Rmr (RMR) Change in Accured Expenses (2014 - 2026)
Rmr (RMR) posted Change in Accured Expenses of $11.52 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), up 51.3% from $7.61 million a year earlier and up 22.0% from the prior quarter.
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Analysis
Rmr (RMR) Change in Accured Expenses (2014 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Change in Accured Expenses at Rmr was $10.95 million, up 312.3% year-over-year; for FY2025 (ended Sep 30, 2025), it was $6.23 million.
- In prior fiscal years, Rmr's Change in Accured Expenses was -$2.32 million in FY2024, $2.29 million in FY2023 (+48.3%), $1.55 million in FY2022 and -$1.72 million in FY2021.
- The fiscal Q3 2026 figure stands as the highest quarterly Change in Accured Expenses since fiscal Q3 2023.
- On a year-over-year basis, Change in Accured Expenses increased in two of the last four quarters, with an average decline of 16.5%.
- The strongest year-over-year quarter for Change in Accured Expenses in the past five years was fiscal Q3 2023, with growth of 77.3%; the weakest was fiscal Q1 2026, with a decline of 91.6%.
- According to Business Quant data, Change in Accured Expenses for the three prior fiscal quarters was $9.44 million (Q2 2026), $924,000 (Q1 2026) and -$10.93 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Cbre | 37.56 Bn | 31.32 Bn | 2.09 Bn | 138.00 Mn |
| 2 | KE Holdings | 36.95 Bn | 17.65 Bn | 1.03 Bn | - |
| 3 | Jones Lang Lasalle | 14.12 Bn | 12.33 Bn | - | 10.10 Mn |
| 4 | Compass | 6.95 Bn | 5.41 Bn | - | -63.00 Mn |
| 5 | Colliers International | 4.59 Bn | 3.66 Bn | 635.11 Mn | 85.81 Mn |
| 6 | Cushman & Wakefield | 2.80 Bn | 278.27 Mn | 512.00 Mn | -25.90 Mn |
| 7 | Newmark | 2.01 Bn | 1.39 Bn | - | 2.95 Mn |
| 8 | Marcus & Millichap | 1.08 Bn | 178.91 Mn | - | 5.31 Mn |
| 9 | Agnt | 609.98 Mn | 139.66 Mn | 98.80 Mn | 36.44 Mn |
| 10 | Rmr | 568.78 Mn | 493.24 Mn | - | 11.52 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 11.52 Mn |
| Mar 31, 2026 | 9.44 Mn |
| Dec 31, 2025 | 924,000.00 |
| Sep 30, 2025 | -10.93 Mn |
| Jun 30, 2025 | 7.61 Mn |
| Mar 31, 2025 | -1.42 Mn |
| Dec 31, 2024 | 10.97 Mn |
| Sep 30, 2024 | -14.50 Mn |
| Jun 30, 2024 | 11.18 Mn |
| Mar 31, 2024 | -9.33 Mn |
| Dec 31, 2023 | 10.33 Mn |
| Sep 30, 2023 | -20.70 Mn |
| Jun 30, 2023 | 16.97 Mn |
| Mar 31, 2023 | -4.63 Mn |
| Dec 31, 2022 | 10.66 Mn |
| Sep 30, 2022 | -15.29 Mn |
| Jun 30, 2022 | 9.57 Mn |
| Mar 31, 2022 | -20,000.00 |
| Dec 31, 2021 | 7.29 Mn |
| Sep 30, 2021 | -20.68 Mn |
API Access
Rmr Change in Accured Expenses API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=RMR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "RMR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=RMR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();