Stress Test & Risk Analytics for LTR?

Question

Hey all,

I’ve been thinking a lot about how most people underwrite LTR deals, and one thing I keep noticing is that downside risk doesn’t always get as much attention as the base-case numbers.

A lot of the focus tends to be on:

• purchase price
• rent comps
• basic cash flow

Which makes sense—but it usually stops there.

But what I don’t see as often is people really asking: What actually breaks this deal if a few assumptions are off?

When I stress test a deal, I usually just run a few simple downside scenarios like:

• higher vacancy than expected
• rent coming in below comps
• higher maintenance or operating costs
• tighter financing than assumed
• CapEx or repairs taking longer than planned

At the end of the day, I'm just trying to see if this still works when reality isn't perfect.

I’ve also been using a simple setup I use to test different cases (best case / base case / downside) so I’m not relying on just one version of the numbers.

Curious how others think about this—do you build out full sensitivity models, or is it more of a gut check / rule-of-thumb approach when you’re underwriting?

G. Brian Davis · Answer

Hi @@Hasan Gabareen we’re similar in that we don’t overcomplicate it, but we do push hard on a few “what breaks it” levers.. vacancy, exit cap, and financing. If a deal can’t survive a modest hit in those, it’s usually a pass. Big one for us too is asking, would I still be comfortable owning this if things take longer than planned? Time risk doesn’t get talked about enough.

Jay Toluganti · Answer

Location is important. Is there rental demand in the area and what is driving that denand? Is it new employment opportunity? Lack of supply etc. Talking to couple of property managenent companies can get you the details. I would start there.

Priya Menon · Answer

I run all 6 of my SFHs through a pretty simple stress test before I buy, and then I compare against the actuals once I have trailing 12 data. The two numbers that have deviated the most from my original proforma are vacancy and turnover costs. I underwrote my first few deals at 5% vacancy because that's what every BP post said to use, but my actual vacancy has averaged closer to 3% because I screen hard and retain tenants. But turnover costs hit harder than I expected. Every turnover in Indy runs me 6-8 weeks vacant plus $1,500-2,500 in make-ready, and that one event can wipe out a couple months of cash flow on a single property.

The stress test that actually matters to me now is: what happens if two properties turn over in the same quarter. That happened once in 2022 and it was tight. Not catastrophic, but I felt it. So now when I'm running the numbers on a new deal I model the base case and then I run a scenario where vacancy doubles and I add a full turnover event in year one. If the deal still cash flows positive after that, I move forward. If it only works with perfect occupancy, I pass.

I don't build out fancy sensitivity models though. It's literally just a couple extra rows in my Google Sheets tracker where I plug in worse numbers and see what the cash-on-cash drops to. If my 8% target falls below 5% in the downside scenario, the margin is too thin.

G. Brian Davis · Answer

We usually think in ranges, not just does it feel okay. For example, we’ll bump vacancy up a few points, push the exit cap higher, and assume slightly worse financing than projected. Nothing extreme, just enough to reflect a more realistic downside case.

Hasan Gabareen · Answer

That makes sense, especially the time risk piece. That’s something I don’t see talked about much, but it makes a big difference once things don’t go to plan.

I’ve been noticing something similar with occupancy too—small changes don’t seem like much at first, but over time they compound pretty quickly.

When you’re pressure testing those levers, are you thinking in specific ranges, or more like does this still feel solid if a metric shifts a bit?

Patricia Steiner · Answer

There's more to it than you even suggests...not everyone will be willing to give away their 'secret sauce.'  Let's just say that most experienced investors/landlords have a more comprehensive model.

Stress Test & Risk Analytics for LTR?

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