Lease-by-Lease Modeling: How to Underwrite Tenant Rollover, Renewal Probability, and Cash Flow at Every Expiration

Key Takeaways

What Lease-by-Lease Modeling Is and Why It Matters

Every multi-tenant commercial property has a lease expiration schedule. Tenants signed at different times, for different terms, at different rents. Some will renew. Some will leave. The question for any acquirer, lender, or asset manager is: what happens to cash flow as each lease rolls?

The lease-by-lease approach answers that question one tenant at a time. Rather than applying a single vacancy rate and a single rent growth rate to the entire building, the model tracks each tenant's lease individually. It asks: when does this tenant's lease expire? What is the probability that this tenant renews? If they renew, at what rent and what TI allowance? If they leave, how long will the space sit vacant, what will the new lease look like, and what will the re-tenanting costs be?

The alternative is aggregate vacancy modeling. In an aggregate model, the analyst applies a stabilized vacancy rate (say 8%) and a market rent growth rate (say 3% per year) to the entire building. The model does not know which tenants are expiring, when they expire, or what their individual renewal economics look like. It treats rollover risk as a smooth, predictable drag on revenue rather than the lumpy, concentrated event that it actually is.

Both approaches produce a cash flow projection. But they produce different numbers, and the difference matters. PropertyMetrics explains that market leasing assumptions require two distinct sets of inputs: one for tenant renewals and one for new tenants. The renewal assumptions are often at a discount to market because renewing a tenant already in place costs less than finding and building out space for a new one. The lease-by-lease model is the framework that makes those two-path economics operational.

The lease-by-lease approach is standard practice on institutional acquisitions of multi-tenant office, retail, and industrial properties. Lenders require it for construction and bridge loans on transitional assets. Asset managers use it to track rollover exposure across portfolios. The methodology is not new. But the gap between how it should be done and how it is actually done in practice remains wide. Most analysts understand the concept. Fewer build it correctly.

Starting from the Rent Roll

The rent roll is the foundation of the lease-by-lease model. It is the source document that tells you who is in the building, how much space they occupy, what they are paying, and when their leases expire. Every input in the rollover model traces back to a line item on the rent roll.

A complete rent roll for modeling purposes includes the following fields for each tenant: tenant name, suite number, rentable square footage, lease commencement date, lease expiration date, current base rent per square foot, annual escalation structure (fixed steps, CPI-based, or percentage), any free rent or abatement periods remaining, renewal option terms (if any), and tenant credit quality or rating.

The rent roll typically comes from the seller's offering memorandum or directly from the property management company. The first step in the modeling process is to reconcile the rent roll against the trailing twelve months (T-12) of operating statements. The sum of contractual base rents on the rent roll should match the base rental revenue line on the T-12 within 1% to 2%. If it does not, there is either a data error, a tenant that moved in or out during the trailing period, or a free rent concession that is suppressing actual collections.

Organizing the Rent Roll for Rollover Analysis

Once reconciled, the rent roll needs to be reorganized for rollover analysis. Sort tenants by lease expiration date, earliest to latest. This sorting immediately reveals the rollover concentration: how much square footage expires in each year of the hold period. A building where 60% of the square footage expires in a single year has a fundamentally different risk profile than one where expirations are spread evenly.

Next, calculate each tenant's share of total building square footage and total base rent. A 40,000 square foot anchor tenant paying $28 per square foot is a different modeling problem than ten 4,000 square foot tenants paying $35 per square foot, even if the total square footage is the same. The anchor tenant's renewal probability, TI budget, and downtime assumptions are all different from the small tenants. The rent roll analysis surfaces these differences before the cash flow model is built.

Finally, note each tenant's in-place rent relative to the current market rent. This is the mark-to-market analysis that will drive the rent adjustment at rollover. A tenant paying $28 per square foot in a market where comparable space leases for $36 per square foot has $8 per square foot of loss-to-lease that becomes upside at renewal or re-leasing. A tenant paying $40 per square foot in the same market has $4 per square foot of gain-to-lease that represents downside risk at expiration.

Renewal Probability by Tenant Type

Renewal probability is the single most influential assumption in the lease-by-lease model. It determines the weighting between two fundamentally different cash flow outcomes at each expiration: the lower-cost, no-downtime renewal scenario versus the higher-cost, downtime-laden vacancy scenario. Getting this assumption wrong by 15 to 20 percentage points can swing the property valuation by 5% to 10%.

Renewal probability is not a random variable. It correlates strongly with tenant type, credit quality, industry, remaining lease term, and the tenant's investment in their space. CBRE's 2025 Americas Office Occupier Sentiment Survey found that 86% of office occupiers indicated plans to renew their current leases, driven by high relocation costs and the difficulty of assessing alternative space during periods of market uncertainty. That headline number, however, obscures the wide variation beneath it.

Credit Anchor Tenants: 75% to 85%

Credit anchor tenants are investment-grade corporations or government entities occupying 20,000 square feet or more with lease terms of seven to fifteen years. These tenants have made substantial investments in their space. They have built out executive floors, trading floors, data centers, or specialized lab and research facilities. The cost of relocating is measured in millions of dollars and months of disruption.

Renewal probability for credit anchors runs 75% to 85%. The primary risk factor is corporate restructuring: a merger, an acquisition, a headquarters relocation, or a strategic decision to consolidate into a single campus. These events are difficult to predict but are low-frequency. In the absence of a corporate event, credit anchors overwhelmingly renew. The negotiation is about terms (rent, TI allowance, lease length), not about whether they stay.

When modeling credit anchor renewals, the key assumption is the renewal rent. Anchors have leverage. They know the landlord cannot afford to lose a 30,000 square foot tenant. Renewal rents for anchors typically come in at 0% to 5% below market because the landlord accepts a slight discount to avoid the catastrophic downtime and re-tenanting cost of losing the anchor. TI allowances on anchor renewals are modest: $10 to $20 per square foot for cosmetic refreshes, not full buildouts.

National Chain Tenants: 65% to 75%

National chain tenants are multi-location businesses with standardized space requirements: law firms with regional offices, accounting firms, insurance companies, bank branches, national retailers, and restaurant chains. These tenants operate on portfolio strategies. Their renewal decision is driven by the performance of the specific location relative to the portfolio, the remaining depreciation on the buildout, and the availability of comparable space in the submarket.

Renewal probability for national chains runs 65% to 75%. The lower bound applies to tenants in underperforming locations or tenants whose portfolio strategy is shifting (e.g., a retailer closing marginal stores or a law firm consolidating regional offices). The upper bound applies to tenants with strong location-specific performance and significant remaining buildout investment.

National chain renewals tend to be more formulaic than anchor renewals. The tenant's real estate team has standard lease parameters. Renewal rents for national chains typically land at market or within 2% to 3% of market. TI allowances run $15 to $25 per square foot for a mid-cycle refresh. The modeling risk is not the renewal terms but the binary question of whether the chain decides to close the location entirely.

Local and Regional Tenants: 50% to 65%

Local and regional tenants are single-location or multi-location businesses with a geographic footprint limited to one metro area or region. This category includes local professional services firms (lawyers, accountants, consultants), medical practices, regional retailers, and mid-size companies with 20 to 200 employees.

Renewal probability for local tenants runs 50% to 65%. The variance is wider than for national tenants because local businesses are more sensitive to economic cycles, more likely to outgrow or downsize their space, and more likely to relocate for personal reasons (the principal's commute, a lease opportunity at a competing building). Local tenants also have less negotiating leverage, so renewal terms are closer to market. TI allowances on renewals run $10 to $15 per square foot.

The modeling challenge with local tenants is that their renewal decision is harder to predict from the outside. There is no portfolio strategy to analyze, no public financial data to review, and no corporate announcement to anticipate. The analyst relies on lease vintage (tenants who have been in the building for multiple renewal cycles are more likely to renew again), tenant industry (stable industries like healthcare and legal have higher retention than cyclical industries like construction and real estate), and the tenant's remaining buildout value.

Small and Startup Tenants: 35% to 50%

Small tenants occupy fewer than 3,000 square feet. Startup tenants are early-stage companies with limited operating history and uncertain growth trajectories. These tenants are the most volatile component of any multi-tenant rent roll.

Renewal probability for small and startup tenants runs 35% to 50%. Many of these tenants are on short-term leases (two to three years) to begin with. Their space requirements change rapidly as they grow or contract. Some will outgrow their suite and move to a larger space in the same building or a different building. Some will fail entirely. Some will be acquired by larger companies. The churn rate for small tenants is two to three times higher than for anchors.

The saving grace for the landlord is that small tenant spaces are easier to re-lease. A 1,500 square foot suite in a Class B office building has a deeper market than a 40,000 square foot anchor floor. Downtime on small spaces is typically shorter (two to four months versus four to eight months for large spaces), and TI costs per square foot are lower because small suites are often leased with standard finishes or minimal buildout.

The Two-Path Framework: Renew vs Vacate

At every lease expiration, two things can happen. The tenant renews, or the tenant vacates. Each outcome carries a different cost structure, a different revenue trajectory, and a different timeline. The lease-by-lease model builds both paths for every tenant and then weights them by renewal probability to produce an expected cash flow.

Adventures in CRE demonstrates this two-path methodology in their tenant rollover analysis model series, showing how the renewal and vacancy scenarios are constructed in Excel with separate assumption sets that feed into a probability-weighted outcome. The concept is straightforward. The execution requires discipline.

Path 1: Renewal

In the renewal scenario, the tenant stays. The key assumptions are: renewal rent (often set at the lesser of market rent or a negotiated rate that reflects the tenant's leverage), renewal TI allowance ($10 to $25 per square foot for office, depending on lease term and tenant size), leasing commission (2% to 4% of total lease value, paid to the tenant's broker), and downtime (zero months, because the tenant does not vacate). The renewal scenario preserves cash flow continuity. There is no gap in rent collection, no re-tenanting risk, and no speculative exposure to future market conditions.

Path 2: Vacancy and Re-Leasing

In the vacancy scenario, the tenant leaves. The key assumptions are: downtime (the number of months the space sits vacant before a new tenant begins paying rent), new tenant rent (set at projected market rent at the time of the new lease commencement), new tenant TI allowance ($40 to $80 per square foot for office, reflecting a full buildout), leasing commission (4% to 6% of total new lease value, paid to both the listing and tenant brokers), and free rent concession (one to three months, common in competitive office markets).

The vacancy scenario produces higher long-run revenue if market rents exceed in-place rents (the mark-to-market upside), but it also produces a period of zero revenue during downtime, a large upfront capital expenditure for tenant improvements, and significant leasing commission expense. The net present value of the vacancy scenario is often lower than the renewal scenario even when the new lease rate is higher, because the costs and downtime erode the rent premium.

Probability-Weighted Outcome

The expected cash flow at each expiration is the probability-weighted average of the two paths. If the renewal probability is 70%, the model weights the renewal scenario at 70% and the vacancy scenario at 30%. The weighted outcome captures the expected TI/LC spend, the expected downtime, and the expected rent trajectory in a single number.

This weighting is the core mechanism of the lease-by-lease model. It is what distinguishes the approach from aggregate vacancy modeling, which applies a single vacancy rate to the entire building without differentiating between the two outcomes. The probability-weighted approach produces a more accurate estimate of expected cash flow because it accounts for the asymmetric cost structure of renewal versus vacancy.

Downtime Assumptions by Asset Class

Downtime is the period between when a tenant vacates and when a replacement tenant begins paying rent. It is one of the most punishing variables in the rollover model because it produces zero revenue on space that still carries operating expenses, debt service, and property taxes. Downtime assumptions must reflect the reality of the specific asset class, submarket, and space size. Using a generic assumption across all tenant types and asset classes is a common source of modeling error.

Office: 3 to 6 Months (General), 6 to 12 Months (Large Blocks)

Office downtime varies with space size and market conditions. Small suites under 5,000 square feet in well-located Class A or B buildings can be re-leased in three to four months in a healthy market. The space may already be built out to a standard configuration, and the tenant pool for small suites is deep.

Mid-size spaces of 5,000 to 15,000 square feet typically require four to six months of downtime. The prospective tenant pool is narrower, the TI buildout takes longer, and the lease negotiation for mid-size spaces involves more complexity than a small suite lease.

Large blocks of 15,000 square feet or more can sit vacant for six to twelve months or longer. JLL's Q2 2026 U.S. Office Market Dynamics report shows that total vacancy rates are declining, with a 60 basis point reduction quarter over quarter, but availability for large blocks remains elevated in many submarkets. A 30,000 square foot vacancy in a Class B suburban office building can take twelve to eighteen months to fill in a soft market.

The lease-by-lease model should assign downtime assumptions at the individual tenant level based on space size, building class, and submarket conditions. A blanket six-month assumption across all tenants understates the risk on large spaces and overstates it on small ones.

Retail: Variable by Tenant Type

Retail downtime is driven by the distinction between anchor tenants and inline tenants. Inline retail spaces of 1,000 to 5,000 square feet in well-trafficked centers can be re-leased in two to four months. The spaces are relatively generic and the tenant pool (restaurants, service providers, specialty retail) turns over frequently.

Anchor spaces are a different story entirely. A 40,000 square foot former grocery anchor or 60,000 square foot department store anchor can sit vacant for six to twelve months in a strong market and twelve to twenty-four months or more in a weak one. Anchor spaces often require significant capital to re-demise (splitting the space into smaller units) or re-tenant (attracting a new anchor), and the loss of an anchor can trigger co-tenancy clauses that allow inline tenants to reduce their rent or terminate their leases.

Industrial: 1 to 3 Months

Industrial is the fastest-absorbing asset class. Warehouse and distribution space in logistics corridors can be re-leased in one to three months. The space is essentially a box with a clear height and truck court. There is minimal buildout, and the industrial tenant pool has been expanding for a decade as e-commerce continues to drive demand for distribution space. Even in 2026, with industrial vacancy rates normalizing from their pandemic lows, downtime for standard warehouse space remains short.

Specialized industrial space (cold storage, life sciences, manufacturing with heavy power requirements) has longer downtime because the tenant pool is narrower and the space requirements are more specific. Three to six months is a reasonable assumption for specialized industrial.

Mark-to-Market Rent Adjustments

Mark-to-market analysis compares each tenant's in-place rent to the current (or projected) market rent at the time of lease expiration. The gap between in-place and market rent determines whether the rollover event represents upside or downside for the landlord. This analysis is performed tenant by tenant in the lease-by-lease model, which is one of the primary advantages of the approach over aggregate vacancy modeling.

Loss-to-Lease: In-Place Rent Below Market

Loss-to-lease exists when a tenant's in-place rent is below the current market rent for comparable space. This is common for tenants who signed long-term leases (seven to ten years) in a market that has experienced significant rent growth since lease execution. A tenant paying $28 per square foot on a lease signed in 2019 in a submarket where comparable space now leases for $36 per square foot has $8 per square foot of loss-to-lease.

Loss-to-lease represents embedded upside at rollover. Whether the tenant renews or vacates, the next lease will be executed at or near market rent. If the tenant renews, the renewal rent will be negotiated in the context of current market conditions. The tenant may get a modest discount (2% to 5% below market), but the rent still resets substantially higher than the expiring lease. If the tenant vacates, the new tenant will pay market rent.

The lease-by-lease model captures this upside at the specific year of expiration for each below-market tenant. An aggregate model using a blended rent growth rate partially captures the same effect but spreads it evenly across all years rather than concentrating it in the years when below-market leases actually expire. The timing difference matters for IRR calculations, where earlier cash flows are more valuable than later ones.

Gain-to-Lease: In-Place Rent Above Market

Gain-to-lease exists when a tenant's in-place rent exceeds the current market rent. This is less common but occurs in markets that have experienced rent declines (as many office markets did from 2020 to 2024), in buildings where the landlord granted aggressive concessions at lease signing that are now embedded in a high face rent with offsetting free rent or TI, and in suites where the tenant's specialized buildout makes them reluctant to relocate despite paying above-market rent.

Gain-to-lease represents downside risk at rollover. If the tenant vacates, the new lease will be at market rent, which is lower than the expiring rent. If the tenant renews, the renewal negotiation will be contentious because the tenant knows they are overpaying relative to market and will demand a rent reduction. The renewal rent in a gain-to-lease situation typically resets to market or within 1% to 2% of market, erasing the gain-to-lease premium.

The lease-by-lease model flags gain-to-lease tenants as specific risk concentrations. If a building's two largest tenants are both paying 15% above market and their leases expire in the same year, the mark-to-market reset at that rollover event will produce a meaningful drop in NOI regardless of whether the tenants renew or vacate. An aggregate model would not surface this concentration.

Projecting Market Rent at Future Expiration Dates

The mark-to-market calculation requires a market rent assumption not just for today but for the year each lease expires. If a tenant's lease expires in Year 4 of a seven-year hold, the relevant comparison is the tenant's in-place rent at expiration versus projected market rent in Year 4.

Market rent projections use a growth rate applied to today's market rent. Growth rates should be supported by historical submarket data, broker forecasts, and the analyst's view on supply-demand dynamics. A common approach is to use the trailing five-year CAGR for the submarket as the base case, adjusted upward or downward for known supply additions, demand shifts, or macroeconomic factors.

Typical office market rent growth assumptions range from 2% to 4% per year in stable markets, 0% to 2% in oversupplied markets, and 4% to 6% in supply-constrained markets with strong demand drivers. Industrial rent growth assumptions have been higher (4% to 8% per year) in logistics-heavy markets, though the pace has moderated from pandemic-era levels.

TI/LC Differentials at Rollover

Tenant improvement (TI) allowances and leasing commissions (LC) are below-the-line capital costs that reduce the net cash flow available to equity. They are not operating expenses. They hit below NOI but above free cash flow, and they must be funded from operating cash flow, reserves, or additional equity draws. The differential between renewal TI/LC and new tenant TI/LC is one of the most significant cost variables in the rollover model.

Office TI/LC: Renewal vs New Tenant

Office renewal TI allowances typically range from $10 to $25 per square foot. The tenant is already in occupancy. The buildout exists. The renewal TI covers cosmetic updates: new carpet, fresh paint, updated lighting, and perhaps minor reconfiguration of private offices or common areas. The landlord is not building a space from scratch. The landlord is maintaining a space to retain a tenant.

New tenant TI allowances for office space range from $40 to $80 per square foot. This reflects the cost of a full buildout from shell condition (or a gut and rebuild of the prior tenant's space). The new tenant TI includes demolition of the existing buildout, new partitions, new electrical and data wiring, new HVAC distribution, restroom renovation (if the suite has private restrooms), kitchen/pantry buildout, reception area, conference rooms, and finish materials. In Class A buildings in major markets, new tenant TI on a full-floor lease can exceed $100 per square foot for a premium fit-out.

Leasing commissions on renewals run 2% to 4% of total lease value (base rent times square footage times lease term). On new leases, commissions run 4% to 6% because both the listing broker (landlord's representative) and the tenant's broker are paid. In some markets, the total commission on a new lease reaches 6% to 8% of gross lease value for large transactions with long terms.

Consider the math on a 15,000 square foot tenant signing a five-year renewal at $34 per square foot versus a new tenant signing at $36 per square foot.

The new tenant scenario costs $1,020,000 more than the renewal scenario. The new tenant pays $2 per square foot more in rent ($36 versus $34), which generates $30,000 per year in additional revenue, or $150,000 over the five-year term before escalations. The incremental cost of losing the tenant and re-leasing to a new one exceeds the incremental revenue by $870,000 on an undiscounted basis. This is why landlords aggressively pursue renewals and why renewal probability is the most important assumption in the model.

Retail and Industrial TI/LC

Retail TI allowances for renewals are generally lower than office: $5 to $15 per square foot for inline tenants, $10 to $25 per square foot for junior anchors. New tenant TI for retail runs $25 to $60 per square foot, with the high end for restaurant and food service tenants that require kitchen exhaust, grease traps, and specialized MEP.

Industrial TI allowances are the lowest across asset classes. Industrial renewal TI is typically $2 to $8 per square foot (cosmetic: floor recoating, restriping, minor dock leveler repairs). New industrial tenant TI runs $5 to $20 per square foot for standard warehouse, higher for tenants requiring office buildout within the warehouse shell. Leasing commissions on industrial are similar to office at 4% to 6% for new leases and 2% to 4% for renewals.

Worked Example: Five-Tenant, 80,000 SF Office Building

The following worked example walks through a lease-by-lease cash flow model for a five-tenant, 80,000 square foot suburban office building over a seven-year hold period. The purpose is to demonstrate the mechanics of the lease-by-lease approach and to compare the result against an aggregate vacancy model applied to the same building.

The Rent Roll

Total in-place base rent: $2,474,000 per year. Current market rent in the submarket: $34.00 per square foot. Market rent growth assumption: 3% per year. Building operating expenses: $12.00 per square foot. Acquisition price: $9,600,000 ($120/SF). Exit cap rate: 7.5%. Hold period: 7 years.

Mark-to-Market Position

Before building the cash flow, assess the mark-to-market position for each tenant relative to projected market rent at their expiration date.

All five tenants are below projected market rent at expiration. This is a favorable mark-to-market position. The building has embedded rental upside that will be realized at rollover. The magnitude varies: Tenant B has the largest gap at $8.06 per square foot, while Tenant E has only $2.06.

Lease-by-Lease Rollover Assumptions

For each tenant, the model builds two scenarios with the following assumptions.

Renewal scenario assumptions. Renewal rent: projected market rent minus 3% (reflecting tenant negotiating leverage). Renewal TI: $15/SF for the law firm and insurance company, $12/SF for the marketing agency and accounting firm, $10/SF for the startup. Renewal LC: 3% of total lease value. Downtime: zero months. Lease term on renewal: five years.

Vacancy scenario assumptions. New lease rent: projected market rent at lease commencement (after downtime). New tenant TI: $55/SF for the law firm and insurance company spaces, $50/SF for the marketing agency and accounting firm spaces, $45/SF for the startup space. New lease LC: 5% of total lease value. Free rent: two months. Downtime: six months for the law firm (25,000 SF), five months for the insurance company (20,000 SF), four months for the marketing agency and accounting firm (15,000 and 12,000 SF), and three months for the startup (8,000 SF). Lease term on new lease: seven years.

Year-by-Year Cash Flow

Year 1. No lease expirations. All five tenants are in place paying contractual rent. Base rental income: $2,474,000. Operating expenses: $960,000 ($12/SF x 80,000 SF). NOI: $1,514,000. No TI/LC spend.

Year 2. Two expirations: Tenant B (20,000 SF, 80% renewal probability) and Tenant E (8,000 SF, 40% renewal probability). This is the first rollover event and it concentrates 35% of the building's square footage.

Tenant B probability-weighted outcome: 80% chance of renewal at $34.98/SF (market minus 3%) with $300,000 TI and $104,940 LC. 20% chance of vacancy with five months downtime, $1,100,000 TI, $252,420 LC, and $120,100 in free rent. Weighted TI/LC spend: (0.80 x $404,940) + (0.20 x $1,472,520) = $618,456. Weighted revenue loss from downtime: 0.20 x 5 months x $60,100/month = $60,100.

Tenant E probability-weighted outcome: 40% chance of renewal at $34.98/SF with $80,000 TI and $41,976 LC. 60% chance of vacancy with three months downtime, $360,000 TI, $121,298 LC, and $48,080 in free rent. Weighted TI/LC spend: (0.40 x $121,976) + (0.60 x $529,378) = $366,417. Weighted revenue loss from downtime: 0.60 x 3 months x $24,040/month = $43,272.

Year 2 total weighted TI/LC spend: $984,873. Year 2 weighted revenue loss from downtime: $103,372. Base rental income after mark-to-market resets on expiring tenants: approximately $2,632,000 (reflecting higher rents on renewed/re-leased space). NOI after expenses: approximately $1,672,000. Cash flow after TI/LC: approximately $687,127.

Year 3. One expiration: Tenant A (25,000 SF, 70% renewal probability). This is the building's largest tenant. Weighted TI/LC spend: (0.70 x $487,500) + (0.30 x $1,717,500) = $856,500. Weighted downtime revenue loss: 0.30 x 6 months x $77,396/month = $139,313. The Year 3 cash flow after TI/LC drops significantly because of the anchor tenant rollover event. This is the kind of concentration risk that aggregate models miss entirely.

Year 4. One expiration: Tenant C (15,000 SF, 55% renewal probability). This tenant has the lowest renewal probability among the mid-size tenants. Weighted TI/LC spend: (0.55 x $301,500) + (0.45 x $1,076,625) = $650,306. Weighted downtime revenue loss: 0.45 x 4 months x $47,838/month = $86,108.

Year 5. One expiration: Tenant D (12,000 SF, 60% renewal probability). Weighted TI/LC spend: (0.60 x $245,160) + (0.40 x $837,504) = $482,098. Weighted downtime revenue loss: 0.40 x 4 months x $39,420/month = $63,072.

Years 6 and 7. No original lease expirations. Tenants who renewed in Years 2 through 5 on five-year terms do not roll again during the hold. Cash flow stabilizes at the post-rollover rental rates with annual escalations. TI/LC spend is zero. These are the highest cash flow years in the hold period.

Hold-Period Summary: Lease-by-Lease

Total TI/LC spend over the hold: $2,973,777. Total downtime revenue loss: $391,865. Exit value at Year 7 NOI of $2,200,000 and 7.5% cap rate: $29,333,333. Acquisition price: $9,600,000. Levered IRR (assuming 65% LTV at 6.5% interest): approximately 14.2%.

The Same Building Under Aggregate Vacancy Modeling

Now model the same building using aggregate assumptions. Starting rent: $30.93/SF (weighted average in-place rent). Market rent growth: 3% per year. Stabilized vacancy: 8%. Annual TI/LC reserve: 5% of effective gross income. No tenant-level modeling. No individual renewal probabilities. No rollover-specific downtime.

Total TI/LC reserve over the hold: $872,019. Exit value at Year 7 NOI of $1,757,758 and 7.5% cap rate: $23,436,773. Levered IRR: approximately 12.1%.

The IRR Difference

This comparison illustrates a critical point. The two models are not just producing different numbers. They are telling different stories about the same asset. The lease-by-lease model says: this building has concentrated rollover risk in Years 2 and 3, significant mark-to-market upside, and strong stabilized cash flow once the rollovers are completed. The aggregate model says: this building produces a smooth, gradually increasing cash flow stream with a constant drag from vacancy and TI/LC. The lease-by-lease story is more accurate and more useful for making acquisition and asset management decisions.

When to Use Lease-by-Lease vs Aggregate Vacancy Modeling

The lease-by-lease approach is not always necessary. The right methodology depends on the property type, the purpose of the analysis, and the quality of the available data.

Use Lease-by-Lease When:

• The property has five or fewer tenants. Each tenant represents a material share of the building's income. The loss of any single tenant produces a measurable impact on cash flow and valuation. Aggregate vacancy assumptions cannot capture the binary risk of losing a major tenant.
• Rollover is concentrated. If more than 30% of the building's square footage expires within a two-year window, the rollover event is too significant to smooth. The lease-by-lease model captures the capital impact and revenue disruption of concentrated expirations.
• Mark-to-market gaps are large. If individual tenants are paying 15% or more above or below market rent, the rollover event will produce a meaningful rent reset. Aggregate growth rates will not capture the magnitude or timing of the adjustment.
• The deal involves transitional or value-add underwriting. Lease-up, repositioning, and renovation business plans depend on specific leasing timelines for specific spaces. Aggregate models cannot track the sequence of events that drives value creation.
• Lenders require it. Most construction, bridge, and transitional lenders require lease-by-lease cash flow projections as part of the underwriting package. Aggregate models are not acceptable for loan submissions on multi-tenant transitional assets.

Aggregate Vacancy May Suffice When:

• The property has 20 or more tenants with no single tenant exceeding 10% of revenue. The law of large numbers applies. Individual rollover events are too small to move the needle, and the aggregate vacancy rate is a reasonable approximation of the blended rollover experience.
• The building is fully stabilized with staggered expirations. If lease expirations are distributed evenly across the hold period and in-place rents are near market, the aggregate approach produces a result close to the lease-by-lease approach with significantly less modeling effort.
• The analysis is a screening-level assessment, not an acquisition underwriting. For portfolio-level analysis, market surveys, or initial deal screening, aggregate assumptions provide a reasonable approximation without the time investment of building a tenant-by-tenant model.

CRE Wisdoms notes that rollover analysis reveals the concentration of risk within a property's income stream. A single expiration may not be alarming by itself, but when several leases expire in the same year, the combined rollover exposure can be significant. This concentration risk is precisely what the lease-by-lease model is designed to capture and what aggregate models smooth away.

Common Modeling Errors in Lease-by-Lease Analysis

1. Using a single renewal probability for all tenants. A 65% renewal probability is not wrong as a portfolio-level average, but it is wrong when applied to a credit anchor tenant (who renews at 80%+) and a startup tenant (who renews at 40%) simultaneously. The model must differentiate by tenant type, size, and credit quality. A single blended rate eliminates the information advantage that the lease-by-lease approach is designed to provide.

2. Ignoring the TI/LC timing mismatch. TI/LC costs are incurred upfront, at the time of lease execution. The revenue benefit of the new lease is realized over the lease term. Spreading TI/LC evenly across the hold (as aggregate models do) understates the capital impact in rollover years and overstates it in non-rollover years. The cash flow model must show TI/LC as a lump-sum expenditure in the year incurred, not as a smoothed annual reserve.

3. Applying the same downtime to all spaces. A 3,000 square foot suite and a 30,000 square foot anchor floor do not have the same re-leasing timeline. Downtime should vary by space size, building class, and submarket absorption velocity. Using a flat six-month assumption across all tenants overstates downtime on small spaces and understates it on large ones.

4. Forgetting to grow market rent to the expiration date. A common error is comparing in-place rent to today's market rent rather than projected market rent at the expiration date. A tenant paying $30/SF with a lease expiring in Year 5 should be compared to Year 5 market rent (today's market rent grown at the assumed growth rate for five years), not today's market rent. This error systematically understates the mark-to-market upside (or downside) at future expirations.

5. Modeling renewal rent at current market rather than at a discount. Renewal rents are negotiated, and tenants have leverage. A tenant who has been in the building for ten years, has a specialized buildout, and generates reliable cash flow is not going to pay a premium to stay. Renewal rents typically come in 2% to 5% below market. Modeling renewals at full market rent overstates renewal revenue and understates the cost of tenant retention.

6. Not stress-testing the concentrated rollover year. If 40% of the building rolls in a single year, the base case should be stress-tested at lower renewal probabilities (what if the anchor does not renew?), longer downtime (what if the market softens?), and higher TI (what if construction costs escalate?). The concentrated rollover year is the risk event. The model should quantify the downside scenario, not just the probability-weighted expected outcome.

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Related Articles

• Operating Cash Flow Projection: Drivers and Assumptions. The foundation of any cash flow model. How to build the revenue and expense projections that feed the lease-by-lease rollover analysis.
• Below-the-Line Items: TI, LC, CapEx, and Reserves. A detailed guide to the capital expenditure items that sit between NOI and free cash flow, including the TI/LC mechanics central to rollover modeling.
• Absorption and Lease-Up in Development and Repositioning. How to model the lease-up period for vacant space, including the absorption timeline and concession assumptions that apply when a tenant vacates in the rollover model.
• Hold Period Analysis: IRR vs Equity Multiple. How to evaluate the investment returns produced by the lease-by-lease cash flow model, including the sensitivity of IRR to rollover timing and concentration.
• Office Underwriting: TI, LC, Free Rent, and Effective Rent. The specific cost assumptions for office leasing that feed directly into the rollover model's two-path analysis.