Student housing underwrites differently from conventional multifamily. Demand is anchored on a single institution or cluster, lease cycles run on the academic calendar, and exit liquidity is structurally narrower than market-rate multifamily because the buyer pool concentrates around purpose-built student-housing operators and a small set of institutional platforms. This module auto-detects student-housing applicability from property type, deal name, address, notes, and rent-roll tenant labels (student housing, purpose-built student, PBSA, university, college, campus, dorm, dormitory, residence hall, by-the-bed, per-bed lease) plus seeded flagship and regional university market cues. Non-residential deals without strong text cues return not-applicable and the memo section does not render. Market detection: tier-1 flagship markets (Cornell / Ithaca anchored on Cornell University and Ithaca College, Ann Arbor anchored on University of Michigan, Madison anchored on University of Wisconsin, State College anchored on Penn State, Chapel Hill anchored on UNC, Athens anchored on University of Georgia, Boulder anchored on CU Boulder, Gainesville anchored on University of Florida, College Station anchored on Texas A&M, Bloomington anchored on Indiana University) with enrollment depth 82-90 and campus housing scarcity 78-88; tier-2 regional markets (Austin / University of Texas, Columbus / Ohio State, Knoxville / University of Tennessee, Lawrence / University of Kansas, Tucson / University of Arizona) with enrollment depth 68-80 and scarcity 62-72; generic regional university fallback when university / college / campus cue is present but no specific market anchor matches; thin student market default with enrollment depth 36 and scarcity 38. Six weighted drivers: university demand anchor 25% (tier-driven baseline plus 4 for explicit student or dorm cue), enrollment and household formation 20% (seeded enrollment depth adjusted by demographic overlay population growth: plus 4 above 1.0% YoY, minus 6 below minus 0.5%), campus housing scarcity and off-campus reliance 20% (seeded scarcity plus 4 for by-the-bed cue), rent affordability versus student and guarantor profile 15% (deal rent versus seeded per-bed market baseline: 82 at 95% or below, 66 at 95-105%, 48 at 105-115%, 32 at 115-130%, 20 above 130%; plus rent comp and rent-to-income adjustments), supply pipeline and competing beds 10% (supply pipeline overlay band with tier-1 floor adjustment), exit liquidity and buyer depth 10% (market tier buyer pool blended with transaction liquidity overlay). Lease-cycle risk classification: moderate by default for tier-1 and tier-2 markets, elevated for by-the-bed leasing or thin markets, high when supply pipeline reads soft. Bands: campus-anchored (score 78-plus and anchor 70-plus), enrollment-supported (62-77), lease-cycle-sensitive (45-61), thin-student-demand (less than 45), not-assessable. Memo surface: verdict banner with band, score, market label, and tier; university anchor card; composite score bar with band threshold ticks (45 / 62 / 78); four-cell metric strip (enrollment demand, housing scarcity, affordability, lease-cycle risk); supply pressure callout; six-driver weighted score table; underwriting actions (confirm institutional enrollment trajectory, cross-check 10-year enrollment plans and out-of-state share, map on-campus residence-hall capacity and competing off-campus supply within one mile, verify guarantor profile, stress fall lease-up plan against bed pipeline, identify institutional student-housing buyer pool ahead of close, reserve for fall pre-lease shortfalls when by-the-bed leasing is detected); deal implications by band. Auto-skip when purchase price, hold period, residential unit count, or monthly rent are missing on a student-flagged deal. Student housing demand tracker is a deterministic market-fit overlay. It is not an enrollment forecast, a leasing guarantee, or a university affiliation claim.
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Phase 3 continues: thirteen new specialty and macro overlays land today. Distress-to-Stabilized IRR Path Model, Macroeconomic Regime Switcher, Data Center Power Capacity Tracker, Life Sciences Tenant Demand Tracker, Workforce Housing Premium Tracker, Single Family Rental Yield Index, Healthcare REIT Sub-Sector Analysis, Student Housing Demand Tracker, Retail Anchor Durability Tracker, Retail Trade Area Leakage and Capture Analysis, Mixed-Use Synergy and Conflict Index, Parking Demand and Access Friction Index, and Office Obsolescence and Leasing Friction Index all land. Auto-applicable signal sets across data-center, life-sciences, workforce-housing, SFR / BTR, healthcare, student-housing, retail, mixed-use, parking-sensitive, and office deals join the engine alongside the macro regime transition map. 103 Phase 3 modules cumulative.
Healthcare real estate is not one asset class. Medical office, senior housing, skilled nursing, life sciences, inpatient hospital, outpatient surgery, and behavioral health each carry different demand patterns, payer mixes, operator risks, supply dynamics, and demographic exposures. This module auto-detects healthcare exposure from property type, deal name, address, notes, and rent-roll tenant labels, then classifies the deal into one of eight sub-sectors. Detection order is most-specific first: skilled nursing (SNF, nursing home, post-acute, rehab facility), senior housing (assisted living, independent living, memory care, CCRC, continuing care, retirement community, active adult), hospital (hospital, acute care, medical center), outpatient surgery (ASC, surgery center, ambulatory care), behavioral health (behavioral health, psychiatric, substance abuse, addiction treatment, rehabilitation hospital), life sciences (life science, biotech, biomedical, biolab, wet lab, research park, pharma campus), medical office (MOB, physician office, healthcare office, medical plaza), mixed healthcare (clinic, dialysis, urgent care, imaging, oncology). Non-healthcare deals return not-applicable and the memo section does not render. Sub-sector priors: medical office (defensive score 75, low payer exposure, low operator risk, supportive demographic baseline, low supply sensitivity, margin stability 72, public-REIT mappable), senior housing (defensive 62, moderate payer, elevated operator, supportive demographic, moderate supply, margin 50), skilled nursing (defensive 42, high payer, high operator, supportive demographic, moderate supply, margin 32, the highest payer and operator exposure in the institutional healthcare stack), life sciences (defensive 64, low payer, moderate operator, neutral demographic, elevated supply sensitivity, margin 60), hospital (defensive 58, high payer, elevated operator, supportive demographic, low supply, margin 48), outpatient surgery (defensive 68, moderate payer, moderate operator, supportive demographic, moderate supply, margin 60), behavioral health (defensive 60, moderate payer, elevated operator, supportive demographic, low supply, margin 50, limited public-REIT mapping), mixed healthcare (defensive 60, moderate across the axes). Six weighted drivers: demographic tailwind 25% (sub-sector baseline plus demographic overlay population growth nudges of plus 6 above 1.5% YoY or minus 8 below minus 0.5%), tenant and operator durability 20% (operator risk tier: 80 low, 60 moderate, 42 elevated, 28 high), reimbursement and payer risk 20% (payer exposure tier: 80 low, 60 moderate, 42 elevated, 28 high), supply pipeline pressure 15% (supply pipeline overlay band with sub-sector sensitivity nudges of plus or minus 3-6), operating margin stability 10% (sub-sector baseline plus or minus operating margin trend, minus 6 when insurance load above band), public healthcare REIT read-through 10% (REIT sector overlay positioning: 78 premium-justified, 60 in-line, 36 underpriced, 50/55 no-coverage). Bands: defensive-healthcare (score 78-plus with low or moderate payer exposure), demographic-supported (62-77), operator-sensitive (45-61), reimbursement-risk (less than 45), not-assessable. Memo surface: verdict banner with band, score, sub-sector, and public market read; horizontal score bar with band thresholds; four-cell risk strip (payer exposure, operator risk, demographic support, supply pressure); six-driver weighted score table; underwriting actions tied to payer and operator severity (stress operator coverage under 5% reimbursement compression, diligence operator credit at parent and subsidiary level, confirm catchment-area population trends, map competing supply, pressure-test margin against labor cost inflation, reconcile pricing against public REIT yields, confirm state licensing and certificate-of-need posture for skilled nursing and hospital sub-sectors); deal implications by band including the sub-sector narrative. Auto-skip when purchase price or hold period are missing on a healthcare-flagged deal. Healthcare sub-sector analysis is a deterministic risk overlay. It is not medical advice, not reimbursement guidance, not a licensing opinion, and not a tenant-credit assessment.
SFR and build-to-rent deals underwrite differently from conventional multifamily. The IC question is not only whether the deal clears yield. It is whether the market supports durable rental-home demand, income-qualified renters, tax and insurance drag, and exit liquidity for scattered-site or horizontal rental housing. This module auto-detects SFR, BTR, single-family rental, build-to-rent property types, plus multifamily and mixed-use deals with rental-home, townhome, townhouse, cottage, scattered-site, or horizontal rental cues. Non-applicable for office, retail, industrial, hotel, data center, life sciences, and normal vertical multifamily with no SFR or BTR signals. Yield math: implied gross yield (annual rent over total cost), implied net yield (Y1 NOI over purchase price), and stabilized yield-on-cost (Y3 or hold-end NOI over total cost). Gross yield bands: strong 6.5% or higher, normal 5.25-6.5%, thin 4.25-5.25%, compressed below 4.25%. Net yield bands: strong 4.75% or higher, normal 3.75-4.75%, thin 3.0-3.75%, compressed below 3.0%. Renter affordability evaluated as rent-to-income against a 28-34% institutional band (supportive at or below 28%, neutral 28-34%, watch 34-40%, negative above 40%). Ownership-cost pressure computes for-sale PITI (principal and interest at 30-year fixed, property tax, insurance, on 80% LTV of median for-sale home) and divides by market rent; renters stay when ownership materially exceeds rent (supportive at 1.30x or above, watch at 1.00-1.15x, negative below 0.85x). Twelve market proxies seeded with for-sale median price, mortgage rate, property tax rate, insurance load, migration tailwind, and transaction liquidity tier (Phoenix, Dallas / Fort Worth, Houston, Atlanta, Nashville, Carolina Metro, Florida Metro, Austin, Nevada Metro, Denver / Colorado Front Range, Salt Lake Metro, Southern California, Pacific Northwest, and a generic secondary Sunbelt baseline). Demographic overlay median household income overrides the seeded fallback when covered. Seven weighted drivers: implied net yield and yield-on-cost 25% (band by net yield: 86 strong, 70 normal, 52 thin, 32 compressed, 18 deeply compressed; plus 4 when stabilized YoC outpaces entry by 75 bps), renter affordability 20% (band by rent-to-income: 84 below 28%, 64 28-34%, 42 34-40%, 22 above 40%; adjusted by rent comp positioning), ownership-cost pressure 15% (band by PITI multiple: 84 at 1.30x or above, 68 at 1.15x, 52 at parity, 38 at 0.85x, 22 below), migration and demographic tailwind 15% (seeded market tier blended with migration overlay score when available), insurance and tax and operating drag 10% (insurance load status band with market insurance baseline and property tax rate penalties), exit liquidity and public market read 10% (transaction liquidity band with REIT sector positioning nudges and cap-rate persistence reset-risk penalty), workforce housing fit 5% (workforce premium band when available). Bands: institutional-yield-tailwind (score 78 or higher with net yield strong), durable-renter-depth (63-77), selective-sfr-market (48-62), yield-compression-risk (less than 48), not-assessable. Yield premium bps computed versus a 5.5% institutional benchmark net yield. Memo surface: verdict banner with band, score, asset class, and market; four-stat headline (gross yield, net yield, rent-to-income, yield premium bps); four-cell demand and drag strip (renter demand, operating drag, exit liquidity, ownership cost multiple); six-row yield and affordability metric table with value, benchmark, status, and read; seven-driver weighted score table; underwriting actions (re-underwrite when net yield is thin, pressure-test rent against wages when affordability fails, size buffer when ownership cost is comparable to rent, confirm migration anchors, reserve for insurance and tax shocks, map institutional buyer pool when exit liquidity is thin); deal implications by band. Auto-skip when purchase price, hold period, residential units, or monthly rent are missing on an SFR-flagged deal. Single Family Rental Yield Index is a deterministic market-fit overlay. It is not an appraisal, a broker opinion, or a rent guarantee.
Workforce housing is often underwritten as ordinary multifamily, but institutional buyers care about a different signal set: rent-to-income affordability, local wage depth, essential-worker demand, rent regulation exposure, expense pressure, and political durability. This module shows whether a deal benefits from a durable workforce-housing demand premium or whether the thesis is really just market-rate multifamily with affordability language. Auto-applicability triggers on multifamily and mixed-use deals with meaningful residential exposure, plus any deal flagged with workforce, affordable, attainable, middle-income, essential-worker, LIHTC, mixed-income, or NOAH cues. For multifamily without explicit cues, the module renders only when rent-to-income reads at or below 32% or rent positioning is below market; otherwise it marks itself not-applicable. Non-residential deals (hotel, office, retail, industrial, data center, life sciences) without workforce cues return not-applicable and the memo section does not render. Demand segment classification: essential-worker core (hospital, university, school district, government, logistics cues), middle-income renter (workforce cue or rent-to-income at or below 30%), mixed-income (mixed-income cue), market-rate leaning (no cues plus high rent-to-income). Market profile seeded across 17 metros: high-cost coastal (New York City, Bay Area, Los Angeles, Boston, Seattle, DC Metro, Portland) with median household incomes 79K-110K and rent regulation tiers ranging from high to elevated; Sunbelt growth markets (Austin, Dallas / Fort Worth, Houston, Atlanta, Nashville, Phoenix, Florida Metro, Carolina Metro) with incomes 70K-87.5K and low regulation; Midwest and Mountain (Chicago, Twin Cities, Denver) and a university-town anchor (Ithaca). Demographic overlay's median household income overrides the seed when covered. Rent-to-income computed as annual rent divided by median household income; affordability cushion equals 30% threshold minus rent-to-income. Workforce premium bps inferred from the band verdict: +50 durable, +25 affordability-supported, 0 policy-sensitive, -25 market-rate-disguised. Six weighted drivers: affordability cushion and rent-to-income fit 30% (90 if R2I ≤ 25%, 76 if ≤ 30%, 52 if ≤ 35%, 32 if ≤ 40%, 18 above; plus 8 if LIHTC cue), wage depth and essential-worker demand 20% (cluster wage depth with essential-worker cue plus 8 and NOAH cue plus 4), rent comp support 15% (below-market 80, in-band 64, above-market 38, no-comp 50), supply pipeline and migration 15% (supply pipeline overlay with migration overlay blending when available), policy and rent-regulation durability 10% (low 78, moderate 64, elevated 48, high 32; plus 6 for strong political durability, minus 6 for fragile, plus 4 for LIHTC), operating margin resilience 10% (expanding 78, stable 62, compressing 36). Bands: durable-workforce-premium (score 78-plus, rent-to-income 30%-or-below, policy risk not high), affordability-supported (62-77), policy-sensitive (45-61), market-rate-disguised (less than 45), not-applicable, not-assessable. Memo surface: verdict banner with band, score, demand segment, and market; four-stat headline (rent-to-income, affordability cushion, workforce premium bps, demand segment); affordability bar showing rent-to-income against 30% and 35% threshold ticks; four-cell metric strip (wage depth, essential-worker demand, rent regulation risk, political durability); nine-row demand metric table; six-driver weighted score table; underwriting actions (re-underwrite at the 30% threshold when affordability is thin, diligence local wage base by submarket, reconcile rent comps against underwritten rent, stress occupancy against supply pipeline, map rent regulation and inclusionary zoning exposure, pressure-test operating margin against insurance, utility, and property-tax escalation); deal implications by band. Auto-skip when purchase price, hold, residential units, or monthly rent are missing on a workforce-flagged deal. Workforce housing premium tracker uses deterministic affordability, wage-depth, and policy proxies. It is not a rent-regulatory opinion, a subsidy analysis, a legal opinion, or a housing-policy certification.
Life sciences real estate is not just office with lab rent. Demand is highly clustered around university research, NIH funding, venture formation, pharma presence, wet-lab infrastructure, specialized HVAC, power, floor loading, and tenant credit depth. Institutional underwriters need to know whether a lab or conversion deal has real tenant demand behind the rent assumptions, or whether the business plan is relying on a thin tenant universe. This module auto-detects life sciences cues from property type, deal name, address, and notes (life science, life sciences, biotech, biolab, biomedical, lab, laboratory, wet lab, research park, R&D campus, pharma campus, pharma). Office and industrial deals receive partial applicability only when lab cues are present; non-lab deals return not-applicable and the memo section does not render. Cluster detection from address: tier-1 biotech clusters (Boston / Cambridge / Kendall, San Diego / La Jolla / Sorrento Valley / Torrey Pines, Bay Area / South San Francisco / Oyster Point / Mission Bay) with tenant depth 86-92; emerging clusters (Research Triangle, Seattle / South Lake Union, Philadelphia / King of Prussia, New York City) with tenant depth 66-72; institutional research nodes (Maryland / DC corridor including Bethesda / Gaithersburg / Rockville / Frederick, Denver / Boulder, Chicago, university towns like Ithaca / Ann Arbor / Madison / Austin / Nashville) with tenant depth 52-64; thin lab markets with tenant depth 36. Research anchor bumps: tier-1 university cue (Harvard, MIT, Stanford, UCSF, UCSD, Johns Hopkins, Yale, Princeton, Columbia, Cornell, Duke, Berkeley, Chicago, Northwestern) plus 20; medical center or hospital adjacency plus 12; research park or innovation district cue plus 15. Venture funding proxy and pharma presence seeded by cluster tier with cue adjustments (biotech cue plus 4 on venture proxy; pharma cue plus 6 on pharma presence). Conversion fit base 60 with wet-lab cue bumped to 78, conversion cue penalized to 40, generic office penalized to 45; construction cost inflation drag of minus 8 when capex-heavy or YoY 6.5%-plus. Supply pressure from supply pipeline risk overlay (constrained 80, balanced 66, moderate-oversupply 45, heavy-oversupply 25) with cluster-tier fallback when unavailable. Rent comp support driven by rent comp positioning (below-market 72, in-band 65, above-market 38, no-coverage 50). Rent premium versus a 50 dollar per SF office baseline approximates the lab-premium signal; inferred lab share derived from premium magnitude (95% if 7500 bps plus, 80% if 5000 bps plus, 60% if 2500 bps plus, defaults driven by wet-lab and conversion cues). Six weighted drivers: tenant depth and cluster tier 25%, research anchors 20%, venture and pharma demand 15%, conversion or building-fit credibility 15%, supply pressure 15%, rent comp support 10%. Bands: cluster-tailwind (score 78-plus and tenant depth 70-plus), selective-depth (62-77), conversion-dependent (45-61), tenant-depth-risk (less than 45), not-applicable, not-assessable. Memo surface: verdict banner with band, score, cluster label, and tier; four-stat headline (tenant depth, estimated lease-up months, rent premium bps, inferred lab share); horizontal demand bar showing tenant depth versus supply pressure; five-cell metric grid (research anchor, venture proxy, pharma presence, conversion fit, supply pressure); nine-row demand metric table; six-driver weighted score table; underwriting actions (diligence tenant universe, map research anchor network within five miles, validate building fit with lab engineering scope, cross-check competing supply, reconcile rent versus current lab comps); deal implications by band. Auto-skip when SF, hold, or purchase price are missing on a life-sciences-flagged deal. Life sciences tenant demand tracker uses deterministic cluster and building-fit proxies. It is not a leasing forecast, a tenant commitment, a lab engineering report, or a market study.
Data center underwriting is increasingly constrained by power, not just rent, cap rate, or construction cost. Institutional buyers need to know whether a site's economics are supported by credible utility capacity, substation access, power delivery timing, grid congestion, and tenant load requirements. This module translates power availability into a deterministic underwriting signal: can this deal actually support the demand profile the sponsor is assuming? Applicability is auto-detected from deal cues (property type, deal name, address, notes) using the same signature list as the AI-native asset classifier: data center, data centre, datacenter, hyperscale, colocation, colo, powered shell. Non-data-center deals return not-applicable and the memo section does not render. Critical load estimation: total leasable SF times load density. Density seeded by detected profile: hyperscale-build 220 W/SF, colocation 130 W/SF, powered shell 60 W/SF, generic enterprise colocation 110 W/SF. Secured capacity from stabilization profile: stabilized colocation 90% secured, conversion 50%, powered shell 55%, hyperscale build 35%, development 30%. Capacity gap percentage drives the interconnection timeline proxy: 9 months when gap below 10%, 24 months when 10-30%, 36 months when 30-55%, 48 months when above 55%. Market detection from address: Northern Virginia (Ashburn, Loudoun, Manassas, Sterling), Phoenix, Silicon Valley (Santa Clara, San Jose) tagged high grid congestion; Dallas / North Texas, Atlanta, Chicago, Hillsboro / Portland, Columbus tagged elevated; Reno and unknown markets tagged moderate. Utility execution risk computed from congestion plus gap: high when grid is high and gap above 30%; elevated when grid high alone or gap above 45%, or grid elevated with gap above 20%; moderate when gap above 15%; otherwise low. Five weighted drivers scored 0-100: secured capacity coverage 35% (band by coverage: 88 above 90%, 72 above 75%, 55 above 55%, 35 above 35%, 20 below), interconnection timeline 25% (band by months vs required power-online window of lease-up plus 6 months: 88 below 12 months, 65 within window, 40 within window plus 12, 22 longer), grid congestion 20% (band by market: 80 low, 62 moderate, 42 elevated, 25 high; adjusted by utility execution risk), power cost 10% (band by market cost tier; minus 8 when construction cost inflation is capex-heavy or YoY at 6.5%-plus), sector demand 10% (base 65 for the data center sector tailwind; supply pipeline heavy-oversupply or moderate-oversupply minus 12; constrained or balanced plus 8; macro alignment strongly-aligned plus 6; misaligned minus 8). Bands: power-secured (score 80-plus, gap 10%-or-less, interconnection 12-months-or-less), utility-dependent (62-79, manageable timing dependency), interconnection-risk (45-61, primary underwriting item), power-constrained (less than 45, basis or plan must change), not-applicable, not-assessable. Memo surface: verdict banner with band, score, detected profile, and market; four-stat headline (critical load MW, secured MW, gap MW, interconnection months); horizontal capacity bar showing secured versus gap; three-cell risk tier strip (utility execution, grid congestion, power cost); capacity metric rows with status reads; five-driver weighted score table; underwriting actions (validate utility load commitment letters, reconcile interconnection vs lease-up plan, map utility queue position, stress operating margin against 20% power cost increase, pressure-test absorption); deal implications by band. The module auto-skips when SF, hold, or purchase price are missing on a data-center-flagged deal, returning not-assessable. Data center power capacity tracker uses deterministic market and asset proxies. It is not a utility commitment, an interconnection study, an engineering report, or a power procurement recommendation.
Translates the live macro stack into a deterministic regime-transition map across five inflation and credit regimes: stable-expansion (caps anchored, credit competing for deals, modest rent growth), late-cycle-inflation (CPI above target, real policy restrictive, curve flattening or inverting, refi spreads firmer), tight-credit-reset (lender pullback, CMBS spreads wide, refi windows narrow, equity asks rising), disinflation-relief (CPI cooling, forward rates easing, credit reopening, selective cap compression returning), recessionary-stress (real growth weakening, distress rising, liquidity contracting, opportunistic basis emerging for well-capitalized buyers). The module never forecasts a single number. It applies a seeded Markov-style 12-month transition matrix re-weighted by whichever live signals are available, then squares the matrix for the 24-month outlook. Base 12-month transitions: stable-expansion persists at 72% absent shocks; late-cycle-inflation migrates 28% to tight-credit reset and 18% to disinflation relief; tight-credit-reset migrates 26% to recessionary stress and 22% to disinflation relief; disinflation-relief migrates 42% to stable expansion; recessionary-stress migrates 32% to disinflation relief and 20% back to tight-credit reset. Signal re-weighting: CPI above 4% bumps late-cycle-inflation by 8 percentage points; CPI below 2.5% bumps disinflation-relief by 6; forward refi rate shifts of plus or minus 75 bps push tight-credit-reset or disinflation-relief by 6-7 percentage points; restrictive lending conditions bump recessionary-stress by 6 and tight-credit reset by 4; cap-rate persistence in the reset-risk band bumps tight-credit-reset by 5 and recessionary-stress by 3; macro alignment misaligned bumps tight-credit-reset by 3 and recessionary-stress by 2; the row is normalized to sum to 1. Per-regime pressure tags: cap rate pressure in basis points (stable-expansion -10, late-cycle-inflation +40, tight-credit-reset +75, disinflation-relief -25, recessionary-stress +100), rate pressure in basis points (0, +75, +50, -50, -75), credit availability classification (supportive / neutral / tight / stressed). Six weighted drivers scored 0-100: current regime persistence 25% (12-month adjusted probability of staying in the current regime, scaled to 0-100), forward rate path and SOFR pressure 20% (band by refi rate shift: 78 if shift below -50 bps, 65 if within plus or minus 25, 45 if shift 25-100, 25 if shift above 100), inflation and real-return pressure 15% (CPI bands: 72 below 2.5%, 60 in 2.5-3.5%, 40 in 3.5-4.5%, 22 above 4.5%, with hedge-quality adjustments), bank lending and CMBS spreads 15% (band-driven from lending conditions and CMBS positioning), cap-rate persistence and Treasury spread cushion 15% (band-driven from cap-rate persistence forecast with Treasury spread adjustment), deal timing verdict and macro alignment 10% (verdict-driven from deal cycle timing with alignment adjustment). Bands: stable-regime (stability score 78 plus and 12-month transition probability below 25%), watch-transition (63 plus or 25-40% transition), active-transition (48 plus or 40-60% transition), regime-break-risk (below 48 or above 60% transition), not-assessable. Memo surface: verdict banner with band, stability score, 12-month and 24-month transition probabilities; three-stat headline (current regime, most likely next regime, stability score); inline SVG flow diagram connecting the current regime to the top three transition targets with arrow weights proportional to 12-month probability; five-row transition matrix table with 12-month probability, 24-month probability, cap pressure bps, rate pressure bps, credit availability, and per-regime read; six-driver weighted score table; base-case versus transition-case underwriting adjustment list covering exit cap rate, senior refinance rate, lender appetite, and equity ask and structure, each with low / moderate / high severity; deal implications. The module degrades gracefully when upstream snapshot-dependent modules are unavailable: drivers default to neutral defaults and the inferred current regime falls back to stable-expansion. Macroeconomic regime switcher is a deterministic scenario overlay using seeded transition logic and available live-market context. It is not a macro forecast, market prediction, or investment recommendation.
Distressed and transitional CRE deals are not a single IRR. They are a path: acquisition basis, capital needs, lease-up, lender friction, cap-rate reset risk, and eventual stabilization. The IC question is whether the underwriting actually traces a believable trajectory from a depressed Year-1 position to a stabilized exit, or whether the model is hoping for a clean rescue the operating data does not yet support. This module synthesizes the upstream stabilization-year signal, distress cycle context, implied capex yield curve, year-over-year NOI decomposition, exit-liquidity overlay, and debt + refi resilience into a single five-phase path (acquire / fund / stabilize / harvest / exit) with per-year status. Phase assignment: Y1 acquire, Y_hold exit, and the years between are mapped against the stabilization-year signal (pre-stabilization = fund, the stabilization year = stabilize, post-stabilization through Y_hold-1 = harvest). Per-year row carries phase, NOI, year-over-year NOI delta, capex load drawn from the implied capex yield curve when applicable, net cash flow (NOI minus debt service minus capex), cumulative cash flow against the equity check, yield-on-cost, and a status (supportive / neutral / watch / negative) with a phase-aware narrative (funding-year DSCR thinness, stabilization inflection, harvest-period coverage strength, refi window narrowness). IRR bridge decomposes the projected return into four signed dollar contributions: distress basis (purchase price times an estimated basis discount inferred from cycle phase and asset-class distress severity), operational recovery (NOI uplift valued at the stabilized cap), capex drag (total deployed capex, signed negative), and exit multiple (stabilized exit value less the no-recovery baseline less the operational-recovery component). Each component renders as a stacked-bar with positive / negative tint plus an interpretation tied to the dollar magnitudes. Distress basis discount table by cycle phase: peak-distress 18%, early-distress 12%, stabilizing 10%, recovery 5%, expansion 2%, plus asset-class overlay (+10% for severe distress, +5% for elevated, +2% for moderate). Six weighted drivers scored 0-100: stabilization quality 25% (band-driven: 85 stabilized at acquisition, 78 early, 60 mid-hold, 35 late, minus 10 if NOI uplift is negative), distress basis context 20% (cycle phase plus asset-class distress severity), capex productivity 20% (mirror of implied capex yield curve band: 82 value-creating, 68 self-funding, 45 maintenance-drag, 25 capex-burdened), NOI recovery trajectory 15% (band by uplift percentage: 85 >=35%, 72 >=20%, 60 >=10%, 45 >=0%, 25 negative; minus 10 if any year breaches DSCR 1.0), exit liquidity 10% (band-driven from transaction liquidity result with cap rate wave nudge for constructive-reset / dislocation-risk / late-cycle-pressure), debt and refi resilience 10% (refi rate risk max-shift headroom: 82 >=200 bps, 68 >=100 bps, 48 >=50 bps, 30 less; minus 8 if debt yield is binding and underwriting above the lender sizing test). Bands: credible-stabilization (>=78, four-driver alignment with mutually supportive bridge components), basis-driven-upside (63-77, returns rest meaningfully on the discounted entry), execution-dependent (48-62, recovery plausible but each phase carries material risk), distress-trap (<48, deal looks attractive on price but recovery, capex, and exit do not yet close), not-assessable (insufficient inputs). Memo surface: verdict banner with band, score, stabilized year, and projected IRR; four-stat headline (funding years, harvest years, YOC spread bps, total capex load); inline SVG path visual color-banded by phase with year axis and NOI line; year-by-year path table with phase, NOI, delta NOI, capex, net cash flow, yield-on-cost, and status note; IRR bridge bars with signed contributions and per-component interpretation; six-driver weighted score table; underwriting actions tied to band severity (pressure-test stabilization, re-underwrite basis when no discount applies, sequence capex against lease-up, confirm NOI line-item support, identify exit buyer archetype, stress refinancing path); deal implications. The IRR bridge is an attribution, not a forecast: it decomposes the model already on screen rather than predicting an outcome. Distress-to-stabilized IRR path is a deterministic underwriting overlay, not an investment recommendation; cross-check the engineering scope and sponsor track record before underwriting any value-creation story.
Phase 3 begins: live market data overlay (FRED Treasury / SOFR / CPI / inflation expectations) + 18 more institutional analytics. Live macro frame, deal-vs-market positioning, deterministic engine guarantee preserved (Cherry Street regression byte-identical with seeded fallbacks). 90 modules shipped today.
Capex is often modeled as a reserve line, but institutional committees care about whether each future dollar of capex is actually earning its keep. This module converts forward capex obligations into a yield curve by year and category, then compares the spend against incremental NOI and value creation. The practical IC question: are we funding value creation or just feeding the asset? Six capex categories tracked: reserves (recurring replacement, modeled per proforma reserves line or institutional baseline 2% of EGI / 25 bps of price minimum), leasing (TI/LC on lease commencement, modeled from proforma leasing capex), climate (jurisdiction-mandate retrofit per ClimateMitigationCapex, spread over hold), insurance (mitigation budget triggered when InsuranceLoad above-band), compliance (annual 0.10% of purchase price baseline, 0.25% for jurisdictions with material climate mandate), capital-improvements (value-add improvement budget ~1.5% of purchase price front-loaded over lease-up years). Implied capex yield = total incremental NOI over hold divided by total capex spend. Per-year curve includes total capex, six-category breakdown, incremental NOI, implied yield, cumulative capex, cumulative NOI, and phase label (funding / transition / harvest / steady). Payback year computed as first year cumulative incremental NOI exceeds cumulative capex. Peak funding year identified. Bands: value-creating (≥ 78, yield clears 8% unlevered hurdle and payback inside hold), self-funding (63-77, supportable but not alpha), maintenance-drag (48-62, protects rather than creates value), capex-burdened (< 48, absorbs return), not-assessable. Six drivers weighted: implied yield vs hurdle 30%, payback timing 20%, reserve adequacy + funding smoothness 15%, climate + insurance retrofit burden 15%, stabilization + leasing execution 10%, construction cost inflation 10%. Memo surface: inline SVG bar chart (annual capex) with implied yield line overlay and phase labels; category mix table; year-by-year curve with phase progression; per-driver status table; underwriting actions tied to band. Implied capex yield curve is a deterministic underwriting overlay. It is not an engineering report or construction budget.
Cap rates rarely move in a straight line. They compress, stall, reset, and mean-revert across rate cycles, liquidity windows, sector sentiment, and vintage-year entry points. The IC memo has forward cap forecasts and vintage backtests; this module synthesizes those into a readable pattern diagnosis. Six pattern types: stable-range (entry and exit caps within 75 bps of each other and within 50 bps of long-run anchor), compression-wave (modeled exit cap materially below anchor and cap comps imply below-anchor pricing), expansion-wave (modeled exit above entry by 50+ bps and above anchor), mean-reversion-channel (path trends toward anchor, moderate amplitude, no liquidity stress), rate-shock-reset (Treasury spread pressure plus negative leverage plus widening), liquidity-dislocation (transaction liquidity weak or vintage downside elevated, with cap expansion above 100 bps). Wave phase: early / mid / late / reset / not-assessable. Seeded mid-2026 long-run anchors per Codex spec: Multifamily 5.25%, Industrial 5.75%, Retail 6.25%, Office 7.00%, Hotel 8.00%, Mixed-Use 6.00%, Data Center 6.25%, Life Sciences 6.50%, BTR/SFR 5.75%. Scoring weights: distance from anchor 25%, direction + amplitude 20%, Treasury spread + negative leverage 15%, cap comps support 15%, vintage-year downside read-through 15%, transaction liquidity 10%. Bands: constructive-reset (≥ 78, reset looks priced and path is anchored), range-bound-watch (63-77, visible but contained), late-cycle-pressure (48-62, pricing relies on late-cycle assumptions), dislocation-risk (< 48, reset or liquidity risk), not-assessable. Memo surface: pattern diagnosis card, three-column cap snapshot (entry / exit / anchor), inline SVG forecast path with confidence band and anchor reference, per-driver status table with contribution and interpretation, underwriting actions tied to pattern, deal implications. Confidence score derived from how many drivers are negative or watch. Path rows include year, forecast cap, lower / upper confidence bands, and phase label (entry / ramp / approach / exit). Cap rate wave pattern detector is a deterministic cycle-pattern overlay built from seeded institutional anchors and upstream engine signals. It is not a market forecast or valuation opinion.
META synthesis across seven capital-market drivers into one capital-structure recommendation. The institutional question is no longer "what does this deal support?" but "what capital structure should a sponsor actually pursue in this rate, liquidity, and cycle environment?" Drivers weighted: debt sizing + lender risk 25% (debt sizing headroom vs binding constraint, lender risk band AAA-equivalent to Distressed), DSCR + debt yield + coverage 20% (min DSCR over hold, Y1 debt yield against 8% floor), refinance rate risk 15% (max bps shift the deal tolerates while clearing 1.25x DSCR), bank lending + CMBS conditions 15% (lending conditions band + CMBS spread positioning), Treasury spread + negative leverage 10% (entry cap vs senior rate, stabilized spread vs 10Y), existing capital stack recommender 10% (LTV guidance + structure label), foreign capital appetite + exit liquidity 5%. Output: recommended senior LTV range (asset-class adjusted: Office -5pp, Hotel -3pp, MF/Industrial +3pp), total LTV ceiling with mezz allowance (10pp acceptable when institutional-ready + DSCR >= 1.30, 5pp when bankable + DSCR >= 1.20, 0pp otherwise), fixed-versus-floating preference (fixed-preferred when rates elevated or DSCR thin, floating-acceptable when lease-up or NOI growth provides take-out, floating-only-with-cap when modest cushion, avoid-floating when refi failure or thin cushion), mezz tolerance (none / limited / selective / acceptable), preferred term (5/7/10 years based on refi cushion), covenant posture (standard / tightened / defensive), execution route (relationship-bank / life-company / debt-fund / cmbs / agency-or-bank / mixed-market). MF routes to agency-or-bank; institutional-ready Office/Retail/Industrial route to life-company; selective transition deals route to debt fund; CMBS only when spread + collateral signals supportive. Bands: institutional-ready (≥ 78, clear senior LTV, standard covenants), bankable-with-structure (63-77, tighter structure required), selective-lender-fit (48-62, lender-type dependent), capital-stack-friction (< 48, reduce leverage), not-assessable. Memo surface: per-driver status with contribution and interpretation; structure recommendations; lender conversation points; deal implications. Module never names specific lenders as providers. Capital stack optimizer is a deterministic structure recommendation overlay. It is not a financing commitment, lender quote, or securities recommendation.
Country-level granularity on foreign capital appetite, layered onto the market-level Cross-Border Capital signal. Cross-border capital can materially change exit liquidity, pricing depth, and buyer behavior; this module breaks the appetite down by capital pool of origin. Twelve seeded country-level capital pools spanning North America, Asia, Middle East, Europe, and Pacific: Canada (mixed pension + insurance, MF / Industrial / Mixed-Use favored, low friction, low hedge), Singapore (sovereign, Logistics / Data Centers / gateway trophy / operating platforms, mega-check), UAE (sovereign, trophy / Hotel / Mixed-Use / Logistics, AED-USD peg means zero hedge), Norway NBIM (sovereign + pension-style, core income / sustainability-aligned), Japan (insurance + bank, core income with currency-hedged stability, high yen hedge pressure), South Korea NPS (pension + insurance, Logistics / office recapitalizations / income durability), Germany (insurance + pension, core / sustainability-aligned / EU-friendly governance), United Kingdom (institutional + private, gateway-market mid-market), Qatar QIA (sovereign, trophy / Mixed-Use / hospitality / durable income), Saudi PIF (sovereign + private, growing US allocation in Logistics / hospitality / platform-scale, moderate CFIUS friction), Australia superannuation (income assets / platform strategies, moderate AUD hedge), China (private + institutional, materially higher policy + outbound-capital friction in current regime). Per-country signals: asset-class fit modifier (-20 to +30), check-size fit modifier (-15 to +10), regulatory friction (low / moderate / high CFIUS-sensitivity), currency hedge pressure (low / moderate / high). Scoring weights: asset-class fit 35%, check-size fit 20%, regulatory friction 15%, currency hedge 10%, cross-border tailwind from upstream 10%, exit liquidity Treasury-spread bonus 10%. Bands: global-capital-tailwind (score ≥ 78, three or more strong/moderate fits), selective-cross-border-depth (62-77, two or more credible fits), domestic-led-market (45-61, foreign appetite exists but not central to exit), cross-border-friction (< 45 or friction risks dominate), not-assessable. Memo surface: primary capital origins table with appetite score + fit + friction + hedge + check; watchlist origins (high-friction / constrained); buyer pool read-through narrative; currency and policy risks; underwriting actions tied to band; deal implications. Country-level foreign capital appetite uses deterministic seeded proxies, not a live fund-flow database or buyer list. Module never names specific institutions as bidders.
Frames whether the current deal's entry environment looks favorable, neutral, or adverse against seeded historical vintage cohorts. Institutional investors evaluate real estate through vintage-year discipline: year of entry matters because rate regime, cap-Treasury spread, liquidity, inflation, and capital availability shape forward returns. Eight seeded historical cohorts span 2003 through 2026: 2003-2005 (low-rate expansion, +10.5% median unlevered return, 15% downside frequency, 275 bps typical Treasury spread); 2006-2007 (peak liquidity, tight spreads, +4.0% median, 55% downside, 75 bps spread, the weakest cohort and the warning analog); 2009-2011 (distressed reset, +18.0% median, 8% downside, 500 bps spread, the opportunistic vintage); 2013-2015 (recovery expansion, +12.0%, 12% downside, 350 bps spread); 2018-2019 (mature cycle, +9.0%, 25% downside, 200 bps spread); 2020-2021 (emergency-rate compression, +14.0% nominal, 35% downside, 90 bps spread, the reset-risk setup); 2022-2024 (rate shock reset, +7.0%, 25% downside, 175 bps); 2025-2026 (higher-for-longer normalization, +10.0%, 20% downside, 225 bps spread). Deterministic similarity scoring across cap rate direction, liquidity, macro regime, Treasury spread, and asset-class dispersion modifier (Industrial / Data Center favored in 2020-2021 and 2025-2026; Office penalized 2020-2024). Vintage score 0-100 from weighted blend of top-3 cohort matches plus Treasury spread sufficiency adjustment (+/- 20) plus cap persistence band adjustment (+/- 15). Bands: favorable-vintage (≥ 75), selective-vintage (60-74), neutral-vintage (45-59), challenged-vintage (< 45), not-assessable. Memo surface: closest 3 cohorts with similarity, returns, downside frequency, lesson; current entry profile card with Treasury spread + cap persistence + liquidity + inflation + debt market signals; underwriting actions tied to band; deal implications. All cohort returns and downside frequencies are institutional proxy assumptions, not actual fund performance data.
Estimates whether the underwritten exit cap is likely to persist, compress, or mean-revert toward a long-run anchor over the deal hold. Cap rate assumptions are often the most sensitive and least audited part of a CRE underwriting model; this module surfaces the gap between underwriting and likely market trajectory. Mid-2026 long-run anchor cap rates (asset-class seeded institutional estimates): Multifamily 5.25%, Office 7.25%, Retail 6.75%, Industrial 5.75%, Hotel 8.00%, Mixed-Use 6.00%, Data Center 5.50%, Life Sciences 6.25%, BTR / SFR 5.75%. Forecast model: linear blend of starting cap toward anchor over hold, modulated by reversion pressure adjustments. Adjustments: +20% if macro regime is late-cycle or recession, +15% if cap comp average exceeds underwriting, +15% if cycle-adjusted target exceeds underwriting, -10% if cycle-adjusted target below underwriting, -15% relief if underwriting already exceeds long-run anchor. Confidence bands widen with sqrt(time) scaled by asset-class risk multiplier (Office 1.8x and Hotel 1.5x widest, Mixed-Use 1.2x and Retail 1.3x middle, Multifamily and Industrial 1.0x tightest, Data Center 1.4x, Life Sciences 1.3x, BTR/SFR 1.1x). Per-year forecast row includes forecast cap, lower / upper confidence band, confidence tier (high / medium / low based on hold year), and driver narrative. Persistence score 0-100 based on terminal gap (100 at zero gap, drops 2 points per 5 bps). Bands: persistent (score ≥ 75, ≤ 25 bps gap), mild-mean-reversion (≥ 60, 25-75 bps), active-mean-reversion (≥ 45, 75-125 bps), reset-risk (< 45 or > 125 bps gap), not-assessable (insufficient inputs). Exit value impact percentage computed: how much exit value changes if forecast holds instead of underwriting. Inline SVG visual shows forecast path with confidence band and underwriting baseline. Cap rate persistence forecast is a deterministic sensitivity overlay, not a market prediction or appraisal conclusion.
IC committees often start with a return requirement, then work backward to the maximum defensible bid. Module solves for max purchase price at multiple target IRRs using the engine's bisection solver across $100K to $100M of search space, holding operating forecast and capital structure constant (LTV-based debt sizing flexes with price). Risk profile inferred from inputs: value-add when leaseUpYears ≥ 2 or LTV ≥ 0.75 (targets 12%, 14%, 16%); core-plus when leaseUpYears ≥ 1 or LTV ≥ 0.70 (10%, 11%, 12%); core otherwise (8%, 9%, 10%). Base target is the middle of the chosen array. For each target IRR, returns: max purchase price, discount or premium to current price, implied entry cap rate (Y1 NOI / max bid), implied basis per unit/key/SF, and feasibility flag (clears / near / shortfall). Bid discipline bands measured against base target: inside-target (current ≤ max bid, deal clears with headroom), near-target (current 0-3% above max, modest negotiation distance), pricing-gap (3-8% above, material gap requiring upside thesis), overbid-risk (>8% above, requires documented IC override), not-assessable (solver shortfall). Surfaces interpretation, underwriting actions tied to band severity, and IC-grade implications. Reverse-engineered bid holds the current operating forecast constant and solves only for acquisition price sensitivity. This is a sensitivity analysis, not a valuation opinion.