Not Another Investment Podcast

Unearthing Real Estate: Insights into Commercial Properties, Farmland, and Residential Assets (S1 E19)

Edward Finley Season 1 Episode 19

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Ever wondered how the monoliths of commercial buildings and the serene stretches of farmland fit into the economic puzzle? Join me, Edward Finley, as I pull back the curtain on the real estate sector’s impact on both the economy and personal wealth. We start by dissecting the intricacies of commercial real estate, diving into its diversity, location-specific risks, and investment returns with the aid of NCREIF data. While exploring the ins and outs of this market, I'll also unveil insights into why commercial real estate may just be the versatile inflation hedge your portfolio craves.

But our journey doesn't stop at city skylines. We venture into the fields of farmland and forests of timberland, examining their investment allure and uncovering the complexities of these assets. From addressing farmland's surprising performance metrics to timberland's role in the productive economy, we tackle the convolutions of classification and investment potential.

Later, we pivot to residential real estate, analyzing the S&P's Case-Schiller National Home Price Index and thinking about your home as a part of your investment portfolio. Whether you're a seasoned investor or real estate rookie, this episode promises to equip you with valuable knowledge to navigate the vast terrain of real assets.

Episode Notes:  https://1drv.ms/p/s!AqjfuX3WVgp8untrU1lj57PT-_dy

Thanks for listening! Please be sure to review the podcast or send your comments to me by email at info@not-another-investment-podcast.com. And tell your friends!

Speaker 1:

Hi, I'm Edward Finley, a Sum-Time Professor at the University of Virginia and a Veteran Wall Street Investor, and you're listening to Not Another Investment podcast. Here we explore topics and markets and investing that every educated person should understand to be a good citizen. Welcome to the podcast. I'm Edward Finley.

Speaker 1:

Well, we take up this episode, our second installment on real assets, and, as you might have guessed, today we're going to talk about real estate. So it seems sort of fitting that this is in the real assets category. Real estate, I think you can break down into really three primary categories. You'll recall that in my lexicon from earlier, I describe the real estate part of real assets as really being those that produce the commodities that are thought of as the inputs to the economy. So here we're talking primarily about commercial real estate, we're talking about farmland and we're talking about timberland. I'm also going to spend a little bit of time talking about residential real estate, partly because it's increasingly becoming an interesting asset class among investors, but also partly because it's such a large part of the average American's total net worth that I felt like it's useful to consider how to think about it as an investment, why we have it, is it an investment at all? And how should we think about the role it plays in our portfolios? So let's dive right in. Let's talk about commercial real estate. So commercial real estate, you know here think there's a wide, wide variety of things that are commercial real estate. There are apartments, there are hotels, there are office buildings, there are places where, increasingly, internet companies have logistical support as they ship goods around the country and get them to end consumers. There are doctors' offices, there are communities where people with disabilities can live, there are old age communities.

Speaker 1:

Commercial real estate is a really big category, very diverse, but despite its diversity, the asset itself has, as we've discussed before, extraordinary idiosyncratic risk because of the strong dependence on location for returns, and that dependence on location is non-diversifiable. So, for example, if you think about a logistics center that's positioned at the intersection of two main freeways, that's going to have an extraordinarily high value relative to exactly the same structure, with all the same technology, in the same region, but just not easily accessible by those two highways, and just that alone is going to be sufficient to make one property worth a lot more than the other and indeed to grow at a different rate than the other. So highly idiosyncratic risk and we're going to be looking at data when we talk about this idiosyncratic risk. We're going to be looking at data from something called NECRIF, which is the National Council on Real Estate Investments, and NECRIF is an index of directly owned commercial real estate, so it's not an index of funds, it's survey-based data, so that means there are some glitchy things about it, it isn't perfect and it's also not investable, because, of course, it's all the reported real estate all across the country and it would simply be impossible for any investor at all to own a diversified mix of those locations. And then the third reason is because the NECRIF index reports its values on a non-levered basis, but we know, as a matter of course, that investors in commercial real estate always use leverage.

Speaker 1:

It's very, very unusual to find a commercial real estate asset that is not levered, and so, as a consequence, what we would expect to see in this data is data are returns that aren't really going to reflect the returns of an actual investor, because they're not going to be levered and because it's survey data that's provided quarterly, with lag of about a quarter, and there's no market comparables. These are really just estimates of the owners of what their asset is worth. Is that? It sounds a whole lot like the problem we confronted in private equity, which is to say that the data itself is so lagged and so unable to be compared to market variables. It's not transactions. That means that we would expect the volatility in this data to be really artificially depressed by virtue of smoothing, though, since we know that leverage is going to be used in these assets, I suppose we might imagine in some respect that the volatility will then be adjusted by the leverage. That is, if we computed it with leverage, we might actually get a volatility. That's a little bit more realistic.

Speaker 1:

So what does the data tell us about this asset? Is it a real asset and to remind you, from our last episode, we said that a real asset we would expect to have positive correlation to inflation. That is, you want to own it when inflation expectations are dominating markets, because during those periods, equities and bonds will both move in the same direction, ie down, and so you want an asset that's going to be somehow insulated from that, and we would expect a positive correlation to inflation to tell us that that's what the asset's doing. And second, we would expect this asset to be roughly independent of stock and bond returns, for a very similar reason. That is just generally, we want to know that this is an asset that is diversifying the holdings, the risks that we currently have in our portfolio and, last but not least, is we would want to make sure that the asset can be expected to earn positive real returns. So we'll want to think about each of these in that way and we'll think about commercial real estate in that way. So, with all of my caveats.

Speaker 1:

So, looking at the data from 1997 to 2023, a commercial real estate in the US had very modest correlation to equity returns about 7% despite the fact that the asset is really exposure to the productive economy. This is the thing in which the efforts of the productive economy take place. You would expect there to be maybe more correlation there, but despite that, it's not the case. It's very modest correlation and likewise very modest correlation to interest rate risk about 7.6%. So we've got a good independence from equity and bond returns, and our correlation to inflation is 33%. Well, it's not huge, but it's really rather material, and so so far so good. This asset is really shaping up to be a kind of classic real asset Returns for over that period were on par with equity returns. Equity returns were about 9.2% and commercial real estate during that period earned 8.5%. But due to smoothing the volatility, here is only 7.7%, delivering a whopping information ratio of 1.11%. But, as we said, we can pretty much just discount that entirely and not pay too much attention to it. We might also remind ourselves that, because we would expect this asset to be levered, the 8.5% returns will actually be higher.

Speaker 1:

Even once we net out the interest expense of the debt, we see an extraordinarily high degree of illiquidity, with an auto correlation of 85%. This should surprise none of us. Commercial real estate, by its nature, is going to be highly illiquid, and that is largely due to their size of any particular asset, but also it's going to be a function of the fact that these assets are so idiosyncratic that you really might find yourself without a buyer. And that's not because the asset's not great, it's just there isn't a buyer for that very unique, very specific asset, and so we see a high degree of illiquidity, which causes us to then question well, do we really think we're earning any compensation for illiquidity? This has come up a few times in the podcast, most notably when we talked about private equity, and at the time I told you that there's very little evidence that we actually earn compensation for illiquidity. It is part of finance theory that we should. It is a risk for which we should be compensated, but it's not clear that we do, and this is another example of that. If the unlevered returns are in the same neighborhood as equity returns, then it seems to me that there's not much to say that we earned any compensation here for the illiquidity of the asset.

Speaker 1:

Like hedge funds, where we just spent a lot of time, we see that there's really only non-normal risks in this asset. The SKU is very large negative SKU and the kurtosis is a very large positive kurtosis, negative SKU of negative 2, and kurtosis of 5.7, both of which suggests that volatility understates the risk. So now volatility is sort of challenged on two fronts. It understates the risk because of smoothing. It also understates the risk because owning the asset in the real world is going to be levered, which will make it more volatile, and it understates volatility, understates the risk because of negative SKU and very large tail risk.

Speaker 1:

We can look at state-dependent returns, though, and see that, unlike hedge funds, we have very little evidence of any nonlinear risk of, say, concavity or convexity, which is what we talked about a lot in the hedge funds section. Here, when we look at the state-dependent returns of commercial real estate against US equities, we see that there's pretty much no relationship, no concavity, no convexity. It earned 1.5% in the worst months of equity returns and it earned 2.1% in the best months of equity returns, and it was always about 2% to 3% per month in each of the other sections. And then, likewise, we see the same with interest rate risk. When we look at the worst months of returns of the 10-year treasury, commercial real estate earned 1.5% a month. And when we look at the best returns for the 10-year treasury, it earned 2.3%. And again, throughout the quintiles, it's all pretty much the same. So no real evidence for convexity. That's not a risk that we think we're getting paid for when we own commercial real estate.

Speaker 1:

What's the upshot? Well, I think the upshot is that it seems like commercial real estate is a relatively good real asset. It seems like it's the kind of thing that would do the job that we want it to do. It will have some meaningful positive correlation to inflation. It'll be roughly independent from stock and bond returns. It'll earn, we think, positive real returns over the long run.

Speaker 1:

The problem with it is that it's just very difficult to get a sufficiently diversified portfolio of real estate. Now, I should mention that there are things out there called REITs real estate investment trusts and these are securities that really are issued by an entity that owns a lot of commercial real estate, and those securities trade usually over the counter, but sometimes on large public exchanges. The thing about REITs, though, is that when you look at the data on REITs, it stops behaving like real estate and it starts behaving like equities. So the inflation correlation goes away, the low correlation to US equities goes away, and the auto correlation goes away. So what you find is that suddenly, it trades like US equities, but it earns a little less than US equities, and so, when we think about using REITs to own commercial real estate, we don't get the benefits of the commercial real estate.

Speaker 1:

We're really owning a kind of equity risk, and that's why investors who invest in this asset class typically do it through private funds, so funds that would look a lot like a private equity fund, in that it's a limited partnership. There's a general partner who's the expert investor, there are limited partners who are the investors, and not all of the investment is called in the first moment. It's called periodically, and over the life of the fund, the manager, as they sell properties, then distributes capital back to the limited partners. So it has a lot of the same look, touch and feel as private equity funds, but with a slightly different purpose. And the reason that investors choose that avenue is, frankly, because if there's so much idiosyncratic risk in commercial real estate and we otherwise like the other risks and we want to own it and we want to own it with leverage then there's probably some reward for really skilled managers who know how to pick properties, and that means that those returns will be even higher than our index returns, which don't impute any skill. So, altogether an interesting real asset, somewhat tricky to access if you're just a retail investor, but if you're not a retail investor, then it is not only accessible but rather interesting.

Speaker 1:

Okay, let's turn our attention then to farmland. So what are we talking about when we talk about farmland? It might seem obvious, but, just for the avoidance of all doubt, these are assets on which farmers grow the soft agricultural inputs to our economy. They grow wheat, they grow corn, they grow soy and the like sugar. As you might imagine, like commercial real estate, farmland is going to be subject to very high idiosyncratic risks because the returns on farmland, the value of farmland, is strongly dependent on its location. It's strongly dependent on its location because of weather. If you've got farms in Indiana, they're going to have very different weather than farms in Iowa and therefore that makes each of those assets highly idiosyncratic, with risks that are hard to diversify. We also know that pests are going to affect crops in different places, so how much crop is affected by some particular pest in Iowa may be very different if that pest is not in Indiana. But the crop yields are themselves going to be different because a farm in one place with a certain kind of soil and a certain kind of weather condition might be much more productive in making that commodity let's say it's corn than a farm in another place with a different type of soil and different type of weather patterns, et cetera. So, all to say, highly idiosyncratic.

Speaker 1:

Like with commercial real estate, we're using a neck-reef index for farmland, which is unrealistic because with so much idiosyncratic risk, an index, while interesting to think about the asset class, is really hard to think about as an investor because you can't own all the farms all across America, which is what the index reports to us, like we saw with commercial real estate, we know that the volatility here is going to be artificially depressed because of the nature of the index. The index again has quarterly data reported on a lag no market comparables. These are just the best estimates of farmers about the value of their farm. So we would expect volatility to be depressed. But, unlike commercial real estate, it's unlikely that there's going to be much leverage. When you own farms in a portfolio. The index is like commercial real estate unlevered, but real investors tend not to use leverage or, if they do, not, nearly as much leverage as they would in commercial real estate.

Speaker 1:

And so let's take a look at what the summary statistics tell us. First, we see that there is a moderate let's call it correlation to equity risk about 11%. Moderate correlation to interest rate risk about 18%, and so that's not strong. And so we'd say, independent of those returns to be a good real asset. But I don't know, it's pretty low, I'm not going to hang it out to dry just for that reason. But we see that there's a strong negative correlation to inflation. It's negative 18%, and that is definitionally going to make farmland not a real asset, because if it is anything at all, it has to be at least independent of inflation, if not positively correlated. In here we see negative correlation to inflation, which suggests why would that be true? It suggests something that should be pretty obvious to us, which is that farmers are likely to suffer just as other firms do when there's inflation in the economy, because they can't pass on all of their higher costs. That affects their profit, and if their profit is reduced the value of their farm is going to be less. And so this negative 18% correlation to inflation makes sense when we think about this asset and it certainly counts against it when thinking about it as a real asset.

Speaker 1:

The returns for this asset over the period 1997 to 2023 were sort of more robust than equity returns. It was a 10.9% return per year on average, versus equities 9.2%. So that's much more robust and we see that there's little evidence of any illiquidity. The auto correlation here is just 4%, and that suggests to us that there's a ready market for buying and selling farms, that there's not a whole lot of illiquidity here and that prices of farms adjust rather quickly to changes in circumstances. So auto correlation is super low. Not a lot of evidence of non-normality in that case, but we do see non-normality in SKU and kurtosis. The SKU is almost 4%, positive 4 in the kurtosis is 18%. So this is massive tail risks and very positively SKU, suggesting again that volatility is going to be a very poor estimate of the risk of owning this asset.

Speaker 1:

We can also take a look at the state dependent returns here and what we see is that there's very little evidence of convexity. We can look at the state dependent returns against US equities. In the worst months of US equity returns, the strategy earned 2%. In the best months of US equity returns, the strategy earned 3.48% and then in between it ranged up. There's some linear connection here. You can see that it increases as equities do better, so does the strategy, but linearly it doesn't seem to have much in the way of nonlinear relationship. The same could be said for its relationship to 10-year treasury returns. In the worst months it was 2.55%, in the best months it was 2.2% and, with an exception for the middle quintile, the returns per month ranged from about 1.8 to 2.8. So it pretty much showed very little evidence of a relationship to the 10-year, let alone any nonlinear relationship.

Speaker 1:

So, on balance, what do we think about farmland as a real asset? And I think the answer is it's not. It's just not a real asset, as we saw in the last episode. Neither are the commodities that the farms produce. There's very little evidence to suggest that those commodities bear a positive relationship with inflation, and so I think the notion that farmland is a real asset is kind of a mistaken notion. Now, it might be the case that you want to own farmland even though it's not a real asset. Why? Well, because it has very low correlation to equity and bond returns. So that's great. And because over this long period of time it earned returns far in excess of the returns that you could have earned for equity risk in that period, and so that might suggest it's a might be a very interesting thing to own, but it's not going to be because it's a real asset. It's going to be simply on the basis of the kind of profile that farmland represents.

Speaker 1:

Okay, next let's turn our attention to timberland. So timberland, just to set the record straight, here are our commercial farms in which the farmer grows trees, that's all it's. So it's like a farm of any other kind, except that they grow trees. Typically, the division in timberland is between hardwoods and softwoods. Hardwoods are the kinds of things that are used to make furniture and they those trees tend to grow in the northeast of the United States there are some exceptions, for example in the Pacific Northwest. And then softwoods are the sorts of things that are used in building materials are used to produce paper, cardboard, which in a modern e-commerce economy becomes increasingly more important, and those tend to grow in the southeast of the United States and also in the Pacific Northwest. So farmland is again another way in which we see a place where an input to the productive economy gets produced. So the input is going to be lumber, and lumber gets produced in a timberland farm.

Speaker 1:

These farms are going to be highly idiosyncratic in terms of their risk. Not surprisingly, this is going to be a theme for the real estate assets Highly idiosyncratic. Why? Because there's a the returns on the asset. There's going to be a very strong dependence on the location of the asset for returns. So weather is not going to be the same in the northeast of the United States, as the southeast, as the Pacific Northwest, and so if you own a timberland only in the northeast, weather in the northeast is going to have a significant impact on your returns, but may not have an impact on the returns in other regions, pests likewise, and in the category of pests I would also put things like wildfire.

Speaker 1:

These are sort of risks that are not going to be systematic, that you're not going to find anywhere. They're going to be highly idiosyncratic and it's it's yield is not really diversifiable. It's really very difficult to own all of the different kinds of timberland that are out there. Again, we're going to be using a neck grief index for timberland and we're going to think in terms of it as an entire asset class, but I want to just remind us that the timberland index is pretending like we can own timberland everywhere and take away these idiosyncratic risks. We can't. They're going to be very much present, but we have to. We have to at least think about whether they're something that we see in the numbers or not in there, and they're not.

Speaker 1:

Unlike farmland, though, timberland doesn't need to harvest its crop every year and, if you think about it, that creates a rather interesting dynamic. So in the case of farmland, we said that the prices of farmland are going to be highly dependent on the economic cycle, because if you produce corn, if you do produce sugar, et cetera, these are inputs to the productive economy, and the better the economy is doing, the higher the price you can get for your crop, and the higher the price you can get for your crop, the more valuable your farm is. All of which makes sense. But in reverse it's also pretty terrible, because if the economy is in the daldrums and you have wheat and corn and so on, then the price that you're going to get for your commodity is going to be rather low, and that means the value of your farm is going to be rather low.

Speaker 1:

But when we talk about timberland, in the case of timberland, we see that the tree doesn't have to get harvested every year, like corn or wheat or soy or any of the other soft agricultural commodities. You can just let the tree grow another year. Moreover, it will grow every year. It's not like other sorts of growth in the economy that we think of. It's growth in nature, and so not only do you not have to harvest each year, but you know with a certainty that the value of your asset will grow over the course of one year, because the trees will all grow over the course of a year. And so there is a lot about Timberland that makes it rather interesting, and so we want to think very carefully about what the profile then of that looks like in our usual frame.

Speaker 1:

Well, first, volatility, as I said, is going to be something that's going to be highly suspect, primarily because of the index that we're using to understand the data. The index is also providing its data quarterly, and that quarterly data is on a lag and it's not market comparables. It's merely what the owner expects the price or the value of the asset to be, and so that's going to smooth returns, and because we're smoothing returns, it makes volatility lower and that makes the information ratio unreliable. But let's talk about what it is. So the average annual return here on Timberland was about 7% 6.8% over the period that we looked at, with volatility of 5.8. Again, that volatility is highly depressed. It gives us therefore an unrealistic information ratio of 1.2.

Speaker 1:

We see that the returns are roughly independent from equity returns. There's a 3% correlation there, only modestly correlated to bond returns, and 8% correlation there. But what we see that's the most damning is that the correlation to inflation is basically zero. It comes in as negative 0.96%, but it's basically independent of inflation. And so, while the returns were lower than equity returns 6.8% as opposed to equity returns of about 9.2% a year during the period it's still positive real returns but on balance it doesn't sound terribly much like a real asset. It doesn't sound like a real asset because it has no positive correlation with inflation but it otherwise fits the bill. That may make it a good asset to own, but it might not be a good asset to own because of its quote real and quote nature.

Speaker 1:

We see that Timberland has the same non-normality that we saw in commercial real estate. So there is a positive skew of about 1.2. So it's significantly positively skewed. And the kurtosis is also quite large at 5, which is of course around the same as commercial real estate, not terribly massive, but it's not nearly as high as in farmland. We also see that illiquidity is present here with an auto correlation of about 24%. That's a lot less auto correlated than commercial real estate but a lot more correlated than, say, equities or farmland. So there's some evidence of illiquidity and it begs the question whether investors are really getting paid any compensation for that illiquidity.

Speaker 1:

Turning our attention to the state dependent returns, we see again that there's very little evidence of non-linearity. In the worst monthly returns for US equities, the strategy earned 1.5%. In the best monthly returns it earned 1.5% and in between it ranged from 1.2 to 2.2. So pretty much not really showing any convexity in a relationship to equity returns. Nor is it showing any convexity in its relationship to the tenure treasury. If anything, it's showing a sort of a linear relationship with rates. So in the worst month for returns on interest rates, the strategy earned 1.5% a month and in the best months of interest rates the strategy earned 2.2% a month. And it's not perfectly linear, but you can see the sort of upward trend. And so, if anything, that correlation with tenure of 8% doesn't tell us the whole story. Yes, it's not terribly correlated, but it seems to reflect a sensitivity to interest rate risk.

Speaker 1:

So, again, it doesn't seem like it's a particularly good real asset. It's not positively correlated to inflation, but one might want to own it given its low correlation to equities and interest rates. One might want to own it because of this feature of growth that will occur regardless of growth in the economy. And one might want to own it because it is some kind of asset that seems probably able to support most goals, its nominal returns being around 7%. It's not as high as equities but it's not really low like some of the hedge fund strategies we saw that were good diversifiers but didn't earn robust real returns. So it could be an interesting asset to own, but not a real asset.

Speaker 1:

All right, let's wrap up the episode, then, by talking about residential real estate. As I mentioned, it is the case that, increasingly, there are investors interested in investing in residential real estate, but, by and large, residential real estate is not an asset class for investors. However, it is probably the biggest asset on the average American's balance sheet, and so, as a result, I think it's worth thinking about residential real estate because, for the average investor and, I think, probably the average listener to this podcast, if you're talking about your portfolio and what should you buy and what should you own and that sort of thing, don't ignore the asset that you live in. And so, if you own your home, that's going to be a pretty big deal and you're going to want to make sure you think about it in the context of your portfolio. So let's take a look.

Speaker 1:

We have some data here that's courtesy of the S&P. That's the same company standard and pours that provides the index for the 500 largest stocks and is one of the providers we mentioned when we discussed bonds, of credit ratings. On bonds, s&p also runs something called the Case Shiller National Home Price Index Case Shiller named for the two academics who developed the idea of maintaining a database on the prices of homes in the US. The database is, like all of the others that we looked at, unlevered, and so we're going to want to account for that in a minute. So, at least initially, I'm going to talk about it unlevered, but then we'll pivot and we'll think a little bit more carefully about it as a levered asset because, like commercial real estate, the average American owns their home with a mortgage, so we'll want to take that into consideration.

Speaker 1:

So let's do the same analysis as always how is this characterized as a real asset? Is it a real asset and do we want to own it regardless? Inflation, with inflation is 22%. That seems like a real asset to me. That seems like something you would own, so that in the times when inflation expectations dominate asset prices and your stocks and your bonds are going down, this asset is not necessarily going to be going down. So positive correlation to inflation. But in the short term, we know that residential real estate is much more affected by economic growth, by interest rates and by demographics. I mean, the value of homes is going to be so much more dependent on those things than on inflation. I don't want to overstate the idea that a positive correlation to inflation is going to be the be all and end all. But I think it's worth noting here that in the aggregate it exists, and in a minute we're going to look at the data, sort of tweaked for a specific reason, and we'll see that correlation to inflation go away.

Speaker 1:

So, yes, you might think of it as a real asset. The data suggests that it might be bought in general over shorter time horizons. Economic growth, interest rates and demography are far more important to the returns to this asset than inflation is. There's very modest correlation to US equities about 7%, and very modest inverse correlation to the tenure negative 8%. So roughly independent to stock and bond returns.

Speaker 1:

As we've discussed, it's a much more normal distribution. So there's no skew, it's symmetric like a bell curve and the kurtosis is 0.76, which, while in theory, is not a normal distribution, only a zero would be a normal distribution. 0.76, compared to equity markets where the kurtosis is normally around 2, suggests that this is a lot more normally distributed than equity returns. So there's really very little evidence that there's much non-normality risk that you get paid for here. But the auto correlation is 90% and that suggests that what you really own is a highly, highly illiquid asset and, as anybody can tell you who has owned a home and tries to sell it when they need to sell it, that is usually a really, really bad situation Because the kind of asset is so highly idiosyncratic. There's no way to diversify that risk and if you happen to be needing to sell in a market where there are limited numbers of buyers, that is going to significantly affect the value of your home. So, yes, a normal distribution, but beware, highly, highly illiquid asset.

Speaker 1:

It earned lower returns than equities. Over the period. It earned a little shy of 5% a year compared to equities 9.2%, so about half. Nevertheless, there are positive real returns here and so I think, on balance, positive correlation to inflation, independence from stock and bond returns, positive real returns.

Speaker 1:

Okay, it's probably a real asset with some of the caveats that I mentioned, but let's take into consideration now, as we didn't do before, because I want to make this example kind of real for the average homeowner is let's take a look at what returns were like during this period if the asset were levered. So if you assume that you put 25% down and you borrow 75% of the asset, that's equivalent to leverage of about 4x. If I recompute returns and volatility, taking into account leverage, then what I get is a return of a little shy of 21% per year with volatility of about 18% per year, so that the information ratio doesn't change terribly much. But, like in the unlevered case, there's very little to suggest here that volatility is going to be distorted by non-normal or nonlinear risks, and so in that case, with a 21% return, that's clearly a lot higher than equity risk. But you really won't earn the 21% because you're going to have to pay some interest on your mortgage. So if we adjust that, on average, during that period mortgage rates were about 5.25%, and so let's just adjust then for the leverage. When we adjust for the leverage, then the average annual return is a little more like 17%.

Speaker 1:

In addition, we want to take into consideration the fact that the average American lives inside their home, and so that means that they get something. There's some return for owning the home that's not captured by changes in price. Some people call that rental yield. It would be the amount that you could earn if you rented the asset, but instead you live in it, and that has some value to you, and so it's an important part of the returns. We should take it into consideration, but in general, they're excluded from the data. One economist estimates that the rental yields from 1960 to 2008 in the United States were about 5% a year, and so what we might imagine is that that pretty much offsets whatever the interest expense is on the mortgage. If the rental yields about 5%, the average interest rate was about 5%. Maybe they cancel each other out and you're left with at the same sort of maybe the same place.

Speaker 1:

In addition, we want to make sure that we take into consideration that, unlike a lot of other assets, you have to maintain your house. You got to make capital repairs, and that is an investment in the asset. Most estimates of maintenance and capital expenses are about 5% a year as well. So if I adjust then for the rental yield and I adjust for maintenance and capital expenses, then I come up with a net return of around 11%, and 11%, as we mentioned a little while ago, is about 2% a year higher than equity returns. And you get to live in your house, and so I would say not just a real asset, but a really good asset, and you can see why so many Americans who can afford to do it want to own their home. Because if you have limited resources and you have to live somewhere, owning your home is necessarily going to be a very, very prudent thing to do in your wealth accumulation and wealth accretion.

Speaker 1:

As a little bit of a thought experiment, though, I wanted to sort of tease out of the data. The housing bubble, which most people agree, runs from January 2004 until August 2006, when US home prices kind of went nutty and they came crashing down, and that, you'll remember from earlier episodes, is one of the major impetus for the global financial crisis. It's the uniform reduction in the value of houses everywhere in the US all at once. So what if we took out of the case-shiller data the returns during those months? We take out the bubble, the run-up, and we take out the crash in the returns, what do we end up with? It's not terribly different. So the annual returns then are 4.3% as opposed to 4.99, unleveored.

Speaker 1:

The volatility remains around the same, sq and kurtosis remain the same, auto-correlation remains the same. Correlation to equities, correlation to bonds remains the same. What changes is correlation to inflation? And it drops from 22% to 7%. And there's the point that I made just a little while ago when I said that things like economic growth, interest rates and demographics are far more important to this asset than inflation. When you take out that period of the housing bubble, you find then suddenly the correlation to inflation really drops radically, and then we can do the same exercise by levering it 25% down.

Speaker 1:

I won't recite all of the information, but just to say it's roughly the same, and so the reason I did that is because I think, when thinking about residential real estate and I'm using these aggregate numbers and it's just an index, and maybe you know somebody who didn't have that experience it's easy to sort of say well, you had the housing bubble and that changed everything. It skews the numbers and whatnot, but when you remove the housing bubble, it doesn't change the numbers by terribly much. Well, that's it for real assets. As we wrap up our discussion of real estate, next time we're going to come back and not talk about asset classes but instead talk about what we do with them. So we're going to start talking about portfolio construction and understand the notion of strategic asset allocation. As always, thanks for listening. Look forward to talking to you next time.

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