The Modern Apartments San Diego Stress Test

A sponsor is requesting acquisition financing at 70% LTV for The Modern Apartments in San Diego. Stress test the deal: what happens to DSCR if rent growth comes in at the bear-case forecast and exit cap rates widen 50 bps?

Sep 10

Loan proceeds or LTV

70% LTV (proceeds solved off lender value)

Rate or spread

6.01% (Fannie Mae Conventional, 10-yr, 65% LTV tier, quote 9/2/26 — closest agency bracket to 70% ask)

Term / IO / amortization

10-year term, 2 years IO, 30-year amortization thereafter

Loan flavor

Acquisition-term (sized on in-place stabilized cash flow)

Mode

Origination (underwrite the sponsor's request)

Recourse offered

Non-Recourse

Credit box

Max LTV 65-75% (agency), DSCR floor 1.25x (1.20x acceptable with IO), debt yield floor 9.5% (8.5% stabilized MF in strong markets)

Call protection

24-month lockout, 3-month open window, yield maintenance in between

What you want scrutinized

Stress test the deal: what happens to DSCR if rent growth comes in at the bear-case forecast and exit cap rates widen 50 bps?

Command

84 lines

cat > /vercel/sandbox/rent_forecast_payload.json << 'EOF'
{
  "metric": {"name": "mf_rent_ts.in_place_rent_latest_avg (Kearny Mesa submarket)", "units": "$", "family": "rent_or_occupancy"},
  "subject": {"entity_type": "submarket", "entity_id": "982bf6c156483409a1bbdf93bf19e718", "label": "Kearny Mesa submarket (San Diego, CA) - The Modern Apartments"},
  "horizon": {"years": 5, "intervals": "annual"},
  "as_of": "2026-09-10",
  "history": [
    {"period": "2024-07-01", "value": 3022.723997, "source": "datamart"},
    {"period": "2024-08-01", "value": 3024.011463, "source": "datamart"},
    {"period": "2024-09-01", "value": 3036.957698, "source": "datamart"},
    {"period": "2024-10-01", "value": 3030.857595, "source": "datamart"},
    {"period": "2024-11-01", "value": 3021.978720, "source": "datamart"},
    {"period": "2024-12-01", "value": 3020.078533, "source": "datamart"},
    {"period": "2025-01-01", "value": 3017.391461, "source": "datamart"},
    {"period": "2025-02-01", "value": 3007.569557, "source": "datamart"},
    {"period": "2025-03-01", "value": 3007.699089, "source": "datamart"},
    {"period": "2025-04-01", "value": 2995.627378, "source": "datamart"},
    {"period": "2025-05-01", "value": 2996.646853, "source": "datamart"},
    {"period": "2025-06-01", "value": 3001.245485, "source": "datamart"},
    {"period": "2025-07-01", "value": 3001.464247, "source": "datamart"},
    {"period": "2025-08-01", "value": 2997.540537, "source": "datamart"},
    {"period": "2025-09-01", "value": 3034.687400, "source": "datamart"},
    {"period": "2025-10-01", "value": 3029.690126, "source": "datamart"},
    {"period": "2025-11-01", "value": 3028.379745, "source": "datamart"},
    {"period": "2025-12-01", "value": 3022.137412, "source": "datamart"},
    {"period": "2026-01-01", "value": 3019.627989, "source": "datamart"},
    {"period": "2026-02-01", "value": 3004.158792, "source": "datamart"},
    {"period": "2026-03-01", "value": 3005.869574, "source": "datamart"},
    {"period": "2026-04-01", "value": 3006.673684, "source": "datamart"},
    {"period": "2026-05-01", "value": 3009.460202, "source": "datamart"},
    {"period": "2026-06-01", "value": 3011.400054, "source": "datamart"},
    {"period": "2026-07-01", "value": 3016.440423, "source": "datamart"},
    {"period": "2026-08-01", "value": 3019.450457, "source": "datamart"}
  ],
  "history_check": {"count": 26, "first_value": 3022.723997, "last_value": 3019.450457},
  "peer_history": [
    {"period": "2024-07-01", "value": 2845.428015, "source": "datamart"},
    {"period": "2024-08-01", "value": 2853.846655, "source": "datamart"},
    {"period": "2024-09-01", "value": 2864.952843, "source": "datamart"},
    {"period": "2024-10-01", "value": 2865.972254, "source": "datamart"},
    {"period": "2024-11-01", "value": 2863.159043, "source": "datamart"},
    {"period": "2024-12-01", "value": 2861.026584, "source": "datamart"},
    {"period": "2025-01-01", "value": 2857.268342, "source": "datamart"},
    {"period": "2025-02-01", "value": 2863.148358, "source": "datamart"},
    {"period": "2025-03-01", "value": 2865.532390, "source": "datamart"},
    {"period": "2025-04-01", "value": 2865.482531, "source": "datamart"},
    {"period": "2025-05-01", "value": 2866.155698, "source": "datamart"},
    {"period": "2025-06-01", "value": 2868.855569, "source": "datamart"},
    {"period": "2025-07-01", "value": 2872.012853, "source": "datamart"},
    {"period": "2025-08-01", "value": 2870.872415, "source": "datamart"},
    {"period": "2025-09-01", "value": 2877.035058, "source": "datamart"},
    {"period": "2025-10-01", "value": 2870.814240, "source": "datamart"},
    {"period": "2025-11-01", "value": 2867.102616, "source": "datamart"},
    {"period": "2025-12-01", "value": 2866.072514, "source": "datamart"},
    {"period": "2026-01-01", "value": 2869.285334, "source": "datamart"},
    {"period": "2026-02-01", "value": 2869.508619, "source": "datamart"},
    {"period": "2026-03-01", "value": 2870.882704, "source": "datamart"},
    {"period": "2026-04-01", "value": 2874.346933, "source": "datamart"},
    {"period": "2026-05-01", "value": 2877.189242, "source": "datamart"},
    {"period": "2026-06-01", "value": 2882.825459, "source": "datamart"},
    {"period": "2026-07-01", "value": 2891.514593, "source": "datamart"},
    {"period": "2026-08-01", "value": 2897.170591, "source": "datamart"}
  ],
  "peer_history_check": {"count": 26, "last_value": 2897.170591},
  "caller_disclosures": {
    "peer_selection_basis": "parent market (San Diego, CA CBSA) default; level ratio ~1.04 (submarket in-place rent runs ~4% above the metro), both series roughly flat-to-slightly-up over the trailing 12 months",
    "sibling_series_note": "asking rent not pulled in this fetch for the submarket; not checked this call",
    "lookback_note": "full available monthly history (26 months, 2024-07 to 2026-08); prior months null in source and dropped, not zero-filled",
    "signals_omitted": [
      {"signal": "migration", "reason": "not gathered"},
      {"signal": "employment", "reason": "not gathered"}
    ]
  },
  "context_signals": {
    "supply_pipeline": {
      "existing_stock": 24512,
      "permitted_units_t13_t24": 8848
    }
  },
  "scenarios": ["base", "upside", "downside"]
}
EOF
python3 skills/forecasting/scripts/forecast.py --file rent_forecast_payload.json > rent_forecast_result.json
cat rent_forecast_result.json | python3 -m json.tool 2>/dev/null || cat rent_forecast_result.json

Command

137 lines

cat > /vercel/sandbox/populate_credit_model.py << 'PYEOF'
import openpyxl

FN = "The Modern Apartments_Credit_UW_2026-09-10_v1.xlsx"

def write_common(wb, noi_growth):
    A = wb["Assumptions"]
    # Collateral
    A["C5"] = "The Modern Apartments"
    A["C6"] = "3201 Annrae St"
    A["C7"] = "San Diego, CA 92123"
    A["C8"] = "Multifamily"
    A["C9"] = 369
    A["C10"] = 367155
    A["C11"] = "Units"
    A["C13"] = 1959
    A["C14"] = 0.9675
    A["C15"] = "T12 Actuals"

    # Loan request
    A["F5"] = "Origination"
    A["F6"] = "Acquisition-Term"
    A["F7"] = "2026-11-01"
    # F8 requested proceeds written by caller after first pass
    A["F9"] = 0.0601
    A["F10"] = 10
    A["F11"] = 2
    A["F12"] = 30
    A["F14"] = 0.01
    A["F15"] = "Non-Recourse"

    # Credit box
    A["F18"] = 0.75
    A["F19"] = 1.25
    A["F20"] = 1.20
    A["F21"] = 0.095
    A["F22"] = 0.10
    A["F23"] = "default"
    A["F24"] = 50
    A["F25"] = 50

    # Market benchmarks
    A["F29"] = 0.0727
    A["F30"] = 0.05
    A["F32"] = 0.4045
    A["F33"] = 0.42
    A["F35"] = "Yes"
    A["F36"] = 0.0493
    A["F38"] = 3540.36
    A["F44"] = "Modest"

    # Sponsor & growth
    A["C18"] = "Sponsor (undisclosed)"
    A["C19"] = "None"
    A["C20"] = "No"
    A["C28"] = noi_growth
    A["C29"] = 0
    A["C30"] = 0.02
    A["C31"] = "Good"

    # Takeout terms at maturity
    A["C34"] = 0.0601
    A["C35"] = 1.25
    A["C36"] = 0.75
    A["C37"] = 0.095
    A["C38"] = 30
    A["C41"] = "Deep"

    # Recovery-relevant (universal, not bridge-only)
    A["C52"] = 36
    A["C53"] = 0.06
    A["C54"] = 12

    # Rollover (non-MF) — not applicable
    A["F47"] = "No"

    # Flag thresholds
    A["F55"] = 0.90
    A["F56"] = 0.30
    A["F57"] = 0.10
    A["F58"] = 0.03

    # Pro Forma — T12 actuals
    PF = wb["Pro Forma"]
    PF["E5"] = 12485572.08   # GPR
    PF["E6"] = 482471.36     # Vacancy
    PF["E7"] = 0             # Concessions
    PF["E8"] = 0             # Bad debt
    PF["E9"] = 1067470.15    # Other income
    PF["E13"] = 792020.57    # Payroll
    PF["E14"] = 297758.65    # R&M
    PF["E15"] = 813046.50    # Utilities
    PF["E16"] = 0            # Contract services
    PF["E17"] = 0            # Turnover/make-ready
    PF["E18"] = 213359.88    # Marketing & Admin (advertising+G&A)
    PF["E19"] = 326764.27    # Management fee $
    PF["E20"] = 1306170.80   # RE taxes
    PF["E21"] = 320833.83    # Insurance
    PF["E22"] = 128677.91    # Replacement reserves (T12 capex)
    PF["C39"] = 0.0250       # Management fee % of EGI
    PF["C40"] = 348.72       # Replacement reserves $/unit

    # Prepayment
    PP = wb["Prepayment"]
    PP["C4"] = 117
    PP["C5"] = 0.01
    PP["C6"] = 0.02
    PP["C7"] = 50
    PP["C8"] = 24
    PP["C9"] = 3
    PP["C10"] = "Yield Maintenance"
    curve = [0.0400, 0.0415, 0.0439, 0.0444, 0.0457, 0.0468, 0.0477, 0.0526, 0.0525]
    for i, v in enumerate(curve):
        PP.cell(row=27+i, column=4, value=v)  # D27:D35
    PP["C36"] = "2026-09-04"

    # Defeasance
    DF = wb["Defeasance"]
    DF["C11"] = 25000
    DF["C12"] = 40000
    DF["C13"] = 10000
    DF["C14"] = 15000
    DF["C15"] = 10000
    DF["C16"] = "Open Window"

if __name__ == "__main__":
    import sys
    growth = float(sys.argv[1])
    proceeds = sys.argv[2] if len(sys.argv) > 2 else None
    wb = openpyxl.load_workbook(FN)
    write_common(wb, growth)
    if proceeds is not None:
        wb["Assumptions"]["F8"] = float(proceeds)
    wb.save(FN)
    print("wrote", FN, "growth=", growth, "proceeds=", proceeds)
PYEOF
echo done

Now the first pass to establish lender value and size the loan at 70% LTV, then recalc:

The Modern Apartments_Credit_UW_2026-09-10_v1.xlsxAI Created

Excel·123 KB·Sep 10, 2026

Underwriting a $103.3M acquisition loan on The Modern Apartments (369 units, San Diego) at 70% of a $147.5M lender value, 10-year term with 2 years IO, quoted off current Fannie Mae conventional at 6.01% — I ran the credit model, stressed it to bear-case rent growth plus a 50bps cap widening at takeout, and I'm attaching the file. No T12 was uploaded, so the lender case runs off platform-modeled operating data; flag that as the one item to true up against the sponsor's actual books.

70% LTV doesn't clear even before the stress hits — and the stress makes it materially worse

DECLINE at the requested 70% LTV / $103.3M — APPROVE WITH STRUCTURE at $76.6M (pending guarantor review). Debt yield binds hard: lender-case NOI of $7.27M against a 9.5% floor supports only $76.6M, a $26.7M gap to the request . Day-1 DSCR at the full ask is 1.17x — already under both the 1.25x amortizing floor and the 1.20x IO floor — on a 7.04% debt yield and a 20.0% LTV that's fine on its face but meaningless once the income tests fail first .

The credit thesis for a lender at this leverage doesn't hold on in-place income: the 18% haircut from T12 to lender-case NOI (vacancy floor lifted from a reported 3.7% to the market's 7.3%, plus reserves added back into OpEx) leaves too thin a cushion to support 70 cents on the dollar in a market with a going-in cap rate near 4.9% . Even in the base case — a roughly flat 0.4%/year NOI trend drawn from the rent forecast — the maturity refinance already comes up $11.0M short against the standard +50bps rate/+50bps cap stress . Layer in bear-case rent growth (averaging -2.3%/year over the model's five-year forecast horizon, driven by the submarket's flat-to-softening in-place rent trend against a metro peer) and the shortfall triples.

DSCR craters mid-term, not just at maturity. Bear case: 1.15x in Year 1, but the 2-year IO roll-off drags it to 0.91x by Year 3 and it never recovers — 0.78x by Year 10 . Term: a hard 1.20x DSCR cash-sweep trigger from Day 1, since the model shows the cushion is already gone before any stress is applied.
The maturity refinance doesn't clear in either case, and bear-case makes it unbridgeable. Balance at maturity is $90.7M; the stressed takeout (debt-yield-floor bound) delivers $60.7M in the bear case versus $79.7M in the base case — a $30.0M gap versus $11.0M . Term: amortization from Day 1 (no IO extension past year 2) and a mandatory cash-sweep at the 1.20x DSCR trigger to claw back basis before maturity.
No sponsor financials on file. The verdict is capped at Approve with Structure regardless of the numbers above until a PFS substantiates the guarantee . Term: full or springing recourse until financials clear, then release to non-recourse.

Counter-offer: $76.6M (65.7% LTV, 1.58x DSCR, 9.5% debt yield) is what this collateral supports today — an amortization extension doesn't fix it, because debt yield, not DSCR, is the binding constraint at any proceeds level; the only lever is size .

The ask

Sponsor is requesting $103.3M (70% LTV) of acquisition financing on The Modern Apartments, a 369-unit, 1959-built (renovated 2020) garden/townhouse community in Kearny Mesa, San Diego . Non-recourse, 10-year term, 2-year IO, quoted off current Fannie Mae conventional pricing (6.01%, closest agency bracket to the requested leverage) . Origination mode; sponsor undisclosed, no PFS provided.

Coverage

Coverage at the 70% LTV request

Metric	Value
Lender-Case NOI (haircut vs T12)	$7,272,3851
DSCR at Request	1.17x2
Debt Yield at Request	7.04%3
Supportable Loan (binding constraint: Debt Yield Test)	$76,551,417
Surplus/(Gap) vs Request	($26,707,593)

The haircut bites almost entirely on vacancy: the T12's reported 3.7% economic vacancy sits well under the submarket's 7.3% physical vacancy, so the lender case restates revenue at the market floor rather than the sponsor's optimistic actual . In-place income does not carry the requested debt without a business plan — there is no NOI growth story built into Day 1 pricing that gets this to floor at 70% LTV; the gap is basis, not timing.

Getting out at maturity

DSCR over the loan term: base case vs. bear-case rent growth

Balance at maturity is $90.65M regardless of scenario (proceeds and amortization are fixed at close) . What differs is the takeout: at the standard +50bps rate/+50bps cap stress, base-case NOI growth ($7.57M at maturity) supports a stressed value of $139.4M and takeout proceeds of $79.7M — an $11.0M shortfall on its own . Run the same stress against bear-case rent growth (NOI falls to $5.76M by Year 10) and the stressed value collapses to $106.1M, takeout proceeds fall to $60.7M, and the gap widens to $30.0M — 33% short of the balance owed . LTV at maturity climbs from 70.0% to 77.6% under the bear case because value erosion outpaces amortization . San Diego multifamily transaction liquidity is deep enough that a sale exit is realistic, but only at a materially written-down basis from the $147.5M entry value — this is not a refinance that self-heals with time.

Where it breaks

Debt yield never clears the 9.5% floor at any point in the bear case — it runs 6.4%-7.0% throughout the term . NOI break-even (1.00x DSCR) is $6.21M against a $7.27M lender-case NOI, a 14.7% cushion at Day 1 — thin enough that the bear case's cumulative NOI decline burns through it by Year 3. The cap cushion at the takeout is already negative before any stress is layered on: even the unstressed market cap doesn't clear the refinance .

If it defaults

Recovery is strong precisely because the loan is income-constrained, not basis-constrained: at a 20% value decline off the $147.5M lender value, recovery is 98.8% of par — the collateral cushion (basis: 47.8% loan-to-cost equivalent at the counter-offer sizing) absorbs the loss before principal is impaired . What protects par here is basis, not the guarantee — there isn't one on file yet.

Sponsor & guarantee

Sponsor identity, guarantee structure, and financials were not provided with this request.
Verdict is capped at Approve with Structure (pending guarantor review) by the model's own sponsor-and-guarantee test until a PFS is submitted .
Recourse offered is non-recourse; given the debt-yield shortfall at the full ask, full or partial recourse until the covenant package proves out is the more defensible ask.

Collateral & market check

The Modern sits in Kearny Mesa at 96.75% physical occupancy against a submarket running 92.7% — the asset is outperforming its own submarket on occupancy, but submarket in-place rent has been flat to slightly down over the trailing 12 months (0.01% t12 change), consistent with the bear-case forecast's downward path . Supply pressure reads low in the forecast engine's own signal, but San Diego's MF permit pipeline (7,168 units permitted in the trailing 12 months) is not trivial against this submarket's ~24,500-unit base .

Structure

Proceeds: $76.6M (65.7% LTV) — the debt-yield-bound counter-offer, not the requested $103.3M .
Pricing: 6.01%, current Fannie Mae 10-year quote .
Amortization: No IO — begin amortizing from close; extending IO does not fix a debt-yield-bound loan.
Covenants: 1.20x DSCR test with a hard cash-sweep trigger; 9.5% debt-yield test at each anniversary.
Recourse: Partial/springing recourse until a PFS is reviewed and the guarantee structure is set; release to non-recourse on clean financials.
Reserves: Standard replacement reserves at $349/unit/year (matches T12 capex run-rate) .

Bottom line

Decline the $103.3M ask; approve $76.6M with structure, subject to sponsor financials. The single item most likely to move this: a sponsor-submitted T12 and rent roll that shows economic vacancy genuinely running below the 7.3% submarket floor I used — that's the whole haircut, and closing it materially narrows the debt-yield gap. Absent that, the bear-case stress (which is a live scenario, not a tail case, given the submarket's already-flat rent trend) turns a marginal maturity refinance into a $30M hole.

This is a read-only snapshot of a RealAI analysis.