Austin Multifamily Refinance Risk Analysis

AXCS provides preferred equity and rescue capital. In the Austin metro, find market-rate properties of 150+ units built 2000 or later that last sold between mid-2021 and September 2022, with the sale price per unit. For each, show in-place rent change over 12 months, current occupancy, and days on market versus its submarket. Rank them by likelihood that the owner faces a refinancing gap today.

6:13 PM

Content

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"""Refi-gap screen: Austin MF, 150+ units, built 2000+, last sold Jul-2021..Sep-2022 with a recorded price.
Inputs are copied from RealAI Datamart query results (property_mfr, submarket, market caprate_ts,
market mf_pnl_benchmarks, mortgage_rates). Assumptions are labeled and editable at the top.
"""
import json

# ---------------- Assumptions (editable) ----------------
ACQ_LTV = 0.65            # assumed acquisition loan-to-price (2021-22 vintage), interest-only, no paydown
CAP_TODAY = 0.0490        # Green Street Austin MF cap rate, 2Q26
MKT_OTHER_INC = 0.1290    # Austin other income % of net rent (mf_pnl_benchmarks)
MKT_NOI_MARGIN = 0.4511   # Austin NOI % of EGI (mf_pnl_benchmarks)
# Refi tiers (Freddie CME fixed, 10-yr, 30-yr amort): (LTV max, rate, DSCR min)
TIERS = [(0.65, 0.0606, 1.35), (0.80, 0.0618, 1.25)]
AMORT_YRS = 30
CAP_AT_SALE = {"3Q21": 0.0354, "4Q21": 0.0343, "1Q22": 0.0358, "2Q22": 0.0389, "3Q22": 0.0398}

def quarter(d):
    y, m = int(d[:4]), int(d[5:7])
    return f"{(m-1)//3+1}Q{str(y)[2:]}"

def constant(r, yrs=AMORT_YRS):
    i = r / 12; n = yrs * 12
    return 12 * i / (1 - (1 + i) ** -n)

# ---------------- Submarket benchmarks ----------------
SUB = {  # id: (name, in-place t12 median chg, occupancy, DOM median)
 "716dd44f13f312a4817bbd9423eb3dfe": ("East Central Austin", -0.0353, 0.9260, 63),
 "ab4b9968f16b41e70abdec1dadf0974d": ("Far West Blvd", -0.0458, 0.9465, 63),
 "bb42723f5a02e4599a1fbd332212f610": ("Round Rock - south", -0.0191, 0.9253, 72),
 "6181e5d5b72e4069a7e1d2e65ec08c92": ("Pershing", -0.0268, 0.9131, 72),
 "4c7e9a0dd70046840796fcbd67aaaaa0": ("Georgetown - west", -0.0296, 0.9290, 69),
 "762e3ab64c7c40341b840a79defcfb9c": ("Cedar Park", -0.0277, 0.9315, 66),
 "91823b937bfddb257636785e0ee3a381": ("Walnut Forest", -0.0620, 0.9105, 72),
 "d2f950a35ddc82a91e1bd462fb2f0909": ("Round Rock - east", -0.0255, 0.9233, 66),
 "fd7bdff3b0991efa1a43d110b35480b0": ("San Marcos/Kyle", -0.0360, 0.9156, 88),
 "8acfa38b5a1b4de4c7126d7c954edfa6": ("Brushy Creek", -0.0426, 0.9592, 63),
 "8d4dfbd44021ad3126e424824bb3c73b": ("Downtown - south", -0.0539, 0.9532, 67),
}

# ---------------- Properties ----------------
# name, id, submarket, units, yr built, sale date, price, ppu, rent_type,
# in-place avg, in-place t12 median chg, occ, DOM, property NOI margin (None -> market), notes
P = [
 ("Bell South Shore","b0f5b109f9cf11e435983afc757f4cf3","716dd44f13f312a4817bbd9423eb3dfe",506,2013,"2022-06-09",177156000,350110.67,"MARKET",1955.76,0.0076,0.9506,99,None,""),
 ("Nalle Woods of Westlake","5618a6580fbbe9ac55b4d5f9bdca9a83","ab4b9968f16b41e70abdec1dadf0974d",238,2003,"2021-07-01",67500000,283613.45,"MARKET",2255.42,-0.0133,0.9496,92,None,""),
 ("Preserve at Rolling Oaks","2dd0fe6fd999ebf09aa45058e347536b","bb42723f5a02e4599a1fbd332212f610",494,2001,"2022-09-29",137283930,277902.69,"MARKET_AND_AFFORDABLE",1497.22,-0.0221,0.9190,60,0.6157,"Fee owner: Housing Authority of the City of Austin (PFC structure)"),
 ("Nexus East","cfa587bca572237b50bea121bab99440","6181e5d5b72e4069a7e1d2e65ec08c92",352,2021,"2021-11-22",86875000,246803.98,"MARKET_AND_AFFORDABLE",1565.90,-0.0538,0.9659,152,None,"Bought in lease-up; 57% rent sample coverage"),
 ("The Summit at Rivery Park","617eace508a346d397fac87ddcde9432","4c7e9a0dd70046840796fcbd67aaaaa0",228,2015,"2022-01-24",51138500,224291.67,"MARKET",1272.60,-0.0245,0.9211,87,None,"56% rent sample coverage"),
 ("Vera Cedar Park","cd067f2bf9b135a7c42cdd701d10d3df","762e3ab64c7c40341b840a79defcfb9c",242,2022,"2021-12-17",52485125,216880.68,"MARKET",1710.31,-0.0086,0.8430,117,None,"Bought pre-completion"),
 ("The Reserve at Walnut Creek","0fcfa1dfbda9297a603f4a3f9641cb89","91823b937bfddb257636785e0ee3a381",284,2002,"2022-04-01",59388605,209114.81,"MARKET",1348.63,-0.0493,0.8345,103,None,""),
 ("Reveal 54","af7af01ac22d70a8fd77d5e857409e70","d2f950a35ddc82a91e1bd462fb2f0909",418,2019,"2021-09-29",85312500,204096.89,"MARKET",1603.83,-0.0313,0.8995,55,0.48,""),
 ("Palm Valley Apartments","b7ff9ca206175cb45c77cd650e7c51b8","d2f950a35ddc82a91e1bd462fb2f0909",340,2008,"2022-01-14",67250984,197797.01,"MARKET",1255.50,-0.0269,0.9235,48,0.4037,""),
 ("Ventana at Plum Creek","c8cd2636b6b06a15637962ee2daad3ba","fd7bdff3b0991efa1a43d110b35480b0",180,2018,"2022-02-28",32867700,182598.33,"MARKET",1355.80,-0.0185,0.9667,217,0.4101,"DOM on few leases (9 unleased units)"),
 ("Lakeline Parmer Lane Apartments","a6b7c5415c2a024dca145a2146518128","8acfa38b5a1b4de4c7126d7c954edfa6",312,2000,"2021-09-15",35000000,112179.49,"MARKET",1169.36,0.0336,0.9135,14,0.3659,"Reported NOI $1.78M used"),
]
LAKELINE_NOI = 1780164.45  # mf_pnl_net_operating_income

recs = []
for (n, pid, sm, u, yb, sd, price, ppu, rt, ipr, ipchg, occ, dom, margin, note) in P:
    smn, s_chg, s_occ, s_dom = SUB[sm]
    q = quarter(sd)
    net_rent = ipr * u * occ * 12
    egi = net_rent * (1 + MKT_OTHER_INC)
    m = margin if margin is not None else MKT_NOI_MARGIN
    noi = LAKELINE_NOI if pid == "a6b7c5415c2a024dca145a2146518128" else egi * m
    value = noi / CAP_TODAY
    loan = price * ACQ_LTV
    proceeds = max(min(ltv * value, noi / (dscr * constant(r))) for ltv, r, dscr in TIERS)
    gap = loan - proceeds
    recs.append(dict(
        entity=n, id=pid, submarket=smn, units=u, year_built=yb, sale_date=sd, sale_qtr=q,
        sale_price=price, price_per_unit=ppu, rent_type=rt, note=note,
        cap_at_sale=CAP_AT_SALE[q], implied_noi_at_sale=price * CAP_AT_SALE[q],
        in_place_rent=ipr, in_place_t12=ipchg, sub_in_place_t12=s_chg, rent_vs_sub=ipchg - s_chg,
        occupancy=occ, sub_occupancy=s_occ, occ_vs_sub=occ - s_occ,
        dom=dom, sub_dom=s_dom, dom_vs_sub=dom - s_dom,
        noi_today=noi, noi_margin=m, noi_chg_vs_sale=noi / (price * CAP_AT_SALE[q]) - 1,
        value_today=value, value_per_unit=value / u, value_chg=value / price - 1,
        est_loan=loan, refi_proceeds=proceeds, refi_gap=gap, gap_per_unit=gap / u,
        gap_pct_of_loan=gap / loan,
    ))

def label(g):
    return "Severe" if g >= 0.30 else ("Material" if g >= 0.10 else ("Thin" if g > 0 else "No gap"))
for r in recs:
    r["gap_label"] = label(r["gap_pct_of_loan"])

json.dump(recs, open("refi_gap/records.json", "w"), indent=1)

# Sensitivity: gap % of loan at alternative acquisition LTV and cap rate
sens = []
for r in recs:
    row = {"entity": r["entity"]}
    for ltv in (0.55, 0.65, 0.75):
        for cap in (0.049, 0.0525, 0.055):
            v = r["noi_today"] / cap
            pr = max(min(l * v, r["noi_today"] / (d * constant(rt))) for l, rt, d in TIERS)
            row[f"ltv{int(ltv*100)}_cap{cap*100:.2f}"] = round((r["sale_price"] * ltv - pr) / (r["sale_price"] * ltv), 3)
    sens.append(row)
json.dump(sens, open("refi_gap/sensitivity.json", "w"), indent=1)

print(f"debt constants: {[round(constant(t[1]),4) for t in TIERS]}")
hdr = f"{'Property':32} {'$/unit':>8} {'Val/u':>8} {'ValChg':>7} {'NOIchg':>7} {'Loan$M':>7} {'Refi$M':>7} {'Gap$M':>7} {'Gap/u':>8} {'Gap%':>6} {'Label':>8}"
print(hdr)
for r in sorted(recs, key=lambda x: -x["gap_pct_of_loan"]):
    print(f"{r['entity'][:32]:32} {r['price_per_unit']:8.0f} {r['value_per_unit']:8.0f} {r['value_chg']:7.1%} {r['noi_chg_vs_sale']:7.1%} "
          f"{r['est_loan']/1e6:7.1f} {r['refi_proceeds']/1e6:7.1f} {r['refi_gap']/1e6:7.1f} {r['gap_per_unit']:8.0f} {r['gap_pct_of_loan']:6.1%} {r['gap_label']:>8}")
print()
print(f"{'Property':32} {'IPchg':>7} {'SubIP':>7} {'Occ':>6} {'SubOcc':>6} {'dOcc':>6} {'DOM':>4} {'SubDOM':>6} {'dDOM':>5}")
for r in recs:
    print(f"{r['entity'][:32]:32} {r['in_place_t12']:7.2%} {r['sub_in_place_t12']:7.2%} {r['occupancy']:6.1%} {r['sub_occupancy']:6.1%} {r['occ_vs_sub']*100:6.1f} {r['dom']:4d} {r['sub_dom']:6d} {r['dom_vs_sub']:5d}")
print()
for s in sens:
    print(s["entity"][:28], {k: v for k, v in s.items() if k != "entity"})

Instructions

Goal: For a preferred-equity / rescue-capital investor, find public evidence of debt distress or recapitalization for 11 Austin-area apartment properties that last sold between July 2021 and September 2022. This feeds a ranking of which owners likely face a refinancing gap today (current date 2026-09-29).

Properties (name — address — last sale date — sale price — recorded fee owner):

Bell South Shore — 1333 Shore District Dr, Austin TX 78741 — 2022-06-09 — $177.2M — BELL FUND VII SOUTH SHORE DISTRICT LP
Nalle Woods of Westlake — 4700 N Capital of Texas Hwy, Austin TX 78746 — 2021-07-01 — $67.5M — MORNINGSIDE NALLE 770 LLC / MORNINGSIDE NALLE MDP LLC
Preserve at Rolling Oaks — 15450 FM 1325, Austin TX 78728 — 2022-09-29 — $137.3M — HOUSING AUTHORITY OF THE CITY OF AUSTIN (likely PFC partnership)
Nexus East — 720 Airport Blvd, Austin TX 78702 — 2021-11-22 — $86.9M — TMP AIRPORT BLVD PROJECT LLC
The Summit at Rivery Park — 1400 Rivery Blvd, Georgetown TX 78628 — 2022-01-24 — $51.1M — 1400 RIVERY PROPERTY LLC
Vera Cedar Park — 805 C-Bar Ranch Trl, Cedar Park TX 78613 — 2021-12-17 — $52.5M — CRP/SRE CEDAR PARK II OWNER LP
The Reserve at Walnut Creek — 8038 Exchange Dr, Austin TX 78754 — 2022-04-01 — $59.4M — RESERVE WALNUT CREEK PROPERTY OWNER LLC
Reveal 54 — 5401 N Mays St, Georgetown TX 78626 — 2021-09-29 — $85.3M — BVF-V GEORGETOWN 2 LLC
Palm Valley Apartments — 1301 N A W Grimes Blvd, Round Rock TX 78665 — 2022-01-14 — $67.3M — PALM VALLEY ACQUISITION LLC
Ventana at Plum Creek — 4624 Cromwell Dr, Kyle TX 78640 — 2022-02-28 — $32.9M — PLUM CREEK MULTIFAMILY PARTNERS LP
Lakeline Parmer Lane Apartments — 10101 W Parmer Ln, Austin TX 78717 — 2021-09-15 — $35.0M — LAKELINE PARMER LANE I LLC

For each property, use web_search (and web_fetch where a result looks relevant) to look for: acquisition financing details (lender, loan amount, loan type e.g., floating-rate bridge / agency / CLO, maturity), foreclosure postings or notices of trustee sale, loan modifications/extensions, special servicing or watchlist mentions (CRE CLO, CMBS/Freddie K-deal), recapitalizations, rescue capital, or resale/listing since the 2021-22 purchase. Also confirm the buyer/sponsor name for the 2021-22 sale. Try 2-3 queries per property (e.g., "<name> Austin apartments loan", "<name> foreclosure", "<sponsor> <name> acquisition"). Keep it efficient; do not spend more than ~4 tool calls per property.

Rules: Report only what a source actually says; do not infer loan terms. Flag conflicts. If nothing is found, say "nothing found". Note that Texas is a non-disclosure state and deed of trust details may not be online.

Output: Save a JSON file at subagents/distress_scan/findings.json with one object per property: {name, sponsor_buyer, lender, loan_amount, loan_type, maturity, distress_signals (list of short strings), sources (list of {url, verbatim_quote})}. Return a compact summary table in your final report with the same fields plus the URL and a short verbatim quote for every fact.

Results

Summary

Ran targeted web searches (2-4 per property) for public evidence of debt distress, foreclosure, special servicing, recapitalization, or resale activity on 11 Austin-area apartment properties sold 2021-2022. No property returned a confirmed foreclosure notice, special-servicing/watchlist listing, CMBS/CRE-CLO delinquency report, or recapitalization announcement naming that specific asset. Texas's non-disclosure status and the absence of asset-specific trade-press coverage limited what's discoverable online. Full detail with quotes/URLs saved to subagents/distress_scan/findings.json.

Compact summary table:

Property	Sponsor/Buyer (confirmed)	Lender/Loan/Maturity	Distress Signals	Confidence
Bell South Shore	Bell Partners (Bell Fund VII)	nothing found	None found; Bell reported securing normal acquisition financing in 2023 (multifamilydive.com)	Low-med
Nalle Woods of Westlake	Morningside Group	nothing found	None found; still under Morningside mgmt	Low
Preserve at Rolling Oaks	Housing Authority of Austin (PFC likely)	nothing found	None found; couldn't locate PFC bond docs	Low
Nexus East	TMP Airport Blvd Project LLC (buyer name beyond LLC unconfirmed)	nothing found	None found; Newmark confirmed as sale broker (rebusinessonline.com)	Low
Summit at Rivery Park	1400 Rivery Property LLC (unconfirmed)	nothing found	None found	Low
Vera Cedar Park	CRP/SRE Cedar Park II Owner LP — possible Carlyle Realty Partners affiliation (unconfirmed, inferred from unrelated BaFin filing naming "CRP/SRE" entities)	nothing found	None found — flagged conflict: sponsor link is speculative	Low
Reserve at Walnut Creek	Reserve Walnut Creek Property Owner LLC (unconfirmed)	nothing found	None found; a SEC CLO exhibit and a generic syndication-loss article both mention "Walnut Creek" but do not refer to this Austin asset — explicitly excluded as false positives	L

Command

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cd /vercel/sandbox && python - <<'EOF'
import re
p='refi_gap/refi_gap_screen.py'; s=open(p).read()
s=s.replace('''    return "Severe" if g >= 0.30 else ("Material" if g >= 0.10 else ("Thin" if g > 0 else "No gap"))''','''    return "Severe" if g >= 0.40 else ("High" if g >= 0.25 else "Moderate")''')
s+='''
# Current debt yield on assumed loan vs debt yield a 1.25x / 6.18% agency refi requires
req_dy = 1.25 * constant(0.0618)
print(f"required debt yield at 1.25x/6.18%: {req_dy:.2%}")
for r in recs:
    print(f"{r['entity'][:32]:32} DY on assumed loan {r['noi_today']/r['est_loan']:.2%}  NOI ${r['noi_today']/1e6:.2f}M  value ${r['value_today']/1e6:.1f}M")
'''
open(p,'w').write(s)
EOF
python refi_gap/refi_gap_screen.py | tail -13
S=skills/multi-entity-analysis/scripts/cross_check.py
python $S --check buckets --field gap_label --expected "Severe,High,Moderate" refi_gap/records.json | tr -d '\n '; echo
python $S --check composite --components gap_pct_of_loan,occ_vs_sub,rent_vs_sub,dom_vs_sub --weights 0.55,-0.15,-0.15,0.15 refi_gap/records.json > refi_gap/composite.json
python - <<'EOF'
import json
d=json.load(open('refi_gap/composite.json')); R={r['entity']:r for r in json.load(open('refi_gap/records.json'))}
for i,x in enumerate(d['ranked']):
    r=R[x['entity']]
    print(f"{i+1}. {r['entity']} | score {x['score']:.1f} | {r['gap_label']} | ${r['price_per_unit']:,.0f}/u ({r['sale_date']}) | est val ${r['value_per_unit']:,.0f}/u ({r['value_chg']:+.0%}) | gap ${r['refi_gap']/1e6:.1f}M = ${r['gap_per_unit']:,.0f}/u = {r['gap_pct_of_loan']:.0%} of loan | IP t12 {r['in_place_t12']:+.1%} vs {r['sub_in_place_t12']:+.1%} | occ {r['occupancy']:.1%} vs {r['sub_occupancy']:.1%} | DOM {r['dom']} vs {r['sub_dom']}")
EOF
python $S --check extremum --field gap_per_unit --direction max --claim "Bell South Shore" refi_gap/records.json | tr -d '\n '; echo
python $S --check extremum --field occupancy --direction min --claim "The Reserve at Walnut Creek" refi_gap/records.json | tr -d '\n '; echo
python $S --check predicate --field in_place_t12 --op gt --value 0 --claim "Lakeline Parmer Lane Apartments" refi_gap/records.json | tr -d '\n '; echo
python $S --check predicate --field value_chg --op gt --value 0 --claim "Lakeline Parmer Lane Apartments" refi_gap/records.json | tr -d '\n '; echo

Eleven market-rate or mixed-income deals fit your filters and have both a recorded price and current operating data. Every one of them likely has a refinancing gap today. The problem is interest rates, not asset value. At a 4.90% Austin multifamily cap rate and about 6.2% on 10-year agency debt at 1.25x coverage , a lender needs about a 9.2% debt yield. If the buyers borrowed 65% of the price, these assets earn only 4.9–7.8% on that loan . Debt coverage is what caps the new loan in every case, not loan-to-value, so the result doesn't change unless cap rates rise above about 5.5%.

The debt is an assumption. I can't see the actual loans (Texas doesn't require sale prices or loan terms to be disclosed). I assumed each buyer borrowed 65% of the price, interest-only, with no paydown.

Ranked by likelihood of a refinancing gap

#	Property (submarket)	Units / built	Sale date · $/unit	Est. value/unit today	Est. gap ($M · % of loan)	In-place rent 12-mo: property vs submarket	Occupancy: property vs submarket	Days on market: property vs submarket
1	Reserve at Walnut Creek (Walnut Forest)	284 / 2002	Apr-22 · $209,115	$140,369 (−33%)	$17.3M · 45%	−4.9% vs −6.2%	83.5% vs 91.0%	103 vs 72
2	Summit at Rivery Park (Georgetown W)	228 / 2015	Jan-22 · $224,292	$146,201 (−35%)	$15.4M · 46%	−2.5% vs −3.0%	92.1% vs 92.9%	87 vs 69
3	Palm Valley (Round Rock E)	340 / 2008	Jan-22 · $197,797	$129,417 (−35%)	$20.2M · 46%	−2.7% vs −2.5%	92.3% vs 92.3%	48 vs 66
4	Bell South Shore (East Central)	506 / 2013	Jun-22 · $350,111	$231,881 (−34%)	$52.4M · 46%	+0.8% vs −3.5%	95.1% vs 92.6%	99 vs 63
5	Nexus East (Pershing)†	352 / 2021	Nov-21 · $246,804	$188,646 (−24%)	$21.0M · 37%	−5.4% vs −2.7%	96.6% vs 91.3%	152 vs 72
6	Vera Cedar Park (Cedar Park)	242 / 2022	Dec-21 · $216,881	$179,827 (−17%)	$10.9M · 32%	−0.9% vs −2.8%	84.3% vs 93.2%	117 vs 66
7	Ventana at Plum Creek (San Marcos/Kyle)	180 / 2018	Feb-22 · $182,598	$148,613 (−19%)	$7.1M · 33%	−1.8% vs −3.6%	96.7% vs 91.6%	217 vs 88‡
8	Preserve at Rolling Oaks (Round Rock S)†	494 / 2001	Sep-22 · $277,903	$234,234 (−16%)	$27.4M · 31%	−2.2% vs −1.9%	91.9% vs 92.5%	60 vs 72
9	Reveal 54 (Round Rock E)	418 / 2019	Sep-21 · $204,097	$191,461 (−6%)	$12.7M · 23%	−3.1% vs −2.5%	90.0% vs 92.3%	55 vs 66
10	Nalle Woods of Westlake (Far West)	238 / 2003	Jul-21 · $283,613	$267,128 (−6%)	$9.9M · 23%	−1.3% vs −4.6%	95.0% vs 94.7%	92 vs 63
11	Lakeline Parmer Lane (Brushy Creek)	312 / 2000	Sep-21 · $112,179	$116,442 (+4%)	$3.3M · 15%	+3.4% vs −4.3%	91.3% vs 95.9%	14 vs 63

Sources: sale data ; property rent, occupancy and days on market ; submarket benchmarks ; modeled value, gap and ranking .

† Mixed market and affordable units. ‡ Ventana's days-on-market figure rests on only 9 unleased units.

Austin-Metro Multifamily Risk Tiers (Ranks 1-11 + 2 Unranked)

What stands out for AXCS

Walnut Creek is the best rescue candidate. It has the lowest occupancy in the set, 7.5 points below its submarket, and it's in the weakest submarket for rents. Its operations are getting worse on top of a roughly 45% gap, which puts the owner under the most pressure.
Bell South Shore is the largest single check. It was bought at the peak (Austin cap rates were 3.89% in 2Q22) for $350K/unit. The estimated gap is about $52M, or about $104K/unit, the most per unit in the set. It is still operating well: it's one of only two properties with rising in-place rent, and occupancy is above its submarket. That makes it a clean preferred-equity story (a sound asset with the wrong debt) rather than an operational turnaround.
Summit at Rivery Park and Palm Valley are similar: early-2022 purchases that operate about in line with their submarkets. They have gaps of about 46% simply because they were bought at a sub-3.6% cap rate.
Vera Cedar Park and Nexus East were bought before lease-up finished. Vera is still at 84% occupancy. Nexus is full, but its rents are falling twice as fast as its submarket, with days on market twice the submarket's.
Lakeline is the only property worth more than its purchase price. Its $112K/unit price is well below the rest of this vintage, so it may have been a partial-interest or non-market sale. Check it before relying on it.

No public distress was found. Searches turned up no foreclosure notices, special-servicing mentions or recapitalizations tied to any of these 11 properties. The only practical way to see the actual loans is the deed-of-trust records at the Travis, Williamson and Hays county clerks.

How the list was built and scored

How the list was built: I searched the Austin metro for properties with 150+ units, built 2000 or later, last sold July 1, 2021 through September 30, 2022. That returned 139 sales, but only 15 had a recorded price; most of the rest were construction or lease-up deals .
- I dropped Champions Crossing and Legacy Lockhart because they are fully affordable.
- Debut SoCo ($252K/unit) and Siena Round Rock ($237K/unit) have no rent or occupancy data, so they aren't ranked .
Mixed-income owners: Preserve at Rolling Oaks and Siena are held by public housing entities. The Austin Housing Authority and Cameron County Housing Finance Corp. are the recorded owners . That structure likely comes with a property-tax exemption, which helps their income.
Estimated income: In-place rent × units × occupancy × 12, plus other income at 12.9% of rent (Austin benchmark). Operating expenses use the property's own expense ratio where one exists, otherwise the Austin benchmark of 45.1% of income left as NOI . Lakeline uses its reported NOI of $1.78M.
Refinance sizing: Value is NOI ÷ 4.90%. The new loan is the larger of two Freddie Mac 10-year fixed options: 65% of value at 6.06% and 1.35x coverage, or 80% at 6.18% and 1.25x, each on a 30-year payment schedule .
Sensitivity: At 55% borrowed instead of 65%, every property except Lakeline still has a gap. At 75% borrowed, gaps are 26–54% .
Ranking weights: The estimated gap as a share of the loan is 55% of the score. The other 45% is split evenly (15% each) across occupancy vs submarket, rent change vs submarket, and days on market vs submarket. The gap is the direct measure; the three operating metrics show whether things are improving or getting worse. Risk tiers: Severe means a gap of at least 40% of the loan, High 25–40%, Moderate below 25%.

If it would help, I can turn this into an Excel model where you can change the assumed borrowing level, rate and cap rate for each property.

AXCS_logo.svg

Image·2 KB

I would like to propose AXCS capabilities to Walnut Creek and propose a solution based on their unique situation. Here is the website for AXCS you can use for your research, and I have attached our logo. https://www.axcscapital.com/

6:53 PM

Content

60 lines

"""Outside-in recapitalization sizing for The Reserve at Walnut Creek (284 units, Austin 78754).
Inputs from RealAI Datamart; assumptions labeled. Illustrative only - to be replaced by owner's T12, rent roll, loan docs.
"""
UNITS = 284
PRICE = 59_388_605            # Apr-2022 sale
ACQ_LTV = 0.65                # assumption (loan not observed)
IP_RENT = 1348.63             # in-place avg, Sep-2026
OCC_NOW = 0.8345              # physical occupancy, Sep-2026
OCC_STAB = 0.94               # stabilization target (property ran 93-99% Jan-Aug 2026; submarket 91.05%)
OTHER_INC = 0.129             # Austin other income % of net rent
NOI_MARGIN = 0.4511           # Austin NOI % of EGI
CAP = 0.049                   # Austin MF cap 2Q26
TAX = 802_870.41              # 2025 property tax
ASSESSED = 36_449_625         # 2025 assessed value

def constant(r, yrs=30):
    i = r / 12; n = yrs * 12
    return 12 * i / (1 - (1 + i) ** -n)

def noi(occ, rent=IP_RENT):
    return rent * UNITS * occ * 12 * (1 + OTHER_INC) * NOI_MARGIN

loan = PRICE * ACQ_LTV
noi_now, noi_stab = noi(OCC_NOW), noi(OCC_STAB)
val_now, val_stab = noi_now / CAP, noi_stab / CAP
agency_now = min(0.80 * val_now, noi_now / (1.25 * constant(0.0618)))
agency_stab = min(0.80 * val_stab, noi_stab / (1.25 * constant(0.0618)))

print(f"Assumed existing loan: ${loan/1e6:.1f}M (${loan/UNITS:,.0f}/unit)")
print(f"NOI today @ {OCC_NOW:.1%}: ${noi_now/1e6:.2f}M | value ${val_now/1e6:.1f}M (${val_now/UNITS:,.0f}/u)")
print(f"NOI stabilized @ {OCC_STAB:.0%}: ${noi_stab/1e6:.2f}M | value ${val_stab/1e6:.1f}M (${val_stab/UNITS:,.0f}/u)")
print(f"Agency proceeds today ${agency_now/1e6:.1f}M -> gap ${ (loan-agency_now)/1e6:.1f}M")
print(f"Agency proceeds stabilized ${agency_stab/1e6:.1f}M -> gap ${ (loan-agency_stab)/1e6:.1f}M")
print(f"Debt yield on assumed loan: today {noi_now/loan:.2%}, stabilized {noi_stab/loan:.2%}")
print(f"Assessed value ${ASSESSED/1e6:.1f}M = {ASSESSED/PRICE-1:+.0%} vs purchase; tax/unit ${TAX/UNITS:,.0f}")
print(f"Lost occupancy revenue: {(OCC_STAB-OCC_NOW)*UNITS:.0f} units x rent = ${(OCC_STAB-OCC_NOW)*UNITS*IP_RENT*12/1e6:.2f}M/yr gross")

# ---- Illustrative recap: bridge-to-stabilization + AXCS rescue preferred equity ----
SR_LTV = 0.65          # new senior bridge sized on current value (GSP-placed)
PREF_CAP = 0.80        # AXCS pref attaches to 80% of current value (last-dollar basis)
RESERVES = 1_500_000   # capex/lease-up + interest-carry reserve funded by pref (assumption)
senior = SR_LTV * val_now
pref_total = PREF_CAP * val_now - senior
pref_to_payoff = pref_total - RESERVES
payoff_capacity = senior + pref_to_payoff
residual = loan - payoff_capacity
print("\n-- Illustrative recap (sized on today's value) --")
print(f"New senior bridge {SR_LTV:.0%}: ${senior/1e6:.1f}M")
print(f"AXCS preferred equity to {PREF_CAP:.0%}: ${pref_total/1e6:.1f}M (of which reserves ${RESERVES/1e6:.1f}M)")
print(f"Capital available to retire existing loan: ${payoff_capacity/1e6:.1f}M")
print(f"Residual to resolve (lender discount/modification + sponsor equity): ${residual/1e6:.1f}M = {residual/loan:.0%} of existing loan")
for split in (0.5,):
    print(f"  e.g. {split:.0%} lender DPO/modification = ${residual*split/1e6:.1f}M ({residual*split/loan:.0%} of loan); sponsor new equity ${residual*(1-split)/1e6:.1f}M")
# Exit test at stabilization
print("\n-- Exit test at stabilization --")
exit_agency = agency_stab
print(f"Stabilized agency takeout ${exit_agency/1e6:.1f}M vs senior+pref ${ (senior+pref_total)/1e6:.1f}M -> coverage {exit_agency/(senior+pref_total):.0%}")
print(f"Stabilized value ${val_stab/1e6:.1f}M; senior+pref LTV at stabilization {(senior+pref_total)/val_stab:.0%}")
print(f"Pref attachment: {senior/val_now:.0%}-{(senior+pref_total)/val_now:.0%} of today's value; ${senior/UNITS:,.0f}-${(senior+pref_total)/UNITS:,.0f}/unit")

Content

245 lines

import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
from docx import Document
from docx.shared import Pt, RGBColor, Inches, Cm
from docx.enum.text import WD_ALIGN_PARAGRAPH
from docx.enum.table import WD_TABLE_ALIGNMENT
from docx.oxml.ns import qn
from docx.oxml import OxmlElement

NAVY = RGBColor(0x00, 0x3D, 0x59); TEAL = RGBColor(0x2A, 0x84, 0x9E); GREY = RGBColor(0x55, 0x5F, 0x66)
NAVY_HEX, TEAL_HEX, LIGHT_HEX = "003D59", "2A849E", "E8F2F5"

# ---------------- Chart: occupancy and asking rent, monthly (RealAI Rent Index) ----------------
months = ["Sep-24","Oct-24","Nov-24","Dec-24","Jan-25","Feb-25","Mar-25","Apr-25","May-25","Jun-25","Jul-25","Aug-25",
          "Sep-25","Oct-25","Nov-25","Dec-25","Jan-26","Feb-26","Mar-26","Apr-26","May-26","Jun-26","Jul-26","Aug-26","Sep-26*"]
occ = [93.3,95.4,96.8,96.5,94.4,95.4,95.1,96.1,95.4,96.1,96.5,95.1,93.7,93.3,94.0,93.7,93.7,94.7,95.4,97.9,97.2,98.6,98.2,98.6,83.5]
ask = [1465,1422,1427,1495,1474,1479,1466,1460,1426,1455,1458,1436,1423,1386,1393,1425,1417,1369,1354,1307,1325,1349,1207,1235,1071]
fig, ax1 = plt.subplots(figsize=(7.2, 3.0), dpi=200)
ax1.plot(months, occ, color="#003D59", lw=2.2, marker="o", ms=3, label="Physical occupancy (%)")
ax1.axhline(91.05, color="#003D59", ls=":", lw=1); ax1.text(0.2, 91.4, "Walnut Forest submarket occupancy 91.1%", fontsize=6.5, color="#003D59")
ax1.set_ylim(80, 100); ax1.set_ylabel("Occupancy (%)", fontsize=8, color="#003D59")
ax2 = ax1.twinx(); ax2.plot(months, ask, color="#2A849E", lw=2.2, marker="s", ms=3, label="Avg asking rent ($)")
ax2.set_ylim(1000, 1600); ax2.set_ylabel("Asking rent ($/mo)", fontsize=8, color="#2A849E")
for a in (ax1, ax2):
    a.tick_params(labelsize=6.5); [s.set_visible(False) for s in a.spines.values()]
ax1.set_xticks(range(0, len(months), 3)); ax1.set_xticklabels(months[::3])
h1, l1 = ax1.get_legend_handles_labels(); h2, l2 = ax2.get_legend_handles_labels()
ax1.legend(h1 + h2, l1 + l2, fontsize=6.5, loc="lower left", frameon=False)
ax1.grid(axis="y", color="#DDDDDD", lw=0.5)
plt.tight_layout(); plt.savefig("chart_ops.png"); plt.close()

# ---------------- Document ----------------
doc = Document()
sec = doc.sections[0]
sec.left_margin = sec.right_margin = Inches(0.9); sec.top_margin = Inches(0.7); sec.bottom_margin = Inches(0.7)
st = doc.styles["Normal"]; st.font.name = "Calibri"; st.font.size = Pt(10.5); st.font.color.rgb = RGBColor(0x22,0x2B,0x30)
st.element.rPr.rFonts.set(qn("w:eastAsia"), "Calibri")
st.paragraph_format.space_after = Pt(5); st.paragraph_format.line_spacing = 1.12
for lvl, size, col in ((1, 15, NAVY), (2, 12, TEAL)):
    h = doc.styles[f"Heading {lvl}"]; h.font.name = "Calibri"; h.font.size = Pt(size); h.font.bold = True; h.font.color.rgb = col
    h.element.rPr.rFonts.set(qn("w:asciiTheme"), "") if False else None
    h.paragraph_format.space_before = Pt(12 if lvl == 1 else 8); h.paragraph_format.space_after = Pt(4)

def shade(cell, hexcol):
    tcPr = cell._tc.get_or_add_tcPr(); sh = OxmlElement("w:shd")
    sh.set(qn("w:val"), "clear"); sh.set(qn("w:color"), "auto"); sh.set(qn("w:fill"), hexcol); tcPr.append(sh)

def bottom_rule(p, hexcol=TEAL_HEX, sz="12"):
    pPr = p._p.get_or_add_pPr(); b = OxmlElement("w:pBdr"); bt = OxmlElement("w:bottom")
    bt.set(qn("w:val"), "single"); bt.set(qn("w:sz"), sz); bt.set(qn("w:space"), "4"); bt.set(qn("w:color"), hexcol)
    b.append(bt); pPr.append(b)

def para(text="", bold_lead=None, size=None, color=None, italic=False, align=None, after=None):
    p = doc.add_paragraph()
    if bold_lead:
        r = p.add_run(bold_lead); r.bold = True; r.font.color.rgb = NAVY
        if size: r.font.size = Pt(size)
    r = p.add_run(text); r.italic = italic
    if size: r.font.size = Pt(size)
    if color: r.font.color.rgb = color
    if align: p.alignment = align
    if after is not None: p.paragraph_format.space_after = Pt(after)
    return p

def bullet(text, lead=None):
    p = doc.add_paragraph(style="List Bullet")
    if lead:
        r = p.add_run(lead); r.bold = True; r.font.color.rgb = NAVY
    p.add_run(text); p.paragraph_format.space_after = Pt(3)
    return p

def table(rows, widths, header=True, bold_last=False, zebra=True, size=9):
    t = doc.add_table(rows=len(rows), cols=len(rows[0])); t.alignment = WD_TABLE_ALIGNMENT.CENTER
    t.style = "Table Grid"
    for i, row in enumerate(rows):
        for j, val in enumerate(row):
            c = t.cell(i, j); c.width = Inches(widths[j]); c.text = ""
            p = c.paragraphs[0]; r = p.add_run(str(val)); r.font.size = Pt(size)
            p.paragraph_format.space_after = Pt(1)
            if j > 0: p.alignment = WD_ALIGN_PARAGRAPH.RIGHT if any(ch.isdigit() for ch in str(val)[:3]) or str(val)[:1] in "$(-+~[" else WD_ALIGN_PARAGRAPH.LEFT
            if header and i == 0:
                shade(c, NAVY_HEX); r.bold = True; r.font.color.rgb = RGBColor(0xFF,0xFF,0xFF)
            elif zebra and i % 2 == 0:
                shade(c, LIGHT_HEX)
            if bold_last and i == len(rows) - 1: r.bold = True
    # light borders
    tbl = t._tbl; tblPr = tbl.tblPr; borders = OxmlElement("w:tblBorders")
    for e in ("top","left","bottom","right","insideH","insideV"):
        el = OxmlElement(f"w:{e}"); el.set(qn("w:val"), "single"); el.set(qn("w:sz"), "4"); el.set(qn("w:color"), "C9D6DC"); borders.append(el)
    tblPr.append(borders)
    doc.add_paragraph().paragraph_format.space_after = Pt(2)
    return t

# Header / footer
hdr = sec.header.paragraphs[0]; hdr.text = ""; r = hdr.add_run("ΛXCS Capital  |  Confidential discussion draft"); r.font.size = Pt(8); r.font.color.rgb = GREY
hdr.alignment = WD_ALIGN_PARAGRAPH.RIGHT
ftr = sec.footer.paragraphs[0]; r = ftr.add_run("ΛXCS Capital · 1900 Avenue of the Stars, Suite 250, Los Angeles, CA 90067 · 650 Fifth Avenue, Suite 1100, New York, NY 10022 · info@axcscapital.com")
r.font.size = Pt(7.5); r.font.color.rgb = GREY; ftr.alignment = WD_ALIGN_PARAGRAPH.CENTER

# ---------------- Cover block ----------------
p = doc.add_paragraph(); p.add_run().add_picture("logo.png", width=Inches(1.15)); p.paragraph_format.space_after = Pt(10)
p = doc.add_paragraph(); r = p.add_run("Recapitalization Proposal"); r.bold = True; r.font.size = Pt(24); r.font.color.rgb = NAVY
p.paragraph_format.space_after = Pt(0)
p = doc.add_paragraph(); r = p.add_run("The Reserve at Walnut Creek  ·  284 units  ·  8038 Exchange Drive, Austin, TX 78754"); r.font.size = Pt(12.5); r.font.color.rgb = TEAL; r.bold = True
bottom_rule(p)
para("Prepared for: Ownership, Reserve Walnut Creek Property Owner LLC", size=9.5, color=GREY, after=0)
para("Prepared by: ΛXCS Investments, with George Smith Partners (GSP)", size=9.5, color=GREY, after=0)
para("Date: September 29, 2026", size=9.5, color=GREY, after=10)

# ---------------- 1. Executive summary ----------------
doc.add_heading("1. Executive summary", level=1)
para("The Reserve at Walnut Creek is a well-located, 2015-renovated garden community whose rents are still "
     "affordable for its residents. It was bought in April 2022 for $59.4 million ($209,115 per unit), when "
     "Austin multifamily cap rates were near 3.9%. Cap rates are now 4.9% and 10-year agency debt costs about "
     "6.2%. On our outside-in estimate, today's lenders would size a new loan at about $21 million. That leaves "
     "a gap of roughly $17 million against a typical 2022 acquisition loan.")
para("The asset isn't broken; the capital stack is. September's move-outs and rent cuts have made that gap "
     "urgent. ΛXCS proposes a three-part recapitalization that keeps the current sponsor in control and buys "
     "the time and reserves needed to re-stabilize:")
bullet(" GSP negotiates with the current lender: an extension or modification, or a discounted payoff, on the existing loan.", "Lender resolution.")
bullet(" GSP places a senior bridge loan sized to today's value (about $25.9 million, 65% of value).", "New senior bridge.")
bullet(" About $6.0 million of preferred equity from ΛXCS. This fills the stack to 80% of today's value and funds a $1.5 million lease-up, capex and interest reserve. The sponsor keeps the upside after the preferred return.", "ΛXCS rescue preferred equity.")
para("We are asking for a no-cost, NDA-protected exchange of the T-12, rent roll and loan documents. That lets us turn "
     "this outside-in view into an indicative term sheet within two weeks of receipt.", italic=True, color=GREY)

# ---------------- 2. What we see ----------------
doc.add_heading("2. What we see: a good asset under sudden leasing pressure", level=1)
doc.add_picture("chart_ops.png", width=Inches(6.6))
cap = para("Monthly physical occupancy and average asking rent. *Sep-26 is the latest weekly reading (week of Sep 26). Source: RealAI Rent Index.", size=8, color=GREY, italic=True)
table([
    ["Indicator (latest)", "Reserve at Walnut Creek", "Walnut Forest submarket", "Read"],
    ["Physical occupancy", "83.5%", "91.0%", "Down from 98.6% three months ago"],
    ["Asking rent (avg)", "$1,071", "$1,318", "−11.6% in 3 months, −11.6% YoY"],
    ["In-place rent (avg), 12-mo change", "$1,349; −4.9%", "$1,295; −6.2%", "Rents holding better than the submarket"],
    ["New-lease trade-out", "−18.2%", "−5.3%", "Aggressive pricing to refill units"],
    ["Days on market (leases signed, 30 days)", "103", "72", "Absorbing slower than peers"],
    ["Retention (trailing 12 months)", "73.2%", "65.8%", "Residents who stay are sticky"],
    ["Rent-to-income ratio", "15.7%", "n/a", "Below Austin average: residents can afford rent"],
    ["2025 assessed value", "$36.4M ($128,344/unit)", "", "−39% vs. purchase price"],
], [2.0, 1.55, 1.35, 1.9])
para("Our read: until this summer the property ran at 93–99% occupancy. The September drop to 83.5% "
     "(54 unleased units) coincided with a sharp asking-rent reset. That is typical of a leasing push while "
     "cash flow is being squeezed by debt service. The fundamentals that matter for recovery are intact: "
     "better-than-submarket in-place rents, 73% retention, affordable rents relative to income, and a "
     "renovated unit finish (LVP, stone counters, in-unit W/D, garages). If the 30 units lost above 94% occupancy are re-leased at today's "
     "in-place rent, that adds about $0.48 million a year to gross revenue.")

# ---------------- 3. The capital gap ----------------
doc.add_heading("3. The capital gap, outside-in", level=1)
table([
    ["", "Amount", "Per unit", "Basis"],
    ["April 2022 purchase price", "$59.4M", "$209,115", "Recorded sale"],
    ["Assumed acquisition loan (65% LTV)", "$38.6M", "$135,925", "Assumption; loan not publicly recorded"],
    ["Estimated NOI today (83.5% occupied)", "$1.95M", "$6,878", "In-place rent + Austin opex benchmarks"],
    ["Estimated value today (4.90% cap)", "$39.9M", "$140,369", "−33% vs. purchase"],
    ["Max agency refinance today (1.25x DSCR, 6.18%)", "$21.3M", "$74,942", "Coverage, not LTV, sets the loan size"],
    ["Estimated refinance gap", "$17.3M", "$60,898", "≈45% of the assumed loan"],
], [2.6, 0.9, 0.9, 2.4], bold_last=True)
para("Two points shape the solution:")
bullet(" Even at 94% occupancy, NOI of about $2.20 million supports only about $24.0 million of agency debt. Operational recovery alone doesn't close the gap at today's rates, which is why patient structured capital is needed.", "Re-stabilizing helps but doesn't solve it.")
bullet(" The debt yield on the assumed loan is about 5.1%. Today's agency sizing needs roughly 9.2%. Any lender is therefore better served by a funded recapitalization than by a forced sale into a market that has repriced about 33%.", "The lender has a reason to negotiate.")

# ---------------- 4. Proposed solution ----------------
doc.add_heading("4. Proposed solution: a sponsor-friendly rescue recapitalization", level=1)
doc.add_heading("Illustrative sources and uses (sized to today's value)", level=2)
table([
    ["Sources", "Amount", "% of today's value", "Uses", "Amount"],
    ["New senior bridge (GSP-placed)", "$25.9M", "65%", "Retire / restructure existing loan", "$30.4M"],
    ["ΛXCS preferred equity", "$6.0M", "65–80%", "Lease-up, capex & interest reserve", "$1.5M"],
    ["Lender concession + sponsor equity", "$8.2M", "—", "Residual existing-loan balance", "$8.2M"],
    ["Total", "$40.1M", "", "Total", "$40.1M"],
], [2.05, 0.8, 1.05, 2.05, 0.8], bold_last=True)
para("The $8.2 million residual is the piece to negotiate. For example, it could be split between a lender "
     "discount or modification of about $4.1 million (11% of the loan) and $4.1 million of new sponsor equity. "
     "If the actual loan was 55% of the purchase price rather than 65%, the residual falls to about $2.3 million. "
     "If it was 75%, the residual rises to about $14.1 million, and a longer extension with the current lender "
     "becomes the better first step.", size=9.5)

doc.add_heading("Why each piece is there", level=2)
bullet(" GSP's loan restructuring and loan sale teams open the conversation with the current lender, special servicer or CLO manager. The goal is an extension, rate cap or interest relief, or a discounted payoff. If the lender prefers to exit, GSP can arrange a note sale to a friendly buyer.", "Step 1: Lender resolution (GSP).")
bullet(" A 3-year floating-rate bridge (plus extensions) from GSP's bank, debt fund and credit-platform relationships. It is sized to in-place income, with future funding for the leasing plan.", "Step 2: Senior bridge (GSP).")
bullet(" Preferred equity attaching at about 65–80% of today's value (about $91,000–$112,000 per unit). A 2026 purchase at that basis would be a deep discount to the 2022 price. The sponsor keeps control of day-to-day operations and all upside above the preferred return.", "Step 3: ΛXCS preferred equity.")
bullet(" Where the sponsor also needs GP capital, ΛXCS can invest as a co-GP instead of, or alongside, the preferred equity.", "Optional: co-GP capital.")
bullet(" Energy and water upgrades (HVAC, roofs, water fixtures) can be financed off-balance-sheet through Texas PACE via ΛXCS's C-PACE platform, subject to program eligibility and senior lender consent. That preserves reserves for leasing.", "Optional: C-PACE.")

doc.add_heading("Indicative preferred equity framework (for discussion)", level=2)
table([
    ["Term", "Indicative structure"],
    ["Amount", "~$6.0M (including ~$1.5M reserves), to be refined on T-12 / rent roll"],
    ["Position", "Preferred equity in the property-owning entity, behind the new senior bridge"],
    ["Attachment / detachment", "~65% / ~80% of current value (~$91K–$112K per unit)"],
    ["Preferred return", "[__]% current pay + [__]% accrued, set at term sheet"],
    ["Term", "3 years + [1+1] extensions, matched to the senior bridge"],
    ["Sponsor role", "Sponsor remains managing member; ΛXCS has customary major-decision consents"],
    ["Protections", "Budget and leasing-plan approvals; performance triggers; step-in rights on default"],
    ["Redemption", "From sale or refinance proceeds, any time after a minimum-return period"],
], [1.7, 5.1])
para("Economic terms are placeholders pending ΛXCS investment committee review and diligence.", size=8.5, italic=True, color=GREY)

# ---------------- 5. Business plan and exits ----------------
doc.add_heading("5. Path to stabilization and exit", level=1)
bullet(" Re-lease the 54 unleased units and return to at least 94% occupancy. Stop blanket asking-rent cuts; lead with targeted concessions and renewals, building on a 73% retention base.", "Months 0–9: refill.")
bullet(" Hold in-place rent near $1,350 and rebuild trade-outs as Walnut Forest supply is absorbed. Review the property-tax assessment each year (the 2025 assessment of $36.4 million already reflects the repricing).", "Months 6–18: protect rent.")
bullet(" At about $2.20 million of stabilized NOI, the property would be worth about $44.9 million at a 4.9% cap. Senior bridge plus preferred equity would then be about 71% of value, a workable sale or recapitalization exit.", "Months 18–36: exit.")
para("To be candid: at today's 6.2% agency rates, a stabilized agency refinance (about $24.0 million) covers about "
     "75% of the senior bridge plus preferred equity. Taking out both through an agency loan needs either about "
     "33% more NOI or lower rates. At a 5.5% agency rate, proceeds rise to about $25.8 million. The base case "
     "exit is therefore a sale or recapitalization at stabilization, with an agency refinance as the upside case.", size=9.5)

# ---------------- 6. Why AXCS ----------------
doc.add_heading("6. Why ΛXCS", level=1)
bullet(" ΛXCS Investments' focus is co-GP investments and preferred equity / mezzanine capital, including opportunistic and special-situations capital such as preferred equity and rescue capital.", "Built for this situation.")
bullet(" Senior decision makers are involved from sourcing to close. We underwrite in-house, manage documentation and stay hands-on through execution.", "One team, start to finish.")
bullet(" Through George Smith Partners, founded in 1992, we've facilitated transactions totaling over $100 billion, of which GSP directly closed or placed over $35 billion. GSP covers debt, structured finance, JV equity, loan restructuring and loan sales, with affiliates including Texas.", "The full capital stack, in-house.")
bullet(" More than 75 CRE professionals, supported by technology that brings transparency, speed and accuracy to execution.", "Speed and certainty.")

# ---------------- 7. Next steps ----------------
doc.add_heading("7. Proposed next steps", level=1)
table([
    ["Step", "What", "Timing"],
    ["1", "Introductory call; mutual NDA", "Week 1"],
    ["2", "Owner shares T-12, current rent roll, loan agreement, maturity and extension terms, lender contact", "Week 1–2"],
    ["3", "ΛXCS / GSP underwriting; indicative term sheet and lender strategy", "Within 2 weeks of data"],
    ["4", "Joint approach to the existing lender; senior bridge quotes", "Weeks 3–6"],
    ["5", "Diligence, documentation and close", "Target 60–90 days"],
], [0.5, 4.7, 1.6])

# ---------------- Appendix ----------------
doc.add_heading("Appendix: basis of estimates", level=1)
for t in [
    "Outside-in estimates only. The existing loan amount, rate, maturity and lender are not publicly recorded in Texas; we assumed a 65%-of-price, interest-only acquisition loan. Every figure will be replaced with the owner's actual documents.",
    "Property operating data: RealAI Rent Index (weekly, as of September 26, 2026), 74% unit coverage, 'Excellent' sample confidence. Submarket: Walnut Forest.",
    "NOI: in-place rent × 284 units × occupancy × 12, plus other income at 12.9% of rent, times the Austin NOI margin of 45.1% of income (RealAI Ops Benchmarks, 577-property sample).",
    "Value: Green Street Austin multifamily cap rate of 4.90% (2Q26). Agency sizing: Freddie Mac CME 10-year fixed, 80% LTV maximum, 1.25x DSCR, 6.18%, 30-year amortization (as of September 23, 2026).",
    "Property tax and assessment: Travis County tax roll, 2025 tax year ($802,870; $36.4 million assessed).",
]:
    bullet(" " + t)
para("This document is a confidential discussion draft for the recipient only. It is not an offer or a commitment to "
     "lend or invest. Any transaction is subject to diligence, investment committee approval and definitive documentation.",
     size=8, italic=True, color=GREY)

doc.save("AXCS_Proposal_Reserve_at_Walnut_Creek.docx")
print("saved")

AXCS_Proposal_Reserve_at_Walnut_Creek.docxAI Created

Word·165 KB·Sep 29, 2026

I've drafted a 5-page proposal from AXCS to the owner of The Reserve at Walnut Creek, using your logo and brand colors. It proposes a three-part rescue that keeps the current owner in control.

Why now. The property ran at 93–99% occupancy through August. It fell to 83.5% in late September, with 54 units unleased . Over the last three months, asking rent dropped 11.6% to $1,071 , and new leases are signing 18% below the previous tenant's rent . The proposal frames this gently: a good asset with the wrong capital structure. Recovery has a real base:

Tenants renew at 73%, better than the submarket's 66% .
Rent is only 15.7% of tenant income, below the Austin average .

The proposed solution. All figures are my estimates from outside data; the actual loan isn't public.

Existing loan: assumed at $38.6M (65% of the purchase price).
Value today: about $39.9M, with a refinance gap of about $17.3M .

Deal with the current lender (GSP). GSP negotiates an extension, a loan modification, or an early payoff at a discount, or arranges a sale of the loan.
New senior loan (GSP). A short-term bridge loan of about $25.9M, or 65% of today's value.
AXCS preferred equity. About $6.0M, filling the stack from 65% to 80% of value (about $91K–$112K per unit). It includes a $1.5M reserve for leasing, repairs and interest.
What's left to negotiate. About $8.2M still needs to come from a lender discount plus new money from the owner .

Optional add-ons: AXCS investing alongside the owner as a co-general partner, and C-PACE financing for energy and water upgrades.

The exit case. Even back at 94% occupancy, an agency loan at today's 6.2% rate covers only about 75% of the new senior loan plus preferred equity. It would take 33% more income or lower rates to close that . So the base-case exit is a sale or recap once the property is full again. At an estimated $44.9M stabilized value, the senior loan plus preferred equity would be about 71% of value .

The AXCS pitch draws on your website:

Your preferred equity, mezzanine and rescue-capital focus, with senior people involved from sourcing to close and underwriting done in-house .
George Smith Partners' $100B+ of transactions facilitated and $35B+ closed or placed, plus its Texas affiliate .
GSP's loan restructuring and loan sale capabilities .

Before you send it:

The preferred return and extension options are blank placeholders ([__]%) for your investment committee to fill in.
I don't know the sponsor behind the owning company, Reserve Walnut Creek Property Owner LLC, so the proposal is addressed to "Ownership." Add a name if you have one.
The residual depends heavily on the real loan size. If the loan was 55% of the purchase price, the residual drops to about $2.3M; at 75%, it rises to about $14.1M . That's why the proposal's ask is an NDA exchange of the income statement, rent roll and loan documents.