Riyadh Rent Listing Price Delta by District × Category

Date: 2026-09-23 Period: Q1 2025 to Q3 2026, calendar quarters (Q3 2026 is partial: Jul 1 – Sep 22) Scope: Riyadh (city_id = 21), rent categories (yearly prices), excluding daily-rental booking units Data Sources: sadb_listings, sadb_categories, sadb_districts

Question: How did the asking rent of new rent listings in Riyadh change quarter by quarter since Q1 2025, when each (district_id, category) cluster is compared only with itself?

Companion report: Riyadh Sale Listing Price Delta.

Executive Summary

• Riyadh asking rents fell 2.6% from Q1 2025 to Q3 2026 (volume-weighted average delta), or −2.1% on the weighted geometric median, across 209 clusters and 183,907 listings. 36% of clusters ended higher than they started.
• Rents declined for four straight quarters (Q2 2025 → Q1 2026), then recovered. The rent index fell from 105.1 to 96.6, was flat in Q2 2026 (+0.1%), and jumped +4.7% in Q3 2026 with the summer moving season. YoY Q3 2026 vs Q3 2025: +1.7%, back to roughly year-ago levels.
• Apartment for Rent (78% of volume): −4.0% since Q1 2025, but flat YoY (+0.2%). The drop has been largest in the northern districts: An Narjis (−8.7%) and Al Malqa (−8.4%). Ar Rimal (+5.5%) rose.
• Big Flat for Rent: −1.6%, and Villa for Rent: −1.2%. Both fell through 2025 and are now slightly above year-ago levels (YoY +1.0% and +2.0%).
• No quarter since Q1 2025 shows broad rent growth before Q3 2026. This is consistent with the Riyadh rent-increase freeze in effect since September 2025. Sale prices fell much more over the same period (−9.4%, see the companion report).

Methodology

Choice	Value
Listings	city_id = 21, rega_licensed = 1, daily_rentable = 0, price > 0, not deleted
Rent periods	rent_period 0 and 3 are yearly prices (same medians); rent_period 2 (monthly) is excluded
Quarter	Calendar quarter of create_time (Asia/Riyadh). Q3 2026 covers Jul 1 – Sep 22.
Outliers	Per cluster, prices outside the full-period p2–p98 range are dropped
Cluster panel	Balanced: only clusters with ≥ 10 listings in every one of the 7 quarters (209 rent clusters covering over 80% of Riyadh rent listings)
Weight	Cluster’s total listings over the period

A balanced panel means every quarter is measured on exactly the same clusters. A district dropping in or out of a quarter can’t show up as a price change.

Estimators for the Q1 2025 → Q3 2026 delta:

• A: weighted mean of average-price deltas. Σ wᵢ·(avg_Q3’26ᵢ/avg_Q1’25ᵢ − 1) / Σ wᵢ. This is the headline “weighted average price delta”.
• C: weighted geometric mean of median ratios. exp(Σ wᵢ·ln(med_Q3’26ᵢ/med_Q1’25ᵢ) / Σ wᵢ) − 1. This is symmetric for rises and falls and resistant to a few extreme clusters.

The quarterly index is Σ wᵢ·(pᵢ,q/refᵢ) / Σ wᵢ × 100, where refᵢ is the cluster’s full-period average. QoQ is index_q / index_q−1 − 1.

Limitations

• sadb_listings stores only the current price, with no price history. “Price in quarter Q” is the current asking rent of listings created in Q, so price edits made after creation are attributed to the creation quarter.
• These are asking rents, not signed contract rents.
• Rent is seasonal: Q3 (summer moving and back-to-school season) runs high. Compare Q3 2026 with Q3 2025 (YoY), not only with Q2 2026.
• Q3 2026 is partial (it ends Sep 22), but because the panel is balanced, rents are still compared on the same clusters.

Weighted Price Delta by Category

Q1 2025 → Q3 2026, with a same-quarter YoY check (Q3 2026 vs Q3 2025, estimator A). Prices are yearly rent in SAR. Categories with ≥ 5 panel clusters are shown; the “All rent” row includes every category.

Category	Clusters	Listings	Weighted avg rent (Q1’25 → Q3’26)	A: wavg mean Δ	C: wgeo median Δ	YoY Q3 Δ	% clusters up
All rent	209	183,907		−2.6%	−2.1%	+1.7%	36%
Apartment for Rent	91	142,959	51,484 → 49,171	−4.0%	−2.6%	+0.2%	29%
Villa for Rent	29	15,966	113,754 → 110,690	−1.2%	−0.8%	+2.0%	41%
Big Flat for Rent	46	15,776	71,282 → 70,240	−1.6%	−1.2%	+1.0%	37%
Office for Rent	9	2,340	142,701 → 210,496	+45.2%	−10.7%	+74.6%	56%
Lounge for Rent	7	1,620	75,869 → 80,173	+6.1%	+0.1%	+11.8%	43%
Building for Rent	7	1,387	451,045 → 668,613	+44.4%	+58.4%	+50.1%	86%
Room for Rent	5	1,258	14,148 → 12,377	−13.4%	−6.9%	−15.4%	40%
Land for Rent	6	932	1,346,660 → 1,060,713	−11.6%	−37.2%	+30.3%	33%
Store for Rent	5	823	178,793 → 167,763	−3.4%	+7.8%	−6.4%	40%

Only Apartment, Villa and Big Flat for Rent have enough clusters to be reliable. The commercial categories and Room for Rent have fewer than 10 clusters each, and their estimators often disagree on sign, so treat them as noise. Warehouse (3 clusters) and Complex for Rent (1 cluster) are left out of the table. The Complex cluster has an anomalous Q1 2025 median, which nudges the “All rent” C estimate up by about 0.2 pp.

SQL Query

WITH
  base AS (
    SELECT
      l.district_id,
      l.category,
      toStartOfQuarter(toDateTime(l.create_time, 'Asia/Riyadh')) q,
      toFloat64(l.price) price
    FROM
      sadb_listings l FINAL
    WHERE
      l._peerdb_is_deleted = 0
      AND l.rega_licensed = 1
      AND l.daily_rentable = 0
      AND l.price > 0
      AND l.rent_period NOT IN (1, 2)
      AND l.district_id > 0
      AND l.city_id = 21
      AND l.create_time >= toUnixTimestamp(toDateTime('2025-01-01 00:00:00', 'Asia/Riyadh'))
      AND l.create_time < toUnixTimestamp(toDateTime('2026-09-23 00:00:00', 'Asia/Riyadh'))
  ),
  bounds AS (
    SELECT
      district_id,
      category,
      quantile(0.02) (price) lo,
      quantile(0.98) (price) hi
    FROM
      base
    GROUP BY
      1,
      2
  ),
  trimmed AS (
    SELECT
      b.*
    FROM
      base b
      JOIN bounds x USING (district_id, category)
    WHERE
      b.price BETWEEN x.lo AND x.hi
  ),
  cq AS (
    SELECT
      district_id,
      category,
      q,
      count() n
    FROM
      trimmed
    GROUP BY
      1,
      2,
      3
  ),
  -- balanced panel: >= 10 listings in all 7 quarters
  panel AS (
    SELECT
      district_id,
      category,
      sum(n) w
    FROM
      cq
    GROUP BY
      1,
      2
    HAVING
      count() = 7
      AND min(n) >= 10
  ),
  cl AS (
    SELECT
      t.district_id district_id,
      t.category category,
      any(panel.w) w,
      avgIf (price, q = '2025-01-01') a0,
      avgIf (price, q = '2026-07-01') a1,
      avgIf (price, q = '2025-07-01') y0,
      medianIf (price, q = '2025-01-01') m0,
      medianIf (price, q = '2026-07-01') m1
    FROM
      trimmed t
      JOIN panel USING (district_id, category)
    GROUP BY
      1,
      2
  )
SELECT
  c.name_en category,
  count() clusters,
  sum(w) listings,
  round(sum(w * a0) / sum(w)) wavg_q1_25,
  round(sum(w * a1) / sum(w)) wavg_q3_26,
  round(100 * sum(w * (a1 / a0 - 1)) / sum(w), 1) A_delta,
  round(
    100 * (exp(sum(w * log(m1 / m0)) / sum(w)) - 1),
    1
  ) C_delta,
  round(100 * sum(w * (a1 / y0 - 1)) / sum(w), 1) A_yoy_q3,
  round(100 * countIf (a1 > a0) / count()) pct_up
FROM
  cl
  JOIN sadb_categories c FINAL ON cl.category = c.category_id
WHERE
  positionCaseInsensitive(c.name_en, 'rent') > 0 -- rent categories
GROUP BY
  ROLLUP (c.name_en)
ORDER BY
  listings DESC

Quarter-over-Quarter Delta

Weighted quarterly index rebased to Q1 2025 = 100, balanced panel of (district, category) clusters. Hover a point for its value. * Q3 2026 is partial (Jul 1 – Sep 22).

Each value is the weighted rent change from the previous quarter (e.g. Q1’26 = Q1 2026 vs Q4 2025). Cumulative is Q3 2026 vs Q1 2025 on the index. It differs slightly from estimator A above because the index averages normalized rents before dividing, while A averages each cluster’s ratio.

Category	Q2’25	Q3’25	Q4’25	Q1’26	Q2’26	Q3’26*	Cumulative	YoY Q3
All rent	−2.9%	−1.6%	−1.2%	−2.7%	+0.1%	+4.7%	−3.7%	+0.7%
Apartment for Rent	−2.9%	−1.4%	−1.9%	−3.2%	+0.3%	+4.9%	−4.4%	−0.1%
Villa for Rent	−0.9%	−2.7%	+1.0%	−1.8%	+1.2%	+1.2%	−2.0%	+1.6%
Big Flat for Rent	−2.9%	+0.1%	−1.9%	−2.6%	+3.0%	+2.3%	−2.1%	+0.7%

* Q3 2026 is partial (Jul 1 – Sep 22).

Quarterly index (100 = each cluster’s own full-period average):

Category	Q1’25	Q2’25	Q3’25	Q4’25	Q1’26	Q2’26	Q3’26*
All rent	105.1	102.1	100.5	99.3	96.6	96.7	101.2
Apartment for Rent	105.5	102.4	101.0	99.1	95.9	96.2	100.9
Villa for Rent	102.9	102.0	99.2	100.2	98.4	99.6	100.8
Big Flat for Rent	103.4	100.4	100.5	98.6	96.0	98.9	101.2
Listings (all)	23,362	25,386	28,391	25,909	26,254	26,199	28,406

• Apartment for Rent fell for four straight quarters (Q2 2025 → Q1 2026, −9.1% on the index) and bottomed in Q1 2026, which included Ramadan. It then went flat in Q2 and recovered +4.9% in Q3 2026.
• Q3 2025 did not show the same summer jump (−1.4% for apartments). That makes the +4.9% in Q3 2026 more than a normal seasonal rise, although it only brings rents back to year-ago levels (YoY −0.1%).
• Big Flat for Rent turned up earlier than apartments (Q2 2026, +3.0%). Villa for Rent has moved within ±3% every quarter.

SQL Query

-- Same base / bounds / trimmed CTEs as above
cq AS (
  SELECT
    district_id,
    category,
    q,
    avg(price) p,
    count() n
  FROM
    trimmed
  GROUP BY
    1,
    2,
    3
),
panel AS (
  SELECT
    district_id,
    category,
    sum(n) w,
    sum(p * n) / sum(n) ref
  FROM
    cq
  GROUP BY
    1,
    2
  HAVING
    count() = 7
    AND min(n) >= 10
),
j AS (
  SELECT
    cq.category AS cat,
    cq.q AS q,
    cq.p AS p,
    cq.n AS n,
    panel.w AS w,
    panel.ref AS ref
  FROM
    cq
    JOIN panel ON panel.district_id = cq.district_id
    AND panel.category = cq.category
    JOIN sadb_categories c FINAL ON cq.category = c.category_id
  WHERE
    positionCaseInsensitive(c.name_en, 'rent') > 0 -- rent categories
),
r AS (
  SELECT
    cat,
    q,
    100 * sum(w * p / ref) / sum(w) idx,
    sum(n) nq
  FROM
    j
  WHERE
    cat IN (1, 4, 5)
  GROUP BY
    cat,
    q
  UNION ALL
  SELECT
    0 AS cat,
    q,
    100 * sum(w * p / ref) / sum(w) idx,
    sum(n) nq
  FROM
    j
  GROUP BY
    q
)
SELECT
  cat,
  arrayMap(
    x -> round(x.2, 1),
    arraySort(groupArray((q, idx)))
  ) idx_by_quarter,
  arrayMap(x -> x.2, arraySort(groupArray((q, nq)))) listings_by_quarter
FROM
  r
GROUP BY
  cat
ORDER BY
  cat
  -- QoQ = idx[i] / idx[i-1] - 1; Cumulative = idx[Q3'26] / idx[Q1'25] - 1; YoY = idx[Q3'26] / idx[Q3'25] - 1

Top Districts per Category

The 8 highest-volume panel districts per category. The columns are average yearly asking rents (SAR) per quarter. Δ is Q3 2026 vs Q1 2025, and YoY is Q3 2026 vs Q3 2025.

Apartment for Rent

District	Listings	Q1’25	Q3’25	Q3’26	Δ	YoY
An Narjis	13,710	65,015	61,292	59,383	−8.7%	−3.1%
Al Arid	9,774	58,822	58,043	56,396	−4.1%	−2.8%
Al Malqa	9,686	73,849	70,464	67,665	−8.4%	−4.0%
Ar Rimal	6,699	40,307	38,742	42,524	+5.5%	+9.8%
Al Munsiyah	5,661	44,134	43,631	43,015	−2.5%	−1.4%
Dhahrat Laban	5,637	37,636	35,135	36,458	−3.1%	+3.8%
Al Yasmin	5,503	65,283	61,626	62,419	−4.4%	+1.3%
Al Aqiq	4,423	45,807	45,502	46,698	+1.9%	+2.6%

Villa for Rent

District	Listings	Q1’25	Q3’25	Q3’26	Δ	YoY
An Narjis	2,152	143,945	137,400	132,942	−7.6%	−3.2%
Al Arid	1,990	126,711	107,347	113,324	−10.6%	+5.6%
Ar Rimal	1,812	79,699	78,240	73,832	−7.4%	−5.6%
Al Munsiyah	1,041	109,808	119,370	133,349	+21.4%	+11.7%
Al Janadriyah	978	64,385	62,178	62,823	−2.4%	+1.0%
King Khalid International Airport	838	116,665	121,523	155,558	+33.3%	+28.0%
Al Mahdiyah	756	91,353	95,284	89,210	−2.3%	−6.4%
Tuwaiq	634	58,508	56,729	57,342	−2.0%	+1.1%

Big Flat for Rent

District	Listings	Q1’25	Q3’25	Q3’26	Δ	YoY
An Narjis	1,955	83,213	82,020	88,490	+6.3%	+7.9%
Al Yasmin	1,313	80,531	78,071	76,517	−5.0%	−2.0%
Al Arid	1,159	76,669	78,020	75,115	−2.0%	−3.7%
Ar Rimal	939	62,610	58,003	59,729	−4.6%	+3.0%
Tuwaiq	581	47,686	44,638	39,618	−16.9%	−11.2%
Badr	533	37,163	38,516	35,436	−4.6%	−8.0%
Al Munsiyah	497	74,130	66,942	65,805	−11.2%	−1.7%
Al Malqa	453	118,969	103,366	101,346	−14.8%	−2.0%

SQL Query

-- Same base / bounds / trimmed / cq / panel CTEs as the category query, with AND l.category IN (1, 4, 5) in base
cl AS (
  SELECT
    t.district_id district_id,
    t.category category,
    any(panel.w) w,
    avgIf (price, q = '2025-01-01') a0,
    avgIf (price, q = '2025-07-01') y0,
    avgIf (price, q = '2026-07-01') a1
  FROM
    trimmed t
    JOIN panel USING (district_id, category)
  GROUP BY
    1,
    2
),
r AS (
  SELECT
    cl.*,
    row_number() OVER (
      PARTITION BY
        category
      ORDER BY
        w DESC
    ) rk
  FROM
    cl
)
SELECT
  category,
  d.district_name_en district,
  w listings,
  round(a0) q1_25,
  round(y0) q3_25,
  round(a1) q3_26,
  round(100 * (a1 / a0 - 1), 1) delta,
  round(100 * (a1 / y0 - 1), 1) yoy_q3
FROM
  r
  JOIN sadb_districts d FINAL ON r.district_id = d.district_id
WHERE
  rk <= 8
ORDER BY
  category,
  w DESC