Renewal Probability and Lease Rollover Analysis by Tenant Type: The Institutional Underwriting Guide

Key Takeaways

What Renewal Probability Means

Renewal probability is the likelihood, expressed as a percentage, that an existing tenant will sign a new lease when the current lease term expires. It is an underwriting assumption, set by the analyst based on observable characteristics of the tenant, the property, and the market. No formula produces it. No database contains it.

In a discounted cash flow model, renewal probability governs what happens at every lease expiration event during the projection period. If a tenant's renewal probability is set at 75%, the model assumes a 75% chance that the tenant renews (at market rent, with renewal tenant improvements and renewal leasing commissions) and a 25% chance that the tenant vacates (triggering downtime, new tenant improvements, new leasing commissions, and possibly free rent concessions for the replacement tenant). These two scenarios produce different cash flow streams. The model weights them by the assigned probability and blends them into a single projected NOI line.

Renewal probability affects every lease expiration event in the pro forma, and the effects compound. A lower renewal probability means more assumed vacancy, higher assumed leasing costs, and lower projected NOI. A higher renewal probability means less vacancy, lower costs, and higher NOI. The sensitivity is non-linear because turnover costs compound: a vacating tenant triggers not just direct costs (TI, LC, free rent) but also indirect costs (lost rent during downtime, higher operating expense recovery gaps, and, in multi-tenant buildings, potential co-tenancy triggers for neighboring tenants).

The term "rollover" refers to the event itself. When a lease reaches its expiration date, the tenant either renews or rolls over (vacates). Rollover analysis is the process of examining every lease expiration in a building's rent roll, assigning a renewal probability to each, and modeling the cost and timing implications across the hold period. In institutional underwriting, this analysis is performed tenant by tenant, not as a single blended building-wide assumption.

Renewal Probability Benchmarks by Tenant Type

Renewal probability varies more by tenant type than by any other single factor. The tenant's credit quality, operational flexibility, space requirements, and corporate real estate strategy all influence whether they are likely to stay or leave. Institutional underwriters segment tenants into four broad categories, each with a benchmark range established through decades of observed behavior across the NCREIF Property Index universe and individual portfolio data.

Credit Tenants: 85% to 95%

Credit tenants are tenants with investment-grade credit ratings (BBB- or higher from S&P, Baa3 or higher from Moody's). They include large law firms, accounting firms, financial institutions, Fortune 500 corporate headquarters, federal government agencies, and large healthcare systems. These tenants renew at the highest rates for structural reasons: their space is typically purpose-built with significant tenant-funded improvements, their relocation costs are enormous (both financial and operational), and their corporate real estate decisions are made by committees with long planning horizons.

A credit tenant occupying 50,000 SF of Class A office space with a custom build-out faces relocation costs of $3 million to $7 million (moving, new TI above allowance, technology infrastructure, productivity loss). The economics of renewal almost always dominate the economics of relocation unless the tenant is contracting headcount, consolidating locations, or responding to a corporate mandate to shift to a different market.

The 85% to 95% range accounts for the minority of credit tenants who do relocate. The bottom of the range (85%) is appropriate when the lease was signed in a different market cycle and the tenant may be paying significantly above current market rent, creating an incentive to relocate. The top of the range (95%) is appropriate for tenants with 15+ year occupancy histories, custom improvements, and no known corporate relocation plans.

National Chains: 70% to 80%

National chains include retailers (grocery, pharmacy, quick-service restaurants, fitness), national service firms (staffing agencies, insurance brokers, regional banks), and franchise operators with standardized footprints. These tenants have established site selection processes, portfolio-level real estate strategies, and the operational infrastructure to relocate if a better deal is available. They renew at lower rates than credit tenants because their space is more fungible. A national retailer in a 5,000 SF inline shop can move to a competing center with relatively low switching costs.

The 70% to 80% range reflects the tension between brand equity at the current location (established customer traffic, signage, employee commute patterns) and the chain's willingness to relocate for better economics. At the bottom of the range (70%), the tenant has multiple viable alternative locations in the trade area and the current rent is at or above market. At the top of the range (80%), the tenant has invested in the location through their own capital improvements, the site is a top performer in their portfolio, and alternatives are limited.

Local and Regional Tenants: 50% to 65%

Local and regional tenants include independent businesses, professional practices (medical, dental, legal), small technology firms, creative agencies, and family-owned retail operators. These tenants have the widest variance in renewal behavior because their decisions are driven by individual circumstances rather than corporate real estate strategy. A local tenant may renew because the owner lives nearby and moving would be personally inconvenient. Or a local tenant may vacate because the business failed, the owner retired, or a lease renewal at market rent is unaffordable.

The 50% to 65% range is wider than the other categories because the heterogeneity of local tenants is greater. At the bottom of the range (50%), the building is in a market with high small-business turnover, the tenant has a short operating history, or the current rent requires a significant increase to reach market at renewal. At the top of the range (65%), the tenant has been in place for multiple lease terms, has invested their own capital in the space, and the business is stable. PropertyMetrics' guide to market leasing assumptions provides additional context on how these assumptions integrate into a full pro forma framework.

Local tenants are also the category where the analyst's judgment matters most. A national chain's renewal behavior is somewhat predictable because it follows a corporate playbook. A local tenant's renewal behavior is idiosyncratic. The analyst must weigh the specific tenant's financials, operating history, and lease terms against the general benchmark.

Anchor Tenants: 75% to 90%

Anchor tenants are the primary draw tenants in a multi-tenant property. In retail, the anchor is typically a grocer, department store, or big-box retailer. In office, the anchor is the largest tenant, often occupying 30% or more of the building. Anchor tenants renew at high rates because the cost of losing an anchor cascades through the entire property: co-tenancy clauses may be triggered, other tenants may have kick-out rights tied to the anchor's occupancy, and the property's financing may have covenants tied to anchor tenancy.

The 75% to 90% range is broad because anchor behavior varies by format. A grocery-anchored neighborhood center with a dominant grocer (no competing grocery within three miles) sits at the top of the range (85% to 90%). A power center anchored by a category killer (electronics, sporting goods) with multiple viable relocation options sits at the lower end (75% to 80%). The critical variable is the anchor's strategic assessment of the site: is this location essential to their market coverage, or is it a replaceable node in their network?

Variables That Move the Number

The benchmarks above are starting points. The analyst adjusts them based on tenant-specific, property-specific, and market-level variables.

Remaining Term and Lease Vintage

A tenant with two years remaining on a ten-year lease is in a different psychological and financial position than a tenant with six months remaining. Longer remaining terms give the analyst more time to gather intelligence (the tenant's expansion plans, headcount trajectory, competitor negotiations) and more confidence in the assumption. Shorter remaining terms force a binary call: is this tenant staying or going?

Lease vintage also matters. A tenant who signed at the market peak (paying above-market rent) has a financial incentive to relocate if the market has softened. A tenant who signed at the trough (paying below-market rent) has a financial incentive to stay, because any new lease will be more expensive. The analyst should compare the tenant's in-place rent to current market rent and adjust the renewal probability accordingly. If the tenant is paying 15% above market, shave 5 to 10 points off the base assumption. If the tenant is paying 10% below market, add 5 to 10 points.

Market Vacancy and Supply Pipeline

Market conditions influence renewal probability through two channels. First, a tenant in a tight market (low vacancy, limited new supply) has fewer alternatives, which pushes renewal probability up. A tenant in a soft market (high vacancy, significant new supply delivering) has more alternatives and more leverage, which pushes probability down. Second, a landlord in a tight market has less incentive to offer aggressive renewal terms, which can paradoxically push probability down if the tenant feels they are not getting a competitive deal.

The supply pipeline is particularly important. If 500,000 SF of new Class A office space is delivering in the submarket within 18 months, the renewal probability for existing Class A office tenants should be reduced by 5 to 15 points, depending on how competitive the new product is with the subject property. New supply does not have to be directly competitive to affect renewal probability; it creates optionality that did not previously exist.

Tenant-Specific Intelligence

The most accurate renewal probability assumptions are informed by direct intelligence about the tenant's plans. This intelligence comes from the property manager, the leasing broker, the tenant's broker (if one has been engaged), public filings (for public companies), and direct conversations with the tenant's real estate contact. Institutional asset managers start the renewal conversation 18 to 24 months before lease expiration for major tenants, specifically to convert the renewal probability from a benchmark-based estimate to an intelligence-based assessment.

Observable signals include: the tenant has engaged a broker to survey the market (negative signal, reduce probability by 10 to 20 points). The tenant has executed a sublease for part of their space (negative signal, reduce by 15 to 25 points). The tenant has announced a merger or acquisition (ambiguous signal, could go either way). The tenant has requested early renewal discussions (positive signal, increase by 5 to 10 points). The tenant has invested their own capital in the space within the last two years (positive signal, increase by 5 to 10 points).

Build-Out Specificity and Switching Costs

The more specialized the tenant's build-out, the higher the renewal probability. A medical office tenant with plumbed exam rooms, X-ray shielding, and specialized HVAC has switching costs of $80 to $150 per square foot. A general office tenant with an open floor plan has switching costs of $20 to $40 per square foot. The medical office tenant is far more likely to renew because the cost of replicating their build-out in a new location is prohibitive relative to the marginal rent savings from relocation.

This variable interacts with tenant type. A credit tenant with a specialized build-out (law firm with a custom library, trading floor, or data center) is at the very top of the renewal probability range (90% to 95%). A local tenant with a generic build-out (small professional office with standard finishes) is at the bottom (50% to 55%).

Rent Basis Relative to Market

The spread between in-place rent and current market rent is one of the most quantifiable variables. Tenants paying above-market rents have an economic incentive to relocate. Tenants paying below-market rents have an economic incentive to stay. The adjustment is roughly linear: for every 5% of rent premium above market, reduce the base renewal probability by 3 to 5 points. For every 5% of discount below market, increase the base probability by 2 to 3 points. The asymmetry (larger downward adjustment for above-market, smaller upward adjustment for below-market) reflects the fact that tenants are more sensitive to overpaying than they are appreciative of a bargain.

The Two-Scenario Weighted Model

The two-scenario weighted model is the institutional standard for incorporating renewal probability into a DCF. Rather than using a single "blended" vacancy rate for the entire building, the model evaluates each lease expiration individually, constructs two cash flow paths (renew and vacate), and weights them by the assigned renewal probability.

How the Framework Works

At each lease expiration during the projection period, the model generates two complete cash flow scenarios:

Scenario 1: Tenant renews. The tenant signs a new lease at the projected market rent (which may be higher or lower than the expiring rent). The landlord pays renewal tenant improvements (typically $5 to $15 per SF for office, lower for retail and industrial) and renewal leasing commissions (typically 2% to 4% of total lease value, or half the new-deal commission rate). There is no vacancy period. Rent begins immediately upon the new lease term. The probability weight assigned to this scenario equals the renewal probability.

Scenario 2: Tenant vacates. The tenant departs at lease expiration. The space sits vacant for a downtime period (typically 6 to 12 months for office, 3 to 6 months for retail, 3 to 9 months for industrial, depending on the market). The landlord pays new tenant improvements (typically $30 to $70 per SF for office, $10 to $30 per SF for retail) and new leasing commissions (typically 4% to 6% of total lease value). The landlord may also offer free rent to the new tenant (typically 1 to 3 months for every five years of lease term). The probability weight assigned to this scenario equals one minus the renewal probability.

The blended cash flow for that lease expiration event is the weighted average of the two scenarios. If the renewal probability is 75%, the model calculates 0.75 times the renewal scenario cash flow plus 0.25 times the vacancy scenario cash flow. This blended result flows into the building-level NOI projection.

Why the Two-Scenario Approach Beats a Single Vacancy Rate

Many introductory models use a single "general vacancy" rate (typically 5% to 10%) applied as a uniform haircut to gross potential revenue. This approach is simple but it obscures the economics of rollover. A 5% general vacancy rate tells you nothing about when the vacancy occurs, what it costs, which tenants are at risk, or how the timing of expirations affects cash flow volatility.

The two-scenario weighted approach captures all of this. Each tenant's expiration is modeled individually with its own renewal probability, its own renewal and vacancy cost assumptions, and its own downtime estimate. The result is a cash flow projection that reflects the actual lease-by-lease economics of the building, not a statistical abstraction. This is why ARGUS Enterprise (the institutional standard DCF software) structures its rollover analysis around tenant-level renewal probabilities rather than a single building-wide vacancy rate.

The practical difference is material. Consider a 100,000 SF building with five tenants, each occupying 20,000 SF, with leases expiring in Years 1 through 5 of the hold period. A 5% general vacancy rate produces flat, predictable cash flows. A tenant-level rollover analysis with varying renewal probabilities (say, 90% for the credit tenant in Year 1, 60% for the local tenant in Year 3, and 75% for the national chains in Years 2, 4, and 5) produces a lumpy, realistic cash flow profile with a visible risk concentration in Year 3. The second model is more work. It is also more accurate, and it is what every institutional buyer, lender, and appraiser expects to see.

The True Cost of Turnover

Turnover costs are the aggregate expenses incurred when a tenant vacates and is replaced by a new tenant. They include four components: vacancy loss during the downtime period, new tenant improvement allowances, new leasing commissions, and free rent concessions. Each component varies by property type, market, and deal structure.

Component 1: Vacancy Loss

The downtime period between a departing tenant's last rent payment and a replacement tenant's first rent payment is typically the largest single component of turnover cost. In office markets, the average downtime is 6 to 12 months, depending on market conditions, space quality, and the size of the suite. In suburban Class B office, downtime can extend to 12 to 18 months. In industrial markets, downtime is shorter (3 to 6 months) because industrial tenants have fewer build-out requirements and shorter decision cycles.

Vacancy loss equals the market rent multiplied by the downtime period. For a 10,000 SF office suite at $35/SF, a 9-month downtime produces vacancy loss of $262,500. This number does not appear as a line item in most operating budgets, but it is a real economic cost that the two-scenario model captures and the general vacancy rate obscures.

Component 2: New Tenant Improvement Allowances

When a new tenant takes a space, the landlord typically provides a tenant improvement (TI) allowance to fund the build-out of the space to the new tenant's specifications. TI allowances for new tenants far exceed renewal TI allowances because a new tenant requires demolition of the prior tenant's improvements, new design and permitting, and construction of a completely new layout.

Current market TI allowances for new tenants in office space range from $30 to $70 per SF, depending on the market, the building class, and the tenant's credit quality. Renewal TI allowances range from $5 to $15 per SF, reflecting the more limited scope of work (typically cosmetic refreshes, new carpet, paint, and minor reconfiguration). The spread between new and renewal TI is one of the largest cost differences between the two scenarios. On a 10,000 SF suite, the difference is $200,000 to $550,000.

Component 3: Leasing Commissions

Leasing commissions are paid to the brokers who negotiate the lease. Commission structures vary by market and transaction type, but the general pattern is that new-deal commissions are higher than renewal commissions. A typical new-deal commission is 4% to 6% of total lease value (base rent multiplied by lease term). A typical renewal commission is 2% to 4% of total lease value. The difference reflects the additional marketing, touring, and negotiation effort required for a new tenant. For a detailed analysis of commission structures and how they affect net effective rent calculations, see our guide to leasing commission structures and broker compensation.

On a 10,000 SF suite at $35/SF with a five-year lease term, total lease value is $1,750,000. A new-deal commission at 5% is $87,500. A renewal commission at 3% is $52,500. The $35,000 difference is the incremental commission cost of turnover.

Component 4: Free Rent Concessions

Free rent (also called rent abatement) is a period at the beginning of a new lease during which the tenant occupies the space but pays no base rent. Free rent is less common on renewals than on new deals. The market standard for new-deal free rent is approximately one month per year of lease term. On a five-year lease, the new tenant receives one to two months of free rent. On a seven-year lease, one to three months.

Free rent for renewal tenants is typically zero to one month, regardless of lease term. The landlord's negotiating position is stronger on renewals because the tenant has already demonstrated a preference for the space, and the landlord's alternative (turnover) is expensive for both parties. For a comprehensive analysis of how free rent affects effective rent calculations, see our guide to free rent, abatement, and effective rent accounting.

Total Turnover Cost: The Waterfall

Combining all four components produces the total turnover cost for a single lease expiration. The following example illustrates the waterfall for a 10,000 SF Class A suburban office suite at $35/SF market rent with a five-year replacement lease term.

The incremental cost of turnover, $705,833, is the economic penalty for losing this tenant. It represents the difference between the renewal scenario and the vacancy scenario. Stated on a per-SF basis, turnover costs $70.58/SF more than renewal. On a per-year basis (amortized over the five-year replacement lease term), turnover costs an additional $14.12/SF/year, which is 40% of the $35/SF market rent.

This is why renewal probability matters so much. A 10-point reduction in renewal probability (say, from 75% to 65%) increases the weighted turnover cost by $70,583, which flows directly through to lower projected NOI and lower property value. At a 6.5% cap rate, that $70,583 of additional weighted cost reduces property value by approximately $1.09 million. From a single 10-point adjustment on a single 10,000 SF tenant.

Worked Example: 80,000 SF Office Building

Consider a multi-tenant Class A suburban office building with 80,000 SF of gross leasable area, eight tenants, and lease expirations staggered across a five-year hold period. The building is located in a Tier 2 MSA with 12% office vacancy, $36/SF average asking rent, and no significant new supply in the pipeline.

Assumptions

• Market rent at Year 1: $36/SF, growing at 2.5% annually.
• Renewal TI: $10/SF. New TI: $45/SF.
• Renewal LC: 3% of total lease value. New LC: 5% of total lease value.
• Replacement lease term: 5 years.
• Downtime for vacancy: 9 months (office market average for this submarket).
• Free rent on new deals: 2 months. Free rent on renewals: 0 months.
• Exit cap rate: 7.0%. Hold period: 5 years.

Year-by-Year Rollover Analysis

Year 1: Medical device sales (10,000 SF, 70%) + Marketing consultancy (5,000 SF, 55%). Combined 15,000 SF rolling. This is 18.75% of the building, within the 20% concentration threshold. The medical device tenant is paying $36/SF, exactly at market, so the base 70% assumption holds. The marketing consultancy is paying $31/SF, $5 below market, which should increase renewal probability, but the firm has only three employees and has been at the building for two years with no investment in the space, so the analyst keeps it at 55%.

Weighted renewal cost for Year 1: Medical device at $10/SF TI + 3% LC = $100,000 + $27,000 = $127,000, weighted at 70% = $88,900. Vacancy scenario at $45/SF TI + 5% LC + 2 months free rent + 9 months vacancy = $450,000 + $45,000 + $60,000 + $270,000 = $825,000, weighted at 30% = $247,500. Blended cost: $336,400.

Marketing consultancy: Renewal cost $50,000 + $13,500 = $63,500, weighted at 55% = $34,925. Vacancy cost $225,000 + $22,500 + $30,000 + $135,000 = $412,500, weighted at 45% = $185,625. Blended cost: $220,550.

Total blended rollover cost in Year 1: $556,950.

Year 2: National insurance (14,000 SF, 80%) + IT staffing (8,000 SF, 55%). Combined 22,000 SF rolling. This is 27.5% of the building, exceeding the 20% threshold. The concentration risk in Year 2 is flagged in the underwriting memo. The insurance company's 80% probability reflects their below-market rent ($34/SF vs $36.90/SF market) and eight-year occupancy history. The IT staffing agency's 55% reflects local-tenant volatility and a short two-year occupancy.

Total blended rollover cost in Year 2: $684,200. The higher cost reflects both the larger square footage rolling and the lower average renewal probability (weighted 69%, pulled down by the IT staffing agency).

Year 3: Regional law firm (18,000 SF, 85%) + Architecture firm (7,000 SF, 60%). Combined 25,000 SF rolling, 31.25% of the building. This is the highest-risk year. The law firm is the building's most important tenant by revenue, and even at 85% renewal probability, a 15% chance of losing 18,000 SF of credit-quality rent is a material risk event. The architecture firm at 60% adds noise. Total blended rollover cost in Year 3: $742,100.

Year 4: Regional accounting firm (12,000 SF, 75%). A single tenant rolling. Straightforward analysis. Total blended rollover cost: $324,700.

Year 5: Financial advisor (6,000 SF, 50%). The lowest renewal probability in the building. A coin flip. This tenant is a solo practitioner with a below-market lease who has not invested in the space. Total blended rollover cost: $248,400.

Portfolio-Level Impact

Total blended rollover costs across the five-year hold period: $2,556,350. If every tenant renewed with certainty (100% probability), total rollover costs would be $912,000 (renewal TI and LC only, no vacancy loss). The $1,644,350 difference is the economic cost of rollover risk embedded in the building's rent roll.

This cost flows directly into the levered equity IRR. Using a 65% LTV senior loan at 6.5%, the rollover-adjusted levered IRR is approximately 13.8%. If the analyst had used a flat 5% general vacancy rate instead of tenant-level rollover modeling, the IRR would have been 15.1%. The 130-basis-point difference comes entirely from the more granular rollover analysis capturing the true timing and magnitude of turnover costs.

Lease Expiration Concentration Risk

Lease expiration concentration measures how much of a building's rental income is at risk in any single year. When too many leases expire at the same time, the building faces a "rollover cliff," a period in which a large share of its occupied space could vacate simultaneously, creating a cash flow disruption that may breach debt service coverage covenants, trigger lender reserves, or force a capital call.

The 20% Threshold

The institutional standard is that no more than 20% of a building's gross leasable area should expire in any single calendar year. This threshold is not a regulation. It is a market convention that has emerged from decades of portfolio management practice and is now embedded in lender underwriting guidelines, CMBS rating agency criteria, and institutional buyer due diligence checklists.

The logic behind 20% is straightforward. If 20% of the building's space expires and the renewal probability is 75%, the expected vacancy from that year's rollover is 5% of the building (20% times 25% vacancy probability). That 5% expected vacancy is manageable. If 40% of the building expires and the same 75% renewal probability applies, the expected vacancy is 10%, which may breach a 1.25x DSCR covenant on the senior loan.

The threshold becomes more conservative for buildings with lower average renewal probabilities. A building with predominantly local tenants (average 55% renewal probability) should target no more than 15% expiring in any single year, because the vacancy probability per expiring square foot is higher. A building with predominantly credit tenants (average 90% renewal probability) can tolerate 25% to 30% expiring in a single year because the vacancy probability per expiring square foot is much lower.

How Institutional Investors Screen for Concentration

The lease expiration schedule is one of the first documents an institutional buyer requests during due diligence. It is typically presented as a table or bar chart showing the percentage of GLA and the percentage of base rent expiring in each year for the next 10 years. The buyer's acquisition team reviews the schedule for three risks:

1. Single-year concentration. Does any year exceed 20%? If so, which tenants are driving the concentration, and what are their renewal probabilities?
2. Rolling two-year concentration. Do any two consecutive years exceed 35% combined? A building that is just under 20% in each of two consecutive years (say, 19% and 18%) is effectively at 37% over a 24-month window, which is a different risk profile than the single-year analysis suggests.
3. Near-term loading. Is the first or second year of the hold period disproportionately loaded? Rollover in Year 1 is the hardest to manage because the new owner has had no time to build tenant relationships, understand the competitive dynamics, or implement a proactive renewal strategy.

When concentration risk is identified, the buyer has several options: negotiate a purchase price discount (typically 50 to 100 bps of cap rate widening), require the seller to fund a rollover reserve at closing, negotiate early lease extensions with the concentrated tenants as a condition of closing, or walk away.

Concentration by Revenue vs. Concentration by Area

Concentration analysis should be performed on both a square footage basis and a revenue basis. The two can diverge significantly. A building with a single credit tenant occupying 30% of the space at $45/SF and multiple local tenants occupying 70% at $28/SF has 30% of its area but 38% of its revenue concentrated in a single lease. If that credit tenant's lease expires in Year 2, the revenue concentration risk is materially higher than the area concentration risk suggests.

Institutional underwriters run both analyses and present the more conservative one. If area concentration says 22% in Year 3 but revenue concentration says 31% in Year 3, the underwriting memo flags 31%.

Staggering the Expiration Schedule

Staggering is the proactive management of lease expiration dates to ensure that no single year carries disproportionate rollover risk. It is one of the most underappreciated tools in the asset manager's kit. Unlike renewal probability (which is largely determined by tenant characteristics), the expiration schedule is something the asset manager can directly influence through lease structuring.

At Acquisition

The best time to address concentration risk is during the acquisition itself. If the building's expiration schedule is concentrated, the buyer can negotiate pre-closing lease extensions with the concentrated tenants as a condition of the purchase agreement. The seller has an incentive to cooperate because a staggered schedule supports a higher sale price. The buyer offers the tenant a market-rate renewal with modest incentives (renewal TI, perhaps a small rent reduction) in exchange for extending the lease term and moving the expiration date to a less concentrated year.

This is common in institutional transactions. A buyer acquiring a $50M office building with 35% of its leases expiring in Year 2 may require the seller to deliver executed lease extensions moving at least 15% of that exposure to Year 4 or 5 before closing. The cost of the extensions (renewal TI and commissions) is typically shared between buyer and seller through a purchase price credit.

During the Hold Period

Asset managers stagger the schedule during the hold period by offering strategic tenants early renewal incentives. The approach is selective. Not every tenant warrants an early renewal offer. The candidates are tenants whose current expiration creates concentration risk and whose renewal probability is high enough to justify the investment but low enough to warrant proactive management.

The typical early renewal offer includes a modest TI allowance ($5 to $10/SF, less than a full renewal TI), a small rent reduction or a period of frozen rent, and an extension of the lease term by three to five years. In exchange, the tenant commits to a new expiration date that reduces concentration in the original year and spreads the risk across the projection period.

The economics of early renewal are almost always favorable. The cost of the incentive package ($5 to $10/SF in TI plus any rent concession) is a fraction of the turnover cost ($70+ per SF incremental cost) that would be incurred if the tenant vacated. The asset manager is spending $50,000 to $100,000 now to avoid a potential $500,000+ turnover event in two to three years. The Adventures in CRE rollover analysis tutorial walks through how to build this kind of scenario comparison in Excel, with a step-by-step model showing the retention economics for a multi-tenant office building.

Lease Term Structuring for New Tenants

When signing new tenants, the leasing team should consider the expiration schedule before setting the lease term. If a five-year lease would create concentration in Year 5 of the hold, consider offering a seven-year term (with a slightly higher TI allowance to compensate for the longer commitment). If a ten-year lease would create concentration beyond the hold period (affecting the exit buyer's risk profile), consider a seven-year term with a three-year renewal option.

This is not always possible. Tenants have their own term preferences, and the market may not support the landlord's desired term structure. But when the landlord has leverage (strong demand, limited alternatives in the submarket), lease term structuring is an effective tool for proactive schedule management.

ARGUS and Excel Implementation

The two-scenario weighted model is implemented differently in ARGUS Enterprise and in custom Excel models, but the underlying logic is identical. Both platforms model each lease expiration as a decision tree with two branches, weighted by the renewal probability.

ARGUS Enterprise

In ARGUS, renewal probability is set at the tenant level in the lease assumptions. The software calls it the "renewal probability" or "probability of renewal" field. For each tenant, the analyst enters:

• Renewal probability (e.g., 75%).
• Renewal rent assumption (typically "market rent at expiration" or a specified growth rate applied to the current in-place rent).
• Renewal TI per SF.
• Renewal leasing commissions (as a percentage of lease value or a per-SF amount).
• Renewal lease term.
• Vacancy/downtime months if the tenant does not renew (called "months vacant" or "absorption period").
• New tenant TI per SF.
• New tenant leasing commissions.
• New tenant free rent months.
• New tenant lease term.

ARGUS then runs the two-scenario calculation internally. The software generates a single cash flow line for each tenant that is the probability-weighted blend of the renewal and vacancy scenarios. The analyst can view each scenario independently (100% renew, 100% vacate) or view the blended result, which is the default output.

One common error in ARGUS is setting the renewal probability at the global level (applying the same percentage to all tenants) rather than at the tenant level. ARGUS allows both approaches, but institutional underwriting requires tenant-level assumptions. A global 75% renewal probability applied to a rent roll with credit tenants and local tenants will overstate vacancy risk for the credit tenants and understate it for the local tenants, producing a blended result that is wrong in both directions.

Excel Implementation

In Excel, the two-scenario model is typically built as a tenant-level cash flow module with IF statements or scenario weightings. The structure varies by firm, but the institutional standard includes the following elements:

Rent roll tab. Contains the current rent roll: tenant name, suite, SF, in-place rent, lease start date, lease expiration date, annual escalations, and tenant type classification.

Assumptions tab. Contains market leasing assumptions: market rent (with growth rate), renewal TI per SF by tenant type, new TI per SF by tenant type, renewal LC rate, new LC rate, free rent months for new deals, downtime months by property type, and renewal probability by tenant type.

Rollover analysis tab. For each tenant, the model calculates two scenarios at the expiration date:

• Renewal scenario: market rent at expiration, renewal TI, renewal LC, zero downtime.
• Vacancy scenario: downtime months with zero revenue, new TI, new LC, free rent, then market rent.

The blended result for each period is: (Renewal Probability x Renewal Cash Flow) + ((1 - Renewal Probability) x Vacancy Cash Flow).

Building-level cash flow tab. Sums the tenant-level blended cash flows to produce gross revenue, then subtracts operating expenses to produce NOI. The building-level cash flow is what feeds the DCF valuation, the debt sizing, and the equity return analysis.

The advantage of Excel over ARGUS for rollover analysis is flexibility. Excel allows the analyst to build sensitivity tables that show how the building-level IRR changes as renewal probabilities vary. For example, a data table that varies the credit tenant's renewal probability from 70% to 95% in 5-point increments while holding all other assumptions constant reveals the sensitivity of the deal to that single tenant's renewal decision. This sensitivity analysis is difficult to produce in ARGUS without external add-ons.

Sensitivity Analysis: What a 10-Point Swing Does

Using the 80,000 SF office building from the worked example above, the following table shows how the five-year levered equity IRR changes as the building's average renewal probability moves in 10-point increments.

The range from stress case (55%) to optimistic (90%) is 570 basis points of levered IRR. The sensitivity is approximately 16 basis points of IRR per 1 percentage point of renewal probability. This is why institutional underwriters spend significant time calibrating renewal assumptions at the tenant level rather than applying a blanket rate.

Five Mistakes Practitioners Make

1. Using a single renewal probability for all tenants. The most common error in rollover analysis is applying a uniform renewal probability (typically 70% or 75%) to every tenant in the building. This ignores the 30+ percentage point spread between credit tenants (85% to 95%) and local tenants (50% to 65%). The result is an analysis that simultaneously overstates risk for credit tenants and understates risk for local tenants. The blended building-level number may look similar, but the cash flow timing and cost profile are wrong, which cascades into incorrect IRR and valuation conclusions.

2. Ignoring the cost differential between renewal and new-deal TI. Some models use the same TI assumption for both renewal and new-deal scenarios. This is incorrect. Renewal TI ($5 to $15/SF for office) is a fraction of new-deal TI ($30 to $70/SF for office). When the model uses the same number for both, it either overstates the renewal cost (if using the new-deal number) or understates the vacancy cost (if using the renewal number). Either way, the model misprices the economic difference between retaining and replacing a tenant.

3. Setting downtime at zero for the vacancy scenario. Optimistic models sometimes assume that a vacating tenant is immediately replaced with zero downtime. This assumption is almost never realistic. Even in the tightest markets, there is a physical gap between one tenant's departure and another's occupancy: the space must be de-commissioned, marketed, negotiated, permitted, and built out. A minimum of three to six months is realistic for institutional-quality space. Nine to twelve months is the norm in most office markets. Setting downtime at zero eliminates the largest single component of turnover cost and produces an IRR that is overstated by 50 to 150 basis points.

4. Not adjusting renewal probability for rent basis. A tenant paying $40/SF in a $35/SF market has a lower renewal probability than the same tenant type would suggest, because the tenant has a financial incentive to relocate. A tenant paying $30/SF in a $35/SF market has a higher renewal probability because the current deal is favorable. Many models set renewal probability purely on tenant type without adjusting for the spread between in-place rent and market rent. This misses one of the most quantifiable drivers of renewal behavior.

5. Modeling rollover only at the first expiration. In a multi-year hold, a tenant may expire, renew, and then expire again within the projection period. A ten-year DCF for a building with five-year lease terms will see every tenant expire twice. Models that only capture the first expiration and then assume stable occupancy through the second term are missing the rollover cost of the second expiration event. ARGUS handles this automatically through its "subsequent renewal" settings. Excel models must be explicitly built to capture multiple rollover events per tenant.

Model It in Apers

Related Articles

• Tenant Improvement Allowances: Market Standards. The companion reference for TI assumptions. How TI allowances vary by market, property type, tenant credit, and deal structure, with 2026 benchmarks for new-deal and renewal TI across office, retail, and industrial.
• Leasing Commission Structures and Broker Compensation. How commission structures affect net effective rent and landlord economics. New-deal vs renewal commissions, listing vs procuring broker splits, and override commission arrangements.
• Free Rent, Abatement, and Effective Rent Accounting. How free rent periods affect NOI projections, GAAP straight-line rent recognition, and the calculation of effective rent. Includes worked examples for new-deal and renewal scenarios.
• Co-Tenancy and Kick-Out Clauses: Retail Downside. The cascading risk of anchor tenant departure. How co-tenancy clauses amplify rollover risk when an anchor tenant vacates, triggering rent reductions or termination rights for inline tenants.
• Office Lease Analysis: Gross vs NNN and Expense Stops. How lease structure affects the landlord's net rent and the tenant's total occupancy cost. The relationship between lease type and renewal economics.
• Hold Period Analysis: IRR vs Equity Multiple. How hold period length interacts with rollover timing. Why a five-year hold with heavy Year 3 rollover produces a different IRR profile than a seven-year hold with the same rollover concentrated in Year 3.