What’s in a Real Estate Private Equity Case Study?
Can you find anything online?
With many subjects, the answer is “yes” or “almost.”
But it’s still quite difficult to find information on certain topics, one of which is real estate private equity.
You can find academic research, textbooks, and whitepapers from professors, but what about actual examples of RE PE case studies you could get in interviews?
But I want to give away for free as much as humanly possible – especially when the information is hard to find elsewhere.
So I’m going to share with you an example of a real estate private equity case study, the solution file, and the explanation for how you could finish this exercise on your own.
All you have to do is keep reading:
RE PE Case Studies 101
Table of Contents:
- 2:49: Part 1: The Types of RE PE Case Studies
- 7:59: Part 2: This Case Study and What Makes It Tricky
- 11:04: Part 3: How to Challenge the #s with Scenarios
- 15:56: Part 4: The Property Model
- 21:20: Part 5: The Investment Recommendation
- 23:26: Recap and Summary
And in text form:
One of my hobbies, aside from memorizing obscure Excel functions, is collecting case studies from readers and students.
Here’s my “Real Estate” folder:
I find the most interesting ones, combine them, and then create new case studies with different locations and property types.
Based on this 4-5 year survey, there are three main types of case studies you might get, each of which corresponds to a different real estate private equity strategy:
- Core or Core-Plus Cases: These are for “stabilized” properties – the occupancy rate is high (95%+ for multifamily properties in big cities), and the rent and expenses increase at predictable rates, in-line with inflation. “Core-Plus” means there might be an opportunity for a bit more upside through a minor renovation or other improvement.
- Value-Added Cases: These are for existing properties with “issues” – e.g., an office complex with a 70% occupancy rate when everything else is 85-90%, or a retail property with below-market rents. Your success or failure in the investment will be determined by how well you improve the property.
- Opportunistic Cases: These mostly refer to new developments, but could sometimes also refer to redevelopments or massive changes to existing properties – e.g., tearing down 75% of an office complex and replacing it with apartments. If it’s a new multifamily development, the apartment units are often pre-sold, which means the “exit” happens gradually over time.
There are other variations as well.
For example, differences emerge when you analyze multifamily properties vs. office complexes vs. retail vs. industrial vs. mixed-use vs. specialized properties.
Office and retail properties often get more complex because each tenant’s lease might have different terms, in which case you’ll need to project the components of revenue on a lease-by-lease basis.
With multifamily and hotel properties, by contrast, there’s no point in doing this because there are hundreds of tenants or guests with very similar terms.
These three categories of case studies all have different risk/return profiles, and they all require different analysis:
- Core or Core-Plus Cases: The risk/return is lowest since the property already exists and you are barely changing it. You might target an 8-10% IRR, and the returns will come mostly from NOI growth and – hopefully – a slight Cap Rate decline over time. These cases tend to be market-focused since the financial modeling is simple.
- Value-Added Cases: The risk/return profile is higher, and you often target a 10-15% IRR. The returns will come from higher rents, more tenants, or a combination of both, along with a lower Cap Rate by the end. While market analysis is also important for these cases, the financial analysis tends to be more critical since the property is changing.
- Opportunistic Cases: The risk/return profile is highest here, and many funds in this space target a 15-20%+ IRR. The financial analysis can be the most complex in these cases, but that also depends on the property type.
There are other categories as well.
For example, you might have to analyze a potential debt investment or evaluate a senior loan vs. a mezzanine investment in the same property.
I don’t want to turn this into a 20,000-word article, so we’re going to focus on the “core” category here.
The “modeling complexity” referenced above depends on how granular the case study is. Tracking individual tenants makes everything more time-consuming and can make even a core or value-added case more difficult.
There are also certain common exercises you’ll receive across many of these categories: the waterfall schedule (distributing different percentages of the returns to different investor groups depending on the overall IRR), debt and equity schedules, and so on.
This Case Study: The Iron Bank of… Seattle?
Here’s the 17-page PDF document for this case study:
Faced with political turmoil and upheaval in Westeros, the Iron Bank of Braavos has opened a wormhole to an alternate dimension and set its sights on a more stable market: Seattle.
If you don’t know much about the city, it’s in the northwestern part of the US and is a “mini San Francisco.”
Everyone works at Amazon or Microsoft (or sometimes a few other tech companies or Boeing), and people like outdoor activities during the 20% of the year when it’s not raining.
It has also been one of the fastest-growing metropolitan areas of the US, with nearly 100 planned or permitted multifamily properties in a tiny area (as of the time of this case study).
All of that is driven by strong fundamentals Amazon and Microsoft.
Noticing a pattern yet?
The property described here, The Lyric, is a real apartment complex in the city.
I changed around the numbers, the unit types, and other details, but it’s based on this real property.
I actually considered living there once, but I don’t work at Amazon or Microsoft so they rejected me right away.
You can skip to pages 14 – 17 of the case study document to understand what it’s all about:
If we’re targeting a 10% IRR, should we acquire The Lyric for $120 million, assuming a 70% LTV ratio, a 10-year holding period, 3% income and expense growth, and various numbers for CapEx, Tenant Improvements, and Leasing Commissions?
The Plot Twist: How This Case Study is Designed to Trick You
I based this exercise on a real case study that was given a few years ago, but I modified it to make it into more of a “trick case.”
Specifically, I provide this mix of units on page 8, along with the market rent and effective rent for each unit type:
Looking at that, you might be tempted to jump in and model each unit type separately.
You could spend all your time on that and then follow the case study instructions at the end to a tee, inputting the numbers and percentages provided there.
However, this would be exactly the *wrong* approach for this case study.
Remember that this is a core, multifamily case study… the modeling is not supposed to be that complex or granular.
There are 234 separate units in the building, so it’s a bit silly to plot out the monthly rents for each unit type separately.
If this were an office with only 10-15 tenants, it would make more sense – especially if each of the leases had different terms.
But here, the rents are so similar and each tenant contributes such a small percentage of the total revenue that you should simplify and use the average rent per square foot across all units.
Then, you can spend all your extra time on the market analysis and figure out if the assumptions at the end actually make sense.
In this case, those assumptions deserve to be challenged – taking them at face value would be a big mistake.
Scenarios, Toggles, and Market Cycles
In most real estate models, people rarely factor in market cycles.
You’ll see 10-year models where people just assume that rent will increase by 3-4% per year over 10 years… but does that ever happen?
Of course not.
Just like normal companies’ revenue growth and margins fluctuate over time, rent, expenses, and capital costs for properties will also change at different rates over time.
Looking at the 15-year graph of market rents and vacancy rates in this submarket of Seattle, it seems very likely that there will be some type of market downturn, or a downturn and recovery, within the next 5-10 years:
Unless you believe that “this time it’s different.” (Good luck to you there)
As a result, we’re going to come up with our own assumptions to see what might happen if there is some type of downturn followed by a recovery.
There are two likely scenarios:
- Immediate Market Decline, Recovery, and Stabilization – In this case, rental income and expenses will both decline over a few years as the vacancy rate rises. Tenant Improvements and Leasing Commissions will increase as the property owners must pay more to attract new tenants. Then, those trends will reverse and normal growth rates will be restored over 3-4 years, followed by a “stable” period thereafter.
- Continued High Growth, Decline, Recovery, and Stabilization – In this scenario, rents will continue to grow at a fast clip (5-6%) for a few years, but then a decline will begin, a recovery will follow, and the numbers will “stabilize” near the end of the holding period.
It’s important to use scenarios rather than simple sensitivities or toggles here because the key assumptions are interrelated.
So you can’t just say, “Let’s see what happens when rental income declines by 10% and nothing else changes.”
If rental income really falls by 10%, the vacancy rate will almost certainly rise and many of the other expenses will also rise due to a soft market.
You can use sensitivities for the “non-interrelated” assumptions, like the LTV Ratio and the Cap Rate, but scenarios are better for operational items.
The Financial Model, the Valuation, and More
This is a simple model, so I don’t have much to say about it.
You always start with the “potential rental income” at the top of the Pro Forma, add other income sources, subtract income lost from vacancies and collection losses, and then show the operating expenses and maintenance CapEx.
Then, you show the “capital costs” (CapEx, Tenant Improvements, and Leasing Commissions) since they impact the property’s debt repayment capacity but do not affect Net Operating Income.
Since the debt is simple here, we are just using IPMT and PPMT for the calculations.
We also calculate the interest coverage ratio and the debt service coverage ratio (DSCR) because we need to assess whether or not 70% leverage is appropriate; lenders often look for at least a 1.5x interest coverage ratio and a 1.2x DSCR in these types of deals.
And then at the end, we calculate both leveraged and unleveraged IRR, the NPV under both methods, and we even run a simple DCF to value the property.
The overall conclusion from all this analysis is that there’s no way we’ll earn a 10% IRR here.
The leveraged IRR even in the Base Case is only around 6.5%, and it looks worse in all the other cases.
There are a few reasons for these results:
- Little Rental Growth – If rental income and expenses each increase by 3% per year, NOI will only grow by 3% per year… so even if you add leverage to the mix, it’s tough to go above a 5-6% IRR. This could only happen if the Exit Cap Rate falls dramatically, except…
- Cap Rates Are Unlikely to Fall Dramatically – All else being equal, the Exit Cap Rate will actually rise in this case because the property stays the same, but is now older and less appealing after 10 years have passed. That’s why the Going-In Cap Rate is 4.6%, but the Exit Cap Rate is 5.5% in the Base Case. In the other cases, the Cap Rate might decline due to the recovery, but the drop in NOI during the “decline” phase will offset much of that gain.
The DCF also points to the property being overvalued at a $120 million asking price, and the sensitivities confirm everything: the Cap Rate would have to decline even in the Base Case for us to realize a 10% IRR.
Presenting Your Findings and Making an Investment Recommendation
So it’s no surprise that we recommend against acquiring The Lyric for $120 million:
We mention all the reasons above, but we also point out how the DSCR falls below 1x in some of the more pessimistic cases – never a good sign for a “stabilized” property.
Given that Cap Rates in the Seattle area have not fallen below 4.5% in the past 15 years, we think it’s implausible that they could drop even further over the next 5-10 years.
And there is a LOT of competition in the form of new apartment buildings in the area.
When you’re making a positive recommendation, you need to come up with risk factors and ways to mitigate them; in a negative recommendation, you do the opposite and point out why you might be wrong or what might cause you to change your mind.
If rents grow at 6-7% for a few years and then decline to 3% growth, the numbers could work; the numbers might also work if the asking price were closer to $100 million instead.
We do mention a few risk factors at the end if we had made a positive recommendation instead: the vacancy rate might rise to the 7-9% historical highs, Cap Rates might rise to the 6% level, or an oversupply of apartment units might push down rents.
Mitigants might include longer-term contracts or more concessions for tenants, a mild renovation, or a reduction in operating expenses (unlikely, but you never know).
For Further Learning
This is the first of three sample real estate private equity case studies covered here; all of them come from our real estate financial modeling course.
For more in this series, please see:
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