Restaurant Brands International Limited Partnership (RSTRF) Change in Accrued Expenses (2014 - 2026)
Restaurant Brands International Limited Partnership (RSTRF) reported Change in Accrued Expenses of $129 million for Q3 2026, up 38.7% from $93 million a year earlier.
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Analysis
Restaurant Brands International Limited Partnership (RSTRF) Change in Accrued Expenses (2014 - 2026) Analysis & Trends
For FY2025, Restaurant Brands International Limited Partnership posted Change in Accrued Expenses of -$7 million.
- By year, Change in Accrued Expenses came in at -$37 million in FY2024, $9 million in FY2023 (-75.7%), $37 million in FY2022 (-44.8%) and $67 million in FY2021.
- The Q3 2026 figure ranks as the highest quarterly Change in Accrued Expenses since Q4 2024.
- Year over year, Change in Accrued Expenses gained in three of the last four quarters, with growth averaging 51.7%.
- The high point for year-over-year Change in Accrued Expenses in five years was Q4 2021 (growth of 755.6%); the low point was Q4 2025 (a decline of 59.0%).
- Per Business Quant data, the three quarters before Q3 2026 came in at -$8 million (Q2 2026), -$176 million (Q1 2026) and $55 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accrued Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 195.98 Bn | 190.80 Bn | 6.42 Bn | - |
| 2 | Starbucks | 120.13 Bn | 107.76 Bn | - | - |
| 3 | Yum Brands | 44.36 Bn | 41.25 Bn | 1.47 Bn | 4.00 Mn |
| 4 | Chipotle Mexican Grill | 43.92 Bn | 40.41 Bn | - | 13.30 Mn |
| 5 | Restaurant Brands International | 27.10 Bn | 22.88 Bn | 1.40 Bn | 129.00 Mn |
| 6 | Darden Restaurants | 25.62 Bn | 24.72 Bn | 1.68 Bn | -51.80 Mn |
| 7 | Restaurant Brands International Limited Partnership | 24.67 Bn | 20.46 Bn | 1.40 Bn | 129.00 Mn |
| 8 | Yum China Holdings | 17.38 Bn | 11.04 Bn | 537.00 Mn | 107.00 Mn |
| 9 | Texas Roadhouse | 12.08 Bn | 11.42 Bn | - | 15.18 Mn |
| 10 | Dominos Pizza | 11.07 Bn | 10.31 Bn | 476.38 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 129.00 Mn |
| Jun 30, 2026 | -8.00 Mn |
| Mar 31, 2026 | -176.00 Mn |
| Dec 31, 2025 | 55.00 Mn |
| Sep 30, 2025 | 93.00 Mn |
| Jun 30, 2025 | 32.00 Mn |
| Mar 31, 2025 | -187.00 Mn |
| Dec 31, 2024 | 134.00 Mn |
| Sep 30, 2024 | 39.00 Mn |
| Jun 30, 2024 | -35.00 Mn |
| Mar 31, 2024 | -175.00 Mn |
| Dec 31, 2023 | 71.00 Mn |
| Sep 30, 2023 | 73.00 Mn |
| Jun 30, 2023 | -12.00 Mn |
| Mar 31, 2023 | -123.00 Mn |
| Dec 31, 2022 | 111.00 Mn |
| Sep 30, 2022 | 125.00 Mn |
| Jun 30, 2022 | -108.00 Mn |
| Mar 31, 2022 | -91.00 Mn |
| Dec 31, 2021 | 154.00 Mn |
API Access
Restaurant Brands International Limited Partnership Change in Accrued 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=RSTRF&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "RSTRF", "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=RSTRF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();