As I read this piece, my view was reconfirmed that no company is too big to die. Taibbi writes:
The first thing you need to know about Goldman Sachs is that it’s everywhere. The world’s most powerful investment bank is a great vampire squid wrapped around the face of humanity, relentlessly jamming its blood funnel into anything that smells like money. In fact, the history of the recent financial crisis, which doubles as a history of the rapid decline and fall of the suddenly swindled dry American empire, reads like a Who’s Who of Goldman Sachs graduates.
I had only an indirect experience with Goldman, when I was at internet ad server DoubleClick (which is now part of Google). Goldman Sachs was one of the firms that took DoubleClick public. I had stock, as all employees did, and benefited from this offering.
When the crash came—as it does for all bubbles—but which nobody ever remembers—certain “improprieties” in the IPO were discovered by lawyers representing investors who lost money on DoubleClick stock. DoubleClick and Goldman were sued.
I cannot rate the merit of these suits, other than to say that they were thick on the ground when the internet bubble burst. A point in its favor: DoubleClick, unlike most other internet startups, made money.
Not every company Goldman represented in internet IPOs did well. Worse, Taibbi says that Goldman was aware that they would not. Their line was to tout the stocks as shamelessly as the Lemon Drop Kid pushed horses.
After the film of the tech bubble was being wiped off of Wall Street, and as we all know, Goldman and other banks turned to houses and money.
When I was a graduate student in statistics in the mid ’90s, finance was huge. There were lines out the door for stochastic calculus courses. Conferences had endless sessions (sermons) on “portfolio analysis.”
“What, you’re not doing finance!?” was the inevitable question to the poor saps who didn’t have the brains to see that money was it.
The math was complicated, but not that complicated. The models could be beautiful. They made sense once you assimilated a few key equations. News twists and turns were easy to propose and investigate. The future was green.
But I could never get past the feeling that these models, and the careers that went with them, were soul-sucking. Everybody would tell horror stories of statisticians they knew that went to Merrill, Credit Suisse, Goldman and others and were worked harder than young Conan was at the Wheel of Pain1.
You made a lot of money, sure, but you had no life.
The closest I came to working in finance was in the early 2000s, interviewing for a startup that believed it had discovered a fraction-of-a-cent arbitrage model for trades to be executed before any other firms’ computers became aware of them.
Somehow the profits were going to be just larger than transaction costs: bulk trades would guarantee riches. I was to assess the performance of this model and suggest improvements.
The leader did not, evidently, enjoy my stated lack of faith in the performance of finance models in general; perhaps he worried I would bring bad luck because of this, because I never heard from him again. The company is gone (I never followed them closely after the interview), but that doesn’t mean it died: it could easily have been absorbed, and probably was, during the growth of the last bubble.
The newest bubbles are, according to Taibbi, the “bailout”:
After the oil bubble…the financial safari…moved elsewhere, and the big game in the hunt has become the only remaining pool of dumb, unguarded capital left to feed upon: taxpayer money…Goldman went right back to business as usual, dreaming up impossibly convoluted schemes to pick the American carcass clean of its loose capital.
And then “global warming”: especially the upcoming Cap & Trade legislation. “Goldman wants this bill”, he says. Not for altruistic reasons, not to “save” the planet, but to systematically cheat the public out of trillions by managing this new mechanism for speculation.
Yes, it’s a bright future for finance. Too bad there isn’t an instrument for betting on bubbles themselves: guessing the nature of them and so forth. I would make a killing.
How? Well, I have this proprietary computer model that uses sophisticated, powerful mathematics. Send me some money and I’ll tell you how it works.
1This was where he was taken after his parents, and his entire village, were wiped out.