Good Times Restaurants (GTIM) Other Operating Expenses (2009 - 2026)
Good Times Restaurants (GTIM) reported Other Operating Expenses of $5.07 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 3.1% from $5.23 million a year earlier but up 2.4% from the prior quarter.
Good Times Restaurants (GTIM) Other Operating Expenses (2009 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Good Times Restaurants' Other Operating Expenses came in at $20.43 million, up 1.4% year-over-year; for FY2025 (ended Sep 30, 2025), it was $20.74 million, up 2.2% from FY2024.
- Other Operating Expenses has a four-year compound annual growth rate of 128.1% (FY2021 to FY2025).
- By fiscal year, Other Operating Expenses came in at $20.29 million in FY2024 (+6.7%), $19.01 million in FY2023, $332,000 in FY2022 (-56.7%) and $766,000 in FY2021.
- Five-year quarterly Other Operating Expenses spans a low of $30,000 in fiscal Q2 2023 and a high of $27.64 million in fiscal Q1 2023.
- Year over year, Other Operating Expenses gained in five of the last eight quarters, with growth averaging 1.2%.
- The high point for year-over-year Other Operating Expenses in five years was fiscal Q1 2022 (growth of 28.2%); the low point was fiscal Q1 2024 (a decline of 82.9%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $4.95 million (Q2 2026), $4.56 million (Q1 2026) and $5.85 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 199.07 Bn | 195.11 Bn | 6.47 Bn |
| 2 | Starbucks | 125.34 Bn | 125.35 Bn | - |
| 3 | Chipotle Mexican Grill | 45.50 Bn | 42.00 Bn | - |
| 4 | Yum Brands | 42.97 Bn | 38.79 Bn | 1.38 Bn |
| 5 | Restaurant Brands International | 27.07 Bn | 24.44 Bn | 1.40 Bn |
| 6 | Darden Restaurants | 25.87 Bn | 24.97 Bn | 1.68 Bn |
| 7 | Restaurant Brands International Limited Partnership | 24.67 Bn | 20.46 Bn | 1.40 Bn |
| 8 | Yum China Holdings | 16.86 Bn | 11.73 Bn | 652.00 Mn |
| 9 | Texas Roadhouse | 12.35 Bn | 11.68 Bn | 1.02 Bn |
| 10 | Good Times Restaurants | 13.30 Mn | 1.83 Mn | 147,000.00 |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 5.07 Mn |
| Mar 31, 2026 | 4.95 Mn |
| Dec 30, 2025 | 4.56 Mn |
| Jul 1, 2025 | 5.23 Mn |
| Apr 1, 2025 | 4.92 Mn |
| Dec 31, 2024 | 4.75 Mn |
| Jun 25, 2024 | 5.20 Mn |
| Mar 26, 2024 | 5.20 Mn |
| Dec 26, 2023 | 4.73 Mn |
| Jun 27, 2023 | 4.89 Mn |
| Mar 28, 2023 | 30,000.00 |
| Dec 27, 2022 | 4.49 Mn |
| Mar 29, 2022 | 4.67 Mn |
| Dec 28, 2021 | 50,000.00 |
| Jun 29, 2021 | 301,000.00 |
| Mar 30, 2021 | 80,000.00 |
| Dec 29, 2020 | 39,000.00 |
| Jun 30, 2020 | 31,000.00 |
| Mar 31, 2020 | 159,000.00 |
| Dec 31, 2019 | 802,000.00 |
Good Times Restaurants Other 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=other-operating-expenses&ticker=GTIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-operating-expenses", "ticker": "GTIM", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=other-operating-expenses&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();