WEBVTT - Sean Dobson on the US Real Estate Industry 0:00:03.000 --> 0:00:12.160 Bloomberg Audio Studios, Podcasts, radio News. This is Master's in 0:00:12.280 --> 0:00:16.800 Business with Barry rid Hoolds on Bloomberg Radio. 0:00:18.800 --> 0:00:22.360 This week on the podcast, I have an extra special guest. 0:00:22.920 --> 0:00:27.160 Sean Dobson has really had a fascinating career as a 0:00:27.200 --> 0:00:31.040 real estate investor, starring pretty much at the bottom and 0:00:31.120 --> 0:00:35.080 working his way up to becoming a investor in a 0:00:35.159 --> 0:00:39.960 variety of mortgage backed securities, individual homes, commercial real estate, 0:00:40.360 --> 0:00:46.599 really all aspects of the finding, buying, and investing in 0:00:46.640 --> 0:00:50.000 real estate. And on top of that, he's pretty much 0:00:50.200 --> 0:00:53.440 a quantitative geek, so he is looking at this not 0:00:53.800 --> 0:00:58.600 simply from the typical real estate investment perspective, but from 0:00:58.640 --> 0:01:03.880 a deep quantitative analytical basis. If you're interested in any 0:01:04.000 --> 0:01:09.920 aspect of commercial, residential, mortgage back real estate, then you 0:01:09.959 --> 0:01:12.959 should absolutely listen to this. It's fascinating and there are 0:01:13.000 --> 0:01:16.800 a few people in the industry who not only have 0:01:16.920 --> 0:01:21.479 been successful as investors, but also very clearly saw and 0:01:21.560 --> 0:01:25.120 warned about the Great financial crisis coming because it was 0:01:25.200 --> 0:01:26.840 all there in the data if you were looking in 0:01:26.840 --> 0:01:30.520 the right place. And continues to build and expand the 0:01:30.600 --> 0:01:34.360 Amherst Group into a real estate powerhouse. I found this 0:01:34.400 --> 0:01:37.560 conversation to be absolutely fascinating, and I think you will 0:01:37.600 --> 0:01:41.880 also with no further ado my discussion with Amherst groups 0:01:42.000 --> 0:01:42.800 Sean Dobson. 0:01:43.160 --> 0:01:44.720 Thank you very much. It's great to be here. 0:01:44.959 --> 0:01:47.640 So let's talk a little bit about your career in 0:01:47.680 --> 0:01:49.760 real estate. But before we get to that, I just 0:01:49.800 --> 0:01:53.960 got to ask on your LinkedIn under education, it says 0:01:54.520 --> 0:01:58.040 didn't graduate none, working for a living. What does that mean? 0:01:58.520 --> 0:02:02.400 I think I answered questions of of when did you graduate? 0:02:02.440 --> 0:02:04.400 And so I said I didn't graduate, and then that 0:02:04.560 --> 0:02:07.000 was your what degrees did you achieve? And I said none? 0:02:07.720 --> 0:02:09.840 And then I think the question was what were you 0:02:09.880 --> 0:02:11.280 doing or what were your interested in? So I was 0:02:11.320 --> 0:02:13.560 working for a living, but I didn't. 0:02:13.360 --> 0:02:17.200 Go to college, did not go to college. So that 0:02:17.280 --> 0:02:19.760 leads to the next question, what got you interested in 0:02:19.800 --> 0:02:20.320 real estate? 0:02:21.040 --> 0:02:24.680 It was it was happenstance. I took a temporary job 0:02:25.200 --> 0:02:28.760 at a brokerage firm in Houston, Texas the summer after 0:02:28.840 --> 0:02:32.080 high school, between high school and college. Really as the 0:02:32.160 --> 0:02:36.040 office runner, run around picking up people's drying cleaning, grabbing lunch, 0:02:36.400 --> 0:02:39.160 opening the mail, that sort of thing. And I took 0:02:39.200 --> 0:02:42.119 the job really because a friend of ours a friend 0:02:42.160 --> 0:02:44.120 of the families had worked there and just said, what 0:02:44.160 --> 0:02:47.600 an interesting sort of industry it was. This is back 0:02:47.600 --> 0:02:49.800 when mortgages were sort of a backwater of the fixed 0:02:49.880 --> 0:02:51.440 income market, so they were traded a little bit like 0:02:51.480 --> 0:02:55.000 UNI bonds or not really well understood, not. 0:02:55.000 --> 0:02:58.720 Well followed nineteen nineties or eighty. 0:02:58.480 --> 0:03:01.720 Seven, wow, nineteen eighty seven. So after that it was 0:03:02.280 --> 0:03:06.080 I later was given some opportunities to join the research team, 0:03:06.960 --> 0:03:08.639 and then took over the research team, and then took 0:03:08.680 --> 0:03:11.480 over the eventually took over the trading platform, and then 0:03:11.520 --> 0:03:14.080 by nineteen ninety four a group of us had started 0:03:14.080 --> 0:03:17.800 our own business, and that's the predecessor to Amherst, which 0:03:17.840 --> 0:03:20.440 we bought in two thousand and have been running it 0:03:20.800 --> 0:03:21.200 since then. 0:03:22.440 --> 0:03:24.320 So when you say you were running the trading desk, 0:03:24.360 --> 0:03:29.440 you're running primarily mortgage backed securities. That's mortgageback exactly. Anything 0:03:29.440 --> 0:03:31.040 else swaps, derivatives and anything wrong. 0:03:31.080 --> 0:03:32.920 So back then it was really just mortgage back securities 0:03:32.960 --> 0:03:35.600 and structured products that were derivatives of mortgage backed securities. 0:03:35.680 --> 0:03:37.480 We sort of carved out a name for ourselves in 0:03:38.240 --> 0:03:41.720 quant analytics around mortgage risk, and that's still a big 0:03:41.960 --> 0:03:45.160 core competency of Amherst is understanding the risks of mortgages 0:03:45.160 --> 0:03:47.440 are kind of boring, but they're also very complicated. The 0:03:47.480 --> 0:03:50.160 borrower has so many options around when the refinance, how 0:03:50.160 --> 0:03:53.760 to repay, if the repay. It takes quite a lot 0:03:53.760 --> 0:03:56.960 of research, quite a lot of modeling, quite a lot 0:03:57.000 --> 0:03:59.119 of data to actually keep up with the mortgage market. 0:03:59.200 --> 0:04:02.440 It's really forty million individual contracts, forty fifty million individual 0:04:02.480 --> 0:04:05.480 contracts and a million different securities, so it takes quale. 0:04:06.080 --> 0:04:08.440 We've built an interesting system to allow to sort of 0:04:08.480 --> 0:04:10.120 monitor all that and price it in real time. 0:04:10.320 --> 0:04:14.720 So if you're running a desk in the two thousands 0:04:14.800 --> 0:04:16.840 and you're looking at mortgage backed then you're looking at 0:04:16.839 --> 0:04:21.239 securitized product. One would think, especially from Texas as opposed 0:04:21.279 --> 0:04:24.760 to being in the thick of Wall Street, you might 0:04:24.800 --> 0:04:29.240 have seen some signs that perhaps the wheels are coming 0:04:29.279 --> 0:04:31.680 off the bus. Tell us about your experience in the 0:04:31.720 --> 0:04:33.440 two thousands, what did you see? Comment? 0:04:33.560 --> 0:04:37.279 Yeah, So from the late eighties until the really the 0:04:37.400 --> 0:04:41.560 late nineties, we were focused primarily on prepayment related risk 0:04:41.640 --> 0:04:44.320 in agency mortgs backed securities. By the time you get 0:04:44.320 --> 0:04:46.919 to the early two thousands, Freddie mc fanny age and 0:04:46.960 --> 0:04:49.440 may were losing market share. A lot of mortgages were 0:04:49.440 --> 0:04:52.400 coming straight from originators and going and being packaged into 0:04:52.440 --> 0:04:55.600 what later became the private label securities market. So as 0:04:55.640 --> 0:04:58.760 part of our just growth, we attack that market. And 0:04:58.920 --> 0:05:01.400 up until that moment in time, we didn't spend a 0:05:01.400 --> 0:05:03.720 lot of time on credit risk in mortgages. We didn't 0:05:03.720 --> 0:05:05.920 really have the model credit risk because that risk was 0:05:05.960 --> 0:05:09.720 taken by the agencies. But in these private labels you had, 0:05:09.760 --> 0:05:11.839 the market was taking the credit risk. So we took 0:05:11.880 --> 0:05:14.799 the exact same modeling approach, which is loan level detail, 0:05:15.279 --> 0:05:19.920 borrower behavior, stochastic processes, options based modeling, and we said, 0:05:19.960 --> 0:05:21.640 let's just take a little detour here and make sure 0:05:21.640 --> 0:05:24.240 we understand the credit risk of these things before we 0:05:24.279 --> 0:05:28.159 sort of travel start making markets and banking and making 0:05:28.160 --> 0:05:29.839 these a core part of our business. At that time, 0:05:29.960 --> 0:05:32.600 this market was about a third of all mortgages, were 0:05:32.640 --> 0:05:34.440 the ones where the credit risk was going into the 0:05:34.440 --> 0:05:37.320 capital markets. So that little detour was in two thousand 0:05:37.440 --> 0:05:41.360 and three and we found a couple of things we modeled. 0:05:42.160 --> 0:05:45.120 We modeled defaults the same way with model prepayments, which 0:05:45.160 --> 0:05:49.719 is an option for the consumer to not pay most. 0:05:48.880 --> 0:05:50.719 Of it rarely here it described that way. 0:05:50.800 --> 0:05:53.640 Well, it's a unique approach, right, and it was unique 0:05:53.680 --> 0:05:56.520 at the time, and so we thought there were conditions 0:05:56.600 --> 0:05:59.640 under which the option probably should be exercised. If you 0:05:59.680 --> 0:06:01.760 have a two hours set out, if you have a 0:06:01.800 --> 0:06:04.080 two hundred thousand dollars home and one hundred thousand dollars mortgage, 0:06:04.120 --> 0:06:07.000 and the consequence for not paying is ding on your 0:06:07.040 --> 0:06:09.440 credit report, you're probably not supposed to pay, is the 0:06:09.480 --> 0:06:12.120 position we took. So through that lens, we said, okay, 0:06:12.200 --> 0:06:14.040 let's price these securities, and we found a bunch of 0:06:14.240 --> 0:06:17.880 interesting things. For example, we found that the follow on 0:06:18.080 --> 0:06:22.160 rating surveillance for mortgage backed securities doesn't follow the same 0:06:22.279 --> 0:06:25.760 ratings methodology that the initial rating does. So over time 0:06:26.440 --> 0:06:28.880 the risk composition of the pool which would change dramatically. 0:06:28.920 --> 0:06:30.680 So think about two thousand and three. Home price has 0:06:30.760 --> 0:06:33.400 gone up a lot from two thousand, So mortgage position 0:06:33.480 --> 0:06:35.520 in two thousand were way more valuable in two thousand 0:06:35.520 --> 0:06:37.440 and three than they were they originated because they weigh 0:06:37.480 --> 0:06:40.960 less credit risk. Not the same thing couldn't be true 0:06:41.000 --> 0:06:42.280 as you went forward. 0:06:42.080 --> 0:06:44.800 In time, each subsequent vintage became risk, and risk became 0:06:44.880 --> 0:06:47.760 risking risk as prices went up because rates had gone 0:06:47.800 --> 0:06:48.320 lower and lower. 0:06:48.400 --> 0:06:49.520 And that's the way we thought about it. The way 0:06:49.560 --> 0:06:51.000 we think about it when you make someone alone. This 0:06:51.440 --> 0:06:53.800 is sort of the credit oas world. So we think 0:06:53.800 --> 0:06:55.880 about when you make someone alone on a building, whether 0:06:55.920 --> 0:06:59.440 it's this building or or a home, you're implicitly United States, 0:06:59.480 --> 0:07:02.320 you're implicit giving them the option to send you the keys. 0:07:03.360 --> 0:07:06.640 So jingle mail is exactly and so we thought it 0:07:06.680 --> 0:07:09.720 was least Okay, we've been pricing complicated options our whole career, 0:07:09.920 --> 0:07:12.040 so let's just price the option to default as if 0:07:12.080 --> 0:07:14.920 it is a financial option. When you do that, and 0:07:15.040 --> 0:07:17.400 then you looked at the types of loans or being originated, 0:07:17.720 --> 0:07:19.480 and this is where Amher's story is a little different 0:07:19.520 --> 0:07:21.160 than some of the stories you've seen are on the 0:07:21.160 --> 0:07:24.040 financial crisis. What we figured out was that the premium 0:07:24.120 --> 0:07:27.560 that you were being paid as this option seller was 0:07:27.680 --> 0:07:30.320 way below the fair market price of their premium, meaning 0:07:30.360 --> 0:07:32.840 that the default risk you were taking was way higher 0:07:32.880 --> 0:07:35.240 than the market had appreciated. So they were underpricing the 0:07:35.320 --> 0:07:38.560 fault risk dramatically. Then, as we dug in and dug 0:07:38.600 --> 0:07:40.640 in and dug in, we realized that there were a 0:07:40.680 --> 0:07:42.840 lot of loans that were really experiments. There were financial 0:07:42.880 --> 0:07:45.960 experiments where the bar hadn't been through dal diligence, the 0:07:46.840 --> 0:07:50.080 LTV was very high, the underlying risk of the home 0:07:50.120 --> 0:07:51.080 market was very high. 0:07:51.920 --> 0:07:54.600 Other of these were the no dock or Ninja. 0:07:54.360 --> 0:07:57.560 Loans were limited DOC no dock, no. 0:07:57.680 --> 0:08:03.680 Income, no no assets exactly, Ninja no pulse seem seems 0:08:03.720 --> 0:08:04.720 reasonable exactly. 0:08:04.840 --> 0:08:06.280 So you look back at these things, you're like, how 0:08:06.360 --> 0:08:09.880 could it happen? But we're low level people, right, so 0:08:09.960 --> 0:08:12.640 we don't see the mortgage backed securities market as a market. 0:08:12.720 --> 0:08:15.400 We see it as like I said, about fifty million assets, 0:08:15.440 --> 0:08:17.280 and we're modeling up the value of every home in 0:08:17.320 --> 0:08:19.960 the country every every week basically, and we're modeling with 0:08:20.040 --> 0:08:21.960 the value of every mortgage in the country, and we're 0:08:22.000 --> 0:08:24.480 modeling with the value every derivative of that mortgage, of 0:08:24.480 --> 0:08:26.720 the structure, products, and so forth. So through our lens, 0:08:26.800 --> 0:08:29.120 it was like, Okay, we've made these financial experiments. The 0:08:29.240 --> 0:08:32.360 underlying real estate has become very volatile, so we could 0:08:32.440 --> 0:08:36.160 construct trades that had very very low premiums to sell 0:08:36.240 --> 0:08:39.520 this volatility, to basically join the consumer on their side 0:08:39.520 --> 0:08:42.480 of the trade, which is in essense buying insurance on 0:08:43.000 --> 0:08:45.720 the bonds that were exposed of these great risks. Soult. 0:08:45.720 --> 0:08:47.719 We did that for a lot of the market, so 0:08:47.760 --> 0:08:49.480 a lot of the headline names you see, a lot 0:08:49.559 --> 0:08:52.839 of the stories you see about the financial crisis, a 0:08:52.920 --> 0:08:58.079 significant number of those investors we were helping in security selection, 0:08:58.240 --> 0:09:01.160 modeling and analytics. That sort of put Amherst on a 0:09:01.240 --> 0:09:04.280 different pack because prior to that, our core business model 0:09:04.400 --> 0:09:08.120 was investment, banking, brokerage, market making and underwriting. By the 0:09:08.160 --> 0:09:10.640 time we got to two thousand and five and figured 0:09:10.679 --> 0:09:13.240 out that there was such a large sector that was 0:09:13.320 --> 0:09:16.319 so mispriced, we started hedge funds, opportunity funds. We took 0:09:16.400 --> 0:09:19.240 sub mandates from the big global macro hedge funds, and 0:09:19.360 --> 0:09:22.760 we started to build our model around investing in our research. 0:09:23.200 --> 0:09:25.960 Co investing our research and earning carried interest in sort 0:09:26.000 --> 0:09:28.679 of big complicated trades that we thought we had figured 0:09:28.679 --> 0:09:31.400 out the market, maybe the market had imprised something properly. 0:09:31.920 --> 0:09:33.319 How did that end up working out? 0:09:34.000 --> 0:09:35.080 It was a wild ride. 0:09:35.240 --> 0:09:36.240 It was a wild ride. 0:09:36.080 --> 0:09:38.280 Because by the time you got so in two thousand 0:09:38.280 --> 0:09:41.000 and five, we went on a road show trying to 0:09:41.080 --> 0:09:43.760 tell people we had learned and there wasn't a lot 0:09:43.800 --> 0:09:44.240 of reception. 0:09:44.480 --> 0:09:46.760 We literally, let me, let me interrupt you and ask you. 0:09:47.160 --> 0:09:48.520 Did people laugh at you? 0:09:49.679 --> 0:09:52.200 They were more polite than that, but they didn't invest. 0:09:53.520 --> 0:09:57.040 So there were very few people that thought because at 0:09:57.080 --> 0:10:00.360 that time the triling credit performers, for you, single thing 0:10:00.440 --> 0:10:02.480 mortgagees great, impeccable, peckable. 0:10:02.800 --> 0:10:05.319 I want to say five was where we peaked in 0:10:06.559 --> 0:10:08.880 price and six's volume or am I getting that? 0:10:09.080 --> 0:10:10.920 So six O five was six? It started to turn 0:10:11.000 --> 0:10:13.240 over and our thesis on a lot of these mortgages 0:10:13.520 --> 0:10:17.200 and the very very exposed securities within these structured products 0:10:17.320 --> 0:10:19.520 wasn't that home prices needed to go down. It was 0:10:19.640 --> 0:10:21.439 that the only way that the loan was going to 0:10:21.480 --> 0:10:24.600 perform is that the consumer could refinance out of it quickly. Right, 0:10:25.160 --> 0:10:27.439 So you really just wanted the music to stop, right 0:10:27.800 --> 0:10:29.360 or if you mean, this whole thing was going to 0:10:29.400 --> 0:10:31.800 come down if the music stopped. So by the time 0:10:31.840 --> 0:10:33.800 the music stopped, it was pretty apparent, but we had it. 0:10:34.080 --> 0:10:37.679 There's a there's a big industry conference called AFS that 0:10:37.800 --> 0:10:39.880 happens twice a year, and in the two thousand, the 0:10:39.880 --> 0:10:41.920 two thousand and five conference, it's kind of wild. So 0:10:41.960 --> 0:10:44.320 these big brokens frooms get together and they set up 0:10:44.320 --> 0:10:47.000 a convention like like plumbers, and they also give out 0:10:47.080 --> 0:10:49.120 choski's and they have a and then they give presentations 0:10:49.120 --> 0:10:51.120 in their business. And so we participated in this. Our 0:10:51.200 --> 0:10:53.679 choshki that year was a hard helmet, was a was 0:10:53.720 --> 0:10:55.920 an orange hard hat, and they said beware of falling 0:10:55.960 --> 0:10:58.520 home prices. And our whole thesis was that was what 0:10:58.559 --> 0:10:59.760 I'm trying to describe. 0:10:59.400 --> 0:11:01.280 Which is that's a great swag. Do you do you 0:11:01.360 --> 0:11:01.640 still have? 0:11:01.840 --> 0:11:03.959 I have one in my office now. I have a 0:11:04.040 --> 0:11:06.640 helmet from Beware of Falling home Prices, and I have 0:11:06.800 --> 0:11:09.559 one for our new construction division where we build entire neighborhoods. 0:11:10.960 --> 0:11:13.559 And that's really to sort of bring it all together 0:11:14.240 --> 0:11:18.120 with this core competency and analytics, and we're probably the only, 0:11:18.280 --> 0:11:20.839 maybe not the only, but but I don't know of 0:11:20.920 --> 0:11:23.559 a competitor. We're the quant shop in real estate and 0:11:23.600 --> 0:11:27.360 the quant shop in physic glasses. So with that core competency, 0:11:27.480 --> 0:11:29.480 that's the reason we're in the single play rental business. 0:11:29.559 --> 0:11:31.520 You followed that all the way through. There were amazing 0:11:31.640 --> 0:11:34.480 trades to do, amazing opportunities, wild scary things to do. 0:11:35.040 --> 0:11:36.480 I got to spend a lot of time in DC 0:11:36.640 --> 0:11:39.400 consulting on the response to the financial crisis and trying 0:11:39.400 --> 0:11:41.480 to sort out sort of what was really going on. 0:11:42.000 --> 0:11:43.880 And what we figured out in two thousand and nine 0:11:43.920 --> 0:11:46.640 really when we started buying homes is that we made 0:11:46.679 --> 0:11:49.839 the bet that I mean, it wasn't a very exotic bet, 0:11:49.920 --> 0:11:51.840 but we made the bet that the sub primorgage market 0:11:51.920 --> 0:11:53.120 wasn't coming back at all. 0:11:53.280 --> 0:11:55.480 So wait, let me unpack some of that. Christ there's 0:11:55.480 --> 0:11:58.600 a lot of really interesting things. When you mentioned DC, 0:11:59.200 --> 0:12:02.559 I'm aware of the Act that you briefed Congress, the 0:12:02.640 --> 0:12:06.320 Federal Reserve, the White House. Who else did you speak 0:12:06.360 --> 0:12:08.560 to when you were there? Well, what was that experience? 0:12:08.679 --> 0:12:10.840 So I lived in Washington, d C. For five years, 0:12:10.920 --> 0:12:13.600 my family and I moved to McLain, Virginia in two 0:12:13.640 --> 0:12:16.599 thousand and eight. So we were down the street, and 0:12:16.720 --> 0:12:19.160 we were in a pretty interesting situation because we were 0:12:19.559 --> 0:12:21.480 we were one of the biggest, if not the only, 0:12:22.320 --> 0:12:25.600 investment banks specializing in the core risk that the nation 0:12:25.800 --> 0:12:28.760 was facing. And we didn't need any help, right, So 0:12:28.840 --> 0:12:31.440 we weren't there looking for changing of a reg cap, 0:12:31.600 --> 0:12:34.000 you know, of anything. We weren't looking for a bailout. 0:12:34.040 --> 0:12:36.280 We were looking for recapitalization or anything. We were just 0:12:36.960 --> 0:12:39.800 there as a source of information. So we met a 0:12:39.840 --> 0:12:41.760 lot of interesting people in DC, and it was the 0:12:41.840 --> 0:12:45.000 whole gamut. We were consulted on the recapitalization in Freddie 0:12:45.080 --> 0:12:47.760 mckin family. We participated in that with Treasury and FHFA 0:12:47.960 --> 0:12:51.240 and the regulators of the White House. And I would 0:12:51.240 --> 0:12:53.680 say that Washington was pretty interesting because we had gone 0:12:53.920 --> 0:12:55.560 and spoken to people in two thousand and five, two 0:12:55.600 --> 0:12:58.160 thousand and six and to kind of let people know 0:12:58.240 --> 0:13:01.000 that there was something these this is a trillion dollars 0:13:01.000 --> 0:13:02.120 worth miss price risk right. 0:13:02.400 --> 0:13:08.319 And I very vividly recall six even o seven. People were, hey, 0:13:08.400 --> 0:13:10.559 we're in the middle of a giant boom. Why do 0:13:10.679 --> 0:13:13.360 you have to come, you know, rain on our purrass? 0:13:13.520 --> 0:13:14.800 But what was your experience? 0:13:15.120 --> 0:13:17.840 It was lonely, I tell you. The analogy was something 0:13:17.960 --> 0:13:20.640 like this, is that we had seen what had happened, 0:13:20.920 --> 0:13:22.760 and by two thousand and six it was over right. 0:13:22.840 --> 0:13:26.040 The mortgages were defaulting. People were taking out mortgages and 0:13:26.120 --> 0:13:28.439 defaulting in the third payment, the fourth payment. 0:13:28.679 --> 0:13:33.640 Ninety day warranty on those non conforming non Fanny May 0:13:34.200 --> 0:13:37.599 mortgages from those private contractors, like a toaster comes with 0:13:37.679 --> 0:13:39.160 along a warranty, it's amazing. 0:13:39.160 --> 0:13:41.200 So eventually even that was gone, even that they wouldn't 0:13:41.200 --> 0:13:44.240 provide nine day warranty. Eventually it was take it at 0:13:44.320 --> 0:13:47.200 cash for keys or cash and carry. So like for us, 0:13:47.320 --> 0:13:49.079 it was weird though, because the analogy I give is 0:13:49.120 --> 0:13:50.559 it in two thousand and six it happened. It was 0:13:50.600 --> 0:13:52.200 over first four to two thousand and six, the market 0:13:52.240 --> 0:13:56.079 was over. The market kept issuing securities, And I think 0:13:56.080 --> 0:13:57.600 the analogy that we think about it is that if 0:13:57.640 --> 0:13:59.120 you're standing, if you're sitting in front of a bank, 0:13:59.720 --> 0:14:01.880 and you know, a van rolls up and people with 0:14:02.000 --> 0:14:04.360 masks run in and they empty out the bank and 0:14:04.400 --> 0:14:06.400 they leave with all the money, and you see it, 0:14:07.200 --> 0:14:09.040 and then people keep coming and going from the bank 0:14:09.080 --> 0:14:12.000 for another year. You're like, yo, there's there's no money 0:14:12.000 --> 0:14:14.079 in that bank, right, And so so we sort of 0:14:14.120 --> 0:14:15.920 felt pretty stupid for a while because we did a 0:14:15.960 --> 0:14:18.079 lot of losing trades in two thousand and six that 0:14:18.200 --> 0:14:20.240 were the you know, the obviously didn't come to fruition 0:14:20.400 --> 0:14:23.680 until the actual people could see the losses. So in mortgages, 0:14:23.920 --> 0:14:27.360 the barber can stop paying maybe a year to two 0:14:27.440 --> 0:14:31.480 years before the lenders actually book a loss. So there's 0:14:31.560 --> 0:14:35.200 this great lag in housing that is affecting the market, 0:14:35.600 --> 0:14:39.120 affecting today's CPI numbers that the market doesn't do a 0:14:39.200 --> 0:14:41.800 great job of adjusting the real time for information that 0:14:41.800 --> 0:14:43.560 they already have. So when the barber hasn't paid in 0:14:43.600 --> 0:14:46.880 twelve months, probably not going to get back the loan, 0:14:47.040 --> 0:14:49.280 probably not going to start paying again. And then you 0:14:49.320 --> 0:14:51.160 can model up what happens, like what's the home going 0:14:51.200 --> 0:14:52.880 to sell for, what are my expenses to sell, awa, 0:14:52.920 --> 0:14:54.160 how long it's going to take, And all of a sudden, 0:14:54.200 --> 0:14:56.360 you have a loan that was worth, you know, one 0:14:56.400 --> 0:14:58.040 hundred cents on the dollar, and now it's worth thirty 0:14:58.080 --> 0:15:00.640 cents on the dollar. And you knew that eight months 0:15:00.680 --> 0:15:02.200 into the loan or eight or maybe a year ago 0:15:02.280 --> 0:15:03.920 or two years ago, But it takes that long to 0:15:04.040 --> 0:15:05.800 it takes that long for the losses to get through 0:15:05.800 --> 0:15:07.360 to the securities. And so I don't know if it's 0:15:07.400 --> 0:15:10.320 sort of just the fact that we're so myopic into 0:15:10.400 --> 0:15:13.640 the minutia of each little detail, or if it's the 0:15:13.720 --> 0:15:15.560 fact that the market kind of doesn't want to buy 0:15:15.640 --> 0:15:17.080 an umbrella until it starts raining. 0:15:18.800 --> 0:15:23.560 Really very fascinating. So so coming out of this in nine, 0:15:24.160 --> 0:15:28.560 home prices on average across the country down over thirty percent, 0:15:28.720 --> 0:15:32.040 but really in the worst areas like Las Vegas and 0:15:32.160 --> 0:15:35.760 South Florida and you know, parts of California and parts 0:15:35.760 --> 0:15:36.880 of Arizona, Phoenix. 0:15:37.320 --> 0:15:38.320 Two thirds in Phoenix. 0:15:38.520 --> 0:15:41.960 Unbelievable. So you say, I have an idea, Let's buy 0:15:42.000 --> 0:15:44.120 all these distressed real estate and rent them out. 0:15:44.280 --> 0:15:45.960 Yeah, I had. I had a very good idea. So 0:15:45.960 --> 0:15:47.520 I have very good partners, are very patient with me, 0:15:48.080 --> 0:15:50.440 and I said, Okay, we don't think the subprime market 0:15:50.440 --> 0:15:52.400 to mark is coming back, which was a non consensus 0:15:52.480 --> 0:15:54.880 view at the time. People were buying up mortgage originators 0:15:54.920 --> 0:15:56.600 and things waiting for the machines to sort of get 0:15:56.600 --> 0:15:59.960 turned back on. We were thinking, this is investors are 0:16:00.120 --> 0:16:01.920 never going to buy these loans again at any price. 0:16:02.760 --> 0:16:04.240 So what's going to happen, what's going to happen to 0:16:04.240 --> 0:16:06.480 the homes, and what's going to happen to the people 0:16:06.520 --> 0:16:09.000 that were living these homes. And what a lot of 0:16:09.040 --> 0:16:11.480 people I think didn't follow is that there was a 0:16:11.560 --> 0:16:14.760 concept that job loss is called mortgage caused to mortgage defaults. 0:16:15.120 --> 0:16:17.840 But in the Amir's view, a mortgage default can be rational, 0:16:18.080 --> 0:16:20.600 as distasteful as it may sound. And when I give 0:16:20.640 --> 0:16:23.520 this presentation in Europe or the EU or the UK, 0:16:23.640 --> 0:16:25.360 they look at me like you're crazy. Or in Australia 0:16:25.440 --> 0:16:27.480 or in Canada they're like, what do you mean? Mortgage 0:16:27.520 --> 0:16:29.400 is a recourse and so like, well not in the US. 0:16:29.560 --> 0:16:31.240 Well, actually some states are recourse. 0:16:31.280 --> 0:16:32.960 In some states I try to tell people, is that 0:16:33.120 --> 0:16:35.960 one person's default you have, you can handle. But when 0:16:36.000 --> 0:16:38.960 seven or eight million people default, we don't have debtors' 0:16:38.960 --> 0:16:41.880 prisons right their recourse, I mean, they're not recourse. So 0:16:42.400 --> 0:16:45.760 in this in this context of a mortgage now being 0:16:45.840 --> 0:16:48.840 clear to everyone that this default risk is present, it's real, 0:16:49.400 --> 0:16:53.200 and it's hard to price because following the borrowers economic profile, 0:16:53.520 --> 0:16:56.480 there are defaults that are related to just life events, 0:16:56.520 --> 0:16:59.560 but there's also defaults related to a macroeconomic event. So 0:17:00.200 --> 0:17:02.160 the position, you know what, investors are not going to 0:17:02.200 --> 0:17:06.399 buy these loans anymore. The homes are here, and the 0:17:06.920 --> 0:17:09.760 job loss wasn't as big as the mortgage defaults were, right, 0:17:10.160 --> 0:17:12.720 so the people still had jobs, they slid revenue, and 0:17:12.800 --> 0:17:15.080 the homes were very affordable now because the prices have 0:17:15.160 --> 0:17:18.480 been reset. So we asked ourselves, Okay, we've seen this 0:17:18.600 --> 0:17:23.520 movie before. Can we at Amherst make a three hundred 0:17:23.560 --> 0:17:27.160 thousand dollars home investible to a global financial investor? Which 0:17:27.520 --> 0:17:30.120 we spent our whole careers turning a three hundred thousand 0:17:30.119 --> 0:17:34.040 dollars mortgage investible in the global capital markets. So we said, okay, 0:17:34.080 --> 0:17:36.000 this is probably not a long put for us because 0:17:36.040 --> 0:17:38.440 we've been following the mortgage with all this minutia for 0:17:38.520 --> 0:17:40.680 thirty years. Now we're just going to follow the house 0:17:40.720 --> 0:17:42.680 the same way. So we took our same analytic and 0:17:42.760 --> 0:17:45.400 modeling team and we said, let's press down one more 0:17:45.480 --> 0:17:48.000 level so we can actually price the home instead of 0:17:48.359 --> 0:17:51.399 the mortgage with precision. And then let's set up an 0:17:51.400 --> 0:17:55.240 operating capability that allows us to acquire the homes, renovate 0:17:55.280 --> 0:17:59.359 the homes, manage the homes, and then more importantly, scale 0:17:59.400 --> 0:18:02.439 the homes in to an investible pool. So we created 0:18:02.480 --> 0:18:04.919 pools of homes just the same way we created pools 0:18:04.920 --> 0:18:06.480 and mortgages in nineteen eighty nine. 0:18:06.760 --> 0:18:09.080 So are you keeping these homes and leasing them out 0:18:09.200 --> 0:18:10.560 or are they flips? 0:18:11.359 --> 0:18:13.440 So they're kept and leased out, So we're starting in 0:18:13.480 --> 0:18:16.080 two thousand and nine. There was no flip market. There 0:18:16.160 --> 0:18:18.679 was no one to sew them to because the mortgage 0:18:18.720 --> 0:18:22.040 market had basically closed on a large section of the 0:18:22.040 --> 0:18:22.640 consumer base. 0:18:22.680 --> 0:18:26.000 So think about and that credit market was frozen pretty. 0:18:25.800 --> 0:18:28.440 Much, and it's still frozen for most people. So really 0:18:28.600 --> 0:18:32.119 still today, still today. Basically the barrier to entry to 0:18:32.160 --> 0:18:35.879 getting a mortgage became irreversibly higher, and we spent a 0:18:35.920 --> 0:18:37.960 lot of times. You mentioned my time in DC. I 0:18:38.040 --> 0:18:40.399 got to go and brief the Fetal Reserve, which is 0:18:40.480 --> 0:18:41.919 kind of cool. I got to go into the FMC 0:18:42.119 --> 0:18:45.040 room and I got to sit with with Yelling and 0:18:45.119 --> 0:18:48.000 Vernaki and walk them through kind of in our view, 0:18:48.119 --> 0:18:50.600 how we got here and the best way out. And 0:18:50.720 --> 0:18:52.800 I asked them not to shut down the sub prime 0:18:52.840 --> 0:18:56.240 mortgage market because it does serve a large swath of 0:18:56.280 --> 0:18:59.840 the American public who has a slightly higher rent in 0:19:00.160 --> 0:19:03.320 or debt income ratio, or has defaulted on a credit 0:19:03.400 --> 0:19:05.880 card in the past or something, but they can pay, 0:19:06.119 --> 0:19:08.600 they've had a problem in the past, they've cured it. Well, 0:19:08.640 --> 0:19:10.440 those people now are pretty much blocked out of the 0:19:10.440 --> 0:19:13.119 mortgage market. So I was unsuccessful in talking people and 0:19:13.200 --> 0:19:15.720 still to this day unsuccessful into talking to people to 0:19:15.760 --> 0:19:20.080 get back into lending to lower credit quality consumers. Because 0:19:20.119 --> 0:19:22.440 you can do it, you can risk base prizing. So 0:19:22.520 --> 0:19:24.280 we took we took the view like, hey, that market's 0:19:24.280 --> 0:19:25.960 not coming back. People are not going to listen to us. 0:19:25.960 --> 0:19:28.080 They're not going to say there's some good subprime loans 0:19:28.119 --> 0:19:30.840 and some bad sub loans. They're just gonna they're just 0:19:30.920 --> 0:19:33.000 going to draw a line and say you have to 0:19:33.080 --> 0:19:35.280 have a credit score above a certain level, you have 0:19:35.320 --> 0:19:37.119 to have income above a certain level, you have to 0:19:37.200 --> 0:19:39.440 have a debt load below a certain level, or the 0:19:39.520 --> 0:19:41.639 price for you is zero. You just get the answer is. 0:19:41.680 --> 0:19:42.879 No, you're out of the market. 0:19:43.119 --> 0:19:44.640 Used to you would say you would pay one percent 0:19:44.720 --> 0:19:48.400 more or two percent right now. He said no, that's 0:19:48.400 --> 0:19:49.800 so that's how we So we said, okay, well, how's 0:19:49.800 --> 0:19:51.080 it's going to work. And we had seen this movie 0:19:51.160 --> 0:19:55.919 before aggregating mortgages, strapping services on them, getting them rated, 0:19:56.200 --> 0:19:59.080 getting them available to the global capital markets. So we 0:19:59.720 --> 0:20:03.840 also so saw the conflicts and the frictions of the 0:20:03.880 --> 0:20:07.440 mortgage market when it went under duress, the problems with 0:20:07.560 --> 0:20:10.120 getting service to the consumers, the problem with getting service 0:20:10.200 --> 0:20:12.720 to investors. The litigation. A lot of people don't know it, 0:20:12.800 --> 0:20:15.880 but were We represented a large swath of the US 0:20:15.960 --> 0:20:19.520 investor base and their litigation for buying these bus and securities. 0:20:19.880 --> 0:20:22.120 So we said, you know what, let's just build under 0:20:22.200 --> 0:20:27.800 one platform everything you need to originate, managed service, aggregate 0:20:28.400 --> 0:20:31.040 and the long term service. These homes on behalf of 0:20:31.119 --> 0:20:34.840 the residents and the investors. So that's the single platform 0:20:34.880 --> 0:20:35.200 we built. 0:20:35.400 --> 0:20:38.480 H absolutely fascinating. So let's talk a little bit about 0:20:38.920 --> 0:20:42.560 who the clients are for Amherst. I'm assuming it's primarily 0:20:42.680 --> 0:20:46.359 institutional and not retail. Tell us who your clients are 0:20:46.520 --> 0:20:48.800 and what they want to invest in. Sure. 0:20:49.119 --> 0:20:52.960 Over the years, we've migrated really to what I would 0:20:52.960 --> 0:20:54.960 say is the largest customer base in the world, the 0:20:55.080 --> 0:21:00.160 largest single investors. So we do business with most most 0:21:00.200 --> 0:21:03.200 of the sovereign wealth funds, most of the big US 0:21:03.359 --> 0:21:08.159 national insurers, global insurers, the largest pension funds, and we 0:21:08.880 --> 0:21:12.480 try to position ourselves as an extension of their capabilities. 0:21:12.720 --> 0:21:15.520 And since we're smaller, more nimble, we can kind of 0:21:15.560 --> 0:21:17.160 get in there and do some of the gritty things, 0:21:17.200 --> 0:21:20.359 the smaller things. Imagine setting up a platform with in 0:21:20.480 --> 0:21:23.040 thirty two markets that has to buy each individual home 0:21:23.119 --> 0:21:26.600 and execute a CAPEX plan on a thirty forty thousand 0:21:26.640 --> 0:21:29.120 dollars CAPEX plan on a home. So these large investors 0:21:29.160 --> 0:21:31.320 need someone like us to kind of make things investable 0:21:31.359 --> 0:21:34.159 in scale, and so that's where we've been. So it's 0:21:34.160 --> 0:21:38.320 all institutional investors. It's the call it five hundred largest 0:21:38.320 --> 0:21:39.160 investors in the world. 0:21:39.320 --> 0:21:43.320 Is that patient capital? Did they have the bandwidth to hey, 0:21:43.600 --> 0:21:44.560 we're in this for decades. 0:21:44.640 --> 0:21:49.000 Yeah, it's super patient, it's super sophisticated. Their asset allocation 0:21:49.240 --> 0:21:53.800 model driven folks. The bulk of our investors are investing 0:21:53.880 --> 0:21:57.800 on behalf of consumers, on behalf of taxpayers. So we're 0:21:57.840 --> 0:21:59.800 partners with the State of Texas. The actual state of 0:21:59.800 --> 0:22:01.600 time is not one of the pension funds, but the 0:22:01.640 --> 0:22:04.440 state itself. So we have a lot of sovereign wealth 0:22:04.520 --> 0:22:06.359 on types that are investing on behalf of tax payers. 0:22:06.359 --> 0:22:10.840 So it's very long dated capital. They're lower risk tolerance, 0:22:10.880 --> 0:22:14.520 I would say, very high standards on quality of service 0:22:14.600 --> 0:22:17.840 and quality of infrastructure decision making. So we're very proud 0:22:17.920 --> 0:22:20.679 that we're a partner to that type of capital. 0:22:21.040 --> 0:22:23.880 So let's talk a little bit about the residential side. 0:22:23.920 --> 0:22:27.520 Before we look at the commercial side. You mentioned you 0:22:27.840 --> 0:22:31.159 are in thirty two markets buying single family homes. How 0:22:31.240 --> 0:22:32.160 many homes have you, guys? 0:22:32.200 --> 0:22:34.560 So their platform service is about fifty thousand units now. 0:22:34.600 --> 0:22:37.119 So we've purchased and most of the homes were purchased 0:22:37.119 --> 0:22:40.680 one at a time, independent due diligence, independent construction management 0:22:40.760 --> 0:22:42.880 to get the home back up to current market standards, 0:22:43.280 --> 0:22:45.280 and we manage each home independently. 0:22:45.720 --> 0:22:48.680 So that implies that some of the homes you're buying 0:22:48.760 --> 0:22:52.919 are kind of project homes. A wrecked or otherwise neglected 0:22:53.200 --> 0:22:56.159 doesn't even have to be a willf elected destruction, just 0:22:56.280 --> 0:22:57.159 time and tide. 0:22:57.400 --> 0:22:59.880 Just what we like to say is it's deferred cappex. 0:23:00.119 --> 0:23:01.880 So you'll find that owners that have owned the home 0:23:01.920 --> 0:23:05.280 for ten, fifteen, twenty years become pretty comfortable with a 0:23:05.359 --> 0:23:09.200 smudge paint or a stained floor, or old countertops, or 0:23:09.280 --> 0:23:13.440 appliances that may make noises at night or that or 0:23:13.560 --> 0:23:15.960 that you know, that bathroom set that leaks and whatever, 0:23:16.000 --> 0:23:17.520 and so people just get comfortable in their homes and 0:23:17.600 --> 0:23:19.960 they they tend not to reinvest in real time on 0:23:20.119 --> 0:23:22.760 keeping that home up to current market standards. So we 0:23:22.840 --> 0:23:25.080 buy those homes that haven't really been touched in fifteen 0:23:25.119 --> 0:23:28.080 or twenty years. They've still got the original builder interior. 0:23:29.119 --> 0:23:31.240 We make sure that, of course that the bones of 0:23:31.280 --> 0:23:33.240 the house are good, the foundation and the walls and 0:23:33.280 --> 0:23:35.600 so forth, but then we pretty much trip them down 0:23:35.680 --> 0:23:37.520 to I wouldn't say down to the studs, but down 0:23:37.560 --> 0:23:39.840 to the sheet rock and put a brand new interier 0:23:39.920 --> 0:23:42.560 in on. We oftentimes people don't buy a roof, they'll 0:23:42.960 --> 0:23:45.679 let the roof go a longer than maybe the staple 0:23:46.359 --> 0:23:48.359 exact or a third one, or bought a lot of 0:23:48.480 --> 0:23:50.520 roofs and buy a lot of hvacs. We take out 0:23:50.560 --> 0:23:52.760 a lot of compressors that are still running on those 0:23:52.800 --> 0:23:55.480 old toxic gases. So we basically bring the home up 0:23:55.480 --> 0:23:57.119 to a current monitor standard and there's a there's a 0:23:57.200 --> 0:23:59.359 profit in that that the home you get paid to 0:23:59.440 --> 0:24:00.600 go and improve PA's real estate. 0:24:01.880 --> 0:24:04.080 And then how do you figure out what to lease 0:24:04.160 --> 0:24:06.280 these for? And do you ever sell any of these homes? 0:24:06.400 --> 0:24:08.560 We do sell we do. The platform is pretty nimble. 0:24:08.640 --> 0:24:11.080 So if for example, we were talking before the show, 0:24:11.119 --> 0:24:13.760 we were talking about how some markets have really benefited 0:24:13.800 --> 0:24:17.840 from the post COVID migration and it's changed their customer 0:24:17.880 --> 0:24:21.120 based dramatically. So think about Naples, Florida and clear Water 0:24:21.240 --> 0:24:23.680 and those types of places. So in those places, home 0:24:23.800 --> 0:24:28.359 prices since pre COVID are up maybe forty fifty percent 0:24:28.800 --> 0:24:31.159 and rents are up twenty twenty five percent, so they 0:24:31.200 --> 0:24:33.520 really don't really make much sense more as a as 0:24:33.560 --> 0:24:36.320 a rental investment. So we're cleaning those homes back up 0:24:36.359 --> 0:24:38.520 and selling them back to the consumers. So that's an 0:24:38.520 --> 0:24:42.080 active part of portfolio trimming and optimization, and it's cool 0:24:42.119 --> 0:24:45.159 to have the capability to sort of execute in both markets. 0:24:45.440 --> 0:24:48.200 So it's funny you mentioned Naples and Clearwater. A few 0:24:48.280 --> 0:24:51.760 of the areas adjacent to those really got to lacked 0:24:51.800 --> 0:24:54.879 by that last hurricane that came through last year. What 0:24:55.000 --> 0:24:57.119 do you do when you have a natural disaster? Is 0:24:57.200 --> 0:25:00.920 that does that create any interest or is it just 0:25:01.560 --> 0:25:02.280 just too much may. 0:25:02.240 --> 0:25:04.960 Have It's well, we've been hit by hurricanes several times, 0:25:05.119 --> 0:25:08.560 floods several times, tornadoes several times. Given that the homes 0:25:08.600 --> 0:25:11.080 are in thirty markets, the good news is no one 0:25:11.200 --> 0:25:13.560 event has a big impact on the portfolio. The bad 0:25:13.640 --> 0:25:16.200 news is all events you get to experience. 0:25:15.840 --> 0:25:19.040 Right, So diversified, which means you're embracing every natural right. 0:25:19.280 --> 0:25:21.399 So in Houston one year, we got hit in Houston 0:25:21.600 --> 0:25:24.680 and in Florida at the same time, two different hurricanes. 0:25:25.160 --> 0:25:27.840 So what's interesting is that now we have a natural 0:25:27.920 --> 0:25:31.200 disaster of team and response unit and a playbook which 0:25:31.240 --> 0:25:32.720 is a little bit unfortunately you have to have that, 0:25:32.800 --> 0:25:34.080 but we use it every couple of years. 0:25:34.119 --> 0:25:34.280 Now. 0:25:35.240 --> 0:25:38.240 We tend not to invest when those markets are busted. 0:25:39.160 --> 0:25:41.600 We do see a lot of demand for our rentals 0:25:41.640 --> 0:25:43.920 because when you know, a few percent of the housing 0:25:43.920 --> 0:25:46.760 stock gets taken offline for a storm, it creates pressure 0:25:46.840 --> 0:25:49.000 on demand. But now our job is just to go 0:25:49.080 --> 0:25:50.960 in there and get the homes fixed as fast as 0:25:50.960 --> 0:25:52.200 we can and get them back into service. 0:25:52.400 --> 0:25:54.520 So fifty thousand homes, I'm going to assume you're a 0:25:54.600 --> 0:25:56.320 self insurer on all those homes. 0:25:56.400 --> 0:25:58.879 We do so Amerus is completely verted integrated. We own 0:25:58.920 --> 0:26:02.240 our own insurance platform, so we're the we're you know, 0:26:02.320 --> 0:26:05.560 we basically access our coverage through the reinsurance markets. At 0:26:05.600 --> 0:26:08.159 our scale, it's hard to go get insurance through the 0:26:08.200 --> 0:26:10.000 normal channels, and so we set up our own insurance 0:26:10.040 --> 0:26:13.639 brokerage and risk attention platform and now we we insuran 0:26:13.960 --> 0:26:15.600 through the resurance markets. 0:26:16.040 --> 0:26:19.600 Huh really very very intriguing. Uh So let's let's talk 0:26:19.600 --> 0:26:22.720 a little bit about some data and technology you use. Sure, 0:26:22.880 --> 0:26:25.320 you guys created your own platform. Tell us a little 0:26:25.359 --> 0:26:28.320 bit about what it was like developing that and what 0:26:28.560 --> 0:26:31.600 makes it specific and unique to Amhurst. 0:26:31.840 --> 0:26:34.240 It's interesting because you know, today we talk about AI 0:26:34.440 --> 0:26:37.680 and and uh, you know, high speed computing, and what 0:26:38.119 --> 0:26:40.119 I look at, what we do is being comically you know, 0:26:40.359 --> 0:26:42.080 simple compared to what we talked what we're talking about 0:26:42.080 --> 0:26:44.600 today with generative AI. But when we started this in 0:26:44.680 --> 0:26:46.240 the late eighties, so that was the job I was 0:26:46.280 --> 0:26:49.119 pronted into, which was, hey, let's figure out how to 0:26:49.240 --> 0:26:53.080 differentiate pricing from one mortgage pool to the next. They've 0:26:53.119 --> 0:26:55.720 got different interest rates, they've got different LTVs, they've got 0:26:55.760 --> 0:26:58.320 different credit scores, they must have different values. So I 0:26:58.520 --> 0:27:00.879 was part of a small or the our team was 0:27:00.960 --> 0:27:03.560 part of a small group of people tackling this problem 0:27:03.600 --> 0:27:05.800 in the late eighties early nineties, and what we do 0:27:05.880 --> 0:27:08.240 today is just now growth of that original project. So 0:27:08.320 --> 0:27:11.320 it's a quantitative analytics approach. It's highly data driven, but 0:27:11.400 --> 0:27:13.600 we need to know the price history for us, that's 0:27:13.640 --> 0:27:16.520 the correlation to to what drives price, and then we 0:27:16.600 --> 0:27:19.639 have a big consumer behavior modeling infrastructure because we have 0:27:19.800 --> 0:27:22.560 what's nice is that over the thirty years of our 0:27:22.920 --> 0:27:25.440 history and then we purchase data that was probably twenty 0:27:25.480 --> 0:27:28.960 five years old at the time, we can measure how 0:27:29.080 --> 0:27:32.240 consumers behave to changes in their economic environment, and that 0:27:32.320 --> 0:27:35.160 consumer behavior will affect home prices and will affect performance 0:27:35.240 --> 0:27:38.960 on credit. It's that So that's the core competency, and 0:27:39.000 --> 0:27:42.320 it's just leveraged into if it's a loan, if it's 0:27:42.359 --> 0:27:44.320 a security back by a loan, if it's the actual 0:27:44.440 --> 0:27:46.960 estate itself. So from a data perspective, think about it 0:27:47.000 --> 0:27:48.800 this way. So obviously the S and P five hundred 0:27:48.840 --> 0:27:51.080 is five hundred names and they report four times a year, 0:27:51.720 --> 0:27:53.600 and God loved the analysts that have to figure out 0:27:53.600 --> 0:27:56.159 how to price these things with so little information. We 0:27:56.280 --> 0:27:58.240 have one hundred million items that we're following. Is one 0:27:58.280 --> 0:28:00.520 hundred million piece of real estate in the country. We've 0:28:00.600 --> 0:28:02.639 gathered up all the information you would need to do 0:28:02.680 --> 0:28:05.200 an appraisal, and we keep that information current in real time, 0:28:05.440 --> 0:28:09.600 and we've automated the appraisal process for evaluation both intrinsic value, 0:28:10.160 --> 0:28:11.639 meaning like where would we pay it, where would we 0:28:12.200 --> 0:28:15.560 buy it, and where is the fair market price that asset? 0:28:15.840 --> 0:28:18.760 From that level, from price and from consumer behavior. Now, 0:28:18.800 --> 0:28:21.000 so now we're watching the payments on every mortgage in 0:28:21.040 --> 0:28:24.440 the country, so you can see who paid, Did Maryland 0:28:24.480 --> 0:28:27.480 do better than Texas last month? And more importantly, versus 0:28:27.600 --> 0:28:31.280 the model, who outperforms, who underperformed. Because there's a schedule, 0:28:31.520 --> 0:28:34.280 there's an expectation for not everyone to pay every month. 0:28:34.440 --> 0:28:36.800 So when you're trying to put a value on a home, 0:28:37.040 --> 0:28:40.000 you're not just sending a third party appraiser oute to 0:28:40.120 --> 0:28:42.080 do a drive buy and go. Yeah, that's about two 0:28:42.160 --> 0:28:45.560 seventy five. You're actually crunching a lot of numbers. And 0:28:45.640 --> 0:28:47.200 this is proprietary you're running. 0:28:47.360 --> 0:28:51.080 We're running a ten year Monte Carlo. That's probably twenty thousand, 0:28:51.200 --> 0:28:54.040 ten thousand paths of outcomes on that asset. It includes 0:28:54.080 --> 0:28:57.920 all of its changes in its property taxes, it's depreciable 0:28:58.000 --> 0:29:00.360 life for the improvements of the assets, and course it's 0:29:00.400 --> 0:29:02.000 revenue stream from rental demand. 0:29:02.840 --> 0:29:06.840 So it's interesting that you started this after the financial crisis, 0:29:07.560 --> 0:29:11.880 given your technological expertise and your unique way to value 0:29:11.960 --> 0:29:15.880 these things. I'm curious how much of this is a 0:29:16.000 --> 0:29:20.240 legacy of your experiences during the Great Financial Crisis. How 0:29:20.320 --> 0:29:23.560 did that couple of years affect how you look at 0:29:23.680 --> 0:29:26.120 risk and pricing of real estate process? 0:29:26.320 --> 0:29:30.560 It's infecting, I would say. So the problem, the problem 0:29:30.680 --> 0:29:33.320 for me, I'll speak for myself personally in the financial 0:29:33.440 --> 0:29:36.840 crisis is that once you find something like that, because 0:29:36.920 --> 0:29:39.880 literally we were saying to people these loans aren't going 0:29:39.920 --> 0:29:41.920 to pay off in two thousand and five, two thousand 0:29:41.920 --> 0:29:44.120 and six, and they were like, Sean, in the worst 0:29:44.160 --> 0:29:48.440 of fault rate, it's been geographically focused. Rather it was 0:29:48.480 --> 0:29:51.120 the farm belt crisis or the California crisis. What are 0:29:51.160 --> 0:29:53.840 you talking about? National home prices going down? And oh, 0:29:53.960 --> 0:29:56.200 by the way, the defaults in those micro markets were 0:29:56.240 --> 0:29:58.640 ten or fifteen percent and the losses were five percent. 0:29:59.360 --> 0:30:01.320 So if you we had five percent losses on a 0:30:01.880 --> 0:30:04.480 market and the market was only five percent of a pool, 0:30:05.040 --> 0:30:07.360 the losses are going to be nearly zero, right, And 0:30:07.440 --> 0:30:09.560 we're like, yeah, except for none of that's going to 0:30:09.600 --> 0:30:11.120 happen this time. And they were like sure, Sean, pat 0:30:11.200 --> 0:30:12.360 you on the head and send you down the road. 0:30:12.640 --> 0:30:14.160 So so one of the problems is once you see 0:30:14.200 --> 0:30:16.200 something like that, you kind of look for them everywhere, 0:30:16.600 --> 0:30:18.280 So we spend our time a lot of time looking 0:30:18.360 --> 0:30:22.760 for looking for sasquatch. And so the other thing is 0:30:22.960 --> 0:30:25.959 is that, and I think it's our core risk management culture, 0:30:26.560 --> 0:30:28.360 is that we think that tiller risk is way more 0:30:28.440 --> 0:30:31.160 probable than everyone else does. So we manage the business 0:30:31.240 --> 0:30:34.240 for extreme shocks to prices, for home prices moving twenty 0:30:34.280 --> 0:30:36.520 five to thirty percent in a year, for interest rates 0:30:36.560 --> 0:30:39.560 moving dramatically in a short period of time. And we 0:30:39.680 --> 0:30:43.640 found you know that check check is all these tail risks. Well, 0:30:43.640 --> 0:30:45.560 it's like the one hundred year floods every ten years 0:30:45.640 --> 0:30:47.560 or so. I've been doing this for thirty years, and 0:30:47.600 --> 0:30:49.920 I've had how many hundred your floods? More than more 0:30:49.960 --> 0:30:50.560 than point three? 0:30:51.280 --> 0:30:54.000 You know. The fascinating thing is I have a vivid 0:30:54.120 --> 0:30:57.320 recollection of a paper, a white paper coming out by 0:30:57.400 --> 0:31:01.680 professors rein Hart and Rogueoff. I remembered it was five 0:31:02.120 --> 0:31:08.280 financial crises. So it was Helsinki, it was Sweden, it 0:31:08.600 --> 0:31:12.320 was Japan, it was Mexico, maybe US, and the Great 0:31:12.360 --> 0:31:14.560 Depression was the fifth one. I don't remember exactly what. 0:31:14.800 --> 0:31:18.000 By the way that paper eventually becomes this time is different. 0:31:18.080 --> 0:31:21.960 Eight hundred years of financial folly. But the average of 0:31:22.040 --> 0:31:26.040 the real estate drop in any modern financial we're not 0:31:26.120 --> 0:31:29.720 talking about tulips. Right. The last century was over thirty 0:31:29.760 --> 0:31:32.520 percent in real estate. And once you once I saw 0:31:32.600 --> 0:31:35.000 that paper, I remember saying, hey, this is in a 0:31:35.160 --> 0:31:38.760 theoretical possibility. This has happened once in decades. 0:31:38.840 --> 0:31:41.000 Right. So people think of home prices as being sort 0:31:41.040 --> 0:31:44.880 of four to five percent price movers per annum, and 0:31:45.000 --> 0:31:46.840 that's the case most of the time. But the problem 0:31:46.920 --> 0:31:48.000 is we don't get to live most of the time. 0:31:48.040 --> 0:31:50.640 We get to live all the time, and so sometimes 0:31:50.720 --> 0:31:52.600 that five percent move can be thirty five percent and 0:31:52.640 --> 0:31:55.280 forty percent. So think about that eighty percent l TV mortgage. 0:31:55.560 --> 0:31:57.280 That doesn't seem like a risky loan. The bar will 0:31:57.320 --> 0:31:59.280 put up twenty percent, the lender put up eighty percent, 0:32:00.120 --> 0:32:02.440 but there's a one in something chance that the home 0:32:02.520 --> 0:32:05.800 price goes goes to sixty five, And if the home 0:32:05.920 --> 0:32:07.920 goes to sixty five, the loan is no longer going 0:32:07.960 --> 0:32:10.960 to pay off. So that was the sort of the 0:32:11.080 --> 0:32:13.640 thing that we built that people hadn't thought through, is 0:32:13.680 --> 0:32:16.560 how to you stochastically forecast a range of outcomes for 0:32:16.600 --> 0:32:19.000 the asset price? Then how does it affect the repayment 0:32:19.080 --> 0:32:19.360 risk on. 0:32:19.360 --> 0:32:22.800 The loan, So you have to have boots on the ground. 0:32:22.880 --> 0:32:26.800 With fifty thousand homes, how big a staff do you have? 0:32:27.080 --> 0:32:30.400 Is it regional? How do you manage since since you're 0:32:30.480 --> 0:32:33.000 now the landlord for these homes, how do you manage 0:32:33.080 --> 0:32:36.520 the regular maintenance the one off you know, things break 0:32:36.640 --> 0:32:39.600 or refrigerator stops, the toilet kits backed up. How do 0:32:39.680 --> 0:32:40.200 you manage that? 0:32:40.600 --> 0:32:43.680 Yeah, it's complicated. So we have a both of an 0:32:43.760 --> 0:32:47.000 on balance sheet group of repairmen. So we're an investment 0:32:47.440 --> 0:32:51.000 management platform that also has trucks with plumbers crews around 0:32:51.040 --> 0:32:55.800 the country and fixing air conditioners. We also have a 0:32:55.920 --> 0:32:59.040 great vendor network and we have a lot of technology 0:32:59.240 --> 0:33:02.640 that the team, as you mentioned, is about fifteen hundred 0:33:02.680 --> 0:33:05.120 people that are just in that single venderaial platform. This's 0:33:05.120 --> 0:33:07.280 is one of the things Amherst does. But that fifteen 0:33:07.360 --> 0:33:10.240 hundred person team is augmented by about two thousand vendors 0:33:10.280 --> 0:33:15.160 of companies and we're able to handle the properties because 0:33:15.160 --> 0:33:16.960 we have a team in the field. So we literally 0:33:17.040 --> 0:33:20.600 have a repair and maintenance team that's assigned to a 0:33:20.640 --> 0:33:23.320 group of homes. So that person has their three hundred 0:33:23.320 --> 0:33:25.600 homes or something, and then they're part of a local 0:33:25.640 --> 0:33:28.400 team that's managing about fifteen hundred units. So it's not 0:33:28.720 --> 0:33:31.160 that different from how you would manage a multi family 0:33:31.560 --> 0:33:34.040 an apartment complex. It's just that the rooms are further apart, 0:33:34.120 --> 0:33:36.600 the units are further apart, and it causes our drive 0:33:36.680 --> 0:33:38.000 time to be higher. But one of the things that 0:33:38.080 --> 0:33:39.280 we went into this that was one of the big 0:33:39.400 --> 0:33:41.400 questions is could you provide good service and could you 0:33:41.480 --> 0:33:43.080 manage them? And we don't get it right all the time. 0:33:44.000 --> 0:33:46.440 But if you think about the fact that how easy 0:33:46.440 --> 0:33:48.600 it is to get someone out to a home, and 0:33:48.720 --> 0:33:50.560 that's part of our filtering criteria of how we buy 0:33:50.600 --> 0:33:53.480 a home. But think about the fact that for ten bucks, 0:33:53.560 --> 0:33:56.320 you can have Dominoes bringing a pizza and somehow of 0:33:56.360 --> 0:33:58.680 that ten bucks they get the delivery person from their 0:33:58.720 --> 0:34:01.760 store to your home with a hot pizza, and they 0:34:01.800 --> 0:34:03.400 were able to pay for the Super Bowl add out 0:34:04.160 --> 0:34:07.040 embedded in that ten dollar cost, like the transportation cost 0:34:07.160 --> 0:34:08.719 to get people to and from these homes, it just 0:34:08.800 --> 0:34:12.000 isn't a barrier. It's really timing and technology to really 0:34:12.040 --> 0:34:12.480 to rout them. 0:34:12.800 --> 0:34:15.480 So let's talk a little bit about technology over the 0:34:15.560 --> 0:34:21.800 past two decades, real time monitoring of things like fire, flood, 0:34:22.560 --> 0:34:28.520 carbon monoxide break ins, whatever, they've become very inexpensive, very ubiquitous. 0:34:28.840 --> 0:34:32.640 Everybody can have it on a phone. Is that anything 0:34:32.680 --> 0:34:33.839 that you've explored in terms? 0:34:33.880 --> 0:34:35.600 We spent a lot of time on it. There's big 0:34:35.640 --> 0:34:38.600 privacy concerns. So we have families, we have fifty thousand 0:34:38.640 --> 0:34:40.600 families living in their homes and they're their homes and 0:34:40.920 --> 0:34:43.880 we're proud to be part of that process. So, you know, 0:34:44.120 --> 0:34:45.880 a lot of that stuff gets a little creepy to us, 0:34:45.920 --> 0:34:46.640 and so we haven't done well. 0:34:46.680 --> 0:34:49.040 There's a difference between a puppy cam where you're seeing 0:34:49.040 --> 0:34:52.000 what's going on in the bedroom and I know in 0:34:52.080 --> 0:34:55.080 my basement I have a flood. 0:34:54.800 --> 0:34:56.480 Like a high water alarm, that sort of thing. So 0:34:56.600 --> 0:34:59.120 that we're still on their network, we're still so that 0:34:59.239 --> 0:35:02.359 technology for us to go at it stronger. We would 0:35:02.400 --> 0:35:06.600 like for those devices to communicate back to us, uh directly, 0:35:07.120 --> 0:35:07.440 not like. 0:35:07.520 --> 0:35:09.319 A like a cell phone. 0:35:09.600 --> 0:35:11.400 So we are looking at that. There's locks now you 0:35:11.440 --> 0:35:13.960 can buy that have little cell phone transmitters in them, right, 0:35:14.080 --> 0:35:15.920 So we may we may look at things like that, 0:35:16.040 --> 0:35:17.759 but at this point we have so many people on 0:35:17.800 --> 0:35:19.799 the field. We're touching the houses six, eight, nine times 0:35:19.840 --> 0:35:22.960 a year. We have good relationships with our with our residents. 0:35:23.320 --> 0:35:24.480 A lot of that stuff is a little bit of 0:35:24.520 --> 0:35:27.920 pizaz and we see other people charging residents, you know, 0:35:28.000 --> 0:35:30.800 fifty dollars a month for electronic door lock or something. 0:35:31.280 --> 0:35:32.719 We don't think that that's sustainable cost. 0:35:32.760 --> 0:35:34.600 It's a fifty dollar product. How do you chrusee fifty 0:35:34.600 --> 0:35:35.120 dollars a month. 0:35:35.360 --> 0:35:37.120 I no, I don't don't. I don't get it. So 0:35:37.640 --> 0:35:39.799 we will will it's coming along. If I can get 0:35:39.960 --> 0:35:42.080 direct cell phone connections to a high water alarm, I 0:35:42.120 --> 0:35:43.880 would take it. But really, what we have as a 0:35:43.920 --> 0:35:45.800 person go out there and look and touch the property 0:35:45.840 --> 0:35:47.800 eight times a year, and that's how that's how we 0:35:47.840 --> 0:35:49.520 do it. A lot of this is not so complicated, 0:35:49.560 --> 0:35:51.959 but we have you know, through COVID was fascinating because 0:35:52.000 --> 0:35:54.439 that field team and we have a big construction management team. 0:35:54.480 --> 0:35:56.920 So these guys, those fifty thousand homes have all been renovated. 0:35:57.480 --> 0:36:00.440 So that those teams during COVID man they up and 0:36:00.520 --> 0:36:02.400 they went out and they made us so proud they 0:36:02.680 --> 0:36:05.359 provide a service to the residents. They finished construction jobs. 0:36:05.360 --> 0:36:08.200 They got homes back in service so people could move 0:36:08.280 --> 0:36:10.120 out of wherever they were and get into a home. 0:36:11.000 --> 0:36:13.319 So it's been fascinating to watch this business run through 0:36:14.080 --> 0:36:17.080 a crazy COVID cycle, and then a crazy post COVID cycle, 0:36:17.120 --> 0:36:19.200 and now an interest rate cycle. The team has had 0:36:19.239 --> 0:36:20.319 to be pretty nimble. Huh. 0:36:20.840 --> 0:36:24.960 Really quite intriguing. Let's talk a little bit about about 0:36:25.040 --> 0:36:27.840 your space. What are you doing these days in mortgage 0:36:27.880 --> 0:36:31.440 backed securities? Does that market exist remotely like it did 0:36:31.520 --> 0:36:32.360 in the two thousands. 0:36:32.440 --> 0:36:34.480 Well, it's great that you ask about it. So the 0:36:34.600 --> 0:36:36.719 bulk of my career was spent in the mortgage backed 0:36:36.719 --> 0:36:40.800 securities and structure products markets. The single family riendal of 0:36:40.880 --> 0:36:43.920 business kept us very busy while the FED was monetizing 0:36:44.040 --> 0:36:46.239 so many mortgages, so, as you know, they own about 0:36:46.239 --> 0:36:48.960 a third of all mortgages that were ever issued. The 0:36:49.080 --> 0:36:53.200 relative value for non government investors was so bad that 0:36:53.320 --> 0:36:56.000 we wound down a lot of our capabilities in that space. 0:36:56.040 --> 0:36:59.600 We actually sold our investment bank to Manco Santander as 0:36:59.640 --> 0:37:03.319 part of just the frustration with how much intervention had 0:37:03.440 --> 0:37:06.040 sort of driven down value in that space. Well, now 0:37:06.160 --> 0:37:09.160 that's completely reversed and there's a real vacuum today, a 0:37:09.280 --> 0:37:12.919 real vacuum. As the FED stopped buying mortgages, they bought 0:37:12.920 --> 0:37:15.719 a third of the whole market when they stopped buying them. 0:37:15.760 --> 0:37:18.600 I think the belief was that the market would get 0:37:18.680 --> 0:37:21.760 back to its regulary scheduled programming and the traditional investors 0:37:21.800 --> 0:37:24.440 would show up to buy them, and they didn't because 0:37:24.440 --> 0:37:26.520 a lot of those traditional investors don't exist anymore. 0:37:26.640 --> 0:37:30.080 You lose a whole generation, there's no succession beyond. 0:37:30.440 --> 0:37:32.279 This is the largest debt cautter market in the world, 0:37:32.440 --> 0:37:36.279 the largest, most liquid, and it's lost its sponsor. So 0:37:36.360 --> 0:37:39.719 the sponsor went from being the big investment banks, the 0:37:40.120 --> 0:37:43.680 government agencies, the big bank balance sheets, a lot of 0:37:43.680 --> 0:37:45.760 the insurance can be balance sheets, and the money managers. 0:37:46.080 --> 0:37:49.880 The FED displaced all of them. Then they changed regulations 0:37:49.920 --> 0:37:52.279 to where the investment banks can't really step in. The 0:37:52.360 --> 0:37:55.840 agencies are no longer allowed to run balance sheets, the 0:37:55.920 --> 0:37:58.520 reats are not really well positioned to step up in 0:37:58.560 --> 0:38:00.359 the size, as we just saw in the four quarter. 0:38:00.960 --> 0:38:02.960 So there's a real lack of sponsorship with the assets, 0:38:02.960 --> 0:38:06.280 and they've become incredibly attractively priced. So we've been ginning 0:38:06.320 --> 0:38:08.840 back up those strategies. We still we've always run strategy 0:38:08.880 --> 0:38:11.320 that space, but they've been very sort of boring strategies, 0:38:11.360 --> 0:38:14.759 index tracking, index outperformance, that kind of thing. But now 0:38:14.880 --> 0:38:17.399 there's opportunity to really go in and build proper hedge 0:38:17.400 --> 0:38:20.960 fund strategies, proper total return strategies. The relative value is 0:38:21.040 --> 0:38:22.600 sort of startlingly attractive now. 0:38:22.920 --> 0:38:26.200 So I always hated the term financial repression, but what 0:38:26.360 --> 0:38:31.240 you're describing really is the FED engaging in financial repression 0:38:31.400 --> 0:38:32.919 on that corner of the market. 0:38:33.000 --> 0:38:34.560 Well, what I would say is that they were investing 0:38:34.640 --> 0:38:38.160 for a non monetary focus or motivation. Right, They didn't 0:38:38.160 --> 0:38:41.160 care what their returnal the mortgages were they trice and sensitive, right, 0:38:41.239 --> 0:38:44.280 they cared what the lower mortgage rate did to the economy. 0:38:44.800 --> 0:38:47.520 So as a person that's just investing for an economic return, 0:38:47.560 --> 0:38:49.440 you can't compete with that, right, So their motivations were 0:38:49.480 --> 0:38:52.480 totally different, and they and they basically drove down the 0:38:52.560 --> 0:38:56.480 relative value to where on a hedge adjusted basis, if 0:38:56.520 --> 0:38:58.560 you looked at a mortgage and you'd sort of get 0:38:58.600 --> 0:39:00.600 it back to where it's got the same risk a treasury, 0:39:01.120 --> 0:39:03.680 it was yielding almost half a percent less than a treasury. 0:39:04.239 --> 0:39:07.719 They normally yield half a percent more. Now they yield 0:39:08.280 --> 0:39:10.719 one percent more. So in fixed income terms, that's a lot. 0:39:11.200 --> 0:39:13.719 So so now we're really focused on mortgages that we're 0:39:13.719 --> 0:39:15.319 way more active than we have been in the past, 0:39:15.360 --> 0:39:17.440 and we're excited about the opportunities there, and we have 0:39:17.480 --> 0:39:19.120 a commercial morgage lending strategy as well. 0:39:19.640 --> 0:39:22.399 Huh, that's kind of interesting. So let's talk a little 0:39:22.440 --> 0:39:26.600 bit about what's going on in the commercial space. We 0:39:26.719 --> 0:39:29.560 were talking earlier about sixty minutes. Did a piece recently 0:39:30.200 --> 0:39:33.160 on the New York real estate market is never coming 0:39:33.280 --> 0:39:37.000 back and all these big office towers are you know, empty. 0:39:37.760 --> 0:39:40.959 I'm old enough to remember the sea through office towers right. 0:39:40.960 --> 0:39:43.680 Dallas back in the eighties and Dulles the whole right 0:39:43.800 --> 0:39:45.759 the Washington Dulles Quarter was full of sea through right 0:39:45.960 --> 0:39:46.640 see through buildings. 0:39:46.800 --> 0:39:50.880 So we're not there, but certainly the typical high rise 0:39:51.040 --> 0:39:54.000 has you know, a vacancy rate of ten fifteen to 0:39:54.040 --> 0:39:58.880 twenty percent, and the occupancy rate during the day is 0:39:59.080 --> 0:40:02.440 probably another ten to fifteen percent less than that. What's 0:40:02.520 --> 0:40:03.920 going on in the office space. 0:40:04.040 --> 0:40:07.680 So the castle data is pretty fascinating and you can 0:40:07.760 --> 0:40:09.880 get it on your Bloomberg terminal the castle. The castle 0:40:09.920 --> 0:40:12.520 ocup data as we talked about before. 0:40:12.719 --> 0:40:15.600 But by the way, that's all swipe cards of employees 0:40:15.640 --> 0:40:16.279 literally going down. 0:40:16.680 --> 0:40:19.799 The real time physical occupancy data is pretty and it's 0:40:19.840 --> 0:40:22.160 not perfect, like no data set is, but it's pretty startling. 0:40:22.400 --> 0:40:24.920 The last time I looked at it, most markets are 0:40:25.000 --> 0:40:28.960 peaking at fifty percent physical occupancy. Remember I said before 0:40:29.000 --> 0:40:31.239 that in the mortgage market, in the residential mortgage market, 0:40:31.280 --> 0:40:33.840 a borrower can stop making payments and it might be 0:40:33.880 --> 0:40:37.400 two years before the investor actually takes a loss, sometimes 0:40:37.480 --> 0:40:40.120 five years. Well, I think that same thing's been happening 0:40:40.200 --> 0:40:43.520 commercial now for the last since twenty twenty one. Is 0:40:43.600 --> 0:40:48.080 that physical occupancy is the leading indicator to economic occupancy. 0:40:48.480 --> 0:40:52.000 Economic occupancy is who's paying the rent, and in corporate 0:40:52.120 --> 0:40:55.440 leases are of incredibly high credit quality, incredible very few 0:40:55.520 --> 0:41:00.440 leases ever default. Those leases, however, are going to come 0:41:00.560 --> 0:41:04.080 do and the renewal rates are tragically tragically low. So 0:41:04.239 --> 0:41:06.480 if you model out what's going to happen to the 0:41:06.520 --> 0:41:09.600 commercial space from an economic perspective, you don't have to 0:41:09.640 --> 0:41:13.480 be a wizard to figure out that monetary or physical, 0:41:13.760 --> 0:41:16.840 fiscal or financial occupancy is going to track physical accuracy. 0:41:17.239 --> 0:41:19.600 Companies aren't going to be able to give back one 0:41:19.680 --> 0:41:21.640 for one as much space as they're not using because 0:41:21.680 --> 0:41:24.440 they've got this peak and load problem where everyone likes 0:41:24.480 --> 0:41:26.040 to come to work on Wednesdays. So you still need 0:41:26.120 --> 0:41:29.120 the space, but that quantum of space that people need 0:41:29.200 --> 0:41:31.920 has been reduced dramatically and we're seeing it in that 0:41:32.040 --> 0:41:34.560 Castle data. So it's a scary thing to do. But 0:41:34.640 --> 0:41:38.760 if you forecast that the lease payments track the physical usage, 0:41:39.280 --> 0:41:42.320 meaning that what you're seeing today, it's fifteen percent vacancy 0:41:42.400 --> 0:41:44.880 because some leases expired and to get renewed, well, all 0:41:44.960 --> 0:41:47.759 those leases that are being underutilized by half, if those 0:41:47.800 --> 0:41:51.440 don't renew or they renew it much smaller spaces, you 0:41:51.520 --> 0:41:55.960 could create thirty forty percent physical you're actually financial vacancy 0:41:56.239 --> 0:41:59.640 in the commercial space. Now, it's dangerous to forecast that 0:41:59.760 --> 0:42:03.520 far in the future because behavior can change. How much 0:42:03.600 --> 0:42:05.840 space do people need or do they do out the 0:42:05.880 --> 0:42:07.600 fact they want their whole team to get together three 0:42:07.680 --> 0:42:09.560 days a week, so they do they just eat the 0:42:09.640 --> 0:42:13.120 space on the Mondays and Fridays. Some companies are never 0:42:13.160 --> 0:42:15.520 coming back, some jobs are never coming back. So the 0:42:15.560 --> 0:42:17.840 way we look at it, we have some loans in 0:42:17.920 --> 0:42:20.920 the office space. We do feel like it's like bottom 0:42:20.960 --> 0:42:24.920 fishing time and we're taking back real estate. Now that 0:42:25.160 --> 0:42:28.560 is fifty dollars sixty dollars a square foot space for big, 0:42:28.600 --> 0:42:32.800 beautiful buildings that need to be repopulated. But so the 0:42:32.840 --> 0:42:34.680 way we think about is this is that occupancy is 0:42:34.680 --> 0:42:36.759 probably going to drop by a third, but it won't 0:42:36.760 --> 0:42:39.160 be a third for everyone. Right, some places going to 0:42:39.200 --> 0:42:40.960 go to zero, and some guys they won't, They won't 0:42:40.960 --> 0:42:43.480 feel it. So asset selection becomes incredibly important. 0:42:43.520 --> 0:42:46.320 So there's a huge difference between the A class buildings 0:42:46.520 --> 0:42:49.200 and the B and C class. And I've heard people 0:42:49.280 --> 0:42:51.879 say even within A there's a big ring. 0:42:51.880 --> 0:42:53.920 There's the super A stuff, you know, the one Vanderbilt 0:42:53.920 --> 0:42:56.359 thing at two hundred bucks half foot that you can't 0:42:56.440 --> 0:42:59.759 get enough of it. But a block away some traditional 0:43:00.360 --> 0:43:03.360 commodity office space that's just a little draft or whatever, 0:43:04.120 --> 0:43:06.200 you know, that people just don't want it at any price. 0:43:06.520 --> 0:43:09.000 So now that super A space is a very very 0:43:09.040 --> 0:43:10.960 small fracture of the market. So it's not what happens 0:43:11.000 --> 0:43:13.960 there probably isn't going to be sort of impactful, but 0:43:14.080 --> 0:43:17.080 we think that, you know, they're people have to adjust 0:43:17.200 --> 0:43:20.640 to a new normal of demand, like demand function for 0:43:21.040 --> 0:43:23.440 commercial real estate has come down. Now this is, by 0:43:23.480 --> 0:43:26.040 the way, just another domino in a long series of 0:43:26.880 --> 0:43:29.959 what the Inrice Norwitz guys call software eating the world. 0:43:30.360 --> 0:43:32.520 This is technology eating real estate. And so if you 0:43:32.560 --> 0:43:34.000 look at this over longer the time, the way we 0:43:34.040 --> 0:43:37.279 think about it is that technology eight retail and we 0:43:37.360 --> 0:43:39.600 all kind of saw it, right. It was Amazon killed 0:43:39.640 --> 0:43:43.800 the shopping mall. Airbnb has eaten up a lot of 0:43:43.880 --> 0:43:47.160 hotel demand. So technology matching a home to a to 0:43:47.560 --> 0:43:50.600 a rent or a leaser has eaten up a bunch 0:43:50.640 --> 0:43:53.439 of the hotel demand. Now work from home is eating 0:43:53.640 --> 0:43:55.800 is eating office. So we can we kind of have 0:43:55.880 --> 0:43:57.919 a playbook for how this goes. And it's not great. 0:43:58.719 --> 0:44:02.120 And all of these are technology enabled. Without tech, you 0:44:02.160 --> 0:44:04.440 wouldn't be able to do this. The ironic thing is 0:44:05.239 --> 0:44:09.080 the I love people discovered like screen sharing in twenty 0:44:09.160 --> 0:44:11.320 twenty one, right, that tech has been around for a 0:44:11.440 --> 0:44:13.000 dozen plus fifteen years. 0:44:13.200 --> 0:44:15.280 I know, I think about the people that created Skype. 0:44:15.400 --> 0:44:17.360 They must be sort of jumping off a bridge somewhere 0:44:17.400 --> 0:44:20.160 because you know, you couldn't give away Skype pre covid, 0:44:20.200 --> 0:44:22.600 and now now I don't even have calls on my phone, 0:44:22.600 --> 0:44:25.359 my office phone ever anymore. Everything happens over teams are 0:44:25.400 --> 0:44:28.279 over over zoom. So the behavior has changed so quickly. 0:44:28.320 --> 0:44:30.560 But I think that, you know, the CEO from Cisco 0:44:30.640 --> 0:44:32.960 made a good point that the home has become the enterprise, 0:44:33.320 --> 0:44:35.040 and what it was saying is that Cisco is seeing 0:44:35.080 --> 0:44:38.920 people buying really sophisticated communications equipment for their homes because 0:44:38.960 --> 0:44:41.960 now they're they're they're pushing their use case. I so 0:44:42.040 --> 0:44:44.520 for us, it's also kind of fascinating. And this is 0:44:44.560 --> 0:44:47.560 a little bit about how the single trintal trade has 0:44:47.600 --> 0:44:52.040 becomes interesting. Is as people stop going out to the 0:44:52.120 --> 0:44:56.440 mall and they shop at home, as high speed communications 0:44:56.520 --> 0:44:59.799 allows them to stream at home, as delivery allows them 0:44:59.840 --> 0:45:04.560 to and eat at home. Right, these real estate sectors 0:45:04.600 --> 0:45:07.520 are all seeing their demand dry up, the demand for usage. 0:45:07.840 --> 0:45:10.359 All that demand is showing up in the home. It's 0:45:10.360 --> 0:45:13.840 showing up in that eighteen hundred square foot three bedroom 0:45:13.880 --> 0:45:17.279 home because and everyone's use case and demand for real 0:45:17.400 --> 0:45:19.600 estate's changing because they're spending so much more time there. 0:45:20.120 --> 0:45:22.799 So I kind of feel like a lot of those 0:45:23.080 --> 0:45:27.560 big technological shifts we'll post the peak of that like, 0:45:28.080 --> 0:45:31.759 I'm a big online shopper and I've kind of come 0:45:31.840 --> 0:45:35.279 to recognize there's certain things that you just can't buy them. 0:45:35.360 --> 0:45:37.160 Yeah, I have all the time with clothes and things. 0:45:37.680 --> 0:45:40.600 Close is a perfect example. A lot of times you 0:45:40.760 --> 0:45:43.760 order certain things like it's hilarious. You think you're getting 0:45:43.760 --> 0:45:47.719 a four foot tall you know, lamp and this miniature 0:45:47.800 --> 0:45:49.759 and I guess the photo is what the photo is, 0:45:50.160 --> 0:45:53.640 there's just no tape mail tape measure next to it. 0:45:53.760 --> 0:45:55.840 But let me ask you about this, because pre COVID, 0:45:55.920 --> 0:45:58.400 you couldn't have convinced me I could buy groceries on 0:45:58.520 --> 0:45:58.839 an app. 0:45:58.960 --> 0:46:01.080 Oh I was doing that, That's easy. Now. 0:46:01.080 --> 0:46:02.480 I don't think I would ever go back to grocery. 0:46:02.560 --> 0:46:05.439 In fact, Amazon began that when they bought Whole Food. 0:46:05.520 --> 0:46:07.719 So think about what that means that grocery store, that 0:46:07.840 --> 0:46:11.840 grocery store anchored retail. Ordinarily, the grocery store space was 0:46:11.880 --> 0:46:14.040 undwritten at a loss by the real estate developer, right 0:46:14.320 --> 0:46:16.000 because that was your magnet. 0:46:16.280 --> 0:46:18.720 Now it's your distribution hub and there's no people. 0:46:18.880 --> 0:46:20.600 So what happens to the dry clear, what happens to 0:46:20.640 --> 0:46:22.520 the ice cream shop? What happens to the T shirt shop? 0:46:22.560 --> 0:46:24.040 What happens to the travel agent. 0:46:24.719 --> 0:46:27.480 They have to adapt the same technology and do pick 0:46:27.560 --> 0:46:28.160 up and delver. 0:46:28.480 --> 0:46:31.440 So e commerce is changing, like the footprint for a business, 0:46:31.560 --> 0:46:34.719 it's addressable market. And so I don't think this is over. 0:46:34.920 --> 0:46:37.200 I think that that the pricing of it kind of 0:46:37.239 --> 0:46:40.040 like we talked about the loan starts, the loan defaults, 0:46:40.040 --> 0:46:42.480 and then two years later someone takes a loss. Today 0:46:42.920 --> 0:46:46.760 we're CPI prints higher than people expected because owner equivalent 0:46:46.800 --> 0:46:51.000 rents is higher that OER number was calculable four months ago. 0:46:51.440 --> 0:46:54.600 So the market isn't doing a good job of forecasting 0:46:54.640 --> 0:46:56.799 what it already pricing in what it what already knows 0:46:56.840 --> 0:46:59.680 in any cases. And I think that we're still in 0:46:59.800 --> 0:47:02.520 the repricing phase of real estate for a new a 0:47:02.600 --> 0:47:04.360 new type of demand. 0:47:04.560 --> 0:47:08.520 So some of the solutions to these are wholesale changes 0:47:09.160 --> 0:47:11.400 to the way we built out suburbia, which is so 0:47:11.560 --> 0:47:15.799 car dependent. If we were creating these more walkable communities 0:47:16.440 --> 0:47:19.560 like back in the Andy Griffith days, it's fascinating, suddenly 0:47:20.120 --> 0:47:24.479 fascinating you have retailed that's survivable because everything isn't. Getting 0:47:24.520 --> 0:47:27.200 your car and drive to Target that's right, or have 0:47:27.320 --> 0:47:28.920 Target make a delivery exactly. 0:47:29.080 --> 0:47:31.120 So we spend it. You think about how European cities work. 0:47:32.200 --> 0:47:34.320 That's that's what that's how they're that's how they're designed. 0:47:34.719 --> 0:47:37.680 So so the question is is that something we can 0:47:37.840 --> 0:47:40.400 build here? Is there an appetite for that? Is there? 0:47:41.120 --> 0:47:43.480 I'm spending a fair amount of time on just that is. 0:47:44.040 --> 0:47:46.160 Can you respond to this? Should you respond to it? 0:47:46.200 --> 0:47:48.600 Because as you said, like you know, maybe this is 0:47:48.680 --> 0:47:50.640 a flash in the pan. If all the companies decide 0:47:50.680 --> 0:47:53.120 that employees have to come to work every day, then 0:47:53.320 --> 0:47:55.759 then these trends and occupancy will change and quantum of 0:47:55.800 --> 0:47:58.759 demand will change. But I recently was given a book 0:47:58.760 --> 0:48:01.359 and I read it. It's a companion of essays called 0:48:01.400 --> 0:48:03.160 The City Is Not a Tree. It was written in 0:48:03.239 --> 0:48:04.960 nineteen sixty five, and it was about this. It was 0:48:05.000 --> 0:48:09.640 about how a city should work to optimize the experience 0:48:09.760 --> 0:48:11.800 for its residents and think of a city as a product. 0:48:11.880 --> 0:48:13.560 And so we give the speech to mayors when we're 0:48:13.560 --> 0:48:16.200 asked about sort of how we think about their city 0:48:16.280 --> 0:48:19.160 from a migration investment perspective, and we try to tell 0:48:19.239 --> 0:48:21.239 people that a city is a product. So New York 0:48:21.280 --> 0:48:24.680 City is a product and the customers can choose a 0:48:24.680 --> 0:48:27.480 different product, and it's a great product. It's one of 0:48:27.480 --> 0:48:30.279 the greatest products in the world. But like all customers, 0:48:30.680 --> 0:48:34.200 like all businesses, in all product delivery systems, you have 0:48:34.360 --> 0:48:36.880 to freshen your product to keep your customers happy. And 0:48:36.960 --> 0:48:38.759 we see some cities doing that and some cities not 0:48:38.840 --> 0:48:40.719 doing that. So you have to modify. You can't just 0:48:41.320 --> 0:48:42.560 completely tear down and change. 0:48:42.760 --> 0:48:46.040 So one of my favorite YouTube channels is this kind 0:48:46.080 --> 0:48:50.839 of wacky Canadian expat who moved to Amsterdam, and it's 0:48:50.920 --> 0:48:55.400 called Not Just Bikes, and he talks about walkable cities 0:48:55.920 --> 0:49:00.319 and how different countries in Europe do a better job 0:49:00.400 --> 0:49:01.960 of it, and how there are pockets of it in 0:49:02.000 --> 0:49:04.800 the US right and North America, but they're few and 0:49:04.880 --> 0:49:05.440 far between. It. 0:49:05.560 --> 0:49:07.600 Yeah, I think it's something we're spending time on because 0:49:07.640 --> 0:49:11.920 we're with our vertical integration of manufacturing homes, building homes, 0:49:12.160 --> 0:49:15.160 real estate development. The ability to monetize a home either 0:49:15.200 --> 0:49:17.160 as a cell to a consumer or a rent and 0:49:17.239 --> 0:49:19.600 have into an investor. It gives us the ability to 0:49:19.640 --> 0:49:22.839 think big about development and I haven't seen anyone pull 0:49:22.880 --> 0:49:25.280 off yet. So the master plan community the United States, 0:49:26.000 --> 0:49:28.400 other than maybe the woodlands in Houston very few of 0:49:28.440 --> 0:49:31.160 them are actually master planned for multiple product types where 0:49:31.200 --> 0:49:37.040 you have office, medical, civil, residential, entertainment, all kind of 0:49:37.120 --> 0:49:39.520 thought about together the way you would the way European 0:49:39.600 --> 0:49:42.160 cities were developed. But remember Europe, like you said, you 0:49:42.200 --> 0:49:45.680 said a very key thing. European cities were developed before 0:49:45.760 --> 0:49:49.240 the cars became years a lot of our cities stopped 0:49:49.320 --> 0:49:53.000 growing as core cities and started growing as these suburban 0:49:53.080 --> 0:49:55.719 driven cities because of the car. And so this will 0:49:55.719 --> 0:49:58.120 be simple, this will be think if will you reverse? 0:49:58.160 --> 0:50:00.200 And this is something that global real estate investor are 0:50:00.239 --> 0:50:02.279 thinking about a full time basis. There was a paper 0:50:02.320 --> 0:50:04.000 written about five years ago, I think it was put 0:50:04.040 --> 0:50:06.080 out by the research team Prudential, and it was all 0:50:06.080 --> 0:50:09.640 about urbanization and all of the investment themes across our 0:50:09.719 --> 0:50:12.160 investor base, the biggest invests in the world. We're very 0:50:12.200 --> 0:50:14.759 focused on urbanization as a global theme, and you could 0:50:14.760 --> 0:50:16.520 see it in Southeast Asia, you could see it all 0:50:16.600 --> 0:50:19.000 over China, you could see it. Of course, has happened 0:50:19.000 --> 0:50:20.799 in the United States where people left the small town 0:50:20.880 --> 0:50:23.360 to go to the big city. COVID may have reversed 0:50:23.400 --> 0:50:26.520 one of the largest global trends in investing in the 0:50:26.640 --> 0:50:28.520 last one hundred years. It may have turned. It may 0:50:28.600 --> 0:50:33.320 have turned us from urbanization to de urbanization and the 0:50:33.360 --> 0:50:35.680 impact of that. Now we're not calling that just yet, 0:50:35.760 --> 0:50:37.560 but it is probably one of the most important things 0:50:37.600 --> 0:50:39.600 that people can focus on, or are we going to 0:50:39.800 --> 0:50:42.960 shrink the size of these megacities that all benefited from 0:50:43.600 --> 0:50:45.920 urbanization for the last you know, sort of fifty years 0:50:45.960 --> 0:50:48.840 in the US, maybe the last fifteen years in Southeast Asia. 0:50:49.600 --> 0:50:52.120 So it's an interesting time where the I wish I 0:50:52.120 --> 0:50:54.000 could say I was going to turn out, but there 0:50:54.160 --> 0:50:56.400 is a the ball is bouncing around and we need 0:50:56.440 --> 0:50:57.719 to understand which way it's going to land. 0:50:58.040 --> 0:50:59.680 Tell us about Main Street Renewal. 0:51:00.160 --> 0:51:02.439 Is that so that's the operating platform for the single 0:51:02.520 --> 0:51:06.600 fundamental business. That's our construction management, our real estate brokers platform, 0:51:06.760 --> 0:51:10.360 our leasing platform, the customer service platform. So that's the 0:51:10.480 --> 0:51:13.720 brand name that the consumers see, that our their operating 0:51:13.760 --> 0:51:18.040 partners see for the whole vertically integrated single family rental strategy. 0:51:18.680 --> 0:51:22.239 That's basically analogous to the entire ecosystem of the mortgage market, 0:51:22.520 --> 0:51:24.560 wrapped up under one one corporate label. 0:51:25.440 --> 0:51:28.040 And we've been talking a lot about single family homes 0:51:28.120 --> 0:51:30.759 to be purchased and rented a couple of years ago 0:51:30.920 --> 0:51:34.360 sixty Minutes to a piece talking about, hey, is private 0:51:34.400 --> 0:51:37.920 equity pushing out local buyers? I know you have an 0:51:37.920 --> 0:51:40.480 opinion on this. Tell us a little bit about your 0:51:40.520 --> 0:51:42.320 experience with sixty minutes. 0:51:42.560 --> 0:51:45.120 Sure, sure, So, first of all, I love sixty Minutes. 0:51:45.120 --> 0:51:46.640 I don't know it's just because I'm finally old enough 0:51:46.680 --> 0:51:48.319 to age into their demographic. But I think it's one 0:51:48.320 --> 0:51:50.880 of the best news shows on television because in that 0:51:51.000 --> 0:51:53.640 twelve or fifteen minute segment, they really can simplify a 0:51:53.719 --> 0:51:55.840 topic and make it and make it understandable to everyone. 0:51:56.760 --> 0:52:00.480 The topic of where do we fit in the system 0:52:00.520 --> 0:52:02.799 of the single family housing market is what we're doing 0:52:02.840 --> 0:52:05.279 a good thing or a bad thing? Obviously, you know, 0:52:05.320 --> 0:52:06.759 I've got a couple of thousand people that wake up 0:52:06.760 --> 0:52:08.160 every day and go to work. They don't think they're 0:52:08.160 --> 0:52:10.200 doing a bad thing. So I can tell you our 0:52:10.239 --> 0:52:11.640 perspective of it. I can kind of give you both 0:52:11.680 --> 0:52:13.560 sides of the argument, and people can decide for themselves. 0:52:13.600 --> 0:52:17.239 I mean, part of the argument is that if Sean 0:52:17.320 --> 0:52:18.920 buys the home, or if amorist buys the home, some 0:52:19.000 --> 0:52:23.200 family couldn't buy the home. And it's true that if 0:52:23.239 --> 0:52:24.600 we buy the home, no one else could buy the home. 0:52:24.760 --> 0:52:27.800 I'll give you that part. Now, in the US, we 0:52:27.960 --> 0:52:31.080 track the home ownership rate over time. The home ownership 0:52:31.120 --> 0:52:33.399 rate has grown to sort of mid sixties and babble around. 0:52:33.440 --> 0:52:34.960 It got really really high when we were giving away 0:52:35.000 --> 0:52:37.319 mortgages in two thousand and seven, and then it came 0:52:37.360 --> 0:52:40.760 back down. But that number has been a six handle 0:52:40.880 --> 0:52:43.560 for the last fifty years, right, So sixty something percent 0:52:43.640 --> 0:52:46.120 of people own their homes. The inverse of that number 0:52:46.280 --> 0:52:48.120 is the people that don't own their homes. So that 0:52:48.320 --> 0:52:52.040 number has been between thirty and call it thirty and 0:52:53.120 --> 0:52:55.520 twenty five percent for a very long time. So that 0:52:55.719 --> 0:52:58.879 third of how of families in the US that rent 0:52:58.920 --> 0:53:01.440 their home rent for a mere reasons. One of the 0:53:01.480 --> 0:53:03.600 reasons that they rent is because they can't get amorage. 0:53:04.160 --> 0:53:07.000 And part of our bet in two thousand and nine 0:53:07.440 --> 0:53:09.320 was that the group of people who are going to 0:53:09.360 --> 0:53:10.759 be locked out of the mortgage market is going to 0:53:10.800 --> 0:53:15.640 grow substantially, partially because the standards became higher, and partially 0:53:15.680 --> 0:53:19.080 because student loans became kind of a predatory financial product. 0:53:19.640 --> 0:53:23.160 So having a student loan makes it way more difficult 0:53:23.200 --> 0:53:25.279 to get a mortage. So in this argument of are 0:53:25.360 --> 0:53:27.080 we buying a home that a family is not moving into, 0:53:27.520 --> 0:53:30.040 I put the paradigm in a slightly different way. When 0:53:30.080 --> 0:53:33.000 that home comes up for sale, a lot of families 0:53:33.040 --> 0:53:34.800 show up that want to live in that home. A 0:53:34.880 --> 0:53:37.000 group of those families show up and they can get 0:53:37.000 --> 0:53:39.399 a mortgage and they can buy the home. A group 0:53:39.440 --> 0:53:40.719 of those famili show up and they can't get a 0:53:40.719 --> 0:53:42.840 mortage for that second group of families to get to 0:53:42.880 --> 0:53:44.960 live with that home, and investors got to buy the home. 0:53:45.480 --> 0:53:47.839 And that investor can be and historically has been very 0:53:47.880 --> 0:53:50.560 small investors, people that own one or two homes. Maybe 0:53:50.600 --> 0:53:53.200 they owned a home, lived there, moved away, kept it, 0:53:53.440 --> 0:53:57.239 rented it. And now through the through technology and through 0:53:57.400 --> 0:54:00.960 significant investment platforms like ours, allow larger investors to go 0:54:01.320 --> 0:54:04.000 and invest in that home. So when I sit down 0:54:04.000 --> 0:54:07.000 with policy makers and they're sort of of this mindset 0:54:07.120 --> 0:54:10.120 that I should have stayed away and let the family 0:54:10.200 --> 0:54:12.000 buy the home, what I like to do is say, 0:54:12.160 --> 0:54:14.400 can you guys just put together the pictures of these 0:54:14.440 --> 0:54:17.160 two families and who's going to get to live in 0:54:17.239 --> 0:54:19.480 that home? If the only people who can get a 0:54:19.520 --> 0:54:21.799 mortgage can live there? And who can live there if 0:54:21.840 --> 0:54:24.840 Sean buys the home, because demographically they look more like 0:54:24.960 --> 0:54:27.440 the people that get served by the home when I 0:54:27.560 --> 0:54:29.279 buy it, look a lot more like the people the 0:54:29.320 --> 0:54:32.160 government should be trying to help. And that usually takes 0:54:32.200 --> 0:54:33.799 people and they step back and they go, wait a minute, 0:54:33.800 --> 0:54:35.319 what do you mean. I'm like, well, so Shawn doesn't 0:54:35.320 --> 0:54:37.759 live in fifty thousand homes. Someone's living in there. And 0:54:37.840 --> 0:54:39.879 the people that live in those homes, for the most part, 0:54:40.280 --> 0:54:42.440 are not candidates to get a mortgage in the twenty 0:54:42.719 --> 0:54:44.560 twenty four mortgage standards. 0:54:45.400 --> 0:54:47.279 And it's not because they don't have a jobs and 0:54:47.400 --> 0:54:48.280 they aren't. 0:54:48.440 --> 0:54:51.560 Currently they're paying two thousand dollars a month in rent. 0:54:51.640 --> 0:54:54.239 Our average customer only pays twenty five percent of their 0:54:54.320 --> 0:54:57.920 income in rent. For two thousand dollars. They cover everything, 0:54:58.080 --> 0:55:00.680 They cover the chance that the ac breaks. They don't 0:55:00.760 --> 0:55:03.480 have to pay for that, property taxes, insurance, the whole 0:55:03.560 --> 0:55:05.920 nine yards. So right now, the cost to rent is 0:55:05.920 --> 0:55:08.200 probably thirty percent cheaper than the cost to own. But 0:55:08.320 --> 0:55:10.680 more importantly, if you're not given a chance to get 0:55:10.719 --> 0:55:13.080 a mortgage, it doesn't matter what the cost to own is. 0:55:13.239 --> 0:55:15.200 The cost for you is infinite because you're not allowed 0:55:15.200 --> 0:55:17.440 to get a mortgage. So when they when Dodd Frank 0:55:17.520 --> 0:55:20.719 passed and the standards for mortage credit became unfairly high, 0:55:21.320 --> 0:55:23.640 we said, Okay, this is what's gonna this is what 0:55:23.719 --> 0:55:25.520 the nation to decided it wants to do now against 0:55:25.560 --> 0:55:27.440 my advice when I sat, when I sat at full reserve, 0:55:27.480 --> 0:55:29.480 I said, this doesn't have to happen. This way, we 0:55:29.560 --> 0:55:31.520 can sort out for you what the good subprime was 0:55:31.600 --> 0:55:35.000 from the bad subprime. People are like, we agree, you can, 0:55:35.160 --> 0:55:38.680 but that's not how policy works. That mortgage market has 0:55:38.680 --> 0:55:40.239 been shut down and it's going to stay shut down. 0:55:40.280 --> 0:55:43.000 So what should we do to reopen that mortgage market 0:55:43.719 --> 0:55:47.680 for people who are currently employed have a half decent credit. 0:55:47.960 --> 0:55:49.359 Now, you're baby, we're gonna give in the two hours 0:55:49.400 --> 0:55:50.719 for the podcast. I got a whole list of things 0:55:50.800 --> 0:55:52.719 need to do, but the give us a short PNT. 0:55:53.080 --> 0:55:54.880 The primary, the primary thing you have to do is 0:55:54.920 --> 0:55:56.719 you have to put risk. You have to make risk 0:55:56.840 --> 0:56:00.920 based pricing legal in the US mortgage system. Dodd Frank 0:56:01.080 --> 0:56:05.000 made risk based pricing illegal. So if someone comes in 0:56:05.120 --> 0:56:07.920 with a lower credit score, a higher likelihood of default, 0:56:08.200 --> 0:56:11.120 and remember the likelihood of default could mean that they 0:56:11.200 --> 0:56:13.640 go from being five percent likely to ten percent likely, 0:56:13.800 --> 0:56:16.719 not ninety percent likely. But if someone comes in that 0:56:17.320 --> 0:56:19.719 that has a likelihood default above a certain level, the 0:56:19.760 --> 0:56:21.960 answer is you can't make them the mortgage. 0:56:21.560 --> 0:56:24.719 At any price as opposed to where it's I'll make 0:56:24.800 --> 0:56:27.200 up a round number. If we're at five percent, they 0:56:27.239 --> 0:56:28.840 could buy get a mortgage at six and. 0:56:28.880 --> 0:56:31.759 Three we used the rate used to be three points 0:56:31.840 --> 0:56:34.880 hire two points are so Dodd Frank basically carved out 0:56:34.960 --> 0:56:37.759 the maximum premium you can charge to anyone, and then 0:56:37.800 --> 0:56:40.920 they created recourse for the borrower. So I give this 0:56:41.040 --> 0:56:43.920 presentation in the UK, and I gave this presentation to 0:56:43.960 --> 0:56:46.400 France once and I said, okay, the US passed. They 0:56:46.440 --> 0:56:48.080 were like, why is the demand for rental so high? 0:56:48.080 --> 0:56:50.560 And I said, people can't get mortgages. He said why, 0:56:50.880 --> 0:56:53.080 I said, well, Dodd Frank created a precedent that said 0:56:53.480 --> 0:56:55.239 that if I lend you money to buy your home 0:56:56.360 --> 0:56:59.320 and then you can't pay me back, you can sue me. 0:57:00.440 --> 0:57:02.200 And even in France, the guy would say no, no, no, 0:57:02.440 --> 0:57:05.080 you mean the other way around. I lend you the 0:57:05.120 --> 0:57:07.759 money you don't pay, I can sue you and I'm like, no, no. 0:57:08.600 --> 0:57:11.759 So there's there's this concept that that that was part 0:57:11.840 --> 0:57:15.279 of the the ether in the financial crisis, that the 0:57:15.360 --> 0:57:18.480 banks were the proximate cause for the default, and so 0:57:18.600 --> 0:57:20.680 the bank should not be allowed to make these loans. 0:57:22.000 --> 0:57:23.360 There were some bad back that's a. 0:57:23.400 --> 0:57:28.160 Wild statement because as someone literally wrote a book on this, 0:57:28.920 --> 0:57:31.440 banks did a bunch of stuff that wasn't very smart. 0:57:31.920 --> 0:57:35.640 But it's hard to say the banks making loans were approximate, 0:57:35.720 --> 0:57:38.680 cause now there's a handful of banks doing the ninja stuff, 0:57:38.760 --> 0:57:39.640 and but that was. 0:57:39.640 --> 0:57:41.800 There really enough bad acts to go around. The banks 0:57:41.840 --> 0:57:47.600 had culpability, the securitization industry had culpability, Serving industries culpability, 0:57:47.720 --> 0:57:50.760 The ratings agency agencies had culpability. And this is why 0:57:50.760 --> 0:57:52.600 I spend time washing trying to explain to people. But 0:57:52.760 --> 0:57:54.920 the consumers had culpability as well. So a lot of 0:57:54.960 --> 0:57:57.320 people with fraudulent loans six eight loans. So we bought 0:57:57.320 --> 0:58:00.160 a bunch of these loans. Something people don't know is 0:58:00.160 --> 0:58:02.919 that we audited eighty thousand loan contracts that we bought, 0:58:03.400 --> 0:58:06.040 and we there's a return to cinder clause in mortgage 0:58:06.040 --> 0:58:07.480 contracts that most people don't know about. 0:58:07.560 --> 0:58:07.680 Right. 0:58:07.840 --> 0:58:10.000 And if the bar were defaulted and the contracts were 0:58:10.080 --> 0:58:11.800 in a certain way, the person that sold your loan 0:58:11.840 --> 0:58:14.200 has to buy it back. So in these eighty thousand 0:58:14.280 --> 0:58:17.120 loans you kind of had sort of two big populations 0:58:17.200 --> 0:58:21.360 of predatory borrowers. One with a little mini we call 0:58:21.360 --> 0:58:23.280 the little Minnie Donald Trump's. They would have like twenty 0:58:23.320 --> 0:58:25.880 five or thirty or forty homes, no equity down. They're 0:58:25.880 --> 0:58:29.320 all rented, no management, kind of like yolo of like 0:58:29.400 --> 0:58:30.960 if they go up, we're going to refinance them. If 0:58:30.960 --> 0:58:32.320 they don't, we're going to send the keys back in. 0:58:32.440 --> 0:58:35.760 And these were loans that were made with no equity 0:58:35.800 --> 0:58:39.200 from the barrower eighty percent first, twenty percent second investor loans. 0:58:40.160 --> 0:58:42.200 And then then there were a group of people who 0:58:42.320 --> 0:58:44.480 really just wanted a house and they were willing to 0:58:44.520 --> 0:58:47.560 fib about their financial standards to get there, right, and 0:58:47.680 --> 0:58:49.680 so and the banks and the mortga originators. In many 0:58:49.720 --> 0:58:52.640 cases there's eighty thousand files. You would open up the 0:58:52.720 --> 0:58:54.680 file and it would say the person was a dental 0:58:54.760 --> 0:58:57.760 hygienist and made one hundred thousand dollars a year, no document, 0:58:58.000 --> 0:59:00.200 and that loom was loans approved. Now in this you 0:59:00.280 --> 0:59:03.280 file would be the application that got denied that said 0:59:03.320 --> 0:59:05.640 that they were a dental assistant and they made fifty 0:59:05.680 --> 0:59:07.520 thousand dollars a year, so they would give us the 0:59:07.600 --> 0:59:08.920 file that so they was. 0:59:09.000 --> 0:59:11.240 So those were the I heard stories at the time 0:59:11.360 --> 0:59:15.280 of the mortgage brokers who were able to guide an 0:59:15.360 --> 0:59:19.040 applicant through coaching. Coach, don't write this, don't write here 0:59:19.240 --> 0:59:23.080 what you got to say? And basically, you know, we're 0:59:23.680 --> 0:59:26.320 co conspirators to fraud. 0:59:26.440 --> 0:59:28.600 And you know the Mortriges broker was making five or 0:59:28.640 --> 0:59:30.560 six percent of the loan amount, right, it's a lot 0:59:30.600 --> 0:59:31.120 of incentives. 0:59:31.120 --> 0:59:33.480 So I blame them much more than the person who 0:59:33.600 --> 0:59:35.800 just did what they were told they were wrong. At 0:59:35.840 --> 0:59:37.920 this point, really the professional is the one got a 0:59:37.920 --> 0:59:38.440 whole scount. 0:59:38.480 --> 0:59:40.200 I think that we're hung up on who to blame, 0:59:40.360 --> 0:59:41.840 not you and me. But if the market is who 0:59:41.880 --> 0:59:43.480 to blame, and the market isn't paying attention of who 0:59:43.480 --> 0:59:46.360 got harmed, because in the first degree, the person that 0:59:46.440 --> 0:59:48.720 got harmed was the person who got four clothes up 0:59:48.760 --> 0:59:50.440 on and got addicted from their home, that's a very 0:59:50.480 --> 0:59:53.560 clear harm to see. The harder harm to see is 0:59:53.680 --> 0:59:56.600 that maybe eight million families that haven't been able to 0:59:56.640 --> 0:59:59.520 buy a home since this law went and it's fifteen 0:59:59.600 --> 1:00:03.320 years and there's no progress, So the rental market has 1:00:03.360 --> 1:00:06.600 to grow. Institutional capital is going to play a part 1:00:06.720 --> 1:00:09.720 in every home transaction. Its social capital has to be 1:00:09.760 --> 1:00:12.040 there to make the loan if they're not going to 1:00:12.080 --> 1:00:14.880 buy the home. Providing service to the third of American 1:00:14.920 --> 1:00:17.880 families who rent for various reasons. Now, about a third 1:00:17.880 --> 1:00:19.800 of our customers, or twenty percent of our customers move 1:00:19.840 --> 1:00:21.560 out every year, so they were never like long term 1:00:21.600 --> 1:00:26.400 committed to that location to begin with. The credit scores 1:00:26.520 --> 1:00:30.520 of our customers suggest and the financial condition of our 1:00:30.560 --> 1:00:32.600 customers suggests it would be very difficult. It's not it 1:00:32.680 --> 1:00:35.160 possible for them to get a mortgage on average. So 1:00:35.840 --> 1:00:37.880 this is the solution for people to move out of 1:00:38.560 --> 1:00:39.880 the Other thing people think about it is that it's 1:00:39.880 --> 1:00:42.880 okay to rent apartments. So that's socially acceptable to invest 1:00:42.960 --> 1:00:45.520 in apartments and rent them. But apartments are primarily one 1:00:45.560 --> 1:00:48.520 and two bedroom products, so we're a three bedroom product. 1:00:48.760 --> 1:00:50.960 So as you age out of an apartment or you 1:00:51.080 --> 1:00:52.560 need more space because you work from home, or you 1:00:52.600 --> 1:00:54.640 have a family or whatever, and you age into the 1:00:54.720 --> 1:00:58.120 single family product, which is location driven, local amenities driven 1:00:58.160 --> 1:01:00.720 blah blah blah. So you would go and get a 1:01:00.760 --> 1:01:03.880 mortgage and buy. But that cross section of the customer 1:01:03.960 --> 1:01:06.240 base that the mortgage market serves has shrunk so much 1:01:07.040 --> 1:01:08.720 that we set up this platform because we knew they 1:01:08.720 --> 1:01:10.200 were coming. We knew that they're going to want to 1:01:10.240 --> 1:01:11.880 live in that product and they're going to need to 1:01:11.920 --> 1:01:14.200 get there with a different financial solution than a mortgage. 1:01:14.480 --> 1:01:17.960 So we developed an institutional scale, securitized financing vehicle for 1:01:18.040 --> 1:01:20.680 the pool of homes. We developed the services that wrap 1:01:20.720 --> 1:01:22.600 around the pool of home to lower its cost to capital, 1:01:23.000 --> 1:01:25.000 So the cost of capital for single time really today 1:01:25.080 --> 1:01:26.840 is in the five to five and a half percent range. 1:01:27.680 --> 1:01:29.800 Prior to us getting involved, the cost of capital for 1:01:29.840 --> 1:01:32.720 rental was probably eight hundred over and nine hundred over 1:01:32.760 --> 1:01:36.560 because it was provided by small investors taking very specific 1:01:36.680 --> 1:01:40.400 location risk. Now we can have a thousand homes, all 1:01:40.400 --> 1:01:43.439 the adiosyncratic risk is pretty much gone. So we feel 1:01:43.520 --> 1:01:45.040 very proud of what we're doing. And I wish that 1:01:45.400 --> 1:01:48.320 the conversation about this crowd out would focused more on 1:01:48.400 --> 1:01:51.360 the specifics of who didn't get to buy, but who 1:01:51.440 --> 1:01:53.600 got to live there, and when people see that and 1:01:53.680 --> 1:01:56.000 they see that, Oh wait a minute, these are three 1:01:56.040 --> 1:01:58.720 hundred thousand OAR homes. These are not you know, these 1:01:58.760 --> 1:02:01.360 are homes that that bar, that resident would have a 1:02:01.480 --> 1:02:05.200 very difficult time getting into without us, and we were 1:02:05.200 --> 1:02:08.520 able to provide a really good service at a very 1:02:08.560 --> 1:02:10.320 effective price for that customer base. 1:02:10.760 --> 1:02:14.520 That's a really interesting answer to a complicated question, and 1:02:15.200 --> 1:02:18.560 it still leaves open the problem that there are eight 1:02:18.640 --> 1:02:23.240 million people that might otherwise be on be homeowners. But 1:02:24.280 --> 1:02:25.960 the rule change has been and the. 1:02:25.920 --> 1:02:27.600 Way I think about it, the way you get me 1:02:27.640 --> 1:02:29.880 a slopbox. But in the worst of the worst mortgage 1:02:29.880 --> 1:02:33.520 pools that we were short and the dirtiest of the pools, 1:02:33.560 --> 1:02:36.560 where everybody was lying the bar, where the banker, the securitizer, 1:02:36.560 --> 1:02:38.800 everything age, everybody was lying the worst of the worst. 1:02:39.280 --> 1:02:42.200 About thirty five percent of the loans defaulted, which means 1:02:42.240 --> 1:02:45.000 that two thirds of even those dodgy things paid. So 1:02:45.120 --> 1:02:47.600 those are two thirds of those families got to get 1:02:47.640 --> 1:02:50.920 on the economic ladder and own the piece of America. 1:02:52.200 --> 1:02:55.360 Because the third worked out so poorly, we shut out 1:02:55.360 --> 1:02:57.600 the two thirds. And that's kind of the frustration I 1:02:58.000 --> 1:03:00.360 had with Washington. It is like guys like I know 1:03:00.440 --> 1:03:01.920 there's to throw the baby out with the bath or 1:03:01.920 --> 1:03:03.920 what other. But you're thrown out. You're throwing out an 1:03:04.000 --> 1:03:06.160 opportunity for people to own a piece of the country 1:03:06.960 --> 1:03:10.720 and act as owners in their community because you don't 1:03:10.760 --> 1:03:12.400 have a good way to manage the ones that don't 1:03:12.400 --> 1:03:14.280 work out. So we should be focused on what to 1:03:14.360 --> 1:03:17.080 do when they don't work out. We shouldn't prohibit the 1:03:17.120 --> 1:03:19.120 activity because some of it doesn't. 1:03:18.920 --> 1:03:21.240 Work out well. Congress seems to have its act together. 1:03:21.320 --> 1:03:24.080 I'm sure, I'm sure it's next to the docket, right. 1:03:24.160 --> 1:03:26.720 This will be worked out, all right, So I only 1:03:26.880 --> 1:03:29.560 have you for a limited amount of time. Let's jump 1:03:29.640 --> 1:03:32.640 to our favorite questions. We ask all of our guests 1:03:33.240 --> 1:03:36.480 starting with what have you been entertained with these days? 1:03:36.520 --> 1:03:38.360 Tell us what you're either watching or listening to. 1:03:38.720 --> 1:03:40.960 Oh wow, So I'm a very boring person. I spent 1:03:41.000 --> 1:03:43.440 a lot of my time buried in data and analytics. 1:03:43.960 --> 1:03:46.760 I think that I really love the whole Yellowstone series. 1:03:46.800 --> 1:03:49.480 I'm upset that Costner backed out because I thought the 1:03:49.520 --> 1:03:51.560 production quality was so good. So I've seen all of 1:03:51.600 --> 1:03:54.320 the pre the you know, the prequels and so forth. 1:03:54.360 --> 1:03:56.960 So on the entertainment side, I think that streaming has 1:03:57.000 --> 1:03:59.880 set a whole new bar for quality of broke. 1:04:00.880 --> 1:04:04.360 Yeah, no, that's absolutely on my list. Tell us about 1:04:04.440 --> 1:04:07.800 your early mentors who might have helped shape your career. 1:04:08.880 --> 1:04:10.800 Wow. Well, so I've got a big family. I'm one 1:04:10.880 --> 1:04:15.200 of five kids. My parents were serial entrepreneurs. I've got 1:04:15.240 --> 1:04:18.880 four big sisters, and so they're all successful in various ways, 1:04:18.880 --> 1:04:22.040 and so the family has always been the primary motivator 1:04:22.560 --> 1:04:26.600 and leaders. You have to this in our business. You know, 1:04:26.800 --> 1:04:29.400 in finance, who you marry really matters. So I've been 1:04:29.440 --> 1:04:31.360 married for twenty eight years. My wife was in finance. 1:04:31.400 --> 1:04:33.360 She ran an investment management business, built it up and 1:04:33.440 --> 1:04:36.720 sold it. So having support at home and having a 1:04:36.800 --> 1:04:39.560 real partner in the business is super super important our jobs. 1:04:39.800 --> 1:04:41.960 When you're the founder of a business, you know, the 1:04:42.040 --> 1:04:45.760 hours are long and the mental exercise is significant. So 1:04:46.240 --> 1:04:49.520 having the right teammate at home is absolutely paramount. 1:04:50.520 --> 1:04:51.120 I was. 1:04:51.320 --> 1:04:54.960 I had a high school economics teacher who later went 1:04:55.040 --> 1:04:57.040 to work for the Federal Home Loan Bank of Dallas 1:04:57.160 --> 1:05:00.560 named Sandy Hawkins, who was just fantastic for a high 1:05:00.560 --> 1:05:03.600 school economics teacher. She covered everything from Milton Friedman to 1:05:04.560 --> 1:05:07.200 free lunches in a way that made it fun for 1:05:07.280 --> 1:05:09.800 high school kids, and I absorbed every second of that 1:05:09.880 --> 1:05:12.520 I could. And then I had this really unusual situation 1:05:12.640 --> 1:05:14.280 because I was at this brokerage firm when I was 1:05:14.360 --> 1:05:17.800 very young, and mortgages were just getting some science around them, 1:05:17.840 --> 1:05:20.280 and I was always good at math and I had 1:05:20.320 --> 1:05:22.520 been writing code since I was in the sixth grade. 1:05:23.720 --> 1:05:27.680 So I had real support around Wall Street because at 1:05:27.720 --> 1:05:30.280 the time there was a small club of firms that 1:05:30.440 --> 1:05:33.320 were helping solve this problem together. And so I had 1:05:33.920 --> 1:05:36.240 a guy named Frank Gordon who ran mortgage research at 1:05:36.280 --> 1:05:39.040 First Boston. That was just a great support to kind 1:05:39.040 --> 1:05:40.560 of bring me up up the learning curve. 1:05:41.000 --> 1:05:44.640 Huh interesting. Tell us about some of your favorite books 1:05:44.680 --> 1:05:46.440 and what have you been reading recently. 1:05:46.800 --> 1:05:48.800 Well, I mentioned I read A City Is Not a Tree. 1:05:48.840 --> 1:05:50.880 It's a little bit boring, but it's fascinating because I 1:05:50.920 --> 1:05:52.960 do think that there's an opportunity for us to rebuild 1:05:53.720 --> 1:05:58.240 microcities instead of instead of going to the exerbs and 1:05:58.400 --> 1:06:00.160 trying to adjoin a city. I do think that is 1:06:00.320 --> 1:06:02.600 something that we're working on, to just PLoP in the 1:06:02.640 --> 1:06:04.800 middle of nowhere and build a full stand up city, 1:06:04.800 --> 1:06:08.680 which would be fascinating. My my daughter and I listened 1:06:08.680 --> 1:06:11.240 to crime Junkies and on the entertainment side, I think 1:06:11.240 --> 1:06:13.240 it's one of the most popular, other than Years of course, 1:06:13.280 --> 1:06:15.560 one of the most popular podcasts in the country. It's fascinating. 1:06:15.960 --> 1:06:18.600 It's it's a couple of young women that that tell 1:06:18.680 --> 1:06:22.400 the story of some sort of unsolved mystery or solved 1:06:22.440 --> 1:06:25.680 mystery of real time what they call it there, it's 1:06:25.720 --> 1:06:28.320 a it's the real crime dramas. I think it's been 1:06:28.320 --> 1:06:30.520 pretty fascinating. And I've got we have two kids, and 1:06:30.560 --> 1:06:33.560 my wife and I have a freshman at Columbia and 1:06:33.720 --> 1:06:36.520 a sophomore at Stanford, so we're spending a lot of 1:06:36.600 --> 1:06:38.400 time learning about the college. 1:06:38.120 --> 1:06:40.840 Experience freshmen at Columbia. Oh, so you're you're back and. 1:06:40.920 --> 1:06:43.400 Forth, but my poor wife is on like the coast 1:06:43.440 --> 1:06:44.320 to coast tour. 1:06:44.560 --> 1:06:47.120 Are you are you guys in Austin? 1:06:47.160 --> 1:06:50.920 A lot home is in Austin, so you're halfway or exactly, 1:06:51.000 --> 1:06:53.640 we're equally it's equal travel to either place. 1:06:54.320 --> 1:06:57.160 And uh So, our final two questions, what sort of 1:06:57.200 --> 1:07:00.680 advice would you give a recent college grad interested in 1:07:00.760 --> 1:07:06.280 a career in mortgages real estate cra anything along those lines. 1:07:06.600 --> 1:07:09.160 Yeah, So whenever we have interns come in or we 1:07:09.240 --> 1:07:12.400 have young executives start, I buy them a couple things. 1:07:12.400 --> 1:07:15.760 So I buy them the Frank Fobose Handbook on mortgagsback securities, 1:07:15.920 --> 1:07:19.760 the Mortgage back Nerds Bible, and I buy them a 1:07:19.800 --> 1:07:23.439 book Bernstein's book called Against the Gods. And I really 1:07:23.560 --> 1:07:26.080 think that maybe it's just because I'm such a quant nerd, 1:07:26.520 --> 1:07:28.400 but I think that Against the Gods it's a very 1:07:28.440 --> 1:07:32.040 small book, a very quick read, but it does a 1:07:32.120 --> 1:07:36.080 really good job of teaching people that you can apply 1:07:36.240 --> 1:07:39.560 quantitative analytics and probably a theory to almost anything and 1:07:39.680 --> 1:07:42.600 to everything, to your life decisions, to everything. And I 1:07:42.680 --> 1:07:44.840 think it provides a nice paradigm in a world where 1:07:44.920 --> 1:07:47.760 today it feels like, because of the political environment, people 1:07:47.760 --> 1:07:49.560 are sort of it's black or it's white, it's zero 1:07:49.680 --> 1:07:52.080 or it's one, and it's never zero one, right, There's 1:07:52.120 --> 1:07:55.440 always some difference in between. So that's a book that 1:07:55.480 --> 1:07:57.280 I think is sort of required reading at Amherst to 1:07:57.320 --> 1:07:59.680 really understand the history of risk management, the history of 1:08:00.040 --> 1:08:03.080 ability theory, how it first turned into what are the 1:08:03.120 --> 1:08:06.160 big missed pricings have been? So it's not a super 1:08:06.200 --> 1:08:07.800 complicated read, but I think it does a really good 1:08:07.880 --> 1:08:10.880 job of taking people from thinking about the world as 1:08:10.920 --> 1:08:13.959 trying to predict a thing, instead of saying, wait a minute, 1:08:13.960 --> 1:08:16.360 there's a range of things. Can I be okay with 1:08:16.720 --> 1:08:19.120 a broadery of outcomes versus just betting on that one thing? 1:08:19.320 --> 1:08:22.160 And pretty much everything Peter Bernstein writes is great, awesome. 1:08:22.320 --> 1:08:23.760 The gold One's even good too. 1:08:24.640 --> 1:08:26.640 And our final question, what do you know about the 1:08:26.720 --> 1:08:29.439 world of real estate investing today? You wish you knew 1:08:29.600 --> 1:08:32.719 thirty so years ago when you were first getting started. 1:08:33.080 --> 1:08:37.120 Wow, that's fascinating. The ecosystem of real estate has been 1:08:37.160 --> 1:08:39.280 hard for me to follow, coming at it from the 1:08:39.520 --> 1:08:42.240 fixed income markets, so just understanding the various players of 1:08:42.280 --> 1:08:44.960 what they do and how they're motivated has been something 1:08:45.000 --> 1:08:46.679 I wish I would have just sat down and mapped 1:08:46.680 --> 1:08:50.479 out early on, because understanding how people are sort of 1:08:50.560 --> 1:08:54.240 economically rewarded really helps you predict their behavior. And I 1:08:54.360 --> 1:08:56.519 was kind of confused by that for a long time, 1:08:56.600 --> 1:08:58.320 trying to pick the thing that was the right answer 1:08:58.400 --> 1:09:00.880 instead of the thing that would benefited to most people. 1:09:00.920 --> 1:09:03.639 It's like in the financial crisis, we were we were 1:09:04.800 --> 1:09:09.840 short countrywide in scale hundreds of millions of dollars, and 1:09:10.880 --> 1:09:11.840 Bank of America. 1:09:11.560 --> 1:09:15.240 Bought them but for like next to nothing though right, well, 1:09:15.320 --> 1:09:16.080 but but. 1:09:16.160 --> 1:09:19.200 Yeah, but it was worth less than nothing, and so 1:09:19.479 --> 1:09:21.360 zero was a good was a good outcome for that thing. 1:09:21.840 --> 1:09:24.280 So at that point we realized that the consequence of 1:09:24.320 --> 1:09:27.920 countrywide failing was so great that the system was going 1:09:28.040 --> 1:09:31.479 to find an alternate outcome. So we switched to our 1:09:31.600 --> 1:09:33.439 thesis to that point to understand that the value an 1:09:33.439 --> 1:09:35.720 asset might have more to do with the consequences of 1:09:35.760 --> 1:09:39.080 that asset failing than the assets actually probably a failing. 1:09:39.520 --> 1:09:41.479 And that's something I wish I would have figured out before, 1:09:41.600 --> 1:09:42.000 because it. 1:09:42.080 --> 1:09:44.080 Was so you and I could go down this rabbit 1:09:44.160 --> 1:09:48.679 hole because we were short c T, we were short Leahman, 1:09:48.680 --> 1:09:55.000 and we were short AIG and AIG similarly too systemically important. 1:09:55.439 --> 1:09:58.240 It couldn't be allowed to crash and burn. But what 1:09:58.479 --> 1:10:03.160 was so fascinating was, Okay, how come Leman Brothers was 1:10:03.320 --> 1:10:08.120 left out to fall on its face, uniquely amongst the 1:10:08.280 --> 1:10:11.760 giant financial players. And I have a pet theory which 1:10:11.800 --> 1:10:16.800 I've never been able to validate anywhere. People forget, you know, 1:10:18.400 --> 1:10:21.880 Warren Buffett very famously made alone to Goldman. Sachs sure 1:10:22.040 --> 1:10:25.000 that at very advantageous price has got a nice piece 1:10:25.000 --> 1:10:28.680 of Goldman. Great bit of business for Berkshire Hathaway. What 1:10:28.840 --> 1:10:32.439 people forget is a few months earlier he had offered 1:10:32.439 --> 1:10:35.760 that deal to Dick Folds, and Dick Fold said, what 1:10:35.960 --> 1:10:37.960 is this so man trying to do? Steal the company? 1:10:38.400 --> 1:10:41.360 Tell him to go jump? And once you turned down 1:10:41.400 --> 1:10:44.760 Warren Buffett, how can the Treasury Department or the Fed? 1:10:45.080 --> 1:10:47.400 Yeah right, you know, all right, we're gonna bail you 1:10:47.439 --> 1:10:50.599 out of a couple hundred billion dollars. Chuse you had 1:10:50.640 --> 1:10:53.400 a chance to save yourself, but you waited for us. 1:10:54.040 --> 1:10:55.760 It's super complicated. We were a little bit on the 1:10:55.800 --> 1:10:57.960 outside looking in on that deal. We did price Leman, 1:10:58.040 --> 1:11:01.320 We priced more than Stanley for a lot of different investors. 1:11:01.360 --> 1:11:05.160 We priced bear Stearns. The magnitude of the losses was 1:11:05.240 --> 1:11:06.920 hard to get your head around, but it felt like 1:11:06.960 --> 1:11:08.960 the capital markets had it about right. So when bear 1:11:09.000 --> 1:11:12.920 Stearns was sold, their CDs was trading thirty five points 1:11:13.000 --> 1:11:16.000 up front for the senior unsecured piece. So it's meant 1:11:16.040 --> 1:11:18.400 that the bond portion of the capital structure had about 1:11:18.400 --> 1:11:21.080 a sixty five dollars recovery if you marked the market 1:11:21.120 --> 1:11:23.840 bear Stearns, that was about right. But the consequence of 1:11:23.920 --> 1:11:27.799 wiping out the equity, it had effects that we couldn't 1:11:27.840 --> 1:11:30.439 even years later I figured out what the effects were. 1:11:30.960 --> 1:11:33.280 But like the you know, it's kind of like the 1:11:33.400 --> 1:11:35.439 old anti hall, Like there's what they're saying, and then 1:11:35.439 --> 1:11:38.280 there's what's in the subtitles, like the macro of who 1:11:38.400 --> 1:11:40.639 owned the equity, who was going to get crammed down, 1:11:41.040 --> 1:11:42.840 who owned the fixed income? Who was going to end 1:11:42.920 --> 1:11:45.639 up with control? Like there was a much bigger That's 1:11:45.680 --> 1:11:47.000 what I'm trying to say about what to learn is 1:11:47.040 --> 1:11:50.000 that the first instance of what you see if something 1:11:50.120 --> 1:11:52.120 probably is a fraction of the story. 1:11:52.520 --> 1:11:56.439 Sure, and if you remember, oh, you have a weekend 1:11:56.760 --> 1:11:59.840 to figure this out. We expect a deal before markets open. 1:12:00.240 --> 1:12:02.719 These trillion dollar ballance sheet's a full of complex liquid 1:12:02.720 --> 1:12:05.640 assets and you have a weekend. So it was I 1:12:05.680 --> 1:12:07.960 think that's the thing is, it's probably never as obvious 1:12:07.960 --> 1:12:11.320 as it looks would be one advice, and to understand 1:12:11.360 --> 1:12:14.400 the whole ecosystem, not just one asset's you know sort 1:12:14.439 --> 1:12:15.200 of risk profile. 1:12:15.600 --> 1:12:18.120 Huh. Well, Sean, thank you for being so generous with 1:12:18.200 --> 1:12:22.200 your time. This has been absolutely fascinating. We have been 1:12:22.280 --> 1:12:26.320 speaking with Sean Dobson. He is the chairman, chief executive 1:12:26.360 --> 1:12:31.320 officer and chief investment officer at Amherst Group, managing about 1:12:31.360 --> 1:12:35.679 sixteen point eight billion dollars. If you enjoy this conversation, well, 1:12:36.000 --> 1:12:38.840 be sure and check out any of our previous five 1:12:39.000 --> 1:12:43.160 hundred or so. You can find those at iTunes, Spotify, YouTube, 1:12:43.280 --> 1:12:47.400 wherever you find your favorite podcasts. Check out my new 1:12:47.479 --> 1:12:52.799 podcast at the Money ten minutes of conversation about earning, spending, 1:12:52.880 --> 1:12:56.400 and investing your money with an expert. You can find 1:12:56.479 --> 1:12:59.120 that in the Master's and Business feed, or wherever you 1:12:59.240 --> 1:13:03.240 get your favorite Sign up for my daily reading list 1:13:03.280 --> 1:13:05.960 at rehelts dot com. Follow me on What's left of 1:13:06.080 --> 1:13:09.040 Twitter at rahelts dot com. Follow all of the Bloomberg 1:13:09.120 --> 1:13:13.559 Family of podcasts at Podcasts. I would be remiss if 1:13:13.600 --> 1:13:15.280 I did not thank the correct team that helps us 1:13:15.320 --> 1:13:18.760 put these conversations together each week. Kaylie Lapara is my 1:13:18.880 --> 1:13:21.920 audio engineer. A Tick of Albron is my project manager. 1:13:22.400 --> 1:13:26.120 Pariswold is my producer. Short Rousso is my head of research. 1:13:26.720 --> 1:13:30.640 I'm Barryhots. You've been listening to Masters of business on 1:13:30.800 --> 1:13:31.719 Bloomberg Radio