Co-Founder @ Silver Wave Capital, a senior housing investment firm | Exploring the Aging Economy | Mailing List ⬇️
Davis, CA
Joined March 2014
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I think I'm in the process of learning the power of hyper-local banking relationships. I got a term sheet last week from one and, relative to national banks:
5-10% higher LTC
50 bps lower SOFR spread
And.... zero prepayment penalties!
Plus the banker felt like Grandpa.
We closed our 3rd deal this week 🙏
Good basis in a great market. Bought it from a friend off-market at a time when competition for value-add deals is really heating up.
A senior housing broker succinctly summarized for me the difference between 2024 and 2025:
In 2024, the market had a per-unit cap of $300k. Transactions prices above that cap were scarce.
In 2025, that cap is gone.
Our internal data agrees. On an annualized basis, we see over 4x more deals with guidance above the cap this year.
(Granted this is guidance, not trade price. Still - instructive.)
Another framing of the tremendous supply/demand growth imbalance in senior housing right now:
Unit construction required to meet demand by 2030: 564,000
Units constructed by 2030 at current development pace: 191,000
We will need 3x more units than are on track to be built
Signed an LOI this week for a deal we’ve been evaluating on and off for a year. Price came way down from our first off-market look.
Pays to hang around the hoop.
Cory Wake retweeted
Deal Pricing vs. Reality
@coryDwake and his partner Elan dug into 51 closed senior housing deals since January 2024 where they had both broker guidance and the actual sale price. That’s out of 330 reviewed deals (closing price is notoriously hard to pin down).
What did they find?
•23 traded below guidance
•9 traded at guidance
•19 traded above guidance
•Only 12 landed within a tight ±10% band
Most common outcome? Deals going 5–10% below what brokers were guiding.
What predicts that spread?
They looked at the “Transaction Delta” vs. revPOR, facility size, NOI margin, and vintage.
The results:
•No clear relationship with revPOR or size
•Some correlation with vintage (newer = better)
•Erratic link with NOI margin—except at the low end, where poor margins led to steeper discounts
Two big takeaways:
1.Pricing is more normally distributed around guidance than you’d expect.
2.Newer builds are more likely to beat guidance.
Caveat: This doesn’t capture deals that didn’t close because the price was just too high—but it’s still a super useful lens on the market.
Nice work Cory and Elan.
Last year we solved a problem that was limiting us as a small team: we were wasting too many hours in Excel underwriting deals that never went anywhere.
When a deal piques our interest, we want to test the numbers and tweak assumptions. For too long, we did that by jumping straight to full discounted cashflow underwritings. We’d spend 3-5 hours building a model that was unnecessarily complex.
For raising capital, you need a DCF model. For vetting deals, talking to operators, and submitting LOIs, you don’t. We needed a faster, 80/20 analysis that told us what we needed to know without bogging us down.
Thus, the SWC Roll-Up Analysis was born.
Shown below, this simple dashboard gives us the key info needed for deciding whether to pursue or pass, and the analysis takes an hour at most. We just pull in historical financials, tweak the adjustable inputs, and make minor deal-specific changes.
What results is a 360-view of the deal, including:
• Trended historical financials, including revenue and expenses per occupied unit.
• A pro forma sketch based on 3 simple inputs: occupancy, rate growth, and operating margin. It’s not perfect, but it grounds our expectations.
• Asset info including unit mix, vintage, pricing guidance, and potential bid amount (including cap rates and price-per-unit).
• Sources and Uses.
• Debt assumptions (in this example we’re underwriting a bridge-to-HUD, so we include both the bridge and HUD loan).
• NOI-to-cashflow conversion estimates.
• Historical and projected cash-on-cash return based on our assumed capital stack.
• If we have square footage, we include a discount-to-replacement-cost estimate using NICMap construction cost data.
With this model our throughput significantly increased without reducing the quality of our analysis.
We’re happy to share the template with anyone. If interested, reply/DM me and I'll send you a link.
Monthly expenses at our building in Naples since we acquired it.
This is what happens when you replace an unfocused large operator with a focused local one.
For 51 senior housing transactions since January 2024 we know both broker pricing guidance and the subsequent transaction price. We reviewed 330 deals but transaction price is the hardest data point to collect.
23 traded below guidance, 9 traded at guidance, and 19 traded above.
Only 12 traded at a +/- 10% delta to guidance.
The most frequent bucket was deals trading 5-10% below guidance.
We also investigated correlations between transaction price as a percentage of pricing guidance ("Transaction Delta") and vintage, NOI margin, revenue per occupied room (revPOR), and facility size.
We found no discernable relationship between Transaction Delta and revPOR or facility size (# of units).
We saw some correlation between Transaction Delta and vintage (middle chart).
The relationship with NOI margin (bottom chart) was erratic, except at the low end where poor margins predicted deeper discounts to guidance.
Two clear takeaways are:
(1) There is a reasonably normal distribution of transaction prices around guidance. This surprised us - we were expecting a skew towards under guidance.
(2) Newer construction is more likely to trade above guidance than older construction.
One limitation of this data - it doesn’t capture the many deals that don’t trade because guidance is too high. Still, we found it useful.
Assisted living values bottomed in 2023. Buying now is buying into the upswing.
Data credit: @SeniorCare_Inv
On one hand, in the context of elder care, I'm skeptical that AI will lead to any rapid technological developments that alleviate the need for human caregivers because:
(i) older folks tend to be reluctant to adopt new technologies;
(ii) Home care is not just about monitoring, but also the provision of physical assistance (dressing, bathing, medications, etc.); and
(iii) physical assistance means robots, and robot caregivers will be heavily regulated / slow to be approved by regulators.
On the other hand, as AI automates away other jobs, more people seeking work may consider entering the caregiver profession.
That would have significant positive consequences for home care agencies and senior living communities.
We've reviewed and recorded 314 senior housing deals during our 15-month company history, and we're releasing a new content series analyzing the dataset. We're calling it 𝗦𝗶𝗹𝘃𝗲𝗿 𝗪𝗮𝘃𝗲 𝗠𝗮𝗿𝗸𝗲𝘁 𝗖𝘂𝗿𝗿𝗲𝗻𝘁𝘀.
We didn't review every listing, but we tried. Every deal we saw, we catalogued. The only missing deals are those we weren't sent. Off-market deals are included too.
Our Chief Microsoft Power BI Wizard (@elan) and I used the program to slice and dice our dataset, and we have loads of interesting takeaways.
This chart shows what we've all been feeling - 2025, thus far, is very different from 2024. There are more stabilized listings, and pricing guidance is higher.
We'll be releasing more insights via social media, and the series will culminate in a long-form report released via our mailing list. Subscribe via link in bio.
We spent $200k on exterior painting and landscaping for our Naples building and it paid for itself.
My partner @elanruggill's Mother-in-law lives in Naples, and her friend told her about the delightful assisted living facility around the corner with new ownership and a new look.
We've netted 12 move-ins since these projects were completed. Granted, we also have a strong new leadership team in place that helps.
(Left is old, right is new).
Slow and steady!
