this is John Geanakoplos again. Here to give a lecture,
that I gave one evening, that we couldn’t record.
So I’m going to try and
reproduce the lecture as faithfully as I can.
And I think it’s a historical
lecture. I hope you find it interesting.
It’s about the history of the
mortgage market. And I call it a personal
history because by some accident, I participated at many
of the key points in the recent history of the mortgage market.
So I started off in 1989.
I was professor here at Yale.
I was a mathematical economist.
I thought of myself as using
mathematics to study economics and staying really pretty much
as far from the real world as I could.
But for some reason,
I decided that I wanted to see what was going on on Wall
Street. The most interesting
mathematical modeling of that day was being done on Wall
Street. And mathematical modeling and
finance, that is in economics. And so I decided.
why not go see it?
And so I visited a bunch of
investment banks. A number of my friends,
including one from Yale, had worked at Goldman Sachs.
So that was the natural thing
to do. But, I had a little cousin who
had just been hired recently, a little bit before that,
at Kidder Peabody, which was sort of the number
seventh investment bank at the time,
in terms of size. And he introduced me to the
fellow, Ed Cerullo, who ran fixed income at the
time. And they persuaded me that it
would be much more interesting to go to Kidder,
Peabody and to talk to people like Ed Cerullo,
than go to Goldman Sachs and be one of a hundred visiting
professors. So I decided that the firm was
a little bit smaller, but I would see more of it.
And why not do something a
little bit different? So they never had an academic
visitor, I think, like me spend a year there
before. So I went in 1989 to 1990.
And while I was there I talked
a lot to Ed Cerullo and to the traders and to a bunch of other
people. And at the end of the my
sabbatical, Ed Cerullo came to me and he
said, you know I’ve come to realize that our fixed income
research department isn’t very mathematical.
Why don’t you hire a research
department for me? And I’ll help you along.
But, you find the people,
you know the subject, you can judge,
your business is judging people doing research,
why don’t you hire me a research department?
So I hired him a research
department, which ultimately grew to 75 people.
And I returned to Yale.
And after I got back to Yale,
he called me up and he said, now that you’ve hired the
research department, you have heads of all these
different groups, why don’t you run the research
department? You can do it from Yale,
as a consultant. And so I became the head of
fixed income research at Kidder Peabody from Yale.
And it was quite an experience.
I hadn’t realized,
when I accepted the job, just how many complications
would arise. How many people would get job
offers from other places and want to leave.
And how many models wouldn’t
work. And then there’d have to be a
wild scramble to fix it. But anyway, that placed me at
an investment bank, that would become one of the
key players in the mortgage market.
Now in the mortgage market,
well who are the players? They are the homeowners you all
know about. They are the banks who are
giving mortgage loans. But then there are a number of
other players that are invisible to much of the public,
which really dominate the market.
There’s the government
agencies, Fannie Mae and Freddie Mac, which you’ll hear a lot
about. There are the investment banks,
like Kidder Peabody and Goldman Sachs and a bunch of others.
There are the hedge funds and
there are other investors. And this group of people
creates a gigantic hierarchy, an invisible market,
that’s on the same size, the same scale,
as the stock market. So I think in that time,
1989,1990, if you’d asked anyone in America practically,
what’s an important financial market?
They would have said,
the stock market. What’s another important
financial market? Corporate bond market.
What’s another one?
Well, foreign exchange market.
What’s another one?
I don’t think anyone would have
said the mortgage market. Or at least they wouldn’t have
said it very early on in their list of important financial
markets. But in fact,
as I’m going to try and tell you during this class,
the mortgage market is not only on the same scale as the stock
market, but actually quite a bit more
complicated than the stock market.
More mathematical than the
stock market. And in some ways,
more interesting than the stock market.
And as we’ll see at the end of
the course, it was the mortgage market that led to the greatest
crisis we’ve had since the depression.
And in fact,
caused several similar crises before that.
So mortgages appear at the
bottom. You have homeowners living in
their houses who need to borrow the money to buy the house.
Before they can live in the
house they have to get the money to buy the house.
So they borrow the money by
taking out a mortgage. And it’s a bank or a thrift or
somebody like that who lends the money.
That’s the first step.
So a mortgage is just a promise
to pay the loan back over a long period of time using your house
as collateral. An important part of mortgages
is that you have an option to pre pay the mortgage.
I mean, what if you move?
The mortgage is,
say, a 30-year promise. And after three years,
you might want to move. So, if you’re gone from the
house, the house can no longer serve as collateral because you
don’t live in it anymore. So there has to be some way of
getting out of the mortgage. And so there’s an option to pre
pay it. Now, in the United States,
that option can be used even if you stay in the house.
And it turns out to be one of
the more problematic aspects of valuing mortgages.
And one of the most interesting
aspects of valuing mortgages. We’ll come to that later.
So this idea of a mortgage,
those three ideas, were already known to the
Babylonians more than 3,000 years ago.
So the mortgage is not a recent
invention. It wasn’t invented after the
industrial revolution. It was invented more than 3,000
years ago near the Middle East. So, it’s stayed pretty much the
same for most of those 3,000 years until the 1930s when the
amortizing mortgage was invented.
So what happened in the 1930s,
that was the time of the Great Depression and farmers had lots
of mortgages and they would owe, $7.00 a year,
say, as their interest payment. And at the end of 10 or 15
years, they’d have to pay $107, that is they make their
interest payment. And they pay back the balance.
What’s called now a balloon
payment. That’s how a typical bond works.
Well, of course when things got
really bad, a lot of them defaulted.
they chose to default just before the $107 payment.
So seeing that,
mortgage lenders decided that it would be much safer to make a
flat mortgage loan where the payment was say,
$8.00 a year for all of thirty years.
Now, you pay a little bit more
each year for 29 years, but then you continue to pay
the $8.00 the 30th year. But you see,
if you add up all the extra payments and you realize that
there’s discounting, the $107 way off in the end
isn’t really that much money when looked at from the
beginning. And so by paying $8.00 every
year, you can get the same present discounted value of
paying $7.00 29 years and $107 the 30th year.
So that’s called the amortizing
mortgage. It makes the lender much safer
because after a bunch of years have gone by,
the house presumably has gone up in value.
Or even if it hasn’t gone up in
value, the remaining payments are much less because so many
have been made that the balance has been amortized.
And so actually to get out of
your mortgage, you need to pay less than $100
back. So this amortizing mortgage is
something we’re going to study mathematically in the next
lecture. But now, I just mentioned that
was one of the big innovations, which made the mortgage market
much safer than before. Well so things continued pretty
much the same from the 1930s all the way to the 1970s when we had
securitization. Like many of the great
financial innovations in history, this one was created by
the government. So Fannie Mae and Freddie Mac
were government Agencies They were created by the government.
They then became eventually
separate from the government. But they were given the task,
they were created for the purpose, of making mortgage
pass-throughs. So we’re in the 1970s.
So mortgage pass-throughs are
the second tier of this hierarchy.
So the banks who had lent the
mortgage, remember when you take out a mortgage as a homeowner,
you’re selling your promise. You’re getting the money by
selling your promise to pay back later.
So those promises are collected
by the banks. And instead of just sitting on
the promises, the banks now,
with Fannie Mae and Freddie Mac could sell their promises to
Fannie Mae and Freddie Mac. And Fannie Mae and Freddie Mac
would put them together in gigantic pools called pass
through pools. Why were they called
pass-throughs? Because the mortgage payments
the homeowners made would go to the banks and the banks would
just pass them on to the pools. And then the pools would
collect the money and pass that money on to the shareholders.
So the ultimate lenders to the
homeowners are the people who buy shares in the Fannie and
Freddie pools. So the banks appear to the
homeowner to be lending the money.
they’re not lending it all. They are the middleman.
And so they collect the money
from the homeowner and they send it on to the actual lender,
who’s the shareholder of the pool.
And the banks are also the
servicer, really. They’re getting paid a fee for
collecting the money and writing threatening letters if the
homeowner stops paying. And as we’ll see later,
throwing the homeowner out of his house if the homeowner
doesn’t pay. So Fannie and Freddie played an
extraordinarily important role in the mortgage market.
First of all,
not any mortgage could be sold into these pools.
They had to meet strict
criteria. You had to have a good credit
rating. You had to have a job.
You had to have all sorts of–
sorry about this, I’m going to have to shut off
my cell phone. So the loan to value of the
mortgage had to be, that is if the house is worth
$100, the loan could only be 80% of it.
You had to have a record of the
job you had and so on. So this was very standardized
and very high performing loans. You could contrast with,
say, to the world that you might have seen in the movie
It’s a Wonderful Life. So in the movie It’s a
Wonderful Life, you remember Jimmy Stewart runs
a thrift and he makes mortgage loans.
And people come to him and they
say we want a loan. And you know one guy comes and
says he wants a loan. Jimmy Stewart says,
well do you have any collateral?
No, I haven’t built the house
yet, you know I’m trying to build the house.
Do you have a record of
employment? No, I just moved here,
I don’t have a job yet. Do you have someone who can
vouch for you? No.
Do you have a credit rating?
There’s no such thing as credit
rating. So then Jimmy Stewart looks
into his eyes and realizes this is a good honest person and
gives him a loan. Well, that doesn’t happen in
the Fannie Mae and Freddie Mac pools.
They’re very standardized
criterion. And that guy,
Martini who got the loan from Jimmy Stewart would never have
gotten a conforming Fannie or Freddie loan in the 1980s or
1990s. Might have gotten one in the
2000s though, but we’ll come back to that.
So that kind of market is very
much like the kind of market in the Jimmy Stewart movie,
It’s a Wonderful Life, that gets created in his
fantasy. Where you know,
the town gets taken over by the evil banker and that evil
banker, whose name I’ve forgotten at
the moment, but that evil banker basically
is creating the kind of loans, almost, that we’re talking
about now. Everything’s mechanized and
standardized. Of course with standardization
you get tremendous advantages. For one thing,
these loans being pooled together and being of the same
general good quality, they allow the lenders,
instead of lending to a bunch of homeowners in Peoria like the
bank would do, now all those Peoria loans are
stuck with a bunch of other loans from all over the country
in the same big Fannie pool. And so the lenders,
who are the shareholders, have diversified their risk.
If the big businesses in
Peoria, Illinois go under, it might be that all the
homeowners in Peoria will default on their mortgages.
But not in the Fannie and
Freddie pools, because those are loans from
all over the country. So it would have to be that
businesses all over the country went bad for those loans all to
go bad. So secondly,
if you’re getting a whole pool and there’s an automatic
criterion for getting into the pool,
you don’t have to worry that you’re getting the worst loans
or the cheatiest loans or something.
You know the quality,
the general quality, of all the loans.
And once you have shares in a
pool, you can resell the shares. So a bank who has to study the
homeowner and you know have meetings with them.
And you know,
Jimmy Stewart had to look into his eyes.
So Jimmy Stewart may have
convinced himself the guy is a good risk, but how could Jimmy
Stewart ever sell the loan to somebody else.
The other buyer,
who hasn’t looked into Martini’s eyes,
he’s never going to believe Jimmy Stewart that that’s a good
loan. So Jimmy Stewart is going to be
stuck with that loan for 30 years.
In the Fannie and Freddie
pools, the shareholder who buys the loans and knows they’re
standardized knows exactly the same thing as the next guy who
might buy his shares from him. So if the shareholder will be
willing to pay more for the loan,
because he knows that if he needs cash,
he doesn’t have to wait 30 years, he can just sell his
shares to somebody else. So because of the
diversification, because of the reduction in
adverse selection, and because of this ability to
resell the shares, lenders, that is shareholders,
are willing to pay more for the mortgages.
And so the mortgage rate went
down. So, I’ve estimated that this
operation together with the next one I’m going to talk about,
has reduced mortgage rates by at least a percent.
So if you think the average
loan is $200,000, you’re talking about $2,000 a
year that the average homeowners save by this financial
innovation. So securitization seems to have
been a great boon. Now in 2002,
when I made these slides, I’ll just give you an idea of
the size of the mortgage market. And you have to double all
these numbers today, pretty much.
So you see that you know the
stock market was around $15 trillion and the mortgages
around $7 trillion at the time. And you know that compares to
$2 trillion for corporate bonds or $3 trillion for treasuries.
You see how big the mortgage
market was then, and now it’s twice as big.
It’s the same size basically as
the stock market, which hasn’t really grown since
then. So, I don’t have time to talk
about this. But, of course,
of the mortgage market, some of it is commercial,
some of it is residential. The vast majority is
residential. But there’s a very big
commercial mortgage market. I’m going to be talking mostly
about the residential mortgage market.
Some of these mortgages are in
fact held by the banks without selling them to Fannie Mae and
Freddie Mac. But a lot of them are
securitized just in the way we talked about.
And they’re going to be private
securitizations later that we’ll talk about.
And so now that securitized
part is $10 trillion. I’ll give the numbers,
recent numbers, later.
So actually that may be a
little bit big. The $7 trillion,
the securitized part of the mortgage market.
So in 2002, the agencies
dominated the security market. The securitized loans were
almost all Fannie Mae and Freddie Mac.
There’s also another agency
called Ginnie Mae, but there was another part of
it, which were jumbo loans. So there was a size limit.
The loans couldn’t be too small
and couldn’t be too big for these Fannie and Freddie pools.
The government was trying to
appeal to the middle class. Establish homeownership in the
reliable middle class. And so the wealthy who were
buying million dollar homes weren’t able to get their loans
sold into a Fannie or Freddie pool.
And so those loans were
securitized the same way, but by private agencies and not
by banks, by investment banks, and not by the government.
And that at the time,
in 2002, was half a trillion. We’ll come to all these numbers
later. When we say today’s numbers.
So the next innovation after
the 1970s, came in the 80s and that’s the collateralized
mortgage obligation market. CMOs, they are called.
So the investment banks like
Kidder Peabody and Lehman Brothers, for example,
would buy some of these big pools.
And then they would cut the
pools, which were just pass-throughs.
So the pools just passed
through the money that the homeowners were giving them.
So maybe they were passing
through $1,000 a month as the promise.
Well, say Kidder Peabody,
might buy a pool promising $1,000 a month to the
shareholders. And then cut the promise into
two pieces. Maybe a floater,
which would pay $500 plus the interest rate.
And so when the interest rate
went up, the payments would go up, that’s why it’s called a
floater. And maybe a second piece called
an inverse floater, which is $500 minus the
interest rate. So as the interest rate went
up, the payments would get smaller.
But as the interest rate went
down, the payments would get bigger.
That’s called an inverse
floater. So that way the two add up to
$1,000. But now, you can appeal to two
different buyers. A buyer who needs the money
when interest rates go up would buy the floater.
A buyer who needs the money
when interest rates go down, would buy the inverse floater.
So by creating out of plain
vanilla promise, two more tailored promises,
you can target more sharply a clientele.
And therefore get probably more
than half the money for each of the two pieces.
And that way,
of course competition in the CMO market raises the amount
people are willing to pay for the pass-throughs.
Because they can then buy them
and split them up. And sell them for more.
So that raises the price of the
pass-throughs, which in turn raises the price
that the homeowners can sell their mortgage,
which in turn lowers the interest rate that the
homeowners have to pay. So again, it’s another reason
why this whole operation of securitization improved the
welfare of almost everybody. So, the pieces gradually got
more complicated So if there was default or somebody prepaid,
as we talked about, used their option to pay early,
instead of getting the money you expected,
you get extra or less money than you expected.
That created risk.
And some of these buyers didn’t
want to bear the risk. So maybe you’d make the pieces
$400 plus the interest rate and $400 minus the interest rate.
And leave $200 to what might be
called a residual piece or a derivative or something.
And that $200 would bear the
risk. So if someone defaulted,
you take it out of the $200 piece and not of the first two
pieces. So that split up,
again, made the floater and inverse floater safer and
encouraged people to buy it. But of course,
somebody had to buy the residual piece,
which was more complicated. So, as I said,
this whole operation was a way of accomplishing two things.
It made homeowners able to sell
their promises for more. So they effectively were paying
a lower interest rate. So it made it easier to move
into houses. And that’s precisely what the
government intended by creating these agencies.
It also allowed buyers and
investors to get money in the cases they needed it,
in the states they needed it. Because the pieces were tailor
made for them. So I realized,
while I was there at Kidder Peabody,
that this whole multi trillion-dollar operation behind
the scenes was, as I said, invisible to
everybody and was worth writing about.
It was bringing great welfare
gain to the country and nobody quite knew about it.
So for me, it crystalized what
the essence of finance is. The essence of finance is
you’re trying to create promises,
the financial system is creating promises,
that deliver money to people in circumstances or states as I
call it, that they really need the money.
But of course,
you have to guarantee that the money is going to be paid to
them. So in order to do that,
you have to have collateral. So this entire system is a way
of creating promises and backing them with collateral.
So if you remember,
here are the potential promises, and maybe some people
want money down here. That’s when the interest rates
go up, they’re buying the floaters.
Way over there,
the money’s going down, the interest rates are going
down, that’s the people who buy the inverse floaters.
That’s when they’re getting
most of their money. But these promises,
you have a reason to expect to get paid, because they’re backed
by the collateral. OK, so this is not a very good
picture. The houses backed the promises
of the homeowner like in Babylonian times.
If the homeowner doesn’t pay,
he loses his house. Then those mortgages
themselves, those mortgage promises, are backing the pools,
which are selling shares to the shareholders.
But those shares are backing
the CMOs, which are making more complicated promises.
So the collateral you see is
used once by the homes, once by the pools,
once for the CMOs. And then it will turn out,
as we’ll see in a few minutes, that the investors who buy are
borrowing money, buying on margin,
using the CMO pieces they buy, as collateral for their
purchases. So the collateral is being used
and reused. And so in fact,
the entire system is stretching the available collateral as much
as possible. So collateral is a very scarce
resource. It’s very important to running
a financial system. Many developing countries don’t
have any collateral. And therefore they have a
primitive financial system. Here, there’s a tremendous
incentive to stretch the collateral as much as possible.
You can stretch it by using it
over and over again or by letting the same collateral back
many promises. We saw both of those,
the tranching, the different CMO pieces,
and the pyramiding, the using the same collateral
over and over again. So I wrote my first paper,
published it, in 1997.
I had written it while I was at
Kidder Peabody. And one of the questions I
asked was, when you take out a loan,
not only what interest rate do you have to pay,
but how much collateral do you have to put up?
And that was a question that
nobody seemed to have asked really before,
in a general equilibrium model. So that was my first paper on
the subject. I want to get back to Kidder
Peabody. Kidder Peabody,
as I said when I started, was a sleepy number seven
ranked investment bank. Didn’t dominate any market.
But it came to completely
dominate the CMO market. So this, as I said,
was a multi trillion-dollar market.
And if you look at all the
pieces that are being promised here,
what Kidder decided to do was, things got more and more
complicated, there weren’t just two pieces,
there weren’t just three pieces,
there were 90 pieces typically at that time.
And so a typical investment
bank that wanted to buy a pool and sell these CMO pieces.
Like let’s say,
Salomon or First Boston, they were the ones who first
did these CMOs. They would try to line up 90
buyers and figure out what each of the 90 were willing to pay.
And then when they added up the
prices each of the 90 willing to pay,
they’d go and if they thought the sum of those was bigger than
the price in the pool, they’d go to the pool and buy
the pool. And then immediately make a
profit by selling off the 90 pieces.
Well, at Kidder,
the head of mortgages, who by this time by the way,
was my young little cousin, who through hard work had
worked his way up to running the small CMO operation.
He got the idea that what
Kidder could do, was to find a buyer for the
riskiest piece. The one that I’ve put in
yellow, remember, the residual.
Which was maybe called an
inverse IO, it had different names, but the riskiest pieces.
Once he found the buyer,
a place to put the riskiest piece,
he would borrow the money to buy the pass through,
and hold an inventory of all the other pieces.
So he knew, that eventually,
we would be able to sell off all the other pieces.
And so we had a tremendous
advantage. While everyone else was looking
for buyers for 90 pieces, we had to find a buyer for one
piece or two pieces. So we then had an inventory of
88 pieces, say, to sell.
And as we did deal after deal,
that inventory would get bigger and bigger.
So our sales force would have a
much easier time selling a piece.
We wouldn’t have to call
someone up and say, do you want piece number four,
that’s the one we’re trying to get you to buy.
We’d call up and say we’ve got
a huge stock of different kinds of pieces, of all kinds,
from all kinds of deals. Maybe you’re interested in one
of them. So it’s much easier for a sales
force to sell with that situation than it was for the
other investment banks to sell. So of course,
we lured away some of the best sales people.
So of course,
the down side to all of that is we had to be very careful that
the pieces we held, we knew how to hedge.
We had to be very careful that
when we held all these pieces, between the time we held them
and finally sold them, we didn’t lose a lot of money.
And sometimes we were the ones
who held the most dangerous piece, too.
So we had to figure out what
were going to be the cash flows of these pieces and how to model
them. And that’s what we’re going to
mathematically talk about the next few days.
But I’m going to give you a
hint of this now. So we had to predict,
among other things, what the prepayments would be,
OK. And so, if you talked to a
macro economist, especially in those days,
and you say, what do you think is going to
happen in the world? They’ll usually say,
well I think in the next two quarters,
unemployment is going to go up half a percent,
and then maybe things are going to get better for the next year,
and beyond that it’s too hard to tell.
So these mortgages are 30-year
mortgages. You can’t have a prediction
that lasts a year and a half, you have to have a 30-year
prediction. And the macro economists,
by the way, are typically wrong.
Even in their two-month
prediction or six month predictions.
So how can we risk billions of
dollars holding an instrument that’s 30 years long,
which depends on what people are going to do over the next 30
years? Well the answer is you can’t
make a prediction and expect it to be right.
But you can make a conditional
prediction. You can say,
if interest rates do such and such for the next four years,
and housing prices do such and such for the next four years,
then in that fifth year, pre payments will be so and so.
That’s a conditional prediction.
It’s much easier to make a
conditional prediction than an unconditional prediction.
It’s shocking that so many
economists are lured into making unconditional predictions.
It’s not a business we should
be in. We should always be making
conditional predictions. Well, I learned that lesson at
Kidder. So, you know,
the idea of possible worlds is going to play a central role in
our course from here on out. And the possible worlds are the
paths of interest rates or home prices.
And so here’s a very short,
this is maybe a one year into the future, and we’d have to go
30 years in the future. As you can imagine,
and this is just actually a much smaller group of
possibilities than we used to consider.
But, you see all the
possibilities that could unfold over the next 12 months.
And you see the blue line is
one of those possible paths. So we have to predict,
if we knew which path interest rates and housing prices were
going to take, like that blue line,
could we then predict, at the end of the blue line,
what pre payments would be. Of course, if you followed
another path down to here, we’d make a different
prediction about pre payments. So, the cash flows are the pre
payments and defaults. That’s what we have to predict.
And so, you might say,
what good is it to predict a different number on each of
these trees. Then basically what you’re
saying is you don’t know what’s going to happen.
But that’s far from the truth.
If you know what the payments
are on each of the paths and then you can hedge those paths.
So for example,
suppose the payments are very low here and very high at the
top. Well, if you can buy another
instrument that pays you something at the bottom,
and you pay at the top, you can offset the variation in
cash flows and the mortgage by that other instrument and
guarantee yourself the same safe payment all the way through.
That’s the sort of thing that
we did it at Kidder Peabody, which we’re going to study in
great detail. We held these complicated
pieces whose payments would vary tremendously.
So we ran a huge risk of losing
all our money. But then we would hedge them
with some other instruments. So in the end,
we’ve got a pretty safe return. And because we knew the return
was safe, we felt we could pay up a good amount of money for
it. Whereas other buyers who
couldn’t hedge it, wouldn’t want to buy it at all.
So, now let’s just see how good
the predictions were. Here’s a typical history of pre
payments. So you can see it ranges to 99
from 88, something like that. So it’s 10 years,
11 years, of pre payments. So that’s the percentage of
people who prepay every year. So it’s the annualized
percentage. So every month,
you check how many people paid off their mortgage early,
and you assume that rate stayed the same for the whole 12
months, what would the pre payment
percentage be? That’s what the number measures
all the time. You see in some months it’s
practically zero. These are pre payments for a
mortgage issued in 1986 that had an 8% coupon.
So all basically,
1986 mortgages with an 8% coupon issued by Fannie Mae or
some big pool of them anyway. So you see sometimes the pre
payments are very low, sometimes they’re incredibly
high. How standing at the bottom at
the back there, in ’88 say, could you possibly
have predicted that pre payment going forward?
You know with the ups and downs
and stuff like that. Well you couldn’t,
if you made it unconditional. But if you made it conditional,
it’s not so hard. Because what do you think
happened in ’93 that made pre payments go up so high?
It was interest rates went down.
Homeowners had an opportunity
to refinance at a lower interest rate with a different mortgage.
So of course they did that.
And in those other months,
when pre payments are very low, the interest rates were higher.
So clearly, there’s a
connection between the mortgage rate you got and your original
mortgage and the new rate that you can refinance into.
And that is part of your
conditional prediction. But another thing that’s
interesting is burn out. So if you look at two pools,
one issued in ’95 and one issued in ’92,
and with exactly the same coupons, you’ll see that the
older one is always pre paying less than the new one.
At least starting from ’95
onward. So it’s as if the old one burns
out. Once it has an opportunity to
pre pay, you see a lot of pre payments and then they slow
down. So that’s another thing people
had observed. So you might have thought the
standard way of modeling things at that time was to just do a
regression. You say, well we figured out
that pre payments depend on the new interest rate and how much
more in the money you are. And it depends on how long
you’ve been in the money because of the burn out.
You try to estimate a curve,
like an S curve or something, that depends on parameters,
that’s on the interest rate, and on the burn out.
How long you’ve been in the
money. And according to some
parameters that described the S and you tried estimate those
parameters. So that would be an old
fashioned way of measuring things.
But as we’re going to see in
this course, we look at everything from an agent based
approach. So what are the individual
agents doing? So, I got the idea of trying to
model all you care about is aggregate pre payments,
what is the whole pool doing? But I decided,
let’s try and predict every single homeowner.
So let’s try to put ourselves
in the mind of every homeowner in the country.
Why are they pre paying or not
pre paying? Well, they’re pre paying if
they get an opportunity to save some money.
But, we know from that graph
that lots of people don’t prepay.
Even when there’s a tremendous
opportunity, only 60% percent of the people are pre paying in a
whole year. So that means the whole year
goes by, and only 60% percent of them have prepaid.
So every month,
8% or 10% are pre paying. So the other 90% haven’t seen
their opportunity. They’ve missed it or they’ve
waited. So clearly, not everybody jumps
at the opportunity. So it must be that people are
different somehow. Even though they’re in exactly
the same circumstance in terms of refinancing.
So, you have to account for the
difference. So, I imagined that different
people have a different cost of prepaying.
It’s a hassle to prepay.
Maybe you literally have to pay
some money to prepay. Maybe you have to take a day
off from your job. Some people have other things
to do. They’re not that alert because
they’re paying attention to their kids or they’re paying
attention to their work. So not everybody has the same
alertness. And not everyone follows
financial matters as closely as everybody does.
So, also over time,
people are getting more rational and beginning to
understand the market and pre paying more and more.
And of course,
people hear from their friends. If their friends are all
prepaying, it’s more likely that they’ll think about it and
prepay themselves. So I built a model,
together with the researchers at Kidder Peabody.
And then later we built the
model of pre payments based on every individual making a
different decision. So an individual is
characterized by his cost and his alertness.
So different individuals have
different costs and different alertness.
And by watching how they
behave, we can come to guess what the cost and alertness is
of each of these people. So you see this model captures
all the effects that we talked about already.
If you have a pool of people,
you can see the vertical is how many people of each types.
So there are different costs
and different alertnesses. And so at the beginning,
when you have a new pool, like on the right,
there are a lot of people. And as, they get opportunities
to refinance, it’s not random people who
prepay, it’s the people with the highest alertness and the lowest
cost who prepay. So over time,
as a pool gets older, the distribution of people is
going to shift. It’s going to be have less
hyper alert and low cost people and more high cost and low alert
people. That’s why the pool is going to
slow down. So burn out is naturally
explained by an agent based approach.
So anyway, as we go through the
course, we’re going to emphasize this agent based approach.
So building a model like that,
starting in the 1980s, and making a conditional
prediction, you can get a fit that looks like this.
So notice, you make some
gruesome errors, like over here,
that was an expensive, ’97, ’98, that was an important
mistake. But you can fit this kind of
pre payment surprisingly well. OK, so that was my Kidder
Peabody days. And I thought,
my gosh, we’re doing incredibly well.
We’re helping the country.
We’re doing things in a
colossal scale that nobody had ever done before.
I think I may have not
emphasized enough that Kidder Peabody came to dominate this
market. We controlled over 20% of all
the issuance. Remember, there were trillions
of dollars of things being issued.
So this little group of 20 year
old kids basically, plus me the old guy in
research. So them, the traders,
they were issuing something on the scale of half a trillion to
a trillion dollars of these CMOs.
These kids in their mid 20s or
late twenties. And the world seemed to be a
better place for it. And I thought,
my gosh this is an untold story that needs telling.
And it’s an incredible success
story. Well, things suddenly changed
and in 1994 there was a crash. So this is the first of three
crashes I’ve lived through. There was a scandal at Kidder
Peabody, the Joe Jet scandal,
who was a trader, a government bond trader,
who was accused of doctoring the books and faking his big
profits. He had been Kidder Peabody man
of the year in 1993. And then in 1994,
they decided that all his profits were fictitious and that
he doctored the books. And so he was fired.
But he sued Kidder for
discrimination. And it was a tremendous
controversy that was in the front pages of the papers for
months on end. And finally,
General Electric, who owned Kidder Peabody,
closed the firm. After hundred 135 five years,
or I guess 129 years, they closed the firm.
So I had to go back one day,
from Yale, to Kidder Peabody,
and I invited those 75 people in the research department into
my office, and I said you’re fired.
And then I got up and I went to
the office next door and somebody said to me,
you’re fired. And so we all fired each other
and the entire 130-year-old company came to a close.
So, the head trader of
mortgages and bunch of his top lieutenants decided from a hedge
fund. So Kidder Peabody got closed,
actually sold, it wasn’t closed,
it was sold to Paine Webber. And Paine Webber dropped the
name Kidder Peabody and hired many of the people from Kidder
Peabody. And in fact,
the second tier, or the more junior group of
mortgage traders at Kidder Peabody,
which was the leading mortgage company at the time,
they took over the desk at Paine Webber.
And then Paine Webber was
bought by UBS. And those same guys took over
the desk at UBS. So the junior crew at Kidder
Peabody, some of whom were Yalies by the way,
ended up running the UBS. Or a big part of the UBS
mortgage desk. But in any case,
our mortgage traders, the head guys,
decided to from a hedge fund. Instead of selling,
the CMOs, they would buy the CMOs.
And we called it Ellington
Capital Management. So I was one of six partners.
I was a small partner,
because again, I stayed at Yale.
So this introduces the last
player, the hedge funds. So what is a hedge fund?
You heard the name,
I’m sure a thousand times. It has a bad name now.
But a hedge fund basically
means four things. It means it’s someone who
hedges. You don’t just buy and hold the
thing and hope that the cash flows are good,
you try to protect yourself against as many risks as
possible. Just like I explained,
we were doing at Kidder when we tried to get the same cash flows
in every scenario. And we’re going to
mathematically study that in remaining lectures.
But you try to hedge,
that’s where the name comes from.
So you try to offset as many
risks as you can. Of course, you still run some
risks. But you’re offsetting setting
as many as you can. The second most important
thing, is most of it’s done, or a lot of a buying is done,
not most, but a lot of the buying is done with borrowed
money. That’s called leverage.
You don’t just take your
investor capital and buy something, you take your
investor capital, you borrow some extra money,
and then you buy some stuff. And the stuff you buy you use
as collateral to guarantee that the lenders are going to get
their money paid back. So a hedge fund is generally
leveraged. The third definition of a hedge
fund, third characteristic, is that they’re very lightly
regulated. So what does that mean?
That means that a broker who
sells something has to make sure that the client on behalf of
whom he’s buying, the broker, the stockbroker,
has to make sure that the purchased item is appropriate
for his client. We have no such obligations.
We can buy and sell with anyone
we choose on behalf of our clients.
But our clients have to be
sophisticated investors. We have to vouch that they’re
sophisticated. If they have enough money,
like say $5 million to invest in the hedge fund,
they are by definition sophisticated.
And then they don’t need to be
protected by having a broker who’s necessarily watching out
to see whether investments are appropriate.
We tell them what we’re
investing in and, of course, we’re obliged to
explain our strategy. But once they understand our
strategy, we don’t have to meet the same
test that a simple broker meets on behalf of,
let’s say a poor retired individual.
So there’s less regulation and
the fourth characteristic is hedge funds typically charge
higher fees. So that’s what a hedge fund is.
Now, the first hedge fund was
started in the 1940s, I believe, by someone named
Jones. And he was a stock picker.
And what he did,
is instead of picking let’s say the best car company,
which he might have thought was Ford and leaving it at that,
he would try to hedge his risk. So he’d buy Ford,
and he’d short all the other car companies.
he wasn’t just betting on Ford doing well.
Because he could lose if the
whole economy went badly, Ford and every other car
company could go badly. Instead he was betting that
Ford would do better than the other car companies.
So he was concentrating his bet
on something he understood more. You can’t be an expert about
everything. Presumably he was an expert
about cars. And he knew Ford was better
than General Motors. So that was a bet he wanted to
take. But he didn’t want to take a
bet on the whole economy doing well or badly.
So that was the beginning of
the idea of the hedged fund. Now there’s so many risks that
a car company or any company runs.
Does their president know what
he’s doing? Is Detroit going to be a good
city? Is there going to change in
government regulation? Is some foreign competitor
going to appear on the scene? Is the price of oil suddenly
going to change? There’s so many things they can
go wrong in a company, it really is very hard to
hedge. So hedging really makes much
more sense when you can make the problem mathematical.
Well see, with mortgages it
really is a mathematical problem to a much greater extent.
So it makes much more sense to
hedge. And I think it makes much more
sense to be a hedge fund if you’re trading in the mortgage
market. Anyway, that’s what I found out
when I visited Wall Street in those days.
So what did the hedge fund do?
Instead of creating these CMOs,
the hedge fund would buy them. And of course,
buy the most complicated one. So in effect,
the hedge funds would buy the most complicated,
the residual piece we’re talking about,
and try to hedge that. So effectively,
the hedge fund, by hedging it,
was really carving out the cash flows of that last piece into
complicated ways and selling them off to stabilize its
profits. So really, the hedge fund
actually was continuing the work of the investment bank of
creating more and more pieces and trying to allocate the risk.
And so the hedge fund is part
of the entire operation, which was making this mortgage
market behind the scenes make home ownership so much easier
and reduce people’s risk. Or so it seemed.
We had a hard time raising
money to begin with. Because after all,
Kidder Peabody had just gone out of business.
And not only had we gone out of
business, but there was a general crisis at the time.
It was not only the trading
scandal of Joe Jett, but at the same time,
there was a crisis in the derivatives market.
Because all these complicated
pieces that were being created where pieces went up and pieces
went down, of course if you didn’t know
how to hedge your risk, you could end up losing a lot
of money. So Orange County went bankrupt
in 1994. And what did Orange County do?
They bought a bunch of inverse
floaters. So when the interest rates were
going down in the early ’90s, they were making a huge amount
of money. And the fellow who ran Orange
County’s municipal investments, was twice municipal investor of
the year. But in 1994,
when everything turned around and interest rates skyrocketed
for the year, his inverse floaters became
almost worthless, and he bankrupted Orange County.
So, it was some of our inverse
floaters that were being bought, which helped bankrupt Orange
County. Plus Kidder Peabody had just
gone out of business because of Joe Jett.
So it was very difficult for
our hedge fund to raise money. Our motto was we created the
mess, let us clean it up. Nonetheless,
we did raise some money. We had an important starting
investment from the Ziff Brothers and we had an
incredible boom time. We made fantastic returns our
first few years. 50% returns.
And we grew into the biggest
mortgage hedge fund in the country.
And things were booming along.
And then suddenly,
there was another crash in 1998.
So this was the second crash
that I was exposed to. So, what happened in this crash?
Well, as I told you,
we were buying mortgages as the hedge fund, buying that residual
piece, and buying it with borrowed money.
So we would buy the piece,
let’s say for $100, by borrowing $80 dollars.
So we’d use $20 dollars of
investor capital, we’d borrow the other $80,
we’d buy the piece for $100, and then we’d leave the piece
with the lender as collateral. So if we didn’t pay them back
the $80, the guy could keep our piece.
So his $100 piece was
protecting his $80 dollar loan. So things were swimming along.
We’re going to talk a lot about
leverage later. Well, in 1998,
one of the big competitors, Long Term Capital,
which was founded, as I think I mentioned earlier
in the course, by Meriwether,
who was the most important, famous, fixed income trader on
Wall Street from Salomon. And two Nobel Prize winners,
who I’ve mentioned many times, and you’re going to hear about
again, Merton and Scholes,
creators, especially Scholes, of the Black-Scholes model,
the most important tool on Wall Street for managing risk,
as we’ll discover in a few lectures.
So these guys,
the three of them, and nine other partners,
12 of them, created this wildly successful hedge fund.
And in 1998,
it suddenly went out of business.
And in fact,
the government had to step in with all the big investment
banks, coordinating the big investment
banks, to take it over so the whole
market wouldn’t crash down around it.
We celebrated the crash of Long
Term Capital, figuring that was one of our
big competitors out of business and now we would have an easier
time. But, I remember thinking at the
time that was a mistake. But anyway, a few months later,
we got a margin call. So suddenly,
on a Friday morning in October of ’98,
one of our lenders called us up and said,
we think the prices have gone down,
it’s not $100 anymore, it’s less than that.
We need X million dollars of
extra margin to put for us to contribute.
Because the $100 piece
protecting the $80 loan, it was no longer $100 piece,
it was a lower piece, so there was less cushion.
We need extra cash to have a
bigger cushion. So we said, oh this is crazy,
the prices haven’t gone down that far, that’s not fair.
And they said,
you have until 4 o’clock Friday afternoon to pay us back.
And if you don’t pay us back,
then on next business day, which happened to be Tuesday
morning, because it was Columbus Day
holiday on Monday, we’ll just sell off all your
pieces and pay ourselves back out of the proceeds the $80 and
give you whatever is left over. Well, we figured what was left
over wasn’t going to be very much.
Because they only needed their
$80. So they didn’t have an
incentive to sell for the best possible price,
although of course, they would tell us they’d sell
for the best possible price. They wouldn’t and it would be a
fire sale. So we didn’t know what to do.
And we couldn’t raise the money
by 4 o’clock on Friday. So we called up Warren Buffett.
We said, well this is so
unfair, they’re forcing us to sell, there’s no reason why we
should have to sell. This margin call is not proper.
It’s not right.
There’s no reason we have to
sell. What’s going to happen is on
Tuesday we’re going to be forced to sell all of our bonds at the
same time. And they’re going to all sell
for like $80 or something. It’s going to be a terrible
blood bath, a fire sale. Prices will go for nothing.
We’ll be totally wiped out so
unfairly. Why don’t you buy our firm.
We’ll give you half our firm,
some big percentage of our firm.
You just make the margin call
for us. And then you could have this
firm with these great bonds. It’s just a travesty.
And it’s going to be such a
good investment for you. And you can save us and save
the bonds and stop this travesty.
And he said excuse me?
And we said,
well it’s unfair, they’re going to force us to
sell on Tuesday. And the bonds will go for
nothing when they are perfectly valuable bonds.
And they are going to wipe us
out. You can prevent that from
happening and own our great firm.
And he said,
hell I think, I’ll wait for Tuesday and buy
the bonds myself. And so Warren Buffett didn’t
rescue us. And so that Tuesday it looked
like we would go out of business.
But over the weekend,
we managed to hold an auction and sell the bonds ourselves.
So in other classes in
economics, you find out how to conduct auctions.
I don’t have time to describe
this in great detail. But let me just say,
that in a typical auction you have to worry about the winners
curse. Everybody’s thinking,
I’d better not be the highest bidder, because that means I
probably overpaid. Because those smart guys are
bidding against me. So what we did over the weekend
was, we called everybody up and we said, we’ve been forced by a
margin call to sell these things.
There’s going to be a great
deal for you. So why don’t you come back from
your vacation, one guy came back from
Budapest, one big trader on Wall Street.
We got a huge collection of
traders there over the weekend. We showed them our bonds so
they could think about it. And on Monday we held our
auction. We didn’t sell everything at
the same time. At 12 o’clock,
we sold the first third of our bonds.
At 2 o’clock, the second third.
And at 4 o’clock,
the third third. Actually, we got a little
behind schedule, but that was our plan.
And so what happened was that
at 12 o’clock, everybody basically bid $80.
So we said, we’re one of the
bidders ourselves, of course.
We told everybody,
they all did it by email, we emailed everybody back,
you’ve been outbid. Either by someone else or by us.
You’ve been outbid.
And all these guys,
one from Budapest, from all over the world back
there, thinking we’re going out of
business, bidding $80,
they don’t get to buy anything. So what would they do?
What would they be thinking?
So between 12:00 and 2:00,
we’re on the edge of our seats. Are they going to bid $80 again?
of course, we get nothing. Because we just pay back the
loan for $80 and we go out of business and our investors go
out of business. Or are they going to realize
that they have to bid more in order to beat other people.
So we had no idea what was
going to happen. But the price was basically $95
a 2 o’clock and $99 at 4 o’clock.
So we celebrated saving our
firm. And it turned out there was
another complication after that, which I won’t get into.
Which is that the thing had
happened over the holidays. And so the next morning,
the buyers didn’t get their bonds.
Remember, we don’t have the
bonds to sell them. They’re sitting with the person
who lent us the money. So it was over a holiday,
and the bonds didn’t get transferred to the buyers.
And so the prime broker who was
supposed to vouch for all this, it was a holiday for him too.
And so the whole thing was a
mess. And it’s actually quite an
amazing story, which I don’t have time to
tell. But anyway, when the buyers
didn’t get their bonds, the next morning on Tuesday,
they all got alarmed that maybe we didn’t even have the bonds.
And so everybody made a margin
call against us. And we went from celebrating to
suddenly thinking we’re out of business again.
when you’re so badly off, people realize that they have
to stop. And so there was a big
conference call on Wednesday in which all of lenders,
the sort of number two people at all the big investment banks
got together in the conference call,
and they agreed that if they all tried to get their money
back at the same time, none of them would get it.
And so they waited for us to
gradually work ourselves out of the predicament.
So we survived the crash of
1998. And then after that,
we had another boom year. An incredible year in 1999.
And things kept booming again
for eight years or nine years until 2007.
Before, I get to that,
that experience was so seared in my mind,
the second crisis, the 1998 crisis was so seared
in my mind, that I wrote a paper called The
Leverage Cycle. In which I said,
what basically happens is people borrow a lot of money and
they’re very leveraged. Then something bad happens in
the economy. And the lenders suddenly reduce
the leverage. And so the big leveraged
buyers, they go out of business. The leverage goes way down.
Lenders will ask for more
collateral. And there’s also the bad news.
And those three things together
completely crush the market. And so lots of people are out
of business and the whole thing’s a mess.
But then after things settle
down, there’s another boom. And then it’s going to repeat
itself over and over again. So that’s The Leverage Cycle
story I told in 2003. I wrote it right after the
crisis of ’98 and I said that this crisis,
which in ’98 seems to be so small, could be repeated on a
much grander scale for the whole economy.
So we had these boom years,
right after the crisis of ’98. And then in 2007,2008,
there was another crash. This time on a grand scale.
But it was exactly the same
kind. And the last two lectures of
this course are going to be about the most recent crisis.
And so we’re going to
mathematically reexamine this entire story.
And again, after the 2008
crash, when we almost went out of business again,
our hedge fund. In 2009, we had the best year
we’ve ever had. Better than all those other
years, even in ’95. So three times in a row.
There’s a crash,
a boom, a crash, a boom, a crash,
a boom. We made back more money in 2009
than we lost in the crisis of 2007,2008.
So the course has to end with
an explanation of why these cycles happened over and over
again. It can’t be an accident.
It can’t be all my fault that
I’ve been in three of them. There’s got to be something
systematic going on. And that what I’ve been writing
about it. And how I’ll end course.
And by the way,
as you’ll see, I spent a lot of time talking
to the federal reserve, and Bernanke,
and Summers, and also with the ECB,
the European Central Bank about the leverage cycle.
Which I think is generally
becoming recognized as a central problem.
But I want to end this lecture
in the next 15 or so minutes, 20 minutes, by pointing out one
change in the market. The next big change in the
market. The next wave of securitization.
So, this is the sub prime
market, which we haven’t mentioned yet.
And which I will now describe.
OK, so what is the sub prime
mortgage market. So I already pointed out that
securitization was a great idea. Now it was applied,
remember, to prime mortgages. You had to be a very reliable
homeowner to get one of those Fannie or Freddie loans.
And because those people were
so reliable, although they didn’t behave
perfectly rationally, you had cost and alertness
issues, they still were very predictable.
Well, a combination of things
happened in the late ’90s. Investors began to get the
idea, this has worked out so well, and there’s so many people
who don’t own homes in America because they’re poor.
Maybe we can extend home
ownership to still more people. Of course, they’re going to be
riskier, because they’re poorer, they have less resources.
But we’ll charge them a higher
interest rate and that will compensate us for the extra
risk. The government also saw this as
a great opportunity to help the poor.
So this combination of
investors getting the idea and the government wanting to
sponsor it, led to the creation of a new
market, the sub prime market,
which is what I’m going to describe now.
And I’m going to talk about
what went wrong, or begin to talk about what
went wrong, but I’m going to leave most of it for the last
two classes. So as I said,
securitization is so important because,
let me remind you, typically when a bank makes a
loan, the bank finds out a lot about
who it is lending to. But the bank is a bunch of
managers and stuff. The shareholders of the bank
are the people whose money is at risk.
They aren’t the ones looking at
the loans. So if you’re a shareholder,
you own stock in a bank, two years later the bank is
going to make a loan to somebody, risking your money.
And you’ve got no idea who the
guy is that the bank is lending to.
Or what the characteristics are
of the person who is getting a loan.
Think of the securitization
when you’re buying a pool. When you get this pool,
you could be told what are the characteristics of all the
homeowners in the pool. It’s something very concrete.
A bank lends to homeowners,
it lends to businesses. It’s doing 6,000 things.
Of course, it’s risky to have
bank capital. You know, equity,
own shares of the bank. Because you don’t know what
they’re doing. And they are doing so many
different things. You should feel a lot more
comfortable if where your money is going is very well
delineated. That’s the idea of a
securitization. It’s very well defined where
the money is going. So it makes people more willing
to lend. Corporate debt,
that’s another way of lending money.
But if you own bonds in a firm,
you’re not the first person to get paid back.
The people lending with
collateral get their money first.
And if the firm goes bankrupt,
there is a big court case and it takes a long time to get your
money back. Not in a securitization.
So there are many ways that a
securitization is more attractive than lending money
through a bank. And that’s the reason for the
securitizations. Now here are the current
numbers, the 2007 numbers. And there haven’t been much
securitizations since then. So the agencies are now up to
$4 trillion, Fannie and Freddie. Now those jumbo loans I told
you about, the big loans that the rich people take out,
remember, which was $0.5 trillion in 2003,
is now $0.8 trillion. But there are two more markets
that have been created. There’s the Alt-A.
Those are people who don’t have
credit ratings good enough to get the Fannie Freddie loans.
That’s $0.8 trillion.
But they are pretty good credit
ratings. And then the sub prime
population, of which there were $1 trillion loans issued by
2007. That’s $1.8 trillion of lesser
credit loans that didn’t exist at all in 2002.
So you add these numbers up,
4.8,0.8, and 1, that’s $6.6 and $4 trillion of
unsecuritized the banks are just holding loans.
So over $10 trillion of loans
as I said. OK, and then you add the
commercials on top of that and you’re getting very close to the
value of the stock market. So all right so we’ve talked
about this. The advantages of securitized
loans. All right, so how did the sub
prime market began? Well, you had to have a few
legal hurdles. The first one,
which some countries haven’t managed to achieve and some
people now are doubting we should’ve ever done,
is it legal to charge a high interest rate to someone just
because they’re riskier. Is that usury?
Or is that a reasonable return,
because you’re making a bigger risk?
So, there are anti usury laws
on the books. And so in order to make these
loans, they had to become legalized.
You had to get congress to pass
a law to say that higher interest rate loans for riskier
people is not usury. So then, you also had to figure
out the tax treatment, which happened in 1986.
And so the first pools were
created in the late ’80s, the early ’90s,
and Kidder Peabody, by the way, the firm I worked
for at exactly that time, was one of the first creators
of these sub prime like loans. So it was very small in the
early days. And it worked pretty well in
the early days. And, as I said,
by 2007 it had grown to $1 trillion, 5 million people at an
average loan of $200,000. Now, these are people who,
as I said, have bad credit ratings.
And so they pay a higher
interest rate. Instead of say 6% at the time,
or 5% at the time, they might pay 5% or 6% of the
mortgage rate at that time. They might pay 8% for the first
two years. And then at the end of the
first two years, the rate jumps up by another
3%. Maybe to LIBOR plus 6%.
is the inter bank interest rate.
So, it’s already high,
and then it jumps up after a couple of years.
Now, many people have said this
is the kind of predatory lending.
That the homeowner is being
lured into taking out a loan, not realizing that in a couple
of years, the rate is going to go way up.
there’s some rationale to this. It turns out,
that if you’ve made your payments for two or three
consecutive years, the market thinks you’re not
such a subprime person anymore. After all, many subprime
borrower are people who are young.
They didn’t pay their credit
cards in college. Or they defaulted on something.
And once they’re married,
have a house, have kids, and they pay for
three consecutive years, the market figures,
well these people are much better.
So we’ll give them another
loan, they can refinance into a loan with a lower interest rate.
Because they are no longer
considered subprime. Maybe they moved to Alt-A or
maybe even into prime. So you could count on 70%,
by the end of the third year, of people refinancing their
loan. During all those years from the
90s and the early 2000s. So you’d be left with 30% of
the people who didn’t refinance. Why didn’t they refinance?
Probably because there’s
something wrong with them, they were missing their loans
[correction: payments]. They were much riskier than the
original pool to begin with. So naturally,
you’re going to charge them a higher interest rate.
So it’s not such a crazy thing
that the interest rate went up after two years.
It isn’t necessarily a sign of
predatory lending. OK, now how do these loans get
started? There’s somebody called an
originator. A broker would find a
homeowner, a subprime homeowner, and then go to originator who
would create the deal. Now what would the deal be?
The pool would be a bunch of
subprime homeowners and you’d have to get some data on the
people. You’d have to figure out do
they have a job? What’s their debt?
What’s their income?
Things like that.
And all that would have to be
reported to the potential buyers.
So a buyer in the shares of
these subprime pools would get a list.
Not by name.
You can’t reveal the name of
the homeowners. But what the zip code is of
every house. And what the basic
qualifications were of the homeowner.
Do they have a job?
What’s the loan to value on the
loan? What’s their debt to income
ratio? Stuff like that.
Now, the servicer,
who’s often the originator. Let’s say the originator is an
investment bank. The servicer might be the same
investment bank or a specialty servicer.
What they do is just what the
banks did in the Fannie Freddie story.
They’re the ones sending the
letters, telling people they have to
pay, collecting the money, and dividing it up to the
bondholders, as we’ll describe in a second.
And they have one extra job.
Because they’re subprime loans,
you can expect a bigger percentage of them to default.
And when people default,
sometimes they can’t make the payments, they lose their job,
something like that. The servicer is given the right
to modify the loan. The servicer can say,
OK I understand you can’t pay, of course you can’t pay,
you’re out of a job, you don’t have any money.
There’s no point of us throwing
you out of the house right away, maybe you’ll get the job back.
So we’ll work out a deal where
we delay your payments, or maybe reduce the payments,
maybe even we reduce the principle that you owe,
because in the end that’s going to make our bondholders more
money. So the all the bondholders have
no right to talk to the homeowner.
They don’t know even though the
homeowner’s name. But the servicer who is sending
the homeowner letters all the time and getting the money,
of course the servicer knows the name and has the right to
modify the loan. And if the homeowner doesn’t
pay and the loan is not modified,
because the servicer doesn’t think it’s worth it,
then the servicer can kick the homeowner out of his house.
And take the house and sell it
and pay the proceeds to the fund.
But there’s one extremely
interesting provision that if the homeowner is not paying,
during the time the homeowner doesn’t pay,
the servicer has to make the payments for the homeowner into
the trust for the bond holders. That’s supposed to give the
servicer an incentive to hurry up and figure out what to do to
change the loan or throw the homeowner out.
And of course,
when the house is finally sold, the servicer can recoup his
advance payments out of the proceeds of the sale.
And then later,
the rest of the money goes to the bondholders.
Now, the rating agencies played
an important role in determining the ratings that I’m about to
describe. So here’s the thing would look.
You have all the homeowners
stuck into a pool, all those loans.
I’m going to go for ten more
minutes, by the way. You have all these loans stuck
in a pool. So the money would be coming
in, the homeowners, remember, are paying this high
interest rate because they are subprime borrowers.
So there’s $100 of loans that
went out. Let’s say each loans is for
$1.00. Where does the originator get
the money to lend to the homeowners?
Well, the originator is at the
same time creating the bonds. So there’d be AA bonds,
AA, A, BBB, with a bunch of minuses too, the over
collateralization and the residual.
So you’d create $81 of AAA
bonds. These guys would pay that
LIBOR, the inter bank rate, which let’s say was 5% percent.
Plus a tiny bit,
20 basis points, so 5.2%.
The AA would pay a little bit
more than that. And the single a little bit
more than. That’s probably misprint,
that should be LIBOR plus 10. LIBOR plus 20,
LIBOR plus 30, and then the BBBs,
LIBOR plus 130. So you’d issue $81 worth of
triple AAAs, $7 of AAs, $5 of As, $5 of BBBs.
That adds up to $88, $93, $98.
You’re only getting $98.
So you’ve got $98 worth of
bonds that you used. So the originator has sold
these bonds for $98. He’s got to lend $100,
so he’s $2.00 short so far. But you notice that the
interest rate all these bondholders are getting is 5%
percent, or a little bit more. The homeowners are paying 8%.
So there’s extra money coming
in that doesn’t have to go to the bondholders.
So there’s this residual piece
that gets the right to get the extra interest payments.
So the originator either holds
residual piece or finds some hedge fund and says,
OK, you buy the residual piece. And maybe the residual piece is
worth $5.00. So $98 plus $5.00 is $103.
So the originator has gotten
$103. The broker’s fees,
remember the broker had to find the homeowners,
gets $2.00. So now he’s only got $101.
So he lends the $100 and
pockets $1.00. So the originator would get 1%
bear no risk for his work in creating the deal.
Now, how can these AAA pieces
be rated AAA? Now, to be rated AAA mean
there’s a one in a hundred chance, or something,
that you’re going to default. So how could that possibly be,
when the loans are so risky? Well, what happens if somebody
defaults? So this is the calculation.
What happens if somebody
defaults? Well, if you haven’t paid for
the first 30 days, that happens quite often.
But if you go,
60 days without paying, nothing bad happens to you.
After 60 days,
you get a letter saying you’re delinquent and a note is being
made that’s going to have an impact on your credit score.
So being 60 days delinquent,
seriously delinquent, is bad for the homeowner.
After 90 days,
you’re considered likely to default.
And so you get these very
threatening letters from the servicer.
And after 120 days,
the servicer can start to try and throw you out of the house.
But to throw you out of the
house, maybe they have to go to court, they have to do a whole
bunch of things. And so in those days,
it took 18 months, 14 more months,
after the four already, to throw somebody out.
It now, has taken on average,
a couple of years, or three years.
It’s getting more and more
complicated to throw somebody out.
Which we’re going to get to in
a minute. So you could be thrown out
after say 18 months. Now what happens if you’re
thrown out of the house. Let’s say, the house is sold
for $0.80. When you originally had a $1.00
loan. Well, during the time the guy
hasn’t paid for that year and a half, if it was an 8% coupon,
that means a year and a half is 12%.
So $0.12 the guy hasn’t paid.
So the servicers had to pay up
the $0.12. And then you have to hire a
broker to resell the house. That costs six more cents.
And the guy probably didn’t
pays taxes for the whole year and a half.
So that’s another three cents
or so, that you’ve lost, depending on what the tax rate
is. So you’ve lost $0.12 of
servicer advances, $0.06 to the broker,
that’s $0.18 $0.03 cents for the taxes, that’s $0.21.
And the house only sold for
$0.80 instead of 100. That’s $0.41 cents you’ve
already lost. That’s a sort good scenario.
You’ve already lost 40%.
So the bondholders know that
with this scenario they’re going to lose 40% about of their loan.
Where does that 40% is $0.40
cents, because remember there’s only $1.00 loan to that guy,
where does that come out of? Well, there was this over
collateralization of $2.00. This is extra money pouring
into the deal because everyone else is paying a higher coupon.
So you take the money out of
this extra cash flow that’s coming in.
If the default,
the lost $0.40 is more than the extra cash flow coming in that
year, then you reduce the over collateralization.
There was $2.00 dollars.
These bondholders were only
owed $98 and there’s $100 of loans outstanding.
So you could lose $2.00 of
loans and still have as much loans backing these bondholders.
But once you get to the next
dollar, you’re going to take the $0.40 first out of the BBB
piece. So as more and more houses go
under, you go through the over collateralization,
the extra interest. Then you start taking things
out of the BBB piece. After you wipe that out,
then you go to the A piece, and then the AA and finally go
to the AAA. So how could you possibly think
those pieces at the top were AAAs?
Well because let’s do a simple
calculation. Actually, they look incredibly
safe when you start to think about it.
All this extra interest and the
over collateralization and stuff like that it’s sort of 8%
protection. And on top of that,
you’ve got the lower pieces bearing the original losses.
OK, so even if you expected 40%
percent of the homeowners to default, which is an
astronomical figure. It was typically,
in the past, less than a few percent.
Even if you thought 40$ of the
homeowners would be thrown out of their houses,
and 40% of each homeowner was going to be lost in the scenario
we just described of the 40% loss,
40% times 40% is only 16%. But the AAA pieces are
protected by 8% and then are protected by another 19%,
because they’re only the top 81%.
So 16% doesn’t come anywhere
close to the AAA guys. So that, in 2007,
was a horrible scenario to imagine.
That 40% of the homeowners,
they are 5 million homeowners. That means 2 million people
tossed on to the streets, losing 40% of each of the homes
and you don’t come close to touching the AAAs.
That’s why it seemed like they
should be AAAs and so many people were willing to buy them.
I’ve got one more thing to add
to this background piece. The credit default swap.
By the way, things are even
rosier than that, at least looked at from the
point of view of 2007 Because remember,
70% of the people were always prepaying.
That means you got 70% of your
money back for sure. So you only had 30% of the
people left who could possibly default.
So instead of having 40%
default, you’d probably have 40% of the 30%.
So you see, you could easily
imagine that your AAAs were completely safe.
And so I think the credit
rating agencies didn’t do such a horrible thing rating these
things as people say. But I haven’t finished the
story. So watch what happens.
So a new invention that
happened in the end of 2005 was the credit default swap.
CDS they are called,
which you’ve heard a lot. So what is a credit default
swap? It’s just insurance on each of
these bonds. So a credit default swap on the
BBB would say, if there’s a dollar of
principal lost, because the homeowner’s
default, you take the loss out of the triple BBB,
you can get insurance on the triple BBB.
A CDS just is a promise to pay
a dollar for every dollar that’s lost in the triple BBB.
And the CDS on the A is a
promise to pay a dollar for every dollar that’s lost on the
A. So that was a huge market.
It suddenly took off in 2005.
And then there was an index
that was created in 2006. So these are insurance on
particular deals. But if you put all the
insurance together, you can make an index of what
the insurance is like. And so you can tell how
valuable the bonds are. Because if you see that the
insurance premium is changing you know that people realize
there’s a bigger chance of default of the BBB.
So the insurance market,
the index of it, is going to tell you a lot of
information about what what’s going on in the subprime world.
OK, now, I don’t have time to
get to these legal issues. But I want to add the last fact.
Things seemed to be going so
well in the subprime world from the late 80s,
early 90s, all through 2000, all through the middle 2000s
that people got more ambitious still.
So what did they do?
They created CDOs.
So what are CDOs now?
Remember, we had these loans
that got cut up into bonds. There was insurance in the
bonds. So people said,
let’s take the BBB bonds. They’re sort of at the bottom,
they’re protected a little bit, but near the bottom.
Let’s cut those up into
different pieces. So we take BBB bonds from all
different deals, we put those into another pool,
and now we cut those into different pieces.
And so you might have a pool
that’s from California, and a pool that’s from Detroit,
and a pool that’s from Florida, that would just be a horrible
combination, or a pool that’s from Illinois
and Ohio and stuff like that. You put them all together.
And now, somehow the market
decided that we could cut these into AAAs, AAs,
and As with the same logic as before.
But, this turned out to be
catastrophic. In fact, the market went one
step further, and not only took the BBBs that
we said before and made them collateral for more AAA bonds
and CDOs. But then took the As from this,
which came from the BBBs and cut those up into more AAAs,
CDO squareds. So that was the mortgage
market, the subprime mortgage market.
So you see, that there’s a
tremendous amount of synthetic stuff.
By the way, these insurance
pieces, if you’re writing insurance, you’re promising to
pay basically what the BBBs pay, so it’s like an artificial BBB.
So they created the synthetic
BBBs and used those to cut up too in the CDO market.
OK, so I’m going to stop now
with one final word. So the subprime market of $1
trillion, plus the Alt-A market, became the new frontier of
mortgages. And as I said,
everything went swimmingly in the 1990s and the early 2000s.
And then in 2007,
there was a tremendous crash. So in January of 2007,
February of 2007, the BBB insurance index
plummeted from 100 to 75. At that point,
everyone declared, oh this is just the subprime
market. It’s small thing,
don’t worry about it. Bernanke said there’s no
problem. The stock market didn’t blip at
all. It continued on until October
of 2007 when it hit its high. The world took notice of the
subprime collapse, but everybody said it wouldn’t
amount to anything, because everybody
underestimated the importance of the mortgage market.
So we’re going to see in the
last two lectures, how this unraveling of the
subprime market led to the unraveling of the entire
economy. And we’re going to show that
everything that I’ve described, although it sounds very much
more complicated with subprimes than it did with the prime
mortgages earlier, is really when you get down to
it, the same story of leverage and crashes and then booms.
And we’re going to begin the
next class by talking about the mathematics of the prime
mortgage market and prepayments and how to value those.
And gradually we’re going to
get to the crisis and what caused it and what we should do
to prevent future crises. Thanks.