Quote of the Day, II and III
By Arnold Kling
The highly quotable Nassim Taleb has a new essay.
In some situations, you can be extremely wrong and be fine, in others you can be slightly wrong and explode. If you are leveraged, errors blow you up; if you are not, you can enjoy life.
Taleb has a message for Robin Hanson:
“prediction markets” are for fools. They might work for a binary election, but not in the Fourth Quadrant.
The fourth quadrant refers to a matrix where payoff functions are either simple or complex and probability distributions are either well-behaved or highly skewed.
In the first quadrant, the payoff function is simple and the probability distribution is well behaved. When Tony LaRussa orders a squeeze bunt, he is making a decision in the first quadrant.
In the second quadrant, the payoff function is simple, but the probability distribution is highly skewed. If you buy a backup generator, you know what the benefits will be if the power goes off. But it is difficult to estimate how much use you will get out of the backup generator, even based on past data on the number of power outages in your area. The longest power outage you have experienced in your lifetime is not the upper-most estimate of the distribution.
In the third quadrant, the payoff function is complex, but the probability distribution is well behaved. To me, bets on football games seem to belong in this quadrant. I don’t understand the payoff structure that the guys on the radio are talking about (“I’ll give the three.” “I’ll take the under.”) I don’t know what any of it means, and I don’t really care, but I’m assuming it’s more complex than just betting on which team is going to win. However, my guess is that the underlying probabilities are well behaved. It is in this quadrant where Taleb grants that “statistical methods work surprisingly well.”
Finally, we have the fourth quadrant, where the payoff function is complex and the probability distribution is not well behaved. Taleb’s point is that too many finance people are eager to play in the fourth quadrant, believing that they are in the third quadrant.
Taleb wants to argue that the current mortgage meltdown is a case of financial firms playing in the fourth quadrant without realizing it. House prices behaved in an unprecedented manner, and people were caught unprepared.
I will grant that people were caught unprepared, but I do not think that the recent house price declines are outside what seemed plausible based on historical experience. I think that what happened in the mortgage industry is that we moved from the first quadrant to the third quadrant, and then folks decided not to use the statistical models that had worked well for years in mortgage default analysis.
When you make loans with a 20 percent down payment and all the risk of default is held by one institution, the payoff function is relatively straightforward. When you make loans with little or no down payment, and you create “structure securities” in which the default risk is split unevenly, the payoff function gets really complex. In an adverse environment, nobody knows what the securities are really worth. That is why all those mortgage securities today are trading at such a huge discount relative to what is likely to be their fair value.
I think that the Foster-Van Order model worked fine for assessing mortgage risk. It’s just that Wall Street used something different, and Freddie Mac’s CEO decided that the Foster-Van Order model was getting in the way of Freddie’s mission to support affordable housing.