Ark Restaurants (ARKR) Operating Expenses (2010 - 2026)
Ark Restaurants (ARKR) reported Operating Expenses of $41.02 million for fiscal Q3 2026 (quarter ended Jun 27, 2026), down 13.0% from $47.13 million a year earlier but up 7.3% from the prior quarter.
Ark Restaurants (ARKR) Operating Expenses (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 27, 2026, Ark Restaurants' Operating Expenses came in at $157.96 million, down 12.1% year-over-year; for FY2025 (ended Sep 27, 2025), it came in at $169.82 million, down 9.6% from FY2024.
- Operating Expenses has a five-year compound annual growth rate of 8.2% (FY2020 to FY2025).
- By fiscal year, Operating Expenses came in at $187.84 million in FY2024 (-0.9%), $189.63 million in FY2023 (+9.1%), $173.81 million in FY2022 (+38.3%) and $125.66 million in FY2021 (+10.0%).
- Five-year quarterly Operating Expenses spans a low of $36.94 million in fiscal Q4 2021 and a high of $55.1 million in fiscal Q4 2023.
- Year over year, Operating Expenses gained in two of the last eight quarters, with an average decline of 9.3%.
- The high point for year-over-year Operating Expenses in five years was fiscal Q1 2022 (growth of 74.5%); the low point was fiscal Q4 2025 (a decline of 20.2%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $38.24 million (Q2 2026), $39.66 million (Q1 2026) and $39.05 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 163.51 Bn | 158.34 Bn | 6.42 Bn | 3.76 Bn |
| 2 | Starbucks | 107.11 Bn | 94.75 Bn | - | 8.42 Bn |
| 3 | Chipotle Mexican Grill | 40.42 Bn | 36.40 Bn | - | 2.82 Bn |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn | 1.51 Bn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn | 1.80 Bn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn | 3.20 Bn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 1.80 Bn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn | 2.79 Bn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - | 1.54 Bn |
| 10 | Ark Restaurants | 16.23 Mn | -25.84 Mn | 24.49 Mn | 41.02 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 41.02 Mn |
| Mar 28, 2026 | 38.24 Mn |
| Dec 27, 2025 | 39.66 Mn |
| Sep 27, 2025 | 39.05 Mn |
| Jun 28, 2025 | 47.13 Mn |
| Mar 29, 2025 | 44.34 Mn |
| Dec 28, 2024 | 39.30 Mn |
| Sep 28, 2024 | 48.93 Mn |
| Jun 29, 2024 | 49.57 Mn |
| Mar 30, 2024 | 43.46 Mn |
| Dec 30, 2023 | 45.88 Mn |
| Sep 30, 2023 | 55.10 Mn |
| Jul 1, 2023 | 47.41 Mn |
| Apr 1, 2023 | 41.87 Mn |
| Dec 31, 2022 | 45.24 Mn |
| Oct 1, 2022 | 45.46 Mn |
| Jul 2, 2022 | 47.80 Mn |
| Apr 2, 2022 | 39.36 Mn |
| Jan 1, 2022 | 41.20 Mn |
| Oct 2, 2021 | 36.94 Mn |
Ark Restaurants Operating 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=operating-expenses&ticker=ARKR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "ARKR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=ARKR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();