Optimism is genetically implanted in our DNA. We are inclined to look on the bright side, to never say die, to walk on the sunny side of the street. There is no such word as 'can't,' and failure is not an option.
We believe in the triumph of the will, with all that it implies. So when we are provided with powerful technologies that promise to extend our reach while reducing our exposure to unpleasant consequences, we're in. Sign us up. Really smart people created this stuff and even smarter people are applying it. What could go wrong?
Moore's Law, named for Silicon Valley eminence and Intel co-founder Gordon Moore, essentially promised to deliver significantly increased computing power at lower cost every two years. And so far, it has. The problem is that fueling an already hubristic culture with further assurances of infallibility can lead to exaggerated assumptions.
Humans underprice risk because we have become inclined by experience - from the African savannah to the canyons of Wall Street - to believe the benefits of doing so outweigh the costs. And since much of the recent cost of such mistakes has been offloaded on the public, these inclinations are reinforced. But the flip side is that the tolerance and ability to bear these burdens has diminished. Nothing is forever. JL
Quentin Hardy reports in DealBook:
There are plenty of reasons that JPMorgan Chase had a $2 billion trading loss on a hedging strategy gone wrong — poor oversight, mismanaged risk and poorly constructed defenses. Underlying it all, however, may be a seemingly innocent culprit from the technology world: Moore’s Law.
Named for the Intel co-founder Gordon Moore, Moore’s Law is the proposition that the number of transistors on a semiconductor can be inexpensively doubled about every two years. It has proved true for almost five decades. It is the reason why your cellphone can have more computing power than NASA did when it put a man on the moon. Though not often noticed, it is also at the heart of modern financial products
Faster, cheaper computing makes it possible to create more and better models for calculating cash movements, which can be turned into trading instruments. Areas like leasing, mortgages and project finance have exploded – as has the entire financial derivatives market — thanks to cheap computing.
As a result, Wall Street has hired astrophysicists and those with Ph.D.’s in computer science just to keep up with the opportunity. But there is a dangerous downside. Another way to state Moore’s Law is that the same $1 of computing power this year buys you the capability of computing something twice as complex than what $1 bought you in 2010.
Even if budgets stay the same, there is a tendency to seek out more complex and more esoteric swaps, collateralized debt obligations, indexes and other instruments from previously unmapped parts of the economy.
These financial instruments have proved very profitable to Wall Street, so the budgets of such units have been increasing. And everyone’s competitors have their own computers, astrophysicists and financial models – making every bet even more complex.
Soon, it becomes nearly impossible to say what is going on where, and you get events like the 1998 blow-up at Long Term Capital Management, the creation and destruction of the subprime mortgage market in 2008 and perhaps even the “flash crash” in 2010. JPMorgan’s loss seems to be the latest in that series.
I recently saw former Treasury Secretary Henry M. Paulson Jr. at a conference and pointed out to him that Moore’s Law dictates that Wall Street has about four times the computing power now than it had in the 2008 financial crisis. How can we be confident that financial institutions aren’t taking on more complexity and risk than they, or anyone, can effectively model? We can’t, he said.
The best safeguards that Mr. Paulson and others have offered are more transparency in how instruments are structured; a modest tax on the instruments so people have a cost associated with the products they are creating; and rules compelling companies to hold a certain level of their own complex products.
Those are steps that might limit damage from becoming contagion. As the JPMorgan case shows, however, big losses from computer-driven trading may just be the occasional cost of business.