I want this to take the shape of a policy argument, so I’m going to next lay out what a prepayment penalty is, and why banning them at the federal level will not cost consumers as much as you may think. I will then flesh out why they acted as the “Equity Withdrawal” mechanism in subprime loans that banks used to bet on housing prices. However I am a little bit under the weather, so this may not get written for another few days. A humorous aside instead.
While working on this argument of how prepayment penalties formed equity for the banks betting on housing prices with consumers, I dug out my copy of this book:
The Salomon Smith Barney Guide to Mortgage-Backed and Asset-Backed Securities. From 2001. On the back cover, “The Industry’s Most Comprehensive Treatment of the Modern MBS/ABS Marketplace – From the Pioneers Who Helped Create the Market…High Credit quality and superior reutnrs have contributed to the growth of MBSs and ABSs in the institutional investment community. Let the Salomon Smith Barney Guide to Mortgage-Backed and Asset-Backed Securities provide you with the expert, in-depth treatment you need to understand-and profit from-MBS and ABS investments.”
These MBS are the giant bonds filled with subprime loans that investment banks traded to each other, that formed one of the big waves of the financial crash. Walking around holding this book feels like walking around holding the captain’s log of the Titantic. Written in 2001, as the market for these things was maturing, it’s a great primary source for the disaster. Want to take a peek inside?
1) “Mike, they didn’t really think they could just look backwards to see housing default rates?” Of course not.
Projections Are Conditional on Historical Relationships Holding Into The Future
Like any econometric model, a prepayment model is based on observed relationships over a given period in the past. There is no guarantee that relationships in the future will resemble those in the past, and significant changes could make the models obsolete (even if the input variables, such as costs, are correctly predicted). For example, competitive forces could lead to increasing refinancing efficiency in the HEL [home equity loan] market, so that the refinancing levels in a few years could be higher than predicted by current models. (p. 516)
Though a default is a prepayment, prepayment here means a refinancing, which means subprime borrowers have become more creditworthy, and have refinanced into a prime loan. This is very bad for your subprime mortgage-backed bond; it is less juiced by those subprime rates, and is now just getting interest from a boring prime rate. So a subprime borrower refi-ing is a form of risk that they are worried about. So read that again. Want to know why you don’t want to be a risk manager? Because you get in conversations like this in 2003:
Risk Manager (RM): I’m concerned that we can’t trust previous data on housing models going forward.
Head Trader (HT): Us traders are worried about that too. It would be insane for us to just assume that.
RM: Thank god. I thought I was going to have a fight on my hands. I mean, we can’t just assume previous data holds.
HT: Definitely. We are quite worried that the previous data is too pessimistic about subprime borrowers. In the future, markets will be better, and they’ll probably be able to refi into good prime loans at a higher rate than in the past.
RM: Wait what?
HT: We traders are worried your historical risk models aren’t going to account enough for the risk of high earnings prospects among subprime borrowers.
HT: Now if you’ll excuse me, I need to go get paid 80x your salary.
RM: …(drinks heavily)…
2) There’s a lovely worst-case chart on page 549, a doomsday chart, where the rate of defaults on subprime loans goes to 4%. A warning to you traders! Risk managers, hedge against the end of days, when defaults go to 5%! Of course, defaults went to, depending on how you measure it, 12-18%. Whoops.
3) And because I know you are all wondering if the golden logic of the era is written down in the book, it is.
…Although regional economic trends may be useful in explaining prepayment history and offering guidance on short-term prepayment outlook [on subprime and home-equity risks], we prefer to stay away from them when making long-term prepayment projections. The cyclical nature of local economies, coupled with the inherent difficulty of forecasting regional developments, favors a consideration of the economic environment on the national, rather than the regional level. For an investor, the best hedge against local economic fluctuations is geographic diversity of the underlying collateral. (p. 527)
Translation: prices go up and down at the state, city and county level, but there’s no way there’s would be a bubble and crash at the national level. That’s impossible. This was the rationality of the field ~2002.
These dude’s watches are worth more than your car. Click here to read “Wail of the 1%”, New York Magazine’s coverage of how much better the traders of Wall Street, who believed all this stuff listed above hook, line and sinker, think they are than you.