Multifamily Market Performance Analysis

For the Los Angeles, Miami, Portland, Atlanta, Dallas–Fort Worth, San Antonio, Phoenix and Austin multifamily markets, show 12-month in-place and asking rent change, new-lease tradeout, occupancy and its 12-month change, median days on market, and operating expenses as a share of EGI. Rank them from strongest to weakest for a lender underwriting a stabilized acquisition loan today, and tell me which markets are where recapitalization demand will be highest. Include a few data visualizations to illustrate your conclusions.

6:23 PM

Command

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mkdir -p mkt && cd mkt && cat > build_records.py <<'EOF'
import json
snap = {  # from query toolu_bdrk_01Ug7QEc82Yzj5X4nn8nwfpa
"Atlanta":dict(id="12060",ask_t12=-0.0166,ip_t12=-0.0050,trade=0.0019,occ=0.935,occ_12=0.954,occ_chg=-0.0189,dom=68,opex=0.5028,ins=0.0419,rti=0.2992,uc=13609,deliv=7104,absn=6230,vac_cw=0.112,cap=0.0533,ask=1790.62,ip=1665.25,permits_t12=12042,permits_t13=11551,retention=0.663),
"Austin":dict(id="12420",ask_t12=-0.0309,ip_t12=-0.0237,trade=-0.0351,occ=0.9258,occ_12=0.9425,occ_chg=-0.0167,dom=72,opex=0.5489,ins=0.0387,rti=0.2147,uc=15174,deliv=5208,absn=5369,vac_cw=0.127,cap=0.0490,ask=1547.27,ip=1501.88,permits_t12=8433,permits_t13=15559,retention=0.648),
"Dallas-Fort Worth":dict(id="19100",ask_t12=-0.0107,ip_t12=-0.0151,trade=-0.0120,occ=0.9269,occ_12=0.9529,occ_chg=-0.026,dom=74,opex=0.5419,ins=0.046,rti=0.2586,uc=30321,deliv=15375,absn=10146,vac_cw=0.119,cap=0.0519,ask=1619.26,ip=1553.15,permits_t12=23605,permits_t13=25675,retention=0.655),
"Los Angeles":dict(id="31080",ask_t12=0.0126,ip_t12=0.0058,trade=0.0166,occ=0.9609,occ_12=0.9718,occ_chg=-0.011,dom=56,opex=0.4309,ins=0.0384,rti=0.4193,uc=19309,deliv=6509,absn=2910,vac_cw=0.058,cap=0.0519,ask=3087.05,ip=2803.94,permits_t12=21985,permits_t13=14684,retention=0.713),
"Miami":dict(id="33100",ask_t12=-0.0051,ip_t12=0.0075,trade=0.0074,occ=0.9635,occ_12=0.9802,occ_chg=-0.0166,dom=63,opex=0.4437,ins=0.0657,rti=0.4729,uc=15067,deliv=3806,absn=1901,vac_cw=0.087,cap=0.0505,ask=2976.17,ip=2682.74,permits_t12=13151,permits_t13=13627,retention=0.670),
"Phoenix":dict(id="38060",ask_t12=-0.0186,ip_t12=-0.0206,trade=-0.0301,occ=0.9326,occ_12=0.9512,occ_chg=-0.0186,dom=67,opex=0.4006,ins=0.0256,rti=0.2667,uc=16457,deliv=8454,absn=6032,vac_cw=0.116,cap=0.0525,ask=1675.94,ip=1597.19,permits_t12=12626,permits_t13=12753,retention=0.629),
"Portland":dict(id="38900",ask_t12=-0.0208,ip_t12=-0.0132,trade=0.0031,occ=0.952,occ_12=0.9627,occ_chg=-0.0107,dom=54,opex=0.4708,ins=0.0285,rti=0.2917,uc=2466,deliv=1170,absn=1150,vac_cw=0.074,cap=None,ask=1805.68,ip=1729.38,permits_t12=3382,permits_t13=3083,retention=0.704),
"San Antonio":dict(id="41700",ask_t12=-0.0362,ip_t12=-0.0185,trade=-0.0377,occ=0.92,occ_12=0.9497,occ_chg=-0.0297,dom=79,opex=0.5827,ins=0.0512,rti=0.2719,uc=3677,deliv=3092,absn=1764,vac_cw=0.157,cap=0.0573,ask=1300.76,ip=1297.49,permits_t12=1471,permits_t13=3751,retention=0.666),
}
# tracked units + in-place Jul-2024 & Aug-2026 from mf_rent_ts toolu_bdrk_011pNQ9hEwRGvMohGGPQguLu
ts = {"Atlanta":(495715,1654.99,1666.14,1834.20,1779.78),"Austin":(355034,1574.35,1505.42,1723.24,1551.36),
"Dallas-Fort Worth":(835724,1541.62,1552.40,1686.38,1617.78),"Los Angeles":(615349,2671.65,2803.23,3186.45,3059.88),
"Miami":(567656,2464.25,2692.70,3024.42,2984.20),"Phoenix":(419412,1637.43,1596.76,1781.73,1677.01),
"Portland":(184014,1756.04,1728.44,1929.60,1809.89),"San Antonio":(211398,1279.89,1298.59,1454.34,1300.89)}
# cap rates 1Q22 (peak pricing) from caprate_ts toolu_bdrk_013caZkfeqH3TDgKWvq4GsQg
cap22 = {"Atlanta":0.0383,"Austin":0.0358,"Dallas-Fort Worth":0.0395,"Los Angeles":0.0387,"Miami":0.0389,"Phoenix":0.0367,"San Antonio":0.0437,"Portland":None}
recs=[]
for k,v in snap.items():
    u,ip24,ip26,ask24,ask26 = ts[k]
    r=dict(entity=k,**v)
    r["tracked_units"]=u
    r["ip_chg_since_jul24"]=ip26/ip24-1
    r["ask_chg_since_jul24"]=ask26/ask24-1
    r["uc_pct_tracked"]=v["uc"]/u
    r["spread"]=v["ask"]/v["ip"]-1
    r["cap_1q22"]=cap22[k]
    if v["cap"] and cap22[k]:
        r["cap_expansion_bps"]=(v["cap"]-cap22[k])*1e4
        r["value_hit_cap_only"]=cap22[k]/v["cap"]-1
    else:
        r["cap_expansion_bps"]=None; r["value_hit_cap_only"]=None
    recs.append(r)
json.dump(recs,open("records.json","w"),indent=1)
recap=[r for r in recs if r["cap"] is not None]
json.dump(recap,open("records_recap.json","w"),indent=1)
for r in recs: print(r["entity"], {k:(round(r[k],4) if isinstance(r[k],float) else r[k]) for k in ["ip_chg_since_jul24","ask_chg_since_jul24","uc_pct_tracked","spread","cap_expansion_bps","value_hit_cap_only"]})
EOF
python build_records.py
S=../skills/multi-entity-analysis/scripts/cross_check.py
python $S --check coverage records.json | head -c 1500; echo
echo LENDER; python $S --check composite --components ip_t12,ask_t12,trade,occ,occ_chg,dom,opex --weights 0.142857,0.142857,0.142857,0.142857,0.142857,-0.142857,-0.142857 records.json
echo RECAP; python $S --check composite --components value_hit_cap_only,ip_chg_since_jul24,occ_chg,trade,uc_pct_tracked --weights -0.2,-0.2,-0.2,-0.2,0.2 records_recap.json

LA and Miami are the safest collateral for a stabilized acquisition loan today, and they're also where the least recapitalization money will be needed. The demand for recap capital sits in Phoenix and Austin, and in Dallas–Fort Worth by sheer size.

All eight markets lost occupancy over the past 12 months. Los Angeles is the only one where asking rents rose , and only LA and Miami grew in-place rents . So this ranking sorts markets by how much weakness each one has, not by which ones are growing.

Stabilized-Acquisition Lender Ranking — 8 Multifamily Markets

Rank	Market	Lender Score	Tier	In-Place Rent 12-Mo Chg %	Asking Rent 12-Mo Chg %	New-Lease Tradeout %	Occupancy %	Occupancy 12-Mo Chg (pp)	Median Days on Market	OpEx % of EGI	Recap-Demand Score
1	Los Angeles	65.01	Strong1	+0.6%2	+1.3%2	+1.7%	96.1%	-1.1 pp2	56	43.1%	38.9
2	Miami	59.8	Strong	+0.8%	-0.5%	+0.7%	96.4%	-1.7 pp	63	44.4%	35.5
3	Portland	56.2	Strong	-1.3%	-2.1%	+0.3%	95.2%	-1.1 pp	54	47.1%	N/A3
4	Atlanta	50.5	Watch	-0.5%	-1.7%	+0.2%	93.5%	-1.9 pp	68	50.3%	49.3
5	Phoenix	48.3	Watch	-2.1%	-1.9%	-3.0%	93.3%	-1.9 pp	67	40.1%	62.0
6	Dallas-Fort Worth	43.9	Weak	-1.5%	-1.1%	-1.2%	92.7%	-2.6 pp	74	54.2%	52.8
7	Austin	41.2	Weak	-2.4%	-3.1%	-3.5%	92.6%	-1.7 pp	72	54.9%	60.6
8	San Antonio	35.1	Weak	-1.8%	-3.6%	-3.8%	92.0%	-3.0 pp	79	58.3%	50.8

How to read the ranking

Los Angeles (Strong). It has the fastest new-lease tradeout (+1.7%) and the second-lowest expense load, at 43.1% of EGI. The catch is that rent is 41.9% of median income , which is severe burden. Price the loan off in-place rent, not upside.
Miami (Strong). It has the highest occupancy of the group at 96.4%, but that fell 1.7 points from 98.0% a year ago . Rent-to-income is 47.3% , and insurance is the heaviest of the eight at 6.6% of EGI . Stress the insurance line harder than any other.
Portland (Strong). It ranks third on its fundamentals: the fastest leasing (54 days on market) and the smallest construction pipeline, 2,466 units . Rents are still falling, though, which holds it just above the cutoff.
Atlanta and Phoenix (Watch). These are close calls that go opposite ways:
- Atlanta's rents are roughly flat, but it carries 13,609 units under construction and 11.2% vacancy on the Cushman & Wakefield count .
- Phoenix has the lowest expense ratio of the eight at 40.1% of EGI , but new leases are signing 3.0% below the prior tenant's rent . That thin expense ratio is what's keeping its ranking up.
DFW, Austin and San Antonio (Weak). Tradeouts are negative, occupancy is 92–93%, and expenses run 54–58% of EGI. San Antonio is last on every one of those measures: 92.0% occupancy, down 3.0 points, 79 days on market, and a 58.3% expense ratio . With margins that thin, even a small drop in revenue can breach a debt-service coverage test.

Only LA and Miami are growing in-place rent; four Sun Belt markets are signing new leases below the prior rent

Occupancy has slipped everywhere; Miami and LA held the high ground

Where recap demand will be highest

A recap is needed when a loan comes due and the property is worth less than the debt, so the owner has to bring in new equity. I sized that gap from three things: how far cap rates have risen since peak pricing, how rents have moved, and how much new supply is still coming.

Phoenix (score 62.0) and Austin (60.6) rank highest .
- Phoenix cap rates went from 3.67% in 1Q22 to 5.25% in 2Q26 . That alone takes about 30% off a 2022 purchase price, before any change in income.
- Austin's in-place rent is down 4.4% since mid-2024, and its pipeline is the largest of the eight relative to its stock, at 4.3% of tracked units .
- For a 65–70% LTV loan from 2022, a 27–30% value drop wipes out most of the equity.
DFW (52.8) is the largest opportunity by dollar volume, even though it ranks third. It has 835,724 tracked units, the most of the group, and 30,321 under construction . Its percentage value drop is milder, but it will produce the most recap deals.
San Antonio and Atlanta are in the middle. Atlanta's cap rates rose 150 basis points (bps), the second-largest increase after Phoenix , but its rents have held.
LA and Miami have the lowest recap demand. Their cap rates also rose 116–132 bps, but in-place rents are up 4.9% and 9.3% since mid-2024 . That rent growth has made up much of the lost value.
Portland isn't scored because it has no cap-rate coverage in the data. Its small pipeline points to limited recap demand.

A 2022 buyer's value hit from cap rates alone — deepest in Phoenix, Atlanta, Austin

Refinancing is also getting more expensive. One industry source reports the Fed raised its target rate to 3.75–4.00% this month, with the 10-year Treasury near 4.94% . If that holds, the equity gap gets wider in every market.

What I'd act on: lend in LA and Miami at in-place rents and hold back on Miami insurance. Pursue recap and rescue-capital deals in Phoenix and Austin, and in DFW for volume. What would change this: if tradeouts in Austin or Phoenix turn positive for a sustained stretch, those two markets move from recap targets to recovery lending, faster than the ranking implies.

How this was scored

Lender score: equal weight (1/7) across the seven metrics you asked for, with days on market and expense ratio counted lower-is-better.
Recap score: equal weight (1/5) across the cap-rate value drop, in-place rent change since July 2024, occupancy change, tradeout, and under-construction units as a share of tracked units.
Rent history: monthly rent data only starts in July 2024, so rent changes since the 2021–22 peak aren't observable.
Expense ratio: market-level benchmark figures, not a specific property's expenses.