The financial markets are deregulated, banks are “too big to fail”, interest rates were kept low by Alan Greenspan etc…are these the only issues that caused the financial crisis?
Malcolm Gladwell has a very interesting article suggesting overconfidence played a role in causing the bubble that eventually burst. The main protagonist in the story is Jimmy Cayne, former C.E.O. of Bear Stearns. The man was sometimes confident and perhaps over confident:
The high-water mark for Bear Stearns was 2003. The dollar was falling. A wave of scandals had just swept through the financial industry. The stock market was in a swoon. But Bear Stearns was an exception. In the first quarter of that year, its earnings jumped fifty-five per cent. Its return on equity was the highest on Wall Street. The firm’s mortgage business was booming. Since Bear Stearns’s founding, in 1923, it had always been a kind of also-ran to its more blue-chip counterparts, like Goldman Sachs and Morgan Stanley. But that year Fortune named it the best financial company to work for. “We are hitting on all 99 cylinders,’’ Jimmy Cayne told a reporter for the Times, in the spring of that year, “so you have to ask yourself, What can we do better? And I just can’t decide what that might be.’’ He went on, “Everyone says that when the markets turn around, we will suffer. But let me tell you, we are going to surprise some people this time around. Bear Stearns is a great place to be.’’
Gladwell connects overconfidence to success at some games people play in nature and refers to work by biological anthropologists. This all seems quite interesting and I can see chasing it up for fun. But he then goes on to try to connect Cayne’s overconfidence to his success at bridge – appreantly he is an excellent player and it helped him get his job at Bear Stearns. This is a disconnect. Bridge is a zero-sum game. Behavioral biases such as overconfidence lead people to make mistakes and hence lose out more than people who judge hands correctly. If Cayne is good at bridge, he must judge probabilities accurately rather than exaggerating his odds of success. This then implies that he is less likely to be overconfident than others working in finance who are perhaps bad at bridge and poker as they are overaggressive.
So, while Gladwell may have a point to make, he does not do it convincingly as his main example concerns a protagonist who is less likely to be overconfident as he is good at zero-sum games.
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July 21, 2009 at 2:18 pm
Anshu
I think you may have misunderstood the article. Gladwell points out that in Bridge, the consequences of overconfidence are almost immediate – you lose. So you learn to control your confidence in order to win.
In banking, he states that no such near-term feedback loop exists. There is no natural check on your overconfidence because it could be years before the ill-effects of your poor decision making are felt. In the absence of that feedback, its easy to think your decision-making is as sound as it was when playing bridge, even when you have instead become overconfident.
July 21, 2009 at 3:14 pm
sandeep
Hi Anshu: I agree he says that. He also says selection favors those who are overconfident is certain games. But in bridge that is not the case as it is a zero sum game. Hence, if anything, as Cayne is successful at bridge, he should be less overconfident that those who are not good at bridge.
Whether learning kills over confidence or not is debatable – if you’re overconfident you per se disregard disconfirming data. So data will not necessarily destroy overconfidence.
But you’re right that full model should have both selection and learning.
Thanks for your interesting comment.
sandeep