What's in a Real Estate Private Equity Case Study?

What's in a Real Estate Private Equity Case Study?

welcome to another tutorial video this time around we're going to go through what to expect in real estate private equity case studies and I'm going to begin by giving you an overview of what they are and what they typically consist of then we'll move into an actual example from our real estate modeling course and you'll be able to take a look at the documents from that by following the link below if you're looking at this on youtube just go to the link there to mergers and acquisitions if you're watching this on mergers and acquisitions then you'll find all the documents and PDFs and other links directly on the page so let's start by talking about at a high level what exactly you do in real estate private equity the real purpose is just like with normal private equity firms and leveraged buyouts we use debt and equity to acquire a company grow it over time and then sell it you're doing the same thing here you're using debt and equity to acquire a property rather than a company you hopefully grow and improve it over time and then sell it and the reason why you're using both debt and equity of course is because by using some debt you will magnify your returns so if you do well you'll do even better if you use leverage because it means that you're contributing less of your own money upfront so the housing analogy that is often used to describe LBOs where you buy a house using a mortgage and a down payment which is just like debt and equity and a leveraged buyout also applies here but the difference is that this time we really might be buying a house or multiple houses or a whole apartment complex or something like that the real difference with real estate private equity and the case studies that they could give you is that the modeling itself could be much simpler than what you see for normal companies or it might even be more complex depending on the type of case study and the type of property that you're dealing with so in this tutorial we're going to cover five main points first off I'm going to tell you a little bit about the types of different real estate private equity case studies then I'll go through the case study that we're looking at here for a stabilized multi-family property I'll also cover what makes it tricky and how it's also designed in part to trick you and then in part three I will show you how to challenge some of the numbers we've been given with scenarios and how to come up with your own scenarios for use in the model then in part four we will look at the property model itself I'm not going to go through every last detail because we have a limited amount of time here but I will touch on the main points and then in part five we'll take a look at the investment recommendation and look at how you might decide whether to invest or not invest in a property like this so let's start with part one first the different types of real estate private equity case studies in general there are three different types of real estate private equity case studies you get and you see a graph here I just pulled this from another source online but this graph gives a pretty good idea of what those categories are at the bottom in terms of potential returns and also risk you have the core and core plus categories basically this means that the property is not going to change much over time it's already stabilized it already has a pretty high occupancy rate and you're going to acquire it but the chances of getting an outsize return are very small because the property is already doing pretty well it's probably already priced about appropriately and so you're really looking at a lower level of risk and a lower level of potential returns that when you go up you get to the value added category and in this category the risk is higher and the potential returns are also higher because you're not just leaving the property alone you're going to modify it by renovating it by attempting to improve the occupancy rate by getting higher rents from tenants by doing something like that to make the property better so much of the returns here will actually come from the cap rate declining and the property itself becoming more valuable by the end of the holding period and then all the way up the top you have opportunistic this is the riskiest category and also the one with the highest potential for returns this category includes properties where you're doing more than just renovating it or trying to improve the rents or the number of tenants you might be developing a brand new property you might be taking a distressed property that is completely performing and is on the verge of failure and turning it around you might be doing a redevelopment where you take a property you tear it down and build something new you might be tearing out 75% of an existing property and then building something new in its place so you are doing something dramatic here where the risk and potential returns are both much higher now in terms of specific numbers there are a couple ways you can think about this I pasted it in a chart here I found elsewhere but you can see that as I was saying before as you go from core to value add it to opportunistic these different strategies all correspond to different types of case studies you can get and the risk gets higher the targeted return or potential returns get higher the source of earnings changes as you move up to the opportunistic category a lot more of the return is going to come from the property itself becoming more valuable the holding period is also somewhat different in these they're also saying the financial leverage may be different this one is probably less true in my experience from what I've seen but you could also have something like this and then of course the building type going along with what I just mentioned is going to be different as well so those are the different types of case studies as you can imagine when you're dealing with Core case studies the modeling is fairly simple because the property isn't changing much so a lot of what goes into this is market based you're going to have to do a good analysis of the market figure out what is going to change over time what the different outcomes and scenarios might be and incorporate a lot of market data into your analysis now as you move up the case studies tend to become more modeling oriented and the market data still matters of course but here what really matters is how you're going to change the property and what the new financial profile of the property will look like after you're done now on the issue of modeling complexity one other thing I want to mention is that in addition to the extent to which the property is changing it also matters how granular the case study is and to give you an example of this in the case study that we're looking at here it's fairly high level because we don't really look at individual tenants we sort of combine everything together and we just look at the overall rental income growth we know what the total number of apartment units in our building is and we know the average square feet per unit so we have those very high-level variables and as a result this is not a very granular model at all by contrast if you're looking at something like an office complex where each of the tenants has a different start date for their lease a different end date a different rent other terms like that and you only have say 10 to 15 tenants the modeling is going to get more complicated because you're gonna have to track all the tenants individually and come up with some very long and complicated looking Excel formulas so this is what you really have to watch out for yes the changes to the property matter but it also matters how granular it is so the easiest case here is if you have a stabilized property with hundreds of tenants and it's not changing at all over time the hardest case is if you have say an office or retail complex with ten tenants they all have different lease terms they're all major tenants major contributors to revenue and the property itself is changing significantly over time so those are the two extremes and many of the case studies that you get will be somewhere in the middle of these extremes let's turn our attention to this case study I have here the PDF document for it and you can read through it yourself but essentially what is going on here if go through and look at this is that this is a stabilized multi-family property in the Seattle area which is in the northwestern part of the US we're given a mix of the different units at the property in terms of studios one bedrooms two bedrooms and other variations like that we're given comparable properties comparable apartment sales and then a lot of statistics and market data on this market overall so there's a lot of data here but as you'll see there are really only a few key charts that make the biggest difference in this case the basic question we have to answer is if there's an asking price of 120 million for this property should we acquire it for that price or should we not acquire it for that price and we're not given the strict conditions all the way up at the top here but if you scroll down and you move toward the and toward pages 14 through 16 or 17 they tell us right here that we're targeting a 10% levered return so essentially we're targeting 10% internal rate of return on this property over a 10-year holding period and we want to see whether or not it's viable to do this given those conditions and then we also have some other terms the case study document says it's going to be a 70 percent loan to value ratio three percent growth for income and expenses and then they give us some other figures for the capital costs such as capital expenditures tenant improvements and leasing commissions so what's tricky about this case is the following if you go in and look at the document I give you a break out of all the individual units here and you might look at this and say okay well he's giving us this breakout so obviously we should model each of these separately and then see what happens over time the problem is that there are 234 different units here so there are hundreds of tenants in this property and so it's not really a good use of time to actually break it out in that level of detail especially given the fact that many of these are actually pretty close in terms of square feet the total size of each unit in this property so many people would approach it incorrectly and they would start with that and say okay let's make a really granular model and look at all these different units separately but the truth is it doesn't really make a difference you could do that but you're going to waste a huge amount of time and remember this is a stabilized multi-family property with hundreds of tenants so this is the type of case where you're not going to go into a lot of granular detail because each tenant contributes a relatively small percentage of the total rental income so we would say that you should simplify which we've done very much in our model here as you'll see and then spend your time thinking about the different scenarios what's going to happen to rent to the vacancy rate to the cap rates and then think about how you might reflect that in the different scenarios so let's go into the next part of this case study now and think about how you might come up with different scenarios to represent this the key point that you have to realize here is that when you see a graph like the one on screen it's very clear that this market like all real estate markets is cyclical the vacancy rate rises to a high of around 9% in 2002 it falls and then it rises back in 2009 up to about 7% and then it's fallen again recently down to around 4% but look at this it's already rising in the most recent period as of the time of this case study so maybe it'll go up to 9% maybe it won't maybe talk up to 7% we don't really know but the point is it seems very likely given that this market has lasted for about five years now that there's probably going to be some downturn at some point maybe it won't be as bad as one of these but it seems very plausible that at some point in the future rents are going to fall as they have historically the vacancy rate is going to rise and then there will be a recovery and I'll move back to a stabilized state so that's the main point a lot of people would get this wrong and completely miss the fact that there are market cycles in this case study and in the model we're going to build so we would say that there are three possible scenarios to look at the first one is if we just take their numbers at face value once again if you go to the end of the key study document here you'll see that they do provide these numbers for the number of units the average rent other income the growth rates for these probably the most important part and then they give us some data for the capex tenant improvement and leasing Commission growth rates as well as well as what these are an $8 per unit per year basis now they're giving us these instructions in the case study document so they want us to use them so we will use them and in the first scenario in this model it's pretty much what we're doing what I call steady growth everything grows at a stage rate over this ten-year holding period and we simply use all the growth rates that have been provided to us the vacancy and collection loss percentage stays about the same actually stays exactly the same at five percent now scenario number two we're going to have a immediate market decline a recovery and then stabilization so rent and expenses will decline tenant improvements and leasing commission will rise because you need to pay more to attract tenants you need to pay the tenants more and then you also need to pay the real estate agents more in the form of leasing commissions to get those tenants so down here you can see that reflected in scenario number two the decline in recovery our tenant improvements rise by a good clip due to our leasing commissions as our rent and expenses here fall our vacancy rate also goes up but then when we get over to our recovery period those trends start to reverse and we start seeing a decline in the tenant improvements and leasing commissions and then rent eventually reverses and it starts rising again through the end of the stabilization period so we get a decline it gets tougher to find tenants because of a soft market but then we get a recovery and it stabilizes toward the end and then scenario number three this one is very similar except we still have a few years of high growth left what I call the high growth period here so rents will still go up at around five or six percent per year our vacancy rate will actually decline but then as soon as we enter the decline period everything I just mentioned above comes true and our rents fall our expenses fall our tenant improvements and leasing commissions rise and in general we get something very similar a recovery period and then a stable period right after that so those are three scenarios here now the reason why these scenarios matter is that in real estate everything is interrelated so if your rents are falling by 10 percent the vacancy rate is almost certainly going to rise by some amount because you have a soft market if rents are falling the market is soft it's going to get harder to attract tenants it's going to get harder to reduce your own vacancy rate and boost the occupancy rate and you're gonna have to pay more to attract those tenants that's why in these scenarios we don't just look at these in isolation we say rents are falling so our vacancy rate is probably gonna be rising and we're gonna have to pay more to attract tenants which is why a lot of these numbers are moving in opposite directions a lot of people make the mistake of just looking at one of these and trying to sensitize around that and in some cases it makes sense if you're looking at something over say a very short time period for example but we would say that in this case given a ten-year holding period and the market data we already have it makes a lot more sense to look at all these variables together and to avoid this business of looking at them in isolation or only looking at selected sensitivity tables on them so let's take a look at this property model in a bit more detail I've shown you the scenario so far we also have sources and uses the acquisition and exit assumptions and other various parts we don't have time to go through all of it in this short lesson but I will go through a few of the main points with a pro-forma model for a property you typically start with the total potential rental income which we do up here so we calculate this by taking the rentable square feet times the rent per square foot times the number of months in the year and then we grow that by a certain rate we also add in other income from parking and other sources we subtract out the income that corresponds to units that are currently vacant or if tenants are not paying the collection losses we subtract that as well then we have our operating expenses or property taxes and maintenance capex and that's how we get to net operating income very similar to EBIT da for a normal company and then we have our capital costs capital expenditures for growth initiatives tenant improvements when tenants move in we may customize their apartment a bit and pay for that and then leasing commissions what we pay to real estate agents these all impact the property's debt repayment capacity but these do not directly impact net operating income so instead we have them affect our adjusted net operating income right below this and then we have a debt service from the interest and principal payments we're just using simple AIPMT and P PMT functions here because the assumptions given for this in the key study document are so simple and we do track how our debt balance changes over time as well as the interest coverage ratio and the debt service coverage ratio the interest coverage ratio is just measuring interest expense relative to net operating income and the debt service coverage ratio includes both interest expense and debt principle repayment so with these lenders typically look for minimum levels depending on the deal type and the property type often it's around 1.5 X 4 the interest coverage ratio under point to X for the debt service coverage ratio and then moving down we calculate our IR are here at the end just using the IRR function in Excel we look at this on an unleveraged basis ignoring debt and then a leverage basis factoring in debt the main difference of course is that we're still going to sell the property in either case but our cash flows to equity investors are going to be lower at least initially for the leverage case because we're spending more of our properties cash flow on paying interest expense and repaying debt principle we have to repay our debt principle at the end we may have to pay an early prepayment penalty and you can see that as expected for positive IRR s we definitely do get a more positive IRR in the leverage case because again leverage magnifies your returns in either direction but the overall conclusion if you really look through these numbers is that it's extremely unlikely we're going to get to a 10 percent IRR on this deal if you look at these sensitivities I'll just go over here so you can see them no matter how we change the loan-to-value ratio even if we use a lot more debt to fund this it seems unlikely that we're going to get to that 10 percent IRR for one very simple reason which goes up to how we're exiting this property for a property deal like this when you exit it you have to assume an exit cap rate so just like when we purchase the property for 120 million our implied going in cap rate was 4.6 percent we also have to make some type of assumption for the exit cap rates now generally if the property stays the same the cap rate is actually going to rise over time meaning it becomes less valuable simply because it is less appealing after 10 years have passed and after more competition has been introduced and especially if there hasn't been a renovation or some type of other upgrade chances are it's probably not as competitive anymore after 10 years so that's where a cap rate here has gone up by around point nine percent now in the decline in recovery case and the longer term decline in recovery case we vary this a little bit and in those cases just to show you we actually have the cap rates falling for the decline and recovery because we're buying it going into a decline and so it's reasonable to assume that maybe it falls a little bit further if the property is recovered and we're in better shape now and then similarly for the longer term decline in recovery we have the cap rate decline as well but the overall conclusion from this if you look at the sensitivities down here for all those cases it is very very difficult to get to this ten percent IRR to really have a chance of doing it even in the base case our cap rate would have to decline to around 4.2 or 4.3 percent we don't think that's particularly likely and to really ensure a high margin of safety here it would probably have to go to 4% or less now if you look at the market data for this particular urban area and you look at some of the cap rates they've never really been below 4.5% which is what they're at right now as of the time of this case study so we don't think it's particularly likely that ten years into the future they're going to fall even lower than where they're at right now and that is part of the reason why we're not too optimistic about this now you can look at the rest of these sensitivities but you get to basically the same conclusion through all these so to write your investment recommendation I'll pull that up on the screen right now we have a two-page recommendation here really the main point is that the numbers don't work even if you assume more optimistic outcomes like the base case numbers they gave us we may run into issues with a debt service coverage ratio remember we calculated that up here and the tricky part about this is that this declines to blow 1.2 X in the base case which is often a minimum that lenders are looking at for this type of property but in the other cases when we have a decline in recovery for example this debt service coverage ratio falls below 1x which means that we don't even have enough cash flow to pay for normal interest and debt principal repayment here so this is a major concern and something that would mean that we're probably going to have to use less debt which of course is going to further reduce our returns in this deal also we do go through a DCF analysis here at the bottom which I don't really have time to get into here but essentially it's telling us that the property is probably overvalued it is probably only worth between 110 and 120 million not 120 million and in the other more pessimistic cases it's worth closer to 100 million so taken all together we don't think we can achieve our targeted IRR the debt service coverage ratio may present issues and the asking price is probably too high to really make it work we would need faster rent growth with no declines no market downturn in between we need a lower asking price we need a renovation or maybe if we had entered this investment at a different time it might work better so if we had entered this right when a property was constructed in 2012 and then exited in say four or five years it might have worked better because the market wasn't quite as frothy then cap rates had not fallen to this low level so maybe if we have done something like that this would work but as it stands as it's presented to us right now with all this market data it doesn't seem like a strong opportunity to earn the returns that we're targeting so let's do a recap of this tutorial now I started by telling you about the types of real estate private equity case studies you can get core value added and opportunistic each of which corresponds to a different strategy pursued by real estate private equity firms future lessons will cover some of the other ones then we went through this case study and I showed you that it's tricky because it's not about the granularity it's about the different operating scenarios and figuring out what they might be then I showed you how to come up with your own scenarios and the different cases that we looked at here we've looked at the property model and the different parts of that and how we calculate in some of the key numbers and then we concluded by taking a quick look at the two page investment recommendation and what you might say to justify your own investment recommendations in this type of case study so that's it for this tutorial coming up in future lessons and tutorials we're going to cover some of the other cases and also some other common topics that we've gotten questions on relating to real estate and real estate private equity you


  1. Michael Akpawu

    Hello Brian, I came in late…but the lesson was incredibly helpful as I have been able to build a REPE model after watching your tutorial. But Quick one; why did you use WACC in calculating the unleveraged NPV and cost of equity for the leveraged NPV. I thought it should be the other way round because I was thinking since the unleveraged NPV does not include debt then the discount rate should be the cost of equity and vice versa.

  2. Lorenzo Triboli

    Dear Team, thank you for the excellent videos you provide, your work is great quality. I would like to ask you a question which occurred to me to which I didn't have a satistying question. Suppose we have 2 different deals on properties: "A" has 5% cap rate and 50% leverage, "B" has 6% cap rate and 80% leverage; interest rate is 3% for both. What is the best deal?
    Saying that provided cap rates were above interest rate, higher leverage would guarantee a higher IRR wasn't enough, they wanted the calculations. Not knowing how to approach this I just assumed the same entry value for both properties (e.g. 100 M) and got to a ratio of (Cap Rate-Interests / Equity Proceeds) which was higher for "deal B". This kind of felt correct, but not completely satisfying and i have the feeling that there is a key metric in real estate that I am missing, or some other reasoning behind this that could lead me to the answer. In other words, given cap rates and leverage without mor information on purchase price, how to assess which deal has the highest potential IRR?

  3. Yoel Herman1

    Excellent video. In regard to the DSCR, shouldn’t lenders care more about the adjusted NOI DSCR instead of the NOI’s DSCR? Because it reflects a more accurate coverage of debt in the project. In addition, Can you give a short explanation of the difference between the replacement cost and the capex cost in the model?

  4. veryclearwater

    Excellent video, Brian. Appreciated! Is it possible for you to do a free hotel acquisition case study?

  5. Yoel Herman

    Hi Brian. I would be happy if you could assist me with a number of questions about some items on the Replacement Cost Ananlysis – can you explain what are the "Impact & Permit Fees" in the soft costs section? and to whom does the development profit (20%) is attributed to? the contractor or the investor?

  6. Yoel Herman

    Great Video Brian. Two Quick Question about the Model – (1) Can you explain why TI and LC are not a part of the basic NOI, is it different for different methods or companies? How should you decide whether or not the component is relevant to the basic NOI or not? (2)Can you explain more about how did you come up with the Exit Cap Rate for each scenario, it's not clear why you in scenario 2 for example, the Cap rate deceases, what is the logic behind it?Thanks in advance

  7. Jarvis Frazier

    Love the video. Thanks for the breakdown in the tutorial and taking your time with the case study. It's really helpful.

  8. Fadel Kabbaj

    Amazing Tutorial !
    What a pity you did not have time to explain fully the DCF model

    But thanks a lot

  9. Suraj Nambiar

    Thanks for posting this. Love the content. Could you please post more videos on Real Estate Investments on your channel?

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