Retail real estate underwriting is part science, part judgment, and part pattern recognition built from years of watching what actually drives outcomes. Here's a practical framework for how we think about evaluating a neighborhood retail center.
Start with the tenant roster
Before you run a single number, look at who's in the building. Not just the names — the categories. What percentage of the tenant base is needs-based versus discretionary? What's the internet-resistance of each tenant's business? What percentage of base rent comes from national or regional credit tenants versus local operators?
Conventional wisdom says a grocery-anchored center is the safest retail real estate you can own. There's logic to that — grocers drive consistent traffic and anchor co-tenant performance. But that anchor is also a single point of failure. If the grocer leaves, foot traffic collapses, co-tenants follow, and backfilling with another grocer is rarely an option. The concentration risk embedded in an anchor-dependent center is real.
Our preference is a different kind of durability: a diversified mix of small, needs-based local operators — restaurants, personal services, health and wellness, boutiques — where no single tenant represents an outsized share of base rent or foot traffic. No single point of failure. If one tenant leaves, the center absorbs it. That's a different underwriting thesis than chasing credit tenants, and we think it's a more honest one for the markets and asset sizes we operate in.
The same logic applies to big box and junior box retail. Our default has been to avoid anchor-dependent formats for two reasons. First, the income math on a large vacancy is punishing — losing an anchor doesn't just mean one empty space, it means lost rent on a disproportionate share of your GLA while you work to backfill, and potentially accelerated co-tenant loss in the meantime. Second, mid-market retail is getting squeezed from both ends of the consumer spectrum, which means the pool of creditworthy large-format tenants is narrower than it used to be and getting narrower.
We'll follow the thesis, not the format.
Lease structure is everything — once you have it
In commercial real estate, the physical asset and the income it produces are two different things — and you need to understand both. The building has intrinsic value: location, structure, replacement cost, and reuse potential. But what converts a physical asset into a financial one is a lease. When you're buying an occupied center, you're really buying a portfolio of contracts sitting on top of a piece of real estate. When you're buying a vacant building or a lease-up opportunity, you're betting on your ability to create those contracts — which is a different kind of underwriting entirely.
Either way, lease structure is what determines the quality and durability of the income. Key questions:
Weighted average lease term (WALT): How many years of contracted income do you have? A center with a 2-year WALT carries enormous rollover risk. A center with a 7-year WALT has a long runway to operate without the distraction of re-leasing.
Lease type: Are leases gross (landlord pays expenses) or triple-net (tenant pays taxes, insurance, maintenance)? Triple-net leases dramatically simplify operations and reduce landlord expense risk. Most institutional retail prefers NNN or modified gross structures.
Rent bumps: Do leases include annual or periodic rent escalations? Fixed bumps of 1.5-2.5% annually, or CPI-linked escalations, matter significantly over a 10-year hold. A center with no rent bumps is gradually losing purchasing-power-adjusted income.
Rollover schedule: When do leases expire, and how concentrated is the rollover? A center with 40% of its leases expiring in the same year creates significant re-leasing execution risk.
NOI quality
Net Operating Income is the top-line metric, but not all NOI is created equal. NOI from a 10-year lease to a national grocery chain is worth more — and should be capitalized at a lower rate — than NOI from a month-to-month local tenant.
Effective gross income adjustments — vacancy allowances, credit loss reserves, and management fees — need to reflect reality, not optimism. A 5% vacancy allowance on a center that's been running at 12% vacancy is a red flag.
NOI quality is ultimately what determines where in the cap rate range a given asset belongs — which is where the next question comes in.
Cap rate context
The cap rate tells you what the market thinks a given NOI stream is worth — but not all NOI streams are equal, and this is where lazy comp analysis gets investors into trouble. Two centers a block apart, built the same year, selling at the same cap rate are not necessarily equivalent investments. The quality of the income matters as much as the quantity. A center with long-term NNN leases, strong credit tenants, staggered rollover, and recently updated capital improvements deserves a different cap rate than one with short-term gross leases, local-only tenants, concentrated rollover risk, and deferred maintenance — even if the headline NOI looks identical.
Cap rates in a given market are also driven by broader forces: interest rates, local supply and demand, asset quality, and investor sentiment. A 7.5% cap rate in suburban Kansas City might represent excellent value. The same cap rate in a severely distressed market with declining population might represent a trap.
The right question isn't "what are cap rates in this market?" It's "what does this specific income stream deserve, given its credit quality, lease structure, capital condition, and rollover risk?" Comparable sales are a starting point, not an answer.
Debt coverage and downside scenarios
How a deal is financed matters as much as what you're buying. Debt amplifies returns in good markets and amplifies pain in bad ones — and the terms you accept at acquisition can become constraints you can't escape at refinance or sale. We've been on both sides of that equation, and the lessons from the bad side inform how we underwrite every deal today.
Loan-to-value (LTV) measures debt against appraised value. Loan-to-cost (LTC) measures debt against total project cost — more relevant when significant renovation or lease-up is involved. Lower leverage means more equity required upfront but more cushion if values decline. Most institutional lenders on stabilized retail want to see LTV in the 65-75% range. Higher leverage is available, but the margin for error shrinks accordingly.
The debt coverage ratio (DCR) — NOI divided by annual debt service — tells you how much cushion exists between income and the mortgage payment. A DCR of 1.25x means income can drop 20% before you're in trouble. A DCR of 1.05x means you have almost none.
The scenario most pro formas don't show you is the bad refi. If you need to refinance in a higher rate environment with flat or declining NOI, the debt you can support against the same income shrinks, which means either bringing cash to the table, selling at a price that reflects the new rate environment, or getting stuck in an extension you didn't plan for. Sponsors who took on floating rate debt without hedging between 2022 and 2023 learned this the hard way.
We stress test every deal by modeling what happens if occupancy drops to historical market lows, if rents don't grow, and if the exit cap rate is 50-75 basis points higher than assumed — and we look at what a bad refinance environment does to the hold period and return profile. If the deal still works in those scenarios, we have high conviction. If it only works in the base case, we pass.
The bottom line
Underwriting a shopping center well isn't about running the numbers faster than the next buyer. It's about asking better questions before the numbers ever get built. Who are the tenants and how durable is their business? What does the lease structure actually look like underneath the headline NOI? What does this income stream deserve to be capitalized at, given its real quality? And what happens to the deal when things don't go according to plan?
The operators who get this right over time aren't the ones with the most aggressive assumptions. They're the ones who've stress-tested their conviction before they write the check — and have the pattern recognition to know the difference between a deal that's priced for the risk and one that's just priced.