Thursday, November 20, 2008

Mortgage Simulation Circa 2001

In this latest crisis, one thing that really intrigues me is the degree to which everyone underestimated mortgage credit risk. I was oblivious, doing other things, but what were those in this sector thinking? I am skeptical of most of those who loudly claim to have foreseen this crisis for several reasons and I won't rehash them. But this piece estimating mortgage credit risk in 2001 highlights a common error in risk management, or econometric analysis:

To estimate the empirical survival curves, we rely on a large and geographically diverse data set from a major financial services firm. Data includes credit ratings for the borrower at the time of loan origination. Inclusion of this important variable helps ensure unbiased estimation of the coefficients of other risk factors, such as current loan-to-value ratio and changes in local unemployment rates. We should also acknowledge data limitations: it only includes loans originated during 1993-1997 time period when house prices in most (though not all) markets were stable or increasing

Sounds great, like they are just modeling cross-sectional risk, dipping their toe in the empirical pool. After all, 4 years, not including any cyclical volatility, that would be irrelevant for modeling a worst-case-scenario, and they realize this.

But then after torturing the data for 30 pages, the authors conclude with:

We find that the current regulatory standards for capital are too high in most cases.

No mention in the conclusion about the lack of a real cycle in their sample data! They knew the data's limitations, but by the end ignored them. In other words, forget about the business cycle--we have a large number of observations! I see this a lot in default modeling, where someone will look at a bunch of daily data on bonds, and say they have 400,000 observations in the default model, ignoring the fact that the ten years of daily IBM data is not 2520 observations, more like 3.

It's a common problem, mistaking the number of observations for degrees of freedom, because the correlation structure underlying the data may actually drastically reduce the degrees of freedom. Making sure your data has the appropriate sample is a big issue in all social science, as often someone will observe how college kids respond to stimuli to predict how people in general respond, assume men are the same as women. Their is no simple cure other than to be thoughtful about the specific application.

3 comments:

J said...

One research shows that property prices tend to work in 18-year cycles. There are usually 14 years of rising prices followed by four years of recession. Therefore, four year data is almost meaningless.

Anonymous said...

There's no reason why property prices should move on an 18 year 14/4 cycle.
And patterns of home ownership and finance have changed so much since WW II, that it's impossible to make any generalized statement like that. Silly, actually.

maclean said...

The mortgage rates are going downwards. Still today we can see no change in the scenario. I think the mortgage rates cannot be stabilize unless the government take some hard steps. mortgage rate trends that has being depicted in the graph can make us understand of the trouble that the mortgage industry is having in recent time. If this way the graph continues to decline, I suspect the crisis will deepen in future. What you think in near future does this crisis will end?