In this Value-Added Real Estate Private Equity Case Study tutorial video, you’ll learn what to expect in real estate private equity case studies and you’ll get an example of a real value-added RE PE case study with the solution file and a walk-through of the key points.
Please get all the files and the textual description and explanation here:
Table of Contents:
2:41 Part 1: The Types of RE PE Case Studies
5:19 Part 2: This Case Study and What Makes It Tricky
12:40 Part 3: Why Excel is Horrible for This Case Study
16:59 The Scenarios in This Model
17:51 Part 4: The Property Model and Returns Analysis
26:39 Part 5: The Investment Recommendation
28:37 Recap and Summary
Part 1: The Types of RE PE Case Studies
The 3 main types are core / core-plus, value-added, and opportunistic.
In the first category, the property stays nearly the same over the holding period and the market analysis is more important than a complex model.
In the second category, the property changes significantly (more tenants, higher rents, a renovation, etc.) and the models tend to be more complex.
The modeling often gets the most complex in the third category because a new property is developed, an existing one is redeveloped, or the building changes massively (e.g., rescuing a distressed property).
The complexity also depends on how granular the model is – modeling individual tenants with different lease terms always gets more complicated than a high-level model with average unit sizes, square feet or square meters, etc.
Part 2: This Case Study and What Makes It Tricky
This case study is less about analyzing the market data, and more about getting all the Excel formulas correct, making the correct calculations, and finishing on time.
Since we have information on 13 individual tenants in the building, we NEED to do a more granular analysis and look at each tenant separately.
The Excel formulas for free months of rent, TIs and LCs, and other key terms in the leases are somewhat tricky to figure out.
Part 3: Why Excel is Horrible for This Case Study
The problem here is that there are two scenarios for each existing tenant: they might renew, or they might not renew, when their lease expires.
If it’s just these two scenarios you can do a reasonable job plotting them out in Excel. But when it goes beyond that – say, 2-year contracts over a 10-year period, resulting in 5 “renewal points” and 2^5 or 32 scenarios – Excel becomes unwieldy for this exercise.
You’re better off using ARGUS to model this if you have that level of complexity and an entire probability tree.
As it stands, our formulas get quite complex here though they are not THAT difficult to understand if you break down the individual components.
The Scenarios in This Model
The main difference between the three scenarios here is that the occupancy rate stays the same, at 74%, in the Downside Case, whereas it increases to 80% in the Base Case because we find three new tenants, and it increases to 85% in the Upside Case as we find four new tenants.
Also, the growth assumptions and the TIs, LCs, and other concessions such as free months of rent differ between the three cases and are most generous in the Upside Case and least generous in the Downside Case.
Part 4: The Property Model and Returns Analysis
In short, after setting up all the formulas for rent, free months of rent, absorption (the difference between market rent and in-place rent), turnover vacancy (the time between one tenant cancelling and moving out and finding a new one to replace him), and general vacancy, we fill out the rest of the Pro-Forma Model.
We include all the operating expenses to determine the property’s NOI, and then plot out the debt repayments over time and the interest expense paid on debt. The Acquisition/Exit assumptions and Sources & Uses schedule are all quite straightforward: we assume lower Exit Cap Rates due to the renovation, but there’s less of a decline in the Downside Case.
In the Returns Analysis, we set up a “waterfall schedule” to split and distribute the returns: up to a 10% IRR is split 80/20 between the LPs and GPs, then between a 10% and 15% IRR it’s split 70/30, and then above 15% it’s split 60/40.
Part 5: The Investment Recommendation
We recommend acquiring the property because the numbers work well and meet our targeted IRR and CoC multiple in the Base and Downside cases, the market data is positive, and we believe it’s plausible for the occupancy rate and average rents to increase up to the market levels in the area.
For the deal NOT to work, something catastrophic would have to happen: rents falling by 25%, the lease renewal rate dropping to 30%, or something in that vein… and we believe there are ways to mitigate against all those risks.