bonds, bank loans, mortgage-backed securities, whatever you liked. The consequent pools were often known as collateralized debt obligations, or CDOs. You could tranche that pool and create a triple-A security even if none of the components were themselves triple-A. You could even take lower-rated tranches of other CDOs, put them in a pool, and tranche them—an instrument known as a CDO-squared, which at that point was so far removed from any actual underlying bond or loan or mortgage that no one really had a clue what it included. But it didn’t matter. All you needed was Li’s copula function.
Of course, the formula had serious problems, as other mathematicians soon pointed out. But they were largely ignored by Wall Street firms, until things came crashing down in 2008.
In a final bit of irony, last year Li moved to China, where he heads a department of the China International Capital Corporation. He’s in charge of risk assessment for Chinese investments.
Global semiconductor sales fell about 29 percent in January amid slumping demand for an array of products that use chips, ranging from personal computers and mobile phones to automotive products.