Speaker 1: Bloomberg Audio Studios, Podcasts, radio News. This is Master's in
Speaker 1: Business with Barry rid Hoolds on Bloomberg Radio.
Speaker 2: This week on the podcast, I have an extra special guest.
Speaker 2: Sean Dobson has really had a fascinating career as a
Speaker 2: real estate investor, starring pretty much at the bottom and
Speaker 2: working his way up to becoming a investor in a
Speaker 2: variety of mortgage backed securities, individual homes, commercial real estate,
Speaker 2: really all aspects of the finding, buying, and investing in
Speaker 2: real estate. And on top of that, he's pretty much
Speaker 2: a quantitative geek, so he is looking at this not
Speaker 2: simply from the typical real estate investment perspective, but from
Speaker 2: a deep quantitative analytical basis. If you're interested in any
Speaker 2: aspect of commercial, residential, mortgage back real estate, then you
Speaker 2: should absolutely listen to this. It's fascinating and there are
Speaker 2: a few people in the industry who not only have
Speaker 2: been successful as investors, but also very clearly saw and
Speaker 2: warned about the Great financial crisis coming because it was
Speaker 2: all there in the data if you were looking in
Speaker 2: the right place. And continues to build and expand the
Speaker 2: Amherst Group into a real estate powerhouse. I found this
Speaker 2: conversation to be absolutely fascinating, and I think you will
Speaker 2: also with no further ado my discussion with Amherst groups
Speaker 2: Sean Dobson.
Speaker 1: Thank you very much. It's great to be here.
Speaker 2: So let's talk a little bit about your career in
Speaker 2: real estate. But before we get to that, I just
Speaker 2: got to ask on your LinkedIn under education, it says
Speaker 2: didn't graduate none, working for a living. What does that mean?
Speaker 1: I think I answered questions of of when did you graduate?
Speaker 1: And so I said I didn't graduate, and then that
Speaker 1: was your what degrees did you achieve? And I said none?
Speaker 1: And then I think the question was what were you
Speaker 1: doing or what were your interested in? So I was
Speaker 1: working for a living, but I didn't.
Speaker 2: Go to college, did not go to college. So that
Speaker 2: leads to the next question, what got you interested in
Speaker 2: real estate?
Speaker 1: It was it was happenstance. I took a temporary job
Speaker 1: at a brokerage firm in Houston, Texas the summer after
Speaker 1: high school, between high school and college. Really as the
Speaker 1: office runner, run around picking up people's drying cleaning, grabbing lunch,
Speaker 1: opening the mail, that sort of thing. And I took
Speaker 1: the job really because a friend of ours a friend
Speaker 1: of the families had worked there and just said, what
Speaker 1: an interesting sort of industry it was. This is back
Speaker 1: when mortgages were sort of a backwater of the fixed
Speaker 1: income market, so they were traded a little bit like
Speaker 1: UNI bonds or not really well understood, not.
Speaker 2: Well followed nineteen nineties or eighty.
Speaker 1: Seven, wow, nineteen eighty seven. So after that it was
Speaker 1: I later was given some opportunities to join the research team,
Speaker 1: and then took over the research team, and then took
Speaker 1: over the eventually took over the trading platform, and then
Speaker 1: by nineteen ninety four a group of us had started
Speaker 1: our own business, and that's the predecessor to Amherst, which
Speaker 1: we bought in two thousand and have been running it
Speaker 1: since then.
Speaker 2: So when you say you were running the trading desk,
Speaker 2: you're running primarily mortgage backed securities. That's mortgageback exactly. Anything
Speaker 2: else swaps, derivatives and anything wrong.
Speaker 1: So back then it was really just mortgage back securities
Speaker 1: and structured products that were derivatives of mortgage backed securities.
Speaker 1: We sort of carved out a name for ourselves in
Speaker 1: quant analytics around mortgage risk, and that's still a big
Speaker 1: core competency of Amherst is understanding the risks of mortgages
Speaker 1: are kind of boring, but they're also very complicated. The
Speaker 1: borrower has so many options around when the refinance, how
Speaker 1: to repay, if the repay. It takes quite a lot
Speaker 1: of research, quite a lot of modeling, quite a lot
Speaker 1: of data to actually keep up with the mortgage market.
Speaker 1: It's really forty million individual contracts, forty fifty million individual
Speaker 1: contracts and a million different securities, so it takes quale.
Speaker 1: We've built an interesting system to allow to sort of
Speaker 1: monitor all that and price it in real time.
Speaker 2: So if you're running a desk in the two thousands
Speaker 2: and you're looking at mortgage backed then you're looking at
Speaker 2: securitized product. One would think, especially from Texas as opposed
Speaker 2: to being in the thick of Wall Street, you might
Speaker 2: have seen some signs that perhaps the wheels are coming
Speaker 2: off the bus. Tell us about your experience in the
Speaker 2: two thousands, what did you see? Comment?
Speaker 1: Yeah, So from the late eighties until the really the
Speaker 1: late nineties, we were focused primarily on prepayment related risk
Speaker 1: in agency mortgs backed securities. By the time you get
Speaker 1: to the early two thousands, Freddie mc fanny age and
Speaker 1: may were losing market share. A lot of mortgages were
Speaker 1: coming straight from originators and going and being packaged into
Speaker 1: what later became the private label securities market. So as
Speaker 1: part of our just growth, we attack that market. And
Speaker 1: up until that moment in time, we didn't spend a
Speaker 1: lot of time on credit risk in mortgages. We didn't
Speaker 1: really have the model credit risk because that risk was
Speaker 1: taken by the agencies. But in these private labels you had,
Speaker 1: the market was taking the credit risk. So we took
Speaker 1: the exact same modeling approach, which is loan level detail,
Speaker 1: borrower behavior, stochastic processes, options based modeling, and we said,
Speaker 1: let's just take a little detour here and make sure
Speaker 1: we understand the credit risk of these things before we
Speaker 1: sort of travel start making markets and banking and making
Speaker 1: these a core part of our business. At that time,
Speaker 1: this market was about a third of all mortgages, were
Speaker 1: the ones where the credit risk was going into the
Speaker 1: capital markets. So that little detour was in two thousand
Speaker 1: and three and we found a couple of things we modeled.
Speaker 1: We modeled defaults the same way with model prepayments, which
Speaker 1: is an option for the consumer to not pay most.
Speaker 2: Of it rarely here it described that way.
Speaker 1: Well, it's a unique approach, right, and it was unique
Speaker 1: at the time, and so we thought there were conditions
Speaker 1: under which the option probably should be exercised. If you
Speaker 1: have a two hours set out, if you have a
Speaker 1: two hundred thousand dollars home and one hundred thousand dollars mortgage,
Speaker 1: and the consequence for not paying is ding on your
Speaker 1: credit report, you're probably not supposed to pay, is the
Speaker 1: position we took. So through that lens, we said, okay,
Speaker 1: let's price these securities, and we found a bunch of
Speaker 1: interesting things. For example, we found that the follow on
Speaker 1: rating surveillance for mortgage backed securities doesn't follow the same
Speaker 1: ratings methodology that the initial rating does. So over time
Speaker 1: the risk composition of the pool which would change dramatically.
Speaker 1: So think about two thousand and three. Home price has
Speaker 1: gone up a lot from two thousand, So mortgage position
Speaker 1: in two thousand were way more valuable in two thousand
Speaker 1: and three than they were they originated because they weigh
Speaker 1: less credit risk. Not the same thing couldn't be true
Speaker 1: as you went forward.
Speaker 2: In time, each subsequent vintage became risk, and risk became
Speaker 2: risking risk as prices went up because rates had gone
Speaker 2: lower and lower.
Speaker 1: And that's the way we thought about it. The way
Speaker 1: we think about it when you make someone alone. This
Speaker 1: is sort of the credit oas world. So we think
Speaker 1: about when you make someone alone on a building, whether
Speaker 1: it's this building or or a home, you're implicitly United States,
Speaker 1: you're implicit giving them the option to send you the keys.
Speaker 1: So jingle mail is exactly and so we thought it
Speaker 1: was least Okay, we've been pricing complicated options our whole career,
Speaker 1: so let's just price the option to default as if
Speaker 1: it is a financial option. When you do that, and
Speaker 1: then you looked at the types of loans or being originated,
Speaker 1: and this is where Amher's story is a little different
Speaker 1: than some of the stories you've seen are on the
Speaker 1: financial crisis. What we figured out was that the premium
Speaker 1: that you were being paid as this option seller was
Speaker 1: way below the fair market price of their premium, meaning
Speaker 1: that the default risk you were taking was way higher
Speaker 1: than the market had appreciated. So they were underpricing the
Speaker 1: fault risk dramatically. Then, as we dug in and dug
Speaker 1: in and dug in, we realized that there were a
Speaker 1: lot of loans that were really experiments. There were financial
Speaker 1: experiments where the bar hadn't been through dal diligence, the
Speaker 1: LTV was very high, the underlying risk of the home
Speaker 1: market was very high.
Speaker 2: Other of these were the no dock or Ninja.
Speaker 1: Loans were limited DOC no dock, no.
Speaker 2: Income, no no assets exactly, Ninja no pulse seem seems
Speaker 2: reasonable exactly.
Speaker 1: So you look back at these things, you're like, how
Speaker 1: could it happen? But we're low level people, right, so
Speaker 1: we don't see the mortgage backed securities market as a market.
Speaker 1: We see it as like I said, about fifty million assets,
Speaker 1: and we're modeling up the value of every home in
Speaker 1: the country every every week basically, and we're modeling with
Speaker 1: the value of every mortgage in the country, and we're
Speaker 1: modeling with the value every derivative of that mortgage, of
Speaker 1: the structure, products, and so forth. So through our lens,
Speaker 1: it was like, Okay, we've made these financial experiments. The
Speaker 1: underlying real estate has become very volatile, so we could
Speaker 1: construct trades that had very very low premiums to sell
Speaker 1: this volatility, to basically join the consumer on their side
Speaker 1: of the trade, which is in essense buying insurance on
Speaker 1: the bonds that were exposed of these great risks. Soult.
Speaker 1: We did that for a lot of the market, so
Speaker 1: a lot of the headline names you see, a lot
Speaker 1: of the stories you see about the financial crisis, a
Speaker 1: significant number of those investors we were helping in security selection,
Speaker 1: modeling and analytics. That sort of put Amherst on a
Speaker 1: different pack because prior to that, our core business model
Speaker 1: was investment, banking, brokerage, market making and underwriting. By the
Speaker 1: time we got to two thousand and five and figured
Speaker 1: out that there was such a large sector that was
Speaker 1: so mispriced, we started hedge funds, opportunity funds. We took
Speaker 1: sub mandates from the big global macro hedge funds, and
Speaker 1: we started to build our model around investing in our research.
Speaker 1: Co investing our research and earning carried interest in sort
Speaker 1: of big complicated trades that we thought we had figured
Speaker 1: out the market, maybe the market had imprised something properly.
Speaker 2: How did that end up working out?
Speaker 1: It was a wild ride.
Speaker 2: It was a wild ride.
Speaker 1: Because by the time you got so in two thousand
Speaker 1: and five, we went on a road show trying to
Speaker 1: tell people we had learned and there wasn't a lot
Speaker 1: of reception.
Speaker 2: We literally, let me, let me interrupt you and ask you.
Speaker 2: Did people laugh at you?
Speaker 1: They were more polite than that, but they didn't invest.
Speaker 1: So there were very few people that thought because at
Speaker 1: that time the triling credit performers, for you, single thing
Speaker 1: mortgagees great, impeccable, peckable.
Speaker 2: I want to say five was where we peaked in
Speaker 2: price and six's volume or am I getting that?
Speaker 1: So six O five was six? It started to turn
Speaker 1: over and our thesis on a lot of these mortgages
Speaker 1: and the very very exposed securities within these structured products
Speaker 1: wasn't that home prices needed to go down. It was
Speaker 1: that the only way that the loan was going to
Speaker 1: perform is that the consumer could refinance out of it quickly. Right,
Speaker 1: So you really just wanted the music to stop, right
Speaker 1: or if you mean, this whole thing was going to
Speaker 1: come down if the music stopped. So by the time
Speaker 1: the music stopped, it was pretty apparent, but we had it.
Speaker 1: There's a there's a big industry conference called AFS that
Speaker 1: happens twice a year, and in the two thousand, the
Speaker 1: two thousand and five conference, it's kind of wild. So
Speaker 1: these big brokens frooms get together and they set up
Speaker 1: a convention like like plumbers, and they also give out
Speaker 1: choski's and they have a and then they give presentations
Speaker 1: in their business. And so we participated in this. Our
Speaker 1: choshki that year was a hard helmet, was a was
Speaker 1: an orange hard hat, and they said beware of falling
Speaker 1: home prices. And our whole thesis was that was what
Speaker 1: I'm trying to describe.
Speaker 2: Which is that's a great swag. Do you do you
Speaker 2: still have?
Speaker 1: I have one in my office now. I have a
Speaker 1: helmet from Beware of Falling home Prices, and I have
Speaker 1: one for our new construction division where we build entire neighborhoods.
Speaker 1: And that's really to sort of bring it all together
Speaker 1: with this core competency and analytics, and we're probably the only,
Speaker 1: maybe not the only, but but I don't know of
Speaker 1: a competitor. We're the quant shop in real estate and
Speaker 1: the quant shop in physic glasses. So with that core competency,
Speaker 1: that's the reason we're in the single play rental business.
Speaker 1: You followed that all the way through. There were amazing
Speaker 1: trades to do, amazing opportunities, wild scary things to do.
Speaker 1: I got to spend a lot of time in DC
Speaker 1: consulting on the response to the financial crisis and trying
Speaker 1: to sort out sort of what was really going on.
Speaker 1: And what we figured out in two thousand and nine
Speaker 1: really when we started buying homes is that we made
Speaker 1: the bet that I mean, it wasn't a very exotic bet,
Speaker 1: but we made the bet that the sub primorgage market
Speaker 1: wasn't coming back at all.
Speaker 2: So wait, let me unpack some of that. Christ there's
Speaker 2: a lot of really interesting things. When you mentioned DC,
Speaker 2: I'm aware of the Act that you briefed Congress, the
Speaker 2: Federal Reserve, the White House. Who else did you speak
Speaker 2: to when you were there? Well, what was that experience?
Speaker 1: So I lived in Washington, d C. For five years,
Speaker 1: my family and I moved to McLain, Virginia in two
Speaker 1: thousand and eight. So we were down the street, and
Speaker 1: we were in a pretty interesting situation because we were
Speaker 1: we were one of the biggest, if not the only,
Speaker 1: investment banks specializing in the core risk that the nation
Speaker 1: was facing. And we didn't need any help, right, So
Speaker 1: we weren't there looking for changing of a reg cap,
Speaker 1: you know, of anything. We weren't looking for a bailout.
Speaker 1: We were looking for recapitalization or anything. We were just
Speaker 1: there as a source of information. So we met a
Speaker 1: lot of interesting people in DC, and it was the
Speaker 1: whole gamut. We were consulted on the recapitalization in Freddie
Speaker 1: mckin family. We participated in that with Treasury and FHFA
Speaker 1: and the regulators of the White House. And I would
Speaker 1: say that Washington was pretty interesting because we had gone
Speaker 1: and spoken to people in two thousand and five, two
Speaker 1: thousand and six and to kind of let people know
Speaker 1: that there was something these this is a trillion dollars
Speaker 1: worth miss price risk right.
Speaker 2: And I very vividly recall six even o seven. People were, hey,
Speaker 2: we're in the middle of a giant boom. Why do
Speaker 2: you have to come, you know, rain on our purrass?
Speaker 2: But what was your experience?
Speaker 1: It was lonely, I tell you. The analogy was something
Speaker 1: like this, is that we had seen what had happened,
Speaker 1: and by two thousand and six it was over right.
Speaker 1: The mortgages were defaulting. People were taking out mortgages and
Speaker 1: defaulting in the third payment, the fourth payment.
Speaker 2: Ninety day warranty on those non conforming non Fanny May
Speaker 2: mortgages from those private contractors, like a toaster comes with
Speaker 2: along a warranty, it's amazing.
Speaker 1: So eventually even that was gone, even that they wouldn't
Speaker 1: provide nine day warranty. Eventually it was take it at
Speaker 1: cash for keys or cash and carry. So like for us,
Speaker 1: it was weird though, because the analogy I give is
Speaker 1: it in two thousand and six it happened. It was
Speaker 1: over first four to two thousand and six, the market
Speaker 1: was over. The market kept issuing securities, And I think
Speaker 1: the analogy that we think about it is that if
Speaker 1: you're standing, if you're sitting in front of a bank,
Speaker 1: and you know, a van rolls up and people with
Speaker 1: masks run in and they empty out the bank and
Speaker 1: they leave with all the money, and you see it,
Speaker 1: and then people keep coming and going from the bank
Speaker 1: for another year. You're like, yo, there's there's no money
Speaker 1: in that bank, right, And so so we sort of
Speaker 1: felt pretty stupid for a while because we did a
Speaker 1: lot of losing trades in two thousand and six that
Speaker 1: were the you know, the obviously didn't come to fruition
Speaker 1: until the actual people could see the losses. So in mortgages,
Speaker 1: the barber can stop paying maybe a year to two
Speaker 1: years before the lenders actually book a loss. So there's
Speaker 1: this great lag in housing that is affecting the market,
Speaker 1: affecting today's CPI numbers that the market doesn't do a
Speaker 1: great job of adjusting the real time for information that
Speaker 1: they already have. So when the barber hasn't paid in
Speaker 1: twelve months, probably not going to get back the loan,
Speaker 1: probably not going to start paying again. And then you
Speaker 1: can model up what happens, like what's the home going
Speaker 1: to sell for, what are my expenses to sell, awa,
Speaker 1: how long it's going to take, And all of a sudden,
Speaker 1: you have a loan that was worth, you know, one
Speaker 1: hundred cents on the dollar, and now it's worth thirty
Speaker 1: cents on the dollar. And you knew that eight months
Speaker 1: into the loan or eight or maybe a year ago
Speaker 1: or two years ago, But it takes that long to
Speaker 1: it takes that long for the losses to get through
Speaker 1: to the securities. And so I don't know if it's
Speaker 1: sort of just the fact that we're so myopic into
Speaker 1: the minutia of each little detail, or if it's the
Speaker 1: fact that the market kind of doesn't want to buy
Speaker 1: an umbrella until it starts raining.
Speaker 2: Really very fascinating. So so coming out of this in nine,
Speaker 2: home prices on average across the country down over thirty percent,
Speaker 2: but really in the worst areas like Las Vegas and
Speaker 2: South Florida and you know, parts of California and parts
Speaker 2: of Arizona, Phoenix.
Speaker 1: Two thirds in Phoenix.
Speaker 2: Unbelievable. So you say, I have an idea, Let's buy
Speaker 2: all these distressed real estate and rent them out.
Speaker 1: Yeah, I had. I had a very good idea. So
Speaker 1: I have very good partners, are very patient with me,
Speaker 1: and I said, Okay, we don't think the subprime market
Speaker 1: to mark is coming back, which was a non consensus
Speaker 1: view at the time. People were buying up mortgage originators
Speaker 1: and things waiting for the machines to sort of get
Speaker 1: turned back on. We were thinking, this is investors are
Speaker 1: never going to buy these loans again at any price.
Speaker 1: So what's going to happen, what's going to happen to
Speaker 1: the homes, and what's going to happen to the people
Speaker 1: that were living these homes. And what a lot of
Speaker 1: people I think didn't follow is that there was a
Speaker 1: concept that job loss is called mortgage caused to mortgage defaults.
Speaker 1: But in the Amir's view, a mortgage default can be rational,
Speaker 1: as distasteful as it may sound. And when I give
Speaker 1: this presentation in Europe or the EU or the UK,
Speaker 1: they look at me like you're crazy. Or in Australia
Speaker 1: or in Canada they're like, what do you mean? Mortgage
Speaker 1: is a recourse and so like, well not in the US.
Speaker 2: Well, actually some states are recourse.
Speaker 1: In some states I try to tell people, is that
Speaker 1: one person's default you have, you can handle. But when
Speaker 1: seven or eight million people default, we don't have debtors'
Speaker 1: prisons right their recourse, I mean, they're not recourse. So
Speaker 1: in this in this context of a mortgage now being
Speaker 1: clear to everyone that this default risk is present, it's real,
Speaker 1: and it's hard to price because following the borrowers economic profile,
Speaker 1: there are defaults that are related to just life events,
Speaker 1: but there's also defaults related to a macroeconomic event. So
Speaker 1: the position, you know what, investors are not going to
Speaker 1: buy these loans anymore. The homes are here, and the
Speaker 1: job loss wasn't as big as the mortgage defaults were, right,
Speaker 1: so the people still had jobs, they slid revenue, and
Speaker 1: the homes were very affordable now because the prices have
Speaker 1: been reset. So we asked ourselves, Okay, we've seen this
Speaker 1: movie before. Can we at Amherst make a three hundred
Speaker 1: thousand dollars home investible to a global financial investor? Which
Speaker 1: we spent our whole careers turning a three hundred thousand
Speaker 1: dollars mortgage investible in the global capital markets. So we said, okay,
Speaker 1: this is probably not a long put for us because
Speaker 1: we've been following the mortgage with all this minutia for
Speaker 1: thirty years. Now we're just going to follow the house
Speaker 1: the same way. So we took our same analytic and
Speaker 1: modeling team and we said, let's press down one more
Speaker 1: level so we can actually price the home instead of
Speaker 1: the mortgage with precision. And then let's set up an
Speaker 1: operating capability that allows us to acquire the homes, renovate
Speaker 1: the homes, manage the homes, and then more importantly, scale
Speaker 1: the homes in to an investible pool. So we created
Speaker 1: pools of homes just the same way we created pools
Speaker 1: and mortgages in nineteen eighty nine.
Speaker 2: So are you keeping these homes and leasing them out
Speaker 2: or are they flips?
Speaker 1: So they're kept and leased out, So we're starting in
Speaker 1: two thousand and nine. There was no flip market. There
Speaker 1: was no one to sew them to because the mortgage
Speaker 1: market had basically closed on a large section of the
Speaker 1: consumer base.
Speaker 2: So think about and that credit market was frozen pretty.
Speaker 1: Much, and it's still frozen for most people. So really
Speaker 1: still today, still today. Basically the barrier to entry to
Speaker 1: getting a mortgage became irreversibly higher, and we spent a
Speaker 1: lot of times. You mentioned my time in DC. I
Speaker 1: got to go and brief the Fetal Reserve, which is
Speaker 1: kind of cool. I got to go into the FMC
Speaker 1: room and I got to sit with with Yelling and
Speaker 1: Vernaki and walk them through kind of in our view,
Speaker 1: how we got here and the best way out. And
Speaker 1: I asked them not to shut down the sub prime
Speaker 1: mortgage market because it does serve a large swath of
Speaker 1: the American public who has a slightly higher rent in
Speaker 1: or debt income ratio, or has defaulted on a credit
Speaker 1: card in the past or something, but they can pay,
Speaker 1: they've had a problem in the past, they've cured it. Well,
Speaker 1: those people now are pretty much blocked out of the
Speaker 1: mortgage market. So I was unsuccessful in talking people and
Speaker 1: still to this day unsuccessful into talking to people to
Speaker 1: get back into lending to lower credit quality consumers. Because
Speaker 1: you can do it, you can risk base prizing. So
Speaker 1: we took we took the view like, hey, that market's
Speaker 1: not coming back. People are not going to listen to us.
Speaker 1: They're not going to say there's some good subprime loans
Speaker 1: and some bad sub loans. They're just gonna they're just
Speaker 1: going to draw a line and say you have to
Speaker 1: have a credit score above a certain level, you have
Speaker 1: to have income above a certain level, you have to
Speaker 1: have a debt load below a certain level, or the
Speaker 1: price for you is zero. You just get the answer is.
Speaker 2: No, you're out of the market.
Speaker 1: Used to you would say you would pay one percent
Speaker 1: more or two percent right now. He said no, that's
Speaker 1: so that's how we So we said, okay, well, how's
Speaker 1: it's going to work. And we had seen this movie
Speaker 1: before aggregating mortgages, strapping services on them, getting them rated,
Speaker 1: getting them available to the global capital markets. So we
Speaker 1: also so saw the conflicts and the frictions of the
Speaker 1: mortgage market when it went under duress, the problems with
Speaker 1: getting service to the consumers, the problem with getting service
Speaker 1: to investors. The litigation. A lot of people don't know it,
Speaker 1: but were We represented a large swath of the US
Speaker 1: investor base and their litigation for buying these bus and securities.
Speaker 1: So we said, you know what, let's just build under
Speaker 1: one platform everything you need to originate, managed service, aggregate
Speaker 1: and the long term service. These homes on behalf of
Speaker 1: the residents and the investors. So that's the single platform
Speaker 1: we built.
Speaker 2: H absolutely fascinating. So let's talk a little bit about
Speaker 2: who the clients are for Amherst. I'm assuming it's primarily
Speaker 2: institutional and not retail. Tell us who your clients are
Speaker 2: and what they want to invest in. Sure.
Speaker 1: Over the years, we've migrated really to what I would
Speaker 1: say is the largest customer base in the world, the
Speaker 1: largest single investors. So we do business with most most
Speaker 1: of the sovereign wealth funds, most of the big US
Speaker 1: national insurers, global insurers, the largest pension funds, and we
Speaker 1: try to position ourselves as an extension of their capabilities.
Speaker 1: And since we're smaller, more nimble, we can kind of
Speaker 1: get in there and do some of the gritty things,
Speaker 1: the smaller things. Imagine setting up a platform with in
Speaker 1: thirty two markets that has to buy each individual home
Speaker 1: and execute a CAPEX plan on a thirty forty thousand
Speaker 1: dollars CAPEX plan on a home. So these large investors
Speaker 1: need someone like us to kind of make things investable
Speaker 1: in scale, and so that's where we've been. So it's
Speaker 1: all institutional investors. It's the call it five hundred largest
Speaker 1: investors in the world.
Speaker 2: Is that patient capital? Did they have the bandwidth to hey,
Speaker 2: we're in this for decades.
Speaker 1: Yeah, it's super patient, it's super sophisticated. Their asset allocation
Speaker 1: model driven folks. The bulk of our investors are investing
Speaker 1: on behalf of consumers, on behalf of taxpayers. So we're
Speaker 1: partners with the State of Texas. The actual state of
Speaker 1: time is not one of the pension funds, but the
Speaker 1: state itself. So we have a lot of sovereign wealth
Speaker 1: on types that are investing on behalf of tax payers.
Speaker 1: So it's very long dated capital. They're lower risk tolerance,
Speaker 1: I would say, very high standards on quality of service
Speaker 1: and quality of infrastructure decision making. So we're very proud
Speaker 1: that we're a partner to that type of capital.
Speaker 2: So let's talk a little bit about the residential side.
Speaker 2: Before we look at the commercial side. You mentioned you
Speaker 2: are in thirty two markets buying single family homes. How
Speaker 2: many homes have you, guys?
Speaker 1: So their platform service is about fifty thousand units now.
Speaker 1: So we've purchased and most of the homes were purchased
Speaker 1: one at a time, independent due diligence, independent construction management
Speaker 1: to get the home back up to current market standards,
Speaker 1: and we manage each home independently.
Speaker 2: So that implies that some of the homes you're buying
Speaker 2: are kind of project homes. A wrecked or otherwise neglected
Speaker 2: doesn't even have to be a willf elected destruction, just
Speaker 2: time and tide.
Speaker 1: Just what we like to say is it's deferred cappex.
Speaker 1: So you'll find that owners that have owned the home
Speaker 1: for ten, fifteen, twenty years become pretty comfortable with a
Speaker 1: smudge paint or a stained floor, or old countertops, or
Speaker 1: appliances that may make noises at night or that or
Speaker 1: that you know, that bathroom set that leaks and whatever,
Speaker 1: and so people just get comfortable in their homes and
Speaker 1: they they tend not to reinvest in real time on
Speaker 1: keeping that home up to current market standards. So we
Speaker 1: buy those homes that haven't really been touched in fifteen
Speaker 1: or twenty years. They've still got the original builder interior.
Speaker 1: We make sure that, of course that the bones of
Speaker 1: the house are good, the foundation and the walls and
Speaker 1: so forth, but then we pretty much trip them down
Speaker 1: to I wouldn't say down to the studs, but down
Speaker 1: to the sheet rock and put a brand new interier
Speaker 1: in on. We oftentimes people don't buy a roof, they'll
Speaker 1: let the roof go a longer than maybe the staple
Speaker 1: exact or a third one, or bought a lot of
Speaker 1: roofs and buy a lot of hvacs. We take out
Speaker 1: a lot of compressors that are still running on those
Speaker 1: old toxic gases. So we basically bring the home up
Speaker 1: to a current monitor standard and there's a there's a
Speaker 1: profit in that that the home you get paid to
Speaker 1: go and improve PA's real estate.
Speaker 2: And then how do you figure out what to lease
Speaker 2: these for? And do you ever sell any of these homes?
Speaker 1: We do sell we do. The platform is pretty nimble.
Speaker 1: So if for example, we were talking before the show,
Speaker 1: we were talking about how some markets have really benefited
Speaker 1: from the post COVID migration and it's changed their customer
Speaker 1: based dramatically. So think about Naples, Florida and clear Water
Speaker 1: and those types of places. So in those places, home
Speaker 1: prices since pre COVID are up maybe forty fifty percent
Speaker 1: and rents are up twenty twenty five percent, so they
Speaker 1: really don't really make much sense more as a as
Speaker 1: a rental investment. So we're cleaning those homes back up
Speaker 1: and selling them back to the consumers. So that's an
Speaker 1: active part of portfolio trimming and optimization, and it's cool
Speaker 1: to have the capability to sort of execute in both markets.
Speaker 2: So it's funny you mentioned Naples and Clearwater. A few
Speaker 2: of the areas adjacent to those really got to lacked
Speaker 2: by that last hurricane that came through last year. What
Speaker 2: do you do when you have a natural disaster? Is
Speaker 2: that does that create any interest or is it just
Speaker 2: just too much may.
Speaker 1: Have It's well, we've been hit by hurricanes several times,
Speaker 1: floods several times, tornadoes several times. Given that the homes
Speaker 1: are in thirty markets, the good news is no one
Speaker 1: event has a big impact on the portfolio. The bad
Speaker 1: news is all events you get to experience.
Speaker 2: Right, So diversified, which means you're embracing every natural right.
Speaker 1: So in Houston one year, we got hit in Houston
Speaker 1: and in Florida at the same time, two different hurricanes.
Speaker 1: So what's interesting is that now we have a natural
Speaker 1: disaster of team and response unit and a playbook which
Speaker 1: is a little bit unfortunately you have to have that,
Speaker 1: but we use it every couple of years.
Speaker 2: Now.
Speaker 1: We tend not to invest when those markets are busted.
Speaker 1: We do see a lot of demand for our rentals
Speaker 1: because when you know, a few percent of the housing
Speaker 1: stock gets taken offline for a storm, it creates pressure
Speaker 1: on demand. But now our job is just to go
Speaker 1: in there and get the homes fixed as fast as
Speaker 1: we can and get them back into service.
Speaker 2: So fifty thousand homes, I'm going to assume you're a
Speaker 2: self insurer on all those homes.
Speaker 1: We do so Amerus is completely verted integrated. We own
Speaker 1: our own insurance platform, so we're the we're you know,
Speaker 1: we basically access our coverage through the reinsurance markets. At
Speaker 1: our scale, it's hard to go get insurance through the
Speaker 1: normal channels, and so we set up our own insurance
Speaker 1: brokerage and risk attention platform and now we we insuran
Speaker 1: through the resurance markets.
Speaker 2: Huh really very very intriguing. Uh So let's let's talk
Speaker 2: a little bit about some data and technology you use. Sure,
Speaker 2: you guys created your own platform. Tell us a little
Speaker 2: bit about what it was like developing that and what
Speaker 2: makes it specific and unique to Amhurst.
Speaker 1: It's interesting because you know, today we talk about AI
Speaker 1: and and uh, you know, high speed computing, and what
Speaker 1: I look at, what we do is being comically you know,
Speaker 1: simple compared to what we talked what we're talking about
Speaker 1: today with generative AI. But when we started this in
Speaker 1: the late eighties, so that was the job I was
Speaker 1: pronted into, which was, hey, let's figure out how to
Speaker 1: differentiate pricing from one mortgage pool to the next. They've
Speaker 1: got different interest rates, they've got different LTVs, they've got
Speaker 1: different credit scores, they must have different values. So I
Speaker 1: was part of a small or the our team was
Speaker 1: part of a small group of people tackling this problem
Speaker 1: in the late eighties early nineties, and what we do
Speaker 1: today is just now growth of that original project. So
Speaker 1: it's a quantitative analytics approach. It's highly data driven, but
Speaker 1: we need to know the price history for us, that's
Speaker 1: the correlation to to what drives price, and then we
Speaker 1: have a big consumer behavior modeling infrastructure because we have
Speaker 1: what's nice is that over the thirty years of our
Speaker 1: history and then we purchase data that was probably twenty
Speaker 1: five years old at the time, we can measure how
Speaker 1: consumers behave to changes in their economic environment, and that
Speaker 1: consumer behavior will affect home prices and will affect performance
Speaker 1: on credit. It's that So that's the core competency, and
Speaker 1: it's just leveraged into if it's a loan, if it's
Speaker 1: a security back by a loan, if it's the actual
Speaker 1: estate itself. So from a data perspective, think about it
Speaker 1: this way. So obviously the S and P five hundred
Speaker 1: is five hundred names and they report four times a year,
Speaker 1: and God loved the analysts that have to figure out
Speaker 1: how to price these things with so little information. We
Speaker 1: have one hundred million items that we're following. Is one
Speaker 1: hundred million piece of real estate in the country. We've
Speaker 1: gathered up all the information you would need to do
Speaker 1: an appraisal, and we keep that information current in real time,
Speaker 1: and we've automated the appraisal process for evaluation both intrinsic value,
Speaker 1: meaning like where would we pay it, where would we
Speaker 1: buy it, and where is the fair market price that asset?
Speaker 1: From that level, from price and from consumer behavior. Now,
Speaker 1: so now we're watching the payments on every mortgage in
Speaker 1: the country, so you can see who paid, Did Maryland
Speaker 1: do better than Texas last month? And more importantly, versus
Speaker 1: the model, who outperforms, who underperformed. Because there's a schedule,
Speaker 1: there's an expectation for not everyone to pay every month.
Speaker 2: So when you're trying to put a value on a home,
Speaker 2: you're not just sending a third party appraiser oute to
Speaker 2: do a drive buy and go. Yeah, that's about two
Speaker 2: seventy five. You're actually crunching a lot of numbers. And
Speaker 2: this is proprietary you're running.
Speaker 1: We're running a ten year Monte Carlo. That's probably twenty thousand,
Speaker 1: ten thousand paths of outcomes on that asset. It includes
Speaker 1: all of its changes in its property taxes, it's depreciable
Speaker 1: life for the improvements of the assets, and course it's
Speaker 1: revenue stream from rental demand.
Speaker 2: So it's interesting that you started this after the financial crisis,
Speaker 2: given your technological expertise and your unique way to value
Speaker 2: these things. I'm curious how much of this is a
Speaker 2: legacy of your experiences during the Great Financial Crisis. How
Speaker 2: did that couple of years affect how you look at
Speaker 2: risk and pricing of real estate process?
Speaker 1: It's infecting, I would say. So the problem, the problem
Speaker 1: for me, I'll speak for myself personally in the financial
Speaker 1: crisis is that once you find something like that, because
Speaker 1: literally we were saying to people these loans aren't going
Speaker 1: to pay off in two thousand and five, two thousand
Speaker 1: and six, and they were like, Sean, in the worst
Speaker 1: of fault rate, it's been geographically focused. Rather it was
Speaker 1: the farm belt crisis or the California crisis. What are
Speaker 1: you talking about? National home prices going down? And oh,
Speaker 1: by the way, the defaults in those micro markets were
Speaker 1: ten or fifteen percent and the losses were five percent.
Speaker 1: So if you we had five percent losses on a
Speaker 1: market and the market was only five percent of a pool,
Speaker 1: the losses are going to be nearly zero, right, And
Speaker 1: we're like, yeah, except for none of that's going to
Speaker 1: happen this time. And they were like sure, Sean, pat
Speaker 1: you on the head and send you down the road.
Speaker 1: So so one of the problems is once you see
Speaker 1: something like that, you kind of look for them everywhere,
Speaker 1: So we spend our time a lot of time looking
Speaker 1: for looking for sasquatch. And so the other thing is
Speaker 1: is that, and I think it's our core risk management culture,
Speaker 1: is that we think that tiller risk is way more
Speaker 1: probable than everyone else does. So we manage the business
Speaker 1: for extreme shocks to prices, for home prices moving twenty
Speaker 1: five to thirty percent in a year, for interest rates
Speaker 1: moving dramatically in a short period of time. And we
Speaker 1: found you know that check check is all these tail risks. Well,
Speaker 1: it's like the one hundred year floods every ten years
Speaker 1: or so. I've been doing this for thirty years, and
Speaker 1: I've had how many hundred your floods? More than more
Speaker 1: than point three?
Speaker 2: You know. The fascinating thing is I have a vivid
Speaker 2: recollection of a paper, a white paper coming out by
Speaker 2: professors rein Hart and Rogueoff. I remembered it was five
Speaker 2: financial crises. So it was Helsinki, it was Sweden, it
Speaker 2: was Japan, it was Mexico, maybe US, and the Great
Speaker 2: Depression was the fifth one. I don't remember exactly what.
Speaker 2: By the way that paper eventually becomes this time is different.
Speaker 2: Eight hundred years of financial folly. But the average of
Speaker 2: the real estate drop in any modern financial we're not
Speaker 2: talking about tulips. Right. The last century was over thirty
Speaker 2: percent in real estate. And once you once I saw
Speaker 2: that paper, I remember saying, hey, this is in a
Speaker 2: theoretical possibility. This has happened once in decades.
Speaker 1: Right. So people think of home prices as being sort
Speaker 1: of four to five percent price movers per annum, and
Speaker 1: that's the case most of the time. But the problem
Speaker 1: is we don't get to live most of the time.
Speaker 1: We get to live all the time, and so sometimes
Speaker 1: that five percent move can be thirty five percent and
Speaker 1: forty percent. So think about that eighty percent l TV mortgage.
Speaker 1: That doesn't seem like a risky loan. The bar will
Speaker 1: put up twenty percent, the lender put up eighty percent,
Speaker 1: but there's a one in something chance that the home
Speaker 1: price goes goes to sixty five, And if the home
Speaker 1: goes to sixty five, the loan is no longer going
Speaker 1: to pay off. So that was the sort of the
Speaker 1: thing that we built that people hadn't thought through, is
Speaker 1: how to you stochastically forecast a range of outcomes for
Speaker 1: the asset price? Then how does it affect the repayment
Speaker 1: risk on.
Speaker 2: The loan, So you have to have boots on the ground.
Speaker 2: With fifty thousand homes, how big a staff do you have?
Speaker 2: Is it regional? How do you manage since since you're
Speaker 2: now the landlord for these homes, how do you manage
Speaker 2: the regular maintenance the one off you know, things break
Speaker 2: or refrigerator stops, the toilet kits backed up. How do
Speaker 2: you manage that?
Speaker 1: Yeah, it's complicated. So we have a both of an
Speaker 1: on balance sheet group of repairmen. So we're an investment
Speaker 1: management platform that also has trucks with plumbers crews around
Speaker 1: the country and fixing air conditioners. We also have a
Speaker 1: great vendor network and we have a lot of technology
Speaker 1: that the team, as you mentioned, is about fifteen hundred
Speaker 1: people that are just in that single venderaial platform. This's
Speaker 1: is one of the things Amherst does. But that fifteen
Speaker 1: hundred person team is augmented by about two thousand vendors
Speaker 1: of companies and we're able to handle the properties because
Speaker 1: we have a team in the field. So we literally
Speaker 1: have a repair and maintenance team that's assigned to a
Speaker 1: group of homes. So that person has their three hundred
Speaker 1: homes or something, and then they're part of a local
Speaker 1: team that's managing about fifteen hundred units. So it's not
Speaker 1: that different from how you would manage a multi family
Speaker 1: an apartment complex. It's just that the rooms are further apart,
Speaker 1: the units are further apart, and it causes our drive
Speaker 1: time to be higher. But one of the things that
Speaker 1: we went into this that was one of the big
Speaker 1: questions is could you provide good service and could you
Speaker 1: manage them? And we don't get it right all the time.
Speaker 1: But if you think about the fact that how easy
Speaker 1: it is to get someone out to a home, and
Speaker 1: that's part of our filtering criteria of how we buy
Speaker 1: a home. But think about the fact that for ten bucks,
Speaker 1: you can have Dominoes bringing a pizza and somehow of
Speaker 1: that ten bucks they get the delivery person from their
Speaker 1: store to your home with a hot pizza, and they
Speaker 1: were able to pay for the Super Bowl add out
Speaker 1: embedded in that ten dollar cost, like the transportation cost
Speaker 1: to get people to and from these homes, it just
Speaker 1: isn't a barrier. It's really timing and technology to really
Speaker 1: to rout them.
Speaker 2: So let's talk a little bit about technology over the
Speaker 2: past two decades, real time monitoring of things like fire, flood,
Speaker 2: carbon monoxide break ins, whatever, they've become very inexpensive, very ubiquitous.
Speaker 2: Everybody can have it on a phone. Is that anything
Speaker 2: that you've explored in terms?
Speaker 1: We spent a lot of time on it. There's big
Speaker 1: privacy concerns. So we have families, we have fifty thousand
Speaker 1: families living in their homes and they're their homes and
Speaker 1: we're proud to be part of that process. So, you know,
Speaker 1: a lot of that stuff gets a little creepy to us,
Speaker 1: and so we haven't done well.
Speaker 2: There's a difference between a puppy cam where you're seeing
Speaker 2: what's going on in the bedroom and I know in
Speaker 2: my basement I have a flood.
Speaker 1: Like a high water alarm, that sort of thing. So
Speaker 1: that we're still on their network, we're still so that
Speaker 1: technology for us to go at it stronger. We would
Speaker 1: like for those devices to communicate back to us, uh directly,
Speaker 1: not like.
Speaker 2: A like a cell phone.
Speaker 1: So we are looking at that. There's locks now you
Speaker 1: can buy that have little cell phone transmitters in them, right,
Speaker 1: So we may we may look at things like that,
Speaker 1: but at this point we have so many people on
Speaker 1: the field. We're touching the houses six, eight, nine times
Speaker 1: a year. We have good relationships with our with our residents.
Speaker 1: A lot of that stuff is a little bit of
Speaker 1: pizaz and we see other people charging residents, you know,
Speaker 1: fifty dollars a month for electronic door lock or something.
Speaker 1: We don't think that that's sustainable cost.
Speaker 2: It's a fifty dollar product. How do you chrusee fifty
Speaker 2: dollars a month.
Speaker 1: I no, I don't don't. I don't get it. So
Speaker 1: we will will it's coming along. If I can get
Speaker 1: direct cell phone connections to a high water alarm, I
Speaker 1: would take it. But really, what we have as a
Speaker 1: person go out there and look and touch the property
Speaker 1: eight times a year, and that's how that's how we
Speaker 1: do it. A lot of this is not so complicated,
Speaker 1: but we have you know, through COVID was fascinating because
Speaker 1: that field team and we have a big construction management team.
Speaker 1: So these guys, those fifty thousand homes have all been renovated.
Speaker 1: So that those teams during COVID man they up and
Speaker 1: they went out and they made us so proud they
Speaker 1: provide a service to the residents. They finished construction jobs.
Speaker 1: They got homes back in service so people could move
Speaker 1: out of wherever they were and get into a home.
Speaker 1: So it's been fascinating to watch this business run through
Speaker 1: a crazy COVID cycle, and then a crazy post COVID cycle,
Speaker 1: and now an interest rate cycle. The team has had
Speaker 1: to be pretty nimble. Huh.
Speaker 2: Really quite intriguing. Let's talk a little bit about about
Speaker 2: your space. What are you doing these days in mortgage
Speaker 2: backed securities? Does that market exist remotely like it did
Speaker 2: in the two thousands.
Speaker 1: Well, it's great that you ask about it. So the
Speaker 1: bulk of my career was spent in the mortgage backed
Speaker 1: securities and structure products markets. The single family riendal of
Speaker 1: business kept us very busy while the FED was monetizing
Speaker 1: so many mortgages, so, as you know, they own about
Speaker 1: a third of all mortgages that were ever issued. The
Speaker 1: relative value for non government investors was so bad that
Speaker 1: we wound down a lot of our capabilities in that space.
Speaker 1: We actually sold our investment bank to Manco Santander as
Speaker 1: part of just the frustration with how much intervention had
Speaker 1: sort of driven down value in that space. Well, now
Speaker 1: that's completely reversed and there's a real vacuum today, a
Speaker 1: real vacuum. As the FED stopped buying mortgages, they bought
Speaker 1: a third of the whole market when they stopped buying them.
Speaker 1: I think the belief was that the market would get
Speaker 1: back to its regulary scheduled programming and the traditional investors
Speaker 1: would show up to buy them, and they didn't because
Speaker 1: a lot of those traditional investors don't exist anymore.
Speaker 2: You lose a whole generation, there's no succession beyond.
Speaker 1: This is the largest debt cautter market in the world,
Speaker 1: the largest, most liquid, and it's lost its sponsor. So
Speaker 1: the sponsor went from being the big investment banks, the
Speaker 1: government agencies, the big bank balance sheets, a lot of
Speaker 1: the insurance can be balance sheets, and the money managers.
Speaker 1: The FED displaced all of them. Then they changed regulations
Speaker 1: to where the investment banks can't really step in. The
Speaker 1: agencies are no longer allowed to run balance sheets, the
Speaker 1: reats are not really well positioned to step up in
Speaker 1: the size, as we just saw in the four quarter.
Speaker 1: So there's a real lack of sponsorship with the assets,
Speaker 1: and they've become incredibly attractively priced. So we've been ginning
Speaker 1: back up those strategies. We still we've always run strategy
Speaker 1: that space, but they've been very sort of boring strategies,
Speaker 1: index tracking, index outperformance, that kind of thing. But now
Speaker 1: there's opportunity to really go in and build proper hedge
Speaker 1: fund strategies, proper total return strategies. The relative value is
Speaker 1: sort of startlingly attractive now.
Speaker 2: So I always hated the term financial repression, but what
Speaker 2: you're describing really is the FED engaging in financial repression
Speaker 2: on that corner of the market.
Speaker 1: Well, what I would say is that they were investing
Speaker 1: for a non monetary focus or motivation. Right, They didn't
Speaker 1: care what their returnal the mortgages were they trice and sensitive, right,
Speaker 1: they cared what the lower mortgage rate did to the economy.
Speaker 1: So as a person that's just investing for an economic return,
Speaker 1: you can't compete with that, right, So their motivations were
Speaker 1: totally different, and they and they basically drove down the
Speaker 1: relative value to where on a hedge adjusted basis, if
Speaker 1: you looked at a mortgage and you'd sort of get
Speaker 1: it back to where it's got the same risk a treasury,
Speaker 1: it was yielding almost half a percent less than a treasury.
Speaker 1: They normally yield half a percent more. Now they yield
Speaker 1: one percent more. So in fixed income terms, that's a lot.
Speaker 1: So so now we're really focused on mortgages that we're
Speaker 1: way more active than we have been in the past,
Speaker 1: and we're excited about the opportunities there, and we have
Speaker 1: a commercial morgage lending strategy as well.
Speaker 2: Huh, that's kind of interesting. So let's talk a little
Speaker 2: bit about what's going on in the commercial space. We
Speaker 2: were talking earlier about sixty minutes. Did a piece recently
Speaker 2: on the New York real estate market is never coming
Speaker 2: back and all these big office towers are you know, empty.
Speaker 2: I'm old enough to remember the sea through office towers right.
Speaker 1: Dallas back in the eighties and Dulles the whole right
Speaker 1: the Washington Dulles Quarter was full of sea through right
Speaker 1: see through buildings.
Speaker 2: So we're not there, but certainly the typical high rise
Speaker 2: has you know, a vacancy rate of ten fifteen to
Speaker 2: twenty percent, and the occupancy rate during the day is
Speaker 2: probably another ten to fifteen percent less than that. What's
Speaker 2: going on in the office space.
Speaker 1: So the castle data is pretty fascinating and you can
Speaker 1: get it on your Bloomberg terminal the castle. The castle
Speaker 1: ocup data as we talked about before.
Speaker 2: But by the way, that's all swipe cards of employees
Speaker 2: literally going down.
Speaker 1: The real time physical occupancy data is pretty and it's
Speaker 1: not perfect, like no data set is, but it's pretty startling.
Speaker 1: The last time I looked at it, most markets are
Speaker 1: peaking at fifty percent physical occupancy. Remember I said before
Speaker 1: that in the mortgage market, in the residential mortgage market,
Speaker 1: a borrower can stop making payments and it might be
Speaker 1: two years before the investor actually takes a loss, sometimes
Speaker 1: five years. Well, I think that same thing's been happening
Speaker 1: commercial now for the last since twenty twenty one. Is
Speaker 1: that physical occupancy is the leading indicator to economic occupancy.
Speaker 1: Economic occupancy is who's paying the rent, and in corporate
Speaker 1: leases are of incredibly high credit quality, incredible very few
Speaker 1: leases ever default. Those leases, however, are going to come
Speaker 1: do and the renewal rates are tragically tragically low. So
Speaker 1: if you model out what's going to happen to the
Speaker 1: commercial space from an economic perspective, you don't have to
Speaker 1: be a wizard to figure out that monetary or physical,
Speaker 1: fiscal or financial occupancy is going to track physical accuracy.
Speaker 1: Companies aren't going to be able to give back one
Speaker 1: for one as much space as they're not using because
Speaker 1: they've got this peak and load problem where everyone likes
Speaker 1: to come to work on Wednesdays. So you still need
Speaker 1: the space, but that quantum of space that people need
Speaker 1: has been reduced dramatically and we're seeing it in that
Speaker 1: Castle data. So it's a scary thing to do. But
Speaker 1: if you forecast that the lease payments track the physical usage,
Speaker 1: meaning that what you're seeing today, it's fifteen percent vacancy
Speaker 1: because some leases expired and to get renewed, well, all
Speaker 1: those leases that are being underutilized by half, if those
Speaker 1: don't renew or they renew it much smaller spaces, you
Speaker 1: could create thirty forty percent physical you're actually financial vacancy
Speaker 1: in the commercial space. Now, it's dangerous to forecast that
Speaker 1: far in the future because behavior can change. How much
Speaker 1: space do people need or do they do out the
Speaker 1: fact they want their whole team to get together three
Speaker 1: days a week, so they do they just eat the
Speaker 1: space on the Mondays and Fridays. Some companies are never
Speaker 1: coming back, some jobs are never coming back. So the
Speaker 1: way we look at it, we have some loans in
Speaker 1: the office space. We do feel like it's like bottom
Speaker 1: fishing time and we're taking back real estate. Now that
Speaker 1: is fifty dollars sixty dollars a square foot space for big,
Speaker 1: beautiful buildings that need to be repopulated. But so the
Speaker 1: way we think about is this is that occupancy is
Speaker 1: probably going to drop by a third, but it won't
Speaker 1: be a third for everyone. Right, some places going to
Speaker 1: go to zero, and some guys they won't, They won't
Speaker 1: feel it. So asset selection becomes incredibly important.
Speaker 2: So there's a huge difference between the A class buildings
Speaker 2: and the B and C class. And I've heard people
Speaker 2: say even within A there's a big ring.
Speaker 1: There's the super A stuff, you know, the one Vanderbilt
Speaker 1: thing at two hundred bucks half foot that you can't
Speaker 1: get enough of it. But a block away some traditional
Speaker 1: commodity office space that's just a little draft or whatever,
Speaker 1: you know, that people just don't want it at any price.
Speaker 1: So now that super A space is a very very
Speaker 1: small fracture of the market. So it's not what happens
Speaker 1: there probably isn't going to be sort of impactful, but
Speaker 1: we think that, you know, they're people have to adjust
Speaker 1: to a new normal of demand, like demand function for
Speaker 1: commercial real estate has come down. Now this is, by
Speaker 1: the way, just another domino in a long series of
Speaker 1: what the Inrice Norwitz guys call software eating the world.
Speaker 1: This is technology eating real estate. And so if you
Speaker 1: look at this over longer the time, the way we
Speaker 1: think about it is that technology eight retail and we
Speaker 1: all kind of saw it, right. It was Amazon killed
Speaker 1: the shopping mall. Airbnb has eaten up a lot of
Speaker 1: hotel demand. So technology matching a home to a to
Speaker 1: a rent or a leaser has eaten up a bunch
Speaker 1: of the hotel demand. Now work from home is eating
Speaker 1: is eating office. So we can we kind of have
Speaker 1: a playbook for how this goes. And it's not great.
Speaker 2: And all of these are technology enabled. Without tech, you
Speaker 2: wouldn't be able to do this. The ironic thing is
Speaker 2: the I love people discovered like screen sharing in twenty
Speaker 2: twenty one, right, that tech has been around for a
Speaker 2: dozen plus fifteen years.
Speaker 1: I know, I think about the people that created Skype.
Speaker 1: They must be sort of jumping off a bridge somewhere
Speaker 1: because you know, you couldn't give away Skype pre covid,
Speaker 1: and now now I don't even have calls on my phone,
Speaker 1: my office phone ever anymore. Everything happens over teams are
Speaker 1: over over zoom. So the behavior has changed so quickly.
Speaker 1: But I think that, you know, the CEO from Cisco
Speaker 1: made a good point that the home has become the enterprise,
Speaker 1: and what it was saying is that Cisco is seeing
Speaker 1: people buying really sophisticated communications equipment for their homes because
Speaker 1: now they're they're they're pushing their use case. I so
Speaker 1: for us, it's also kind of fascinating. And this is
Speaker 1: a little bit about how the single trintal trade has
Speaker 1: becomes interesting. Is as people stop going out to the
Speaker 1: mall and they shop at home, as high speed communications
Speaker 1: allows them to stream at home, as delivery allows them
Speaker 1: to and eat at home. Right, these real estate sectors
Speaker 1: are all seeing their demand dry up, the demand for usage.
Speaker 1: All that demand is showing up in the home. It's
Speaker 1: showing up in that eighteen hundred square foot three bedroom
Speaker 1: home because and everyone's use case and demand for real
Speaker 1: estate's changing because they're spending so much more time there.
Speaker 2: So I kind of feel like a lot of those
Speaker 2: big technological shifts we'll post the peak of that like,
Speaker 2: I'm a big online shopper and I've kind of come
Speaker 2: to recognize there's certain things that you just can't buy them.
Speaker 1: Yeah, I have all the time with clothes and things.
Speaker 2: Close is a perfect example. A lot of times you
Speaker 2: order certain things like it's hilarious. You think you're getting
Speaker 2: a four foot tall you know, lamp and this miniature
Speaker 2: and I guess the photo is what the photo is,
Speaker 2: there's just no tape mail tape measure next to it.
Speaker 1: But let me ask you about this, because pre COVID,
Speaker 1: you couldn't have convinced me I could buy groceries on
Speaker 1: an app.
Speaker 2: Oh I was doing that, That's easy. Now.
Speaker 1: I don't think I would ever go back to grocery.
Speaker 2: In fact, Amazon began that when they bought Whole Food.
Speaker 1: So think about what that means that grocery store, that
Speaker 1: grocery store anchored retail. Ordinarily, the grocery store space was
Speaker 1: undwritten at a loss by the real estate developer, right
Speaker 1: because that was your magnet.
Speaker 2: Now it's your distribution hub and there's no people.
Speaker 1: So what happens to the dry clear, what happens to
Speaker 1: the ice cream shop? What happens to the T shirt shop?
Speaker 1: What happens to the travel agent.
Speaker 2: They have to adapt the same technology and do pick
Speaker 2: up and delver.
Speaker 1: So e commerce is changing, like the footprint for a business,
Speaker 1: it's addressable market. And so I don't think this is over.
Speaker 1: I think that that the pricing of it kind of
Speaker 1: like we talked about the loan starts, the loan defaults,
Speaker 1: and then two years later someone takes a loss. Today
Speaker 1: we're CPI prints higher than people expected because owner equivalent
Speaker 1: rents is higher that OER number was calculable four months ago.
Speaker 1: So the market isn't doing a good job of forecasting
Speaker 1: what it already pricing in what it what already knows
Speaker 1: in any cases. And I think that we're still in
Speaker 1: the repricing phase of real estate for a new a
Speaker 1: new type of demand.
Speaker 2: So some of the solutions to these are wholesale changes
Speaker 2: to the way we built out suburbia, which is so
Speaker 2: car dependent. If we were creating these more walkable communities
Speaker 2: like back in the Andy Griffith days, it's fascinating, suddenly
Speaker 2: fascinating you have retailed that's survivable because everything isn't. Getting
Speaker 2: your car and drive to Target that's right, or have
Speaker 2: Target make a delivery exactly.
Speaker 1: So we spend it. You think about how European cities work.
Speaker 1: That's that's what that's how they're that's how they're designed.
Speaker 2: So so the question is is that something we can
Speaker 2: build here? Is there an appetite for that? Is there?
Speaker 1: I'm spending a fair amount of time on just that is.
Speaker 1: Can you respond to this? Should you respond to it?
Speaker 1: Because as you said, like you know, maybe this is
Speaker 1: a flash in the pan. If all the companies decide
Speaker 1: that employees have to come to work every day, then
Speaker 1: then these trends and occupancy will change and quantum of
Speaker 1: demand will change. But I recently was given a book
Speaker 1: and I read it. It's a companion of essays called
Speaker 1: The City Is Not a Tree. It was written in
Speaker 1: nineteen sixty five, and it was about this. It was
Speaker 1: about how a city should work to optimize the experience
Speaker 1: for its residents and think of a city as a product.
Speaker 1: And so we give the speech to mayors when we're
Speaker 1: asked about sort of how we think about their city
Speaker 1: from a migration investment perspective, and we try to tell
Speaker 1: people that a city is a product. So New York
Speaker 1: City is a product and the customers can choose a
Speaker 1: different product, and it's a great product. It's one of
Speaker 1: the greatest products in the world. But like all customers,
Speaker 1: like all businesses, in all product delivery systems, you have
Speaker 1: to freshen your product to keep your customers happy. And
Speaker 1: we see some cities doing that and some cities not
Speaker 1: doing that. So you have to modify. You can't just
Speaker 1: completely tear down and change.
Speaker 2: So one of my favorite YouTube channels is this kind
Speaker 2: of wacky Canadian expat who moved to Amsterdam, and it's
Speaker 2: called Not Just Bikes, and he talks about walkable cities
Speaker 2: and how different countries in Europe do a better job
Speaker 2: of it, and how there are pockets of it in
Speaker 2: the US right and North America, but they're few and
Speaker 2: far between. It.
Speaker 1: Yeah, I think it's something we're spending time on because
Speaker 1: we're with our vertical integration of manufacturing homes, building homes,
Speaker 1: real estate development. The ability to monetize a home either
Speaker 1: as a cell to a consumer or a rent and
Speaker 1: have into an investor. It gives us the ability to
Speaker 1: think big about development and I haven't seen anyone pull
Speaker 1: off yet. So the master plan community the United States,
Speaker 1: other than maybe the woodlands in Houston very few of
Speaker 1: them are actually master planned for multiple product types where
Speaker 1: you have office, medical, civil, residential, entertainment, all kind of
Speaker 1: thought about together the way you would the way European
Speaker 1: cities were developed. But remember Europe, like you said, you
Speaker 1: said a very key thing. European cities were developed before
Speaker 1: the cars became years a lot of our cities stopped
Speaker 1: growing as core cities and started growing as these suburban
Speaker 1: driven cities because of the car. And so this will
Speaker 1: be simple, this will be think if will you reverse?
Speaker 1: And this is something that global real estate investor are
Speaker 1: thinking about a full time basis. There was a paper
Speaker 1: written about five years ago, I think it was put
Speaker 1: out by the research team Prudential, and it was all
Speaker 1: about urbanization and all of the investment themes across our
Speaker 1: investor base, the biggest invests in the world. We're very
Speaker 1: focused on urbanization as a global theme, and you could
Speaker 1: see it in Southeast Asia, you could see it all
Speaker 1: over China, you could see it. Of course, has happened
Speaker 1: in the United States where people left the small town
Speaker 1: to go to the big city. COVID may have reversed
Speaker 1: one of the largest global trends in investing in the
Speaker 1: last one hundred years. It may have turned. It may
Speaker 1: have turned us from urbanization to de urbanization and the
Speaker 1: impact of that. Now we're not calling that just yet,
Speaker 1: but it is probably one of the most important things
Speaker 1: that people can focus on, or are we going to
Speaker 1: shrink the size of these megacities that all benefited from
Speaker 1: urbanization for the last you know, sort of fifty years
Speaker 1: in the US, maybe the last fifteen years in Southeast Asia.
Speaker 1: So it's an interesting time where the I wish I
Speaker 1: could say I was going to turn out, but there
Speaker 1: is a the ball is bouncing around and we need
Speaker 1: to understand which way it's going to land.
Speaker 2: Tell us about Main Street Renewal.
Speaker 1: Is that so that's the operating platform for the single
Speaker 1: fundamental business. That's our construction management, our real estate brokers platform,
Speaker 1: our leasing platform, the customer service platform. So that's the
Speaker 1: brand name that the consumers see, that our their operating
Speaker 1: partners see for the whole vertically integrated single family rental strategy.
Speaker 1: That's basically analogous to the entire ecosystem of the mortgage market,
Speaker 1: wrapped up under one one corporate label.
Speaker 2: And we've been talking a lot about single family homes
Speaker 2: to be purchased and rented a couple of years ago
Speaker 2: sixty Minutes to a piece talking about, hey, is private
Speaker 2: equity pushing out local buyers? I know you have an
Speaker 2: opinion on this. Tell us a little bit about your
Speaker 2: experience with sixty minutes.
Speaker 1: Sure, sure, So, first of all, I love sixty Minutes.
Speaker 1: I don't know it's just because I'm finally old enough
Speaker 1: to age into their demographic. But I think it's one
Speaker 1: of the best news shows on television because in that
Speaker 1: twelve or fifteen minute segment, they really can simplify a
Speaker 1: topic and make it and make it understandable to everyone.
Speaker 1: The topic of where do we fit in the system
Speaker 1: of the single family housing market is what we're doing
Speaker 1: a good thing or a bad thing? Obviously, you know,
Speaker 1: I've got a couple of thousand people that wake up
Speaker 1: every day and go to work. They don't think they're
Speaker 1: doing a bad thing. So I can tell you our
Speaker 1: perspective of it. I can kind of give you both
Speaker 1: sides of the argument, and people can decide for themselves.
Speaker 1: I mean, part of the argument is that if Sean
Speaker 1: buys the home, or if amorist buys the home, some
Speaker 1: family couldn't buy the home. And it's true that if
Speaker 1: we buy the home, no one else could buy the home.
Speaker 1: I'll give you that part. Now, in the US, we
Speaker 1: track the home ownership rate over time. The home ownership
Speaker 1: rate has grown to sort of mid sixties and babble around.
Speaker 1: It got really really high when we were giving away
Speaker 1: mortgages in two thousand and seven, and then it came
Speaker 1: back down. But that number has been a six handle
Speaker 1: for the last fifty years, right, So sixty something percent
Speaker 1: of people own their homes. The inverse of that number
Speaker 1: is the people that don't own their homes. So that
Speaker 1: number has been between thirty and call it thirty and
Speaker 1: twenty five percent for a very long time. So that
Speaker 1: third of how of families in the US that rent
Speaker 1: their home rent for a mere reasons. One of the
Speaker 1: reasons that they rent is because they can't get amorage.
Speaker 1: And part of our bet in two thousand and nine
Speaker 1: was that the group of people who are going to
Speaker 1: be locked out of the mortgage market is going to
Speaker 1: grow substantially, partially because the standards became higher, and partially
Speaker 1: because student loans became kind of a predatory financial product.
Speaker 1: So having a student loan makes it way more difficult
Speaker 1: to get a mortage. So in this argument of are
Speaker 1: we buying a home that a family is not moving into,
Speaker 1: I put the paradigm in a slightly different way. When
Speaker 1: that home comes up for sale, a lot of families
Speaker 1: show up that want to live in that home. A
Speaker 1: group of those families show up and they can get
Speaker 1: a mortgage and they can buy the home. A group
Speaker 1: of those famili show up and they can't get a
Speaker 1: mortage for that second group of families to get to
Speaker 1: live with that home, and investors got to buy the home.
Speaker 1: And that investor can be and historically has been very
Speaker 1: small investors, people that own one or two homes. Maybe
Speaker 1: they owned a home, lived there, moved away, kept it,
Speaker 1: rented it. And now through the through technology and through
Speaker 1: significant investment platforms like ours, allow larger investors to go
Speaker 1: and invest in that home. So when I sit down
Speaker 1: with policy makers and they're sort of of this mindset
Speaker 1: that I should have stayed away and let the family
Speaker 1: buy the home, what I like to do is say,
Speaker 1: can you guys just put together the pictures of these
Speaker 1: two families and who's going to get to live in
Speaker 1: that home? If the only people who can get a
Speaker 1: mortgage can live there? And who can live there if
Speaker 1: Sean buys the home, because demographically they look more like
Speaker 1: the people that get served by the home when I
Speaker 1: buy it, look a lot more like the people the
Speaker 1: government should be trying to help. And that usually takes
Speaker 1: people and they step back and they go, wait a minute,
Speaker 1: what do you mean. I'm like, well, so Shawn doesn't
Speaker 1: live in fifty thousand homes. Someone's living in there. And
Speaker 1: the people that live in those homes, for the most part,
Speaker 1: are not candidates to get a mortgage in the twenty
Speaker 1: twenty four mortgage standards.
Speaker 2: And it's not because they don't have a jobs and
Speaker 2: they aren't.
Speaker 1: Currently they're paying two thousand dollars a month in rent.
Speaker 1: Our average customer only pays twenty five percent of their
Speaker 1: income in rent. For two thousand dollars. They cover everything,
Speaker 1: They cover the chance that the ac breaks. They don't
Speaker 1: have to pay for that, property taxes, insurance, the whole
Speaker 1: nine yards. So right now, the cost to rent is
Speaker 1: probably thirty percent cheaper than the cost to own. But
Speaker 1: more importantly, if you're not given a chance to get
Speaker 1: a mortgage, it doesn't matter what the cost to own is.
Speaker 1: The cost for you is infinite because you're not allowed
Speaker 1: to get a mortgage. So when they when Dodd Frank
Speaker 1: passed and the standards for mortage credit became unfairly high,
Speaker 1: we said, Okay, this is what's gonna this is what
Speaker 1: the nation to decided it wants to do now against
Speaker 1: my advice when I sat, when I sat at full reserve,
Speaker 1: I said, this doesn't have to happen. This way, we
Speaker 1: can sort out for you what the good subprime was
Speaker 1: from the bad subprime. People are like, we agree, you can,
Speaker 1: but that's not how policy works. That mortgage market has
Speaker 1: been shut down and it's going to stay shut down.
Speaker 2: So what should we do to reopen that mortgage market
Speaker 2: for people who are currently employed have a half decent credit.
Speaker 1: Now, you're baby, we're gonna give in the two hours
Speaker 1: for the podcast. I got a whole list of things
Speaker 1: need to do, but the give us a short PNT.
Speaker 1: The primary, the primary thing you have to do is
Speaker 1: you have to put risk. You have to make risk
Speaker 1: based pricing legal in the US mortgage system. Dodd Frank
Speaker 1: made risk based pricing illegal. So if someone comes in
Speaker 1: with a lower credit score, a higher likelihood of default,
Speaker 1: and remember the likelihood of default could mean that they
Speaker 1: go from being five percent likely to ten percent likely,
Speaker 1: not ninety percent likely. But if someone comes in that
Speaker 1: that has a likelihood default above a certain level, the
Speaker 1: answer is you can't make them the mortgage.
Speaker 2: At any price as opposed to where it's I'll make
Speaker 2: up a round number. If we're at five percent, they
Speaker 2: could buy get a mortgage at six and.
Speaker 1: Three we used the rate used to be three points
Speaker 1: hire two points are so Dodd Frank basically carved out
Speaker 1: the maximum premium you can charge to anyone, and then
Speaker 1: they created recourse for the borrower. So I give this
Speaker 1: presentation in the UK, and I gave this presentation to
Speaker 1: France once and I said, okay, the US passed. They
Speaker 1: were like, why is the demand for rental so high?
Speaker 1: And I said, people can't get mortgages. He said why,
Speaker 1: I said, well, Dodd Frank created a precedent that said
Speaker 1: that if I lend you money to buy your home
Speaker 1: and then you can't pay me back, you can sue me.
Speaker 1: And even in France, the guy would say no, no, no,
Speaker 1: you mean the other way around. I lend you the
Speaker 1: money you don't pay, I can sue you and I'm like, no, no.
Speaker 1: So there's there's this concept that that that was part
Speaker 1: of the the ether in the financial crisis, that the
Speaker 1: banks were the proximate cause for the default, and so
Speaker 1: the bank should not be allowed to make these loans.
Speaker 1: There were some bad back that's a.
Speaker 2: Wild statement because as someone literally wrote a book on this,
Speaker 2: banks did a bunch of stuff that wasn't very smart.
Speaker 2: But it's hard to say the banks making loans were approximate,
Speaker 2: cause now there's a handful of banks doing the ninja stuff,
Speaker 2: and but that was.
Speaker 1: There really enough bad acts to go around. The banks
Speaker 1: had culpability, the securitization industry had culpability, Serving industries culpability,
Speaker 1: The ratings agency agencies had culpability. And this is why
Speaker 1: I spend time washing trying to explain to people. But
Speaker 1: the consumers had culpability as well. So a lot of
Speaker 1: people with fraudulent loans six eight loans. So we bought
Speaker 1: a bunch of these loans. Something people don't know is
Speaker 1: that we audited eighty thousand loan contracts that we bought,
Speaker 1: and we there's a return to cinder clause in mortgage
Speaker 1: contracts that most people don't know about.
Speaker 2: Right.
Speaker 1: And if the bar were defaulted and the contracts were
Speaker 1: in a certain way, the person that sold your loan
Speaker 1: has to buy it back. So in these eighty thousand
Speaker 1: loans you kind of had sort of two big populations
Speaker 1: of predatory borrowers. One with a little mini we call
Speaker 1: the little Minnie Donald Trump's. They would have like twenty
Speaker 1: five or thirty or forty homes, no equity down. They're
Speaker 1: all rented, no management, kind of like yolo of like
Speaker 1: if they go up, we're going to refinance them. If
Speaker 1: they don't, we're going to send the keys back in.
Speaker 1: And these were loans that were made with no equity
Speaker 1: from the barrower eighty percent first, twenty percent second investor loans.
Speaker 1: And then then there were a group of people who
Speaker 1: really just wanted a house and they were willing to
Speaker 1: fib about their financial standards to get there, right, and
Speaker 1: so and the banks and the mortga originators. In many
Speaker 1: cases there's eighty thousand files. You would open up the
Speaker 1: file and it would say the person was a dental
Speaker 1: hygienist and made one hundred thousand dollars a year, no document,
Speaker 1: and that loom was loans approved. Now in this you
Speaker 1: file would be the application that got denied that said
Speaker 1: that they were a dental assistant and they made fifty
Speaker 1: thousand dollars a year, so they would give us the
Speaker 1: file that so they was.
Speaker 2: So those were the I heard stories at the time
Speaker 2: of the mortgage brokers who were able to guide an
Speaker 2: applicant through coaching. Coach, don't write this, don't write here
Speaker 2: what you got to say? And basically, you know, we're
Speaker 2: co conspirators to fraud.
Speaker 1: And you know the Mortriges broker was making five or
Speaker 1: six percent of the loan amount, right, it's a lot
Speaker 1: of incentives.
Speaker 2: So I blame them much more than the person who
Speaker 2: just did what they were told they were wrong. At
Speaker 2: this point, really the professional is the one got a
Speaker 2: whole scount.
Speaker 1: I think that we're hung up on who to blame,
Speaker 1: not you and me. But if the market is who
Speaker 1: to blame, and the market isn't paying attention of who
Speaker 1: got harmed, because in the first degree, the person that
Speaker 1: got harmed was the person who got four clothes up
Speaker 1: on and got addicted from their home, that's a very
Speaker 1: clear harm to see. The harder harm to see is
Speaker 1: that maybe eight million families that haven't been able to
Speaker 1: buy a home since this law went and it's fifteen
Speaker 1: years and there's no progress, So the rental market has
Speaker 1: to grow. Institutional capital is going to play a part
Speaker 1: in every home transaction. Its social capital has to be
Speaker 1: there to make the loan if they're not going to
Speaker 1: buy the home. Providing service to the third of American
Speaker 1: families who rent for various reasons. Now, about a third
Speaker 1: of our customers, or twenty percent of our customers move
Speaker 1: out every year, so they were never like long term
Speaker 1: committed to that location to begin with. The credit scores
Speaker 1: of our customers suggest and the financial condition of our
Speaker 1: customers suggests it would be very difficult. It's not it
Speaker 1: possible for them to get a mortgage on average. So
Speaker 1: this is the solution for people to move out of
Speaker 1: the Other thing people think about it is that it's
Speaker 1: okay to rent apartments. So that's socially acceptable to invest
Speaker 1: in apartments and rent them. But apartments are primarily one
Speaker 1: and two bedroom products, so we're a three bedroom product.
Speaker 1: So as you age out of an apartment or you
Speaker 1: need more space because you work from home, or you
Speaker 1: have a family or whatever, and you age into the
Speaker 1: single family product, which is location driven, local amenities driven
Speaker 1: blah blah blah. So you would go and get a
Speaker 1: mortgage and buy. But that cross section of the customer
Speaker 1: base that the mortgage market serves has shrunk so much
Speaker 1: that we set up this platform because we knew they
Speaker 1: were coming. We knew that they're going to want to
Speaker 1: live in that product and they're going to need to
Speaker 1: get there with a different financial solution than a mortgage.
Speaker 1: So we developed an institutional scale, securitized financing vehicle for
Speaker 1: the pool of homes. We developed the services that wrap
Speaker 1: around the pool of home to lower its cost to capital,
Speaker 1: So the cost of capital for single time really today
Speaker 1: is in the five to five and a half percent range.
Speaker 1: Prior to us getting involved, the cost of capital for
Speaker 1: rental was probably eight hundred over and nine hundred over
Speaker 1: because it was provided by small investors taking very specific
Speaker 1: location risk. Now we can have a thousand homes, all
Speaker 1: the adiosyncratic risk is pretty much gone. So we feel
Speaker 1: very proud of what we're doing. And I wish that
Speaker 1: the conversation about this crowd out would focused more on
Speaker 1: the specifics of who didn't get to buy, but who
Speaker 1: got to live there, and when people see that and
Speaker 1: they see that, Oh wait a minute, these are three
Speaker 1: hundred thousand OAR homes. These are not you know, these
Speaker 1: are homes that that bar, that resident would have a
Speaker 1: very difficult time getting into without us, and we were
Speaker 1: able to provide a really good service at a very
Speaker 1: effective price for that customer base.
Speaker 2: That's a really interesting answer to a complicated question, and
Speaker 2: it still leaves open the problem that there are eight
Speaker 2: million people that might otherwise be on be homeowners. But
Speaker 2: the rule change has been and the.
Speaker 1: Way I think about it, the way you get me
Speaker 1: a slopbox. But in the worst of the worst mortgage
Speaker 1: pools that we were short and the dirtiest of the pools,
Speaker 1: where everybody was lying the bar, where the banker, the securitizer,
Speaker 1: everything age, everybody was lying the worst of the worst.
Speaker 1: About thirty five percent of the loans defaulted, which means
Speaker 1: that two thirds of even those dodgy things paid. So
Speaker 1: those are two thirds of those families got to get
Speaker 1: on the economic ladder and own the piece of America.
Speaker 1: Because the third worked out so poorly, we shut out
Speaker 1: the two thirds. And that's kind of the frustration I
Speaker 1: had with Washington. It is like guys like I know
Speaker 1: there's to throw the baby out with the bath or
Speaker 1: what other. But you're thrown out. You're throwing out an
Speaker 1: opportunity for people to own a piece of the country
Speaker 1: and act as owners in their community because you don't
Speaker 1: have a good way to manage the ones that don't
Speaker 1: work out. So we should be focused on what to
Speaker 1: do when they don't work out. We shouldn't prohibit the
Speaker 1: activity because some of it doesn't.
Speaker 2: Work out well. Congress seems to have its act together.
Speaker 1: I'm sure, I'm sure it's next to the docket, right.
Speaker 2: This will be worked out, all right, So I only
Speaker 2: have you for a limited amount of time. Let's jump
Speaker 2: to our favorite questions. We ask all of our guests
Speaker 2: starting with what have you been entertained with these days?
Speaker 2: Tell us what you're either watching or listening to.
Speaker 1: Oh wow, So I'm a very boring person. I spent
Speaker 1: a lot of my time buried in data and analytics.
Speaker 1: I think that I really love the whole Yellowstone series.
Speaker 1: I'm upset that Costner backed out because I thought the
Speaker 1: production quality was so good. So I've seen all of
Speaker 1: the pre the you know, the prequels and so forth.
Speaker 1: So on the entertainment side, I think that streaming has
Speaker 1: set a whole new bar for quality of broke.
Speaker 2: Yeah, no, that's absolutely on my list. Tell us about
Speaker 2: your early mentors who might have helped shape your career.
Speaker 1: Wow. Well, so I've got a big family. I'm one
Speaker 1: of five kids. My parents were serial entrepreneurs. I've got
Speaker 1: four big sisters, and so they're all successful in various ways,
Speaker 1: and so the family has always been the primary motivator
Speaker 1: and leaders. You have to this in our business. You know,
Speaker 1: in finance, who you marry really matters. So I've been
Speaker 1: married for twenty eight years. My wife was in finance.
Speaker 1: She ran an investment management business, built it up and
Speaker 1: sold it. So having support at home and having a
Speaker 1: real partner in the business is super super important our jobs.
Speaker 1: When you're the founder of a business, you know, the
Speaker 1: hours are long and the mental exercise is significant. So
Speaker 1: having the right teammate at home is absolutely paramount.
Speaker 2: I was.
Speaker 1: I had a high school economics teacher who later went
Speaker 1: to work for the Federal Home Loan Bank of Dallas
Speaker 1: named Sandy Hawkins, who was just fantastic for a high
Speaker 1: school economics teacher. She covered everything from Milton Friedman to
Speaker 1: free lunches in a way that made it fun for
Speaker 1: high school kids, and I absorbed every second of that
Speaker 1: I could. And then I had this really unusual situation
Speaker 1: because I was at this brokerage firm when I was
Speaker 1: very young, and mortgages were just getting some science around them,
Speaker 1: and I was always good at math and I had
Speaker 1: been writing code since I was in the sixth grade.
Speaker 1: So I had real support around Wall Street because at
Speaker 1: the time there was a small club of firms that
Speaker 1: were helping solve this problem together. And so I had
Speaker 1: a guy named Frank Gordon who ran mortgage research at
Speaker 1: First Boston. That was just a great support to kind
Speaker 1: of bring me up up the learning curve.
Speaker 2: Huh interesting. Tell us about some of your favorite books
Speaker 2: and what have you been reading recently.
Speaker 1: Well, I mentioned I read A City Is Not a Tree.
Speaker 1: It's a little bit boring, but it's fascinating because I
Speaker 1: do think that there's an opportunity for us to rebuild
Speaker 1: microcities instead of instead of going to the exerbs and
Speaker 1: trying to adjoin a city. I do think that is
Speaker 1: something that we're working on, to just PLoP in the
Speaker 1: middle of nowhere and build a full stand up city,
Speaker 1: which would be fascinating. My my daughter and I listened
Speaker 1: to crime Junkies and on the entertainment side, I think
Speaker 1: it's one of the most popular, other than Years of course,
Speaker 1: one of the most popular podcasts in the country. It's fascinating.
Speaker 1: It's it's a couple of young women that that tell
Speaker 1: the story of some sort of unsolved mystery or solved
Speaker 1: mystery of real time what they call it there, it's
Speaker 1: a it's the real crime dramas. I think it's been
Speaker 1: pretty fascinating. And I've got we have two kids, and
Speaker 1: my wife and I have a freshman at Columbia and
Speaker 1: a sophomore at Stanford, so we're spending a lot of
Speaker 1: time learning about the college.
Speaker 2: Experience freshmen at Columbia. Oh, so you're you're back and.
Speaker 1: Forth, but my poor wife is on like the coast
Speaker 1: to coast tour.
Speaker 2: Are you are you guys in Austin?
Speaker 1: A lot home is in Austin, so you're halfway or exactly,
Speaker 1: we're equally it's equal travel to either place.
Speaker 2: And uh So, our final two questions, what sort of
Speaker 2: advice would you give a recent college grad interested in
Speaker 2: a career in mortgages real estate cra anything along those lines.
Speaker 1: Yeah, So whenever we have interns come in or we
Speaker 1: have young executives start, I buy them a couple things.
Speaker 1: So I buy them the Frank Fobose Handbook on mortgagsback securities,
Speaker 1: the Mortgage back Nerds Bible, and I buy them a
Speaker 1: book Bernstein's book called Against the Gods. And I really
Speaker 1: think that maybe it's just because I'm such a quant nerd,
Speaker 1: but I think that Against the Gods it's a very
Speaker 1: small book, a very quick read, but it does a
Speaker 1: really good job of teaching people that you can apply
Speaker 1: quantitative analytics and probably a theory to almost anything and
Speaker 1: to everything, to your life decisions, to everything. And I
Speaker 1: think it provides a nice paradigm in a world where
Speaker 1: today it feels like, because of the political environment, people
Speaker 1: are sort of it's black or it's white, it's zero
Speaker 1: or it's one, and it's never zero one, right, There's
Speaker 1: always some difference in between. So that's a book that
Speaker 1: I think is sort of required reading at Amherst to
Speaker 1: really understand the history of risk management, the history of
Speaker 1: ability theory, how it first turned into what are the
Speaker 1: big missed pricings have been? So it's not a super
Speaker 1: complicated read, but I think it does a really good
Speaker 1: job of taking people from thinking about the world as
Speaker 1: trying to predict a thing, instead of saying, wait a minute,
Speaker 1: there's a range of things. Can I be okay with
Speaker 1: a broadery of outcomes versus just betting on that one thing?
Speaker 2: And pretty much everything Peter Bernstein writes is great, awesome.
Speaker 1: The gold One's even good too.
Speaker 2: And our final question, what do you know about the
Speaker 2: world of real estate investing today? You wish you knew
Speaker 2: thirty so years ago when you were first getting started.
Speaker 1: Wow, that's fascinating. The ecosystem of real estate has been
Speaker 1: hard for me to follow, coming at it from the
Speaker 1: fixed income markets, so just understanding the various players of
Speaker 1: what they do and how they're motivated has been something
Speaker 1: I wish I would have just sat down and mapped
Speaker 1: out early on, because understanding how people are sort of
Speaker 1: economically rewarded really helps you predict their behavior. And I
Speaker 1: was kind of confused by that for a long time,
Speaker 1: trying to pick the thing that was the right answer
Speaker 1: instead of the thing that would benefited to most people.
Speaker 1: It's like in the financial crisis, we were we were
Speaker 1: short countrywide in scale hundreds of millions of dollars, and
Speaker 1: Bank of America.
Speaker 2: Bought them but for like next to nothing though right, well,
Speaker 2: but but.
Speaker 1: Yeah, but it was worth less than nothing, and so
Speaker 1: zero was a good was a good outcome for that thing.
Speaker 1: So at that point we realized that the consequence of
Speaker 1: countrywide failing was so great that the system was going
Speaker 1: to find an alternate outcome. So we switched to our
Speaker 1: thesis to that point to understand that the value an
Speaker 1: asset might have more to do with the consequences of
Speaker 1: that asset failing than the assets actually probably a failing.
Speaker 1: And that's something I wish I would have figured out before,
Speaker 1: because it.
Speaker 2: Was so you and I could go down this rabbit
Speaker 2: hole because we were short c T, we were short Leahman,
Speaker 2: and we were short AIG and AIG similarly too systemically important.
Speaker 2: It couldn't be allowed to crash and burn. But what
Speaker 2: was so fascinating was, Okay, how come Leman Brothers was
Speaker 2: left out to fall on its face, uniquely amongst the
Speaker 2: giant financial players. And I have a pet theory which
Speaker 2: I've never been able to validate anywhere. People forget, you know,
Speaker 2: Warren Buffett very famously made alone to Goldman. Sachs sure
Speaker 2: that at very advantageous price has got a nice piece
Speaker 2: of Goldman. Great bit of business for Berkshire Hathaway. What
Speaker 2: people forget is a few months earlier he had offered
Speaker 2: that deal to Dick Folds, and Dick Fold said, what
Speaker 2: is this so man trying to do? Steal the company?
Speaker 2: Tell him to go jump? And once you turned down
Speaker 2: Warren Buffett, how can the Treasury Department or the Fed?
Speaker 2: Yeah right, you know, all right, we're gonna bail you
Speaker 2: out of a couple hundred billion dollars. Chuse you had
Speaker 2: a chance to save yourself, but you waited for us.
Speaker 1: It's super complicated. We were a little bit on the
Speaker 1: outside looking in on that deal. We did price Leman,
Speaker 1: We priced more than Stanley for a lot of different investors.
Speaker 1: We priced bear Stearns. The magnitude of the losses was
Speaker 1: hard to get your head around, but it felt like
Speaker 1: the capital markets had it about right. So when bear
Speaker 1: Stearns was sold, their CDs was trading thirty five points
Speaker 1: up front for the senior unsecured piece. So it's meant
Speaker 1: that the bond portion of the capital structure had about
Speaker 1: a sixty five dollars recovery if you marked the market
Speaker 1: bear Stearns, that was about right. But the consequence of
Speaker 1: wiping out the equity, it had effects that we couldn't
Speaker 1: even years later I figured out what the effects were.
Speaker 1: But like the you know, it's kind of like the
Speaker 1: old anti hall, Like there's what they're saying, and then
Speaker 1: there's what's in the subtitles, like the macro of who
Speaker 1: owned the equity, who was going to get crammed down,
Speaker 1: who owned the fixed income? Who was going to end
Speaker 1: up with control? Like there was a much bigger That's
Speaker 1: what I'm trying to say about what to learn is
Speaker 1: that the first instance of what you see if something
Speaker 1: probably is a fraction of the story.
Speaker 2: Sure, and if you remember, oh, you have a weekend
Speaker 2: to figure this out. We expect a deal before markets open.
Speaker 1: These trillion dollar ballance sheet's a full of complex liquid
Speaker 1: assets and you have a weekend. So it was I
Speaker 1: think that's the thing is, it's probably never as obvious
Speaker 1: as it looks would be one advice, and to understand
Speaker 1: the whole ecosystem, not just one asset's you know sort
Speaker 1: of risk profile.
Speaker 2: Huh. Well, Sean, thank you for being so generous with
Speaker 2: your time. This has been absolutely fascinating. We have been
Speaker 2: speaking with Sean Dobson. He is the chairman, chief executive
Speaker 2: officer and chief investment officer at Amherst Group, managing about
Speaker 2: sixteen point eight billion dollars. If you enjoy this conversation, well,
Speaker 2: be sure and check out any of our previous five
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