The Hidden Risk in “Stabilized” Pro Formas

Most real estate deals look their best in “stabilized” Year-3 projections—but those numbers often rely on multiple assumptions all going right at the same time. In this episode, we break down the hidden risk inside pro formas, why small misses in rent, occupancy, or expenses can dramatically impact outcomes, and how to stress test deals using volatility, downside scenarios, and resilience metrics. This is about shifting from optimistic projections to understanding what actually happens when reality doesn’t cooperate.

Beacon Hill Property Advisors: https://bhpropertyadvisors.com/

Transcript

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Welcome to Beyond IRR. This podcast examines real estate investments through the lens of structure, risk, and capital durability, not just headline returns. I'm your host, Louis Heiza. This podcast is sponsored by Beacon Hill Property Advisors. Welcome back to the show, everyone. Today we are going to be looking at proformas and hidden risks within quote-unquote stabilized proformas. When you look at most real estate investment pitch decks, you'll notice something interesting. The slide that usually looks the best is year three. The rents are higher, vacancy is lower, expenses are under control, the property is fully stabilized, and cash flow looks strong. And the projected returns, IRR, equity multiple, cash on cash, they all look fantastic. But there's a subtle problem hiding in that slide. Year three proformas often dominate the narrative of the entire deal. And the further you move away from year one, the more assumptions stack up on top of each other. So today I want to talk about the hidden risk in stabilized proformas, why they show up everywhere in real estate investing, and how you can stress test them using volatility metrics and downside analysis. Because stabilization is often presented as if it's a guarantee, when in reality, it's usually just one scenario. Let's start with why year three projections are so common. In most value add or repositioning deals, sponsors need time to improve the property. They might need to renovate units, increase rents, improve occupancy, reduce expenses, replace management, stabilize delinquency. So the pro forma usually looks something like this. Year one, heavy capex, higher vacancy, lower cash flow. Year two, units are coming online, occupancy is improving. We call this the leaseup period, and rents are increasing. Then you get to year three, you're fully stabilized, high occupancy, strong NOI, beautiful returns, and that stabilized year is usually what sponsors highlight. But here's the key issue. Stabilization assumes everything goes right, or at least that nothing goes very wrong. So let's walk through a simple example. Imagine a 40-unit apartment building purchased for $6 million. Here's the current situation upon acquisition. Let's say the occupancy is 85%. Average rent, call it $1,000, gross potential rent, therefore, $480,000. Actual rent collected, let's just say they're collecting $408,000. So that's uh $72,000 per year, uh vacancy or either vacancy or delinquency, bad debt. Let's say expenses are $220,000. So current NOI is roughly, this is year one, uh current NOI $188,000. So at a 6% cap rate, the property might be worth about $3.1 million. So clearly the buyer believes they can push performance higher, right? That's nearly half of uh the acquisition price. Their pro forma might say something like year three stabilized, occupancy 95%, average rent $1,300, gross rents, therefore $625,000. Expenses, let's say $240,000. Expenses might go up a little. This is probably due to as units come online, therefore other expenses are going to come online. Uh, utilities, for example, there's gonna be commissions. So expenses generally go up as occupancy goes up as well, you know, barring some significant type of expense reduction program, such as a rub system or separately metering, swapping out incandescent bulbs and or fluorescent for LED, stuff like that. But otherwise, the expenses are gonna go up. So therefore, we got an NOI of $384,000. Suddenly, the value at a 6% cap rate becomes $6.4 million, which just justifies that $6 million purchase price. But notice what happened here. The Proforma assumed three things simultaneously that improved. It assumed that occupancy increases, rents increase, and expenses remain controlled, right? That 240 is very close to that at original 220. It just went up a tiny bit. Each of those assumptions may be reasonable individually, but together they compound, and that's where the hidden risk lies. Real estate proformas are multiplicative assumption machines. If rents go up and vacancy drops and expenses stay flat and cap rates hold, then the deal looks amazing. But if one variable breaks, the stabilized picture can change dramatically. Let's run a quick stress test. So instead of year three assumptions being perfect, imagine this happens. Occupancy reaches 92% instead of 95%. Let's say average rents are $1,250 instead of $1,300. And let's say expenses run $20,000 higher than projected. And these are all very normal assumptions or different scenarios that don't live up to the original um assumption. We're not off by much here. So now the numbers look something like this. Gross rent, $600,000. At a 92% occupancy, rents collected, let's call it $552,000. Those expenses we said bumped up by $20K, so now we're at $20, uh, $260,000. NOI, therefore, is $292,000 instead of the $384 it was. That's a big change. So a 24% drop in NOI compared to the pro forma stabilization. At a 6% cap rate, the value is only 4.87 instead of 6.4. That's a $1.5 million difference caused by relatively small changes in assumptions. This is why sophisticated investors spend less time admiring stabilized projections and more time asking, how fragile are those assumptions? This is where volatility metrics become incredibly useful. So instead of just asking, what does the deal look like if everything goes right, we ask, what happens if reality behaves like, well, reality. Because real estate performance is rarely smooth, vacancy fluctuates, tenants move out unexpectedly, repairs spike, economic cycles hit, insurance jumps, property taxes get reassessed. These fluctuations create cash flow volatility. So let's illustrate this with a real world example. Imagine two deals with identical projected stabilized NOI. So both say that year three NOI, and we'll assume obviously these are value add deals. So let's say both had year three NOIs of $500,000, half a million, but their historical volatility looks different. So let's look at deal. Monthly NOI swings somewhere between, let's say, $4,000 and $45,000. So that's per month. Deal B, let's say it has significantly more volatility. So let's say the monthly NOI swings between $20,000 on the low end and 60,000 on the high end. So the average NOI is the same, but the risk profile is completely different. Deal B experiences severe downside months. Those months can create stress. They can create debt coverage issues, reserve depletions, delayed distributions. So that's why at BHPA, we always incorporate several stability metrics into our dashboards. In fact, it's an entire section of our dashboard is stability. Because stabilized proformas only tell you the expected scenario. And if the sponsor of the deal, if their moral integrity is, let's say, lacking, the scenario they present to you is probably going to be not only not expected, but optimistic. And there's nothing worse than an optimistic pro forma. Optimism in pro forma is we call that icing on the cake. I underwrite everything pessimistically. And if it looks good then, if things come out better, that's icing on the cake. But they don't tell you the path variability, most pro forma. Some metrics we track include cash flow volatility, worst month performance, percentage of downside months, and sensitivity to rent and vacancy changes. These metrics help answer a much more important question. How resilient is the deal when assumptions break? So let's look at a specific example. Suppose a deal shows stabilized NOI of $400,000 on an annual basis. So the debt service, let's call it $300,000. That's a DSCR of $1.33. That's very comfortable. But what happens during a bad month? Imagine occupancy dips for a few months during renovations. NOI temporarily falls to uh $20,000 a month. So let's say instead of the original $33,000, we're down to 20. So now the annualized NOI becomes closer to $240,000. DSCR is now below one. You are not covering your debt payments. You're coming out of reserves to cover your annual debt payment. The stabilized pro forma never showed this scenario, but volatility analysis reveals it immediately. And anyone who's owned real estate for long enough knows that these months do happen. And the more property you own, the more aware of that you are. Just because statistically speaking, the more the higher the probability that you've had a property or multiple properties that experience months that you didn't expect and probably crunch DSCR. So here's another example involving expense shocks. Many proformas assume relatively smooth expense growth. Let's say 3% per year. In fact, a lot of people kind of tie this to inflation. But real expenses often jump in steps. Insurance is a great example, especially recently. And especially if you live in one of these areas of the country where insurance has been uh jumping dramatically, which honestly, I'm not sure I can think of a region in the country that hasn't experienced this. In many markets over the last few years, insurance has increased 30 to 100% in a single renewal cycle. And if you're thinking that only applies to Florida or high-risk fire areas like Southern California, I've got property in the Midwest, the northmist Midwest, Indiana, Michigan, that has seen dramatic insurance increases. And the insurance carriers are citing severe thunderstorms and hail damage as the reason. So we're not in tornado that those properties are not in tornado alley. There are obviously no risk to earthquakes or hurricanes or wildfires, but thunderstorms, that's that's what's pushing prices. So imagine that a property projected year three expense of $300,000, but insurance jumps by K, which is entirely possible. I've seen it. Now the expenses are $360,000. If NOI was projected at $500, it now becomes $450. And again, the stabilized scenario deteriorates very quickly. The problem isn't that pro forma inherently dishonest, although they can. I always remind myself of the saying that numbers don't lie, but liars use numbers. The problem is that they are deterministic. They show just one single path. But real estate outcomes are probabilistic. There are many possible paths. This is why downside analysis matters. So instead of asking what is the projected NOI, you should be asking, what is the NOI if the top three assumptions fail even just slightly? So for example, you should stress test rents going down 10%. Stress test occupancy going down just 5%. Stress test expenses going up by 10%. Now recalculate the deal. Did it survive? Is DSCR above one? Does cash flow remain positive? Does the investment still make sense from a returns perspective? If the deal collapses under mild stress, then the stabilized proforma was fragile. So let's do a quick hypothetical stress test. These are going to be projected stabilized numbers. So let's say rent revenue a million dollars. Expenses 450,000. So that gives an NOI of 550,000. Let's say debt service is 420,000. That's a DSCR of 1.31. That looks solid, that looks comfortable. Now let's stress test it. Let's say rents drop by 8%. Therefore, revenue is now $920,000. Let's say expenses rise by 10%. Expenses now become $495,000. Just those two little stressors, NOI is now at $425,000. And now DSCR is 1.01. You are scraping by, and you can't have a bad month without using reserve to cover debt payments. And that's just with relatively mild changes. So this is why volatility and downside analysis are essential tools. Another hidden risk of stabilized projections is the timing risk. So even if the property eventually stabilizes, the path may take longer. If stabilization was projected in 18 months, but it takes 36, investors experience delayed cash flows, much lower IRR. Don't forget, IRR is less a return metric than a timing metric. It's extremely sensitive to the timing of cash flows. And the further out they are, the lower IRR drops. Investors are also going to experience higher operating risk and potential refinance issues if that was part of the plan. Because time itself compounds the risks. The longer stabilization takes, the more opportunities there are for unexpected shocks. So let's look at a simple IRR impact example. So the original projection, let's say it was a $1 million investment, years um cash flow, year one, zero. So year zero cash flow is negative a million. That's the investment. And then we've got year one of zero dollar cash flow break-even. So that's that's our you know heavy lift capex period. Year two is again gonna be that lease up period. Let's say year two cash flow 40,000, and then year three and on, now we're stabilized, let's say it's $120,000. Then we'll sell it in year five. Let's now adjust this with stabilization delays. So let's let's adjust those years. Now let's look at cash flow year one is zero still, but this year, year two, let's only do 10K instead of 40. And then in year three, we're still stabilizing. So instead of that 120, let's say we're now at 40. And it takes until year four to get to the 120k. So even though the final stabilized performance might be identical, the IRR can drop several percentage points simply because stabilization took longer. And this is rarely emphasized in pitch decks. So a useful mindset shift is this. Instead of asking whether the deal can stabilize, you should ask whether the deal survives while stabilizing. And those are very different questions. The first is optimistic, the second is defensive, and defensive analysis protects capital. One of the most helpful metrics for this worst month performance. Look at the worst month historically or under stress. What does cash flow look like? Is it negative? And if so, how negative? How many months of reserves would it consume? Those questions reveal the true risk tolerance of a property. We our BHPA dashboards, we always include um a runway count, effectively, which is debt payments or reserve balance divided by debt payments. And what we're trying to see here is how many months of debt payments could you make if cash flow was zero? You know, obviously that's a worst, worst case scenario. And when I say cash flow, I mean revenue. But we want to see what that runway is. How long are you going to last before you're coming out of pocket? So another useful metric is downside month percentage. I love this metric. So for example, if 25% of months have negative cash flow, that's very different from a property that only has 5% months negative, even though the annual NOI is identical because volatility drives risk. Now, a point about downside month percentage. There's two ways to calculate this. And we'll do it depending on the type of property. So a single family home or a small multifamily that's much more likely to have negative months due to either occupancy, delinquency, or high expenses, just because revenue is relatively low. We look at downside months as the percentage of months on a trailing 12 basis that are negative, less than zero. Whereas a much bigger property, a larger multifamily or commercial property that rarely ever goes negative cash flow unless there's significant capex. Because it rarely goes negative, this would kind of skew the result of having a very low downside percentage. And so we actually calculate negative downside month percentage as the percentage of months that are below the trailing 12 average. So we want to know which how many months per year are is the month's cash flow below that year's average cash flow. So this is why reserves are very, very important. A stabilized pro forma often assumes the property operates near its average performance, but volatility means some months will perform below average, and reserves allow the property to absorb these shocks. Without reserves, even a fundamentally good property can experience distress. So if you're looking at a pitch deck or looking at a deal, or buying one yourself, if you're the sole investor, I often see people forget reserves as a use of capital up front. That should be baked into the deal along with purchase price and capex and closing costs, reserve balance. You want to start with a reserve balance. Now, what is that reserve balance? Generally, it's going to be percentage of monthly expenses. You know, give yourself a three to six month runway, depending on your risk tolerance. But you should always be baking in a reserve balance. And another mistake I see people make to attempt to keep upfront capital as low as possible is they say, you know what, once this thing's cash flowing, we'll just stack cash and build a reserve balance with positive cash flow. It's a big mistake because stabilization is the riskiest period. And if you can't even survive that, you're not going to get to this, to the stage where you're positively cash flowing and can stack cash. And here's another little tidbit that people often don't realize is I've met many lenders and done this personally who will bake in a reserve balance into the loan. Now they'll give you a percentage of it. Let's say your loan is 75%. They'll give you 75% of your, you know, operating expenses if you're projecting negative operating expenses because it's a value add deal. But it's worth asking your lender if you can include this. Uh, because oftentimes they'll say yes. So, how should investors interpret stabilized projections? It's not as a prediction, but as a target scenario. It's a goal. It's one possible outcome, but it's never the only outcome. And the real work of underwriting is understanding how easily that target can be missed, what happens when it's missed, and whether the deal survives those misses. So, in other words, a good deal isn't just one that performs well when everything goes right. A good deal is one that remains viable when things go wrong. And at BHPA, this philosophy heavily influences how we design performance dashboards. So instead of focusing only on outcome metrics like IRR or equity multiple, we emphasize risk visibility. We first and foremost look at things like cash flow volatility, downside month, worst case month, sensitivity to rent changes, sensitivity to occupancy changes, because these metrics reveal something critical, how fragile or resilient the property actually is. And resilience is often more important than projection accuracy. When investors become more experienced, their focus shifts. Beginners ask, what are the projected returns? Experienced investors ask, what breaks this deal? And that's a much better question, because the biggest risk in real estate are rarely in the numbers that you see. They're the in the assumptions that you don't question. And stabilized proformas are essentially assumption stacks. The more assumptions required to reach stabilization, the more fragile the projection becomes. So next time you look at a pitch deck and see a beautiful year three projection, pause for a moment and ask three questions. What assumptions must be all true for this scenario to happen? What happens if those assumptions miss slightly? And does the deal still survive? If the answer to that third question is yes, then the deal may actually be strong. And if not, then the stabilized projection might be hiding risk rather than revealing opportunity. So quick fun fact to close out this episode. In professional risk modeling, especially in fields like energy trading and hedge funds, analysts rarely rely on a single projection. Instead, they run thousands of simulated scenarios called Monte Carlo simulations, where variables like price, demand, and volatility change randomly. This produces a distribution of outcomes, not just one expected outcome. Think of that Gaussian or bell curve from high school algebra. Interestingly, very few real estate investors run this kind of probabilistic modeling, even though real estate cash flows are just as variable, if not more. So what that means is that many stabilized proformas are essentially showing only one possible future out of thousands that could actually happen. I hope you found this episode interesting and informative, and stay tuned for the next. Thanks again, everyone. Thank you for listening to Beyond IRR. This podcast is produced by Beacon Hill Property Advisors, where we focus on bringing clarity, structure, and rigor to real estate investment analysis. If you want to evaluate deals beyond headline metrics and better understand the mechanics driving performance, you can learn more about our tools and approach at bhpropertyadvisors.com. You can also connect with us directly for demonstrations, resources, and additional insights. Until next time, analyze deeply, allocate wisely, and always go beyond IRR