“These were egregious mistakes. They were self-inflicted.”
Our strategy was “flawed, complex, poorly reviewed, poorly executed, and poorly monitored.”
“Obviously we should have acted sooner.”
“It could easily get worse.”
Where have we heard this before?
Perhaps in March of 2011, when a massive earthquake and tsunami triggered a nuclear meltdown in the Fukushima prefecture of Japan. Or maybe it was April of 2010, when an explosion at a BP-operated oil rig led to an unprecedented oil spill in the Gulf of Mexico. Or it could be September of 2008, when the seemingly “too big to fail” Lehman Brothers filed for bankruptcy and threw the global economy into the worst recession since the Great Depression.
But actually the above quotes came from last week’s conference call when JP Morgan CEO Jamie Dimon admitted that the bank had lost at least $2 billion in recent derivatives trading.
Let’s face it: We’re bad at predicting crises. We never see them coming. Even when all the warning signs are flashing before our eyes.
In Dimon’s case, those warnings included public concerns voiced last month about the danger of placing a $100 billion bet in a $150 billion market, to which Dimon replied that it was “a complete tempest in a teapot.”
That’s a big friggin’ teapot.
So confident was JP Morgan that they estimated that the most they could expect to lose on this bet in a single day was $57 million. They have since revised that estimate to $129 million. Dimon conceded that the earlier risk model was “inadequate.”
Haven’t we had this debate before?
In the wake of the 2008 crisis, everyone on Wall Street admitted that their risk models were inadequate, that they didn’t consider the possibility of extremely large losses.
Yet here we are all over again.
The fact is, most of us are bad at predicting failure. We’re hard-wired to look on the bright side. It’s what neuroscientist Tali Sharot calls “the optimism bias.”
According to Sharot’s research, we tend to overestimate the likelihood of good events and underestimate the likelihood of bad events. That explains why newlyweds estimate their likelihood of eventual divorce at zero percent, despite a national divorce rate of 40 percent. It also explains why 75 percent of people are optimistic about their own family, but only 30 percent believe that families in general are better off than they were a generation ago.
Basically, we expect bad things to happen to other people, but not to us. Certainly this principle applied to JP Morgan where Jamie Dimon was hailed as the genius risk manager who steered the company away from the worst of the subprime debacle.
Upon learning of Sharot’s research, one fire captain told her, “Fatality investigations for fire-fighters often include ‘We didn’t think the fire was going to do that’ even when all the available information was there to make safe decisions.”
The same could be said about a wide range of disasters, from the Space Shuttle Challenger to the hedge fund Long-Term Capital Management, whose ill-fated gamble was eerily similar to JP Morgan’s. We really have been here before.
It’s brutally difficult to shatter people’s illusions. When people estimated their likelihood of getting cancer at, say, 10 percent, and Sharot informed them that it’s actually closer to 30 percent, they refused to raise their prediction above 11 percent. Science be damned.
In a way, that’s a good thing. Optimism makes us happier, and it makes us work harder. But it also exposes us to unnecessary dangers.
Sharot likens the predicament to jumping off a cliff. The optimist takes the plunge and may plummet to his death. The pessimist stays on the cliff and never experiences the joy of freefalling. The realist jumps off…with a parachute.
JP Morgan needs a parachute. We all need a parachute. Which is why regulations like the Dodd-Frank Act exist: To protect us when we accidentally jump off a cliff.
Let us not make the mistake of cutting the cord, as House Republicans are currently trying to do.
This op-ed was published in today’s South Florida Sun-Sentinel.