REIT NAV Models 101: How to Set Them Up, and What Makes Them Tricky (21:00)

You’ll learn about Net Asset Value (NAV) Models for REITs in this lesson, including the basic idea and what makes them more complex than they seem at first glance.

Tutorial Summary & Description

You’ll learn about Net Asset Value (NAV) Models for REITs in this lesson, including the basic idea and what makes them more complex than they seem at first glance – with examples from Park Hotels, AvalonBay, and Digital Realty.

Table of Contents:

1:47 The Basic Idea Behind a NAV Model

6:30 Why NAV Models Can Get More Complex

9:37 AvalonBay Example

13:25 Digital Realty Example

18:37 Recap and Summary

Lesson Outline:

We get a lot of questions from students and professionals who think that NAV Models seem “too easy.”

The truth is that the basic idea is quite simple – you re-value a REIT’s Assets, re-value its Liabilities, and then subtract its Liabilities from its Assets to calculate its Net Asset Value.

Then, you can calculate NAV per Share and compare it to the REIT’s current share price to determine whether or not it is valued appropriately.

In practice, that means that you project the REIT’s forward NOI from properties, divide by an appropriate Cap Rate to estimate their value, mark up other Assets slightly, write down Goodwill/Intangibles, mark the Debt to fair market value and adjust the Other Liabilities, and then subtract the Adjusted Liabilities from the Adjusted Assets.

However, NAV Models are significantly more complex in real life because it takes more effort to project the REIT’s NOI, it can be tricky to factor in Acquisitions, Developments, Redevelopments, and Dispositions, it takes time and effort to find the right Cap Rates, and you must split out the JV Assets and Liabilities separately, re-value them, and then multiply by the REIT’s ownership percentage to factor them into the calculation.

With AvalonBay, we built a detailed forecast for all the segments, including a split by geography and business activity, and then we applied a separate Cap Rate to each one, based on data from JLL and the company’s investor presentations.

We factored in the REIT’s acquisitions, developments, redevelopments, and dispositions by making the forward NOI include the additional NOI and lost NOI from those activities, and we subtracted out the associated assets from Construction in Progress on the Balance Sheet.

We created mini-projections for the Equity Investments, capped the NOI from them at a similar rate, adjusted the Assets and Liabilities up/down, and multiplied by AVB’s approximate 25% ownership to determine the proper values.

With Digital Realty, we lacked detailed forecasts, so we simply annualized the most recent quarter’s NOI, adjusted it for non-cash items such as the straight-lining of rent and above/below-market lease amortization, and also factored in the NOI lost and gained from other activities in the quarter.

We then assumed a modest growth rate over the next 12 months to calculate the cash NOI.

We reflected acquisitions, developments, and dispositions by including the NOI from those activities in the annualized figure and also subtracting the backlog from Construction in Progress and including several other items related to them on the Balance Sheet.

We Googled for data center Cap Rates and settled on a range of 6.5% – 7.5% based on industry surveys and nationwide data.

We used the company’s own disclosed figures for the Joint Ventures and accepted them at face value, simply applying our own Cap Rate to the annualized cash NOI from JVs.

If you have a lot of time and data, the AvalonBay approach is best because it will give you more accurate results.

But if you have little time or poor data, the Digital Realty approach can work well and still deliver decent results if you’ve chosen reasonable Cap Rates.