Good Times Restaurants (GTIM) Enterprise Value (2010 - 2026)
Good Times Restaurants (GTIM) reported Enterprise Value of $12.08 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 27.3% from $16.62 million a year earlier but up 16.4% from the prior quarter.
Good Times Restaurants (GTIM) Enterprise Value (2010 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, Good Times Restaurants' Enterprise Value came in at $3.41 million, down 51.5% year-over-year; for FY2025 (ended Sep 30, 2025), it came in at $15.34 million, down 45.1% from FY2024.
- Enterprise Value has a five-year compound annual growth rate of 14.6% (FY2020 to FY2025).
- By fiscal year, Enterprise Value came in at $27.93 million in FY2024 (-8.3%), $30.47 million in FY2023 (+59.1%), $19.16 million in FY2022 (-66.2%) and $56.71 million in FY2021 (+631.8%).
- Five-year quarterly Enterprise Value spans a low of $10.23 million in fiscal Q1 2026 and a high of $56.71 million in fiscal Q4 2021.
- Year over year, Enterprise Value has now declined in each of the last ten quarters, with an average decline of 28.7% over the last eight quarters.
- The high point for year-over-year Enterprise Value in five years was fiscal Q4 2021 (growth of 631.8%); the low point was fiscal Q4 2022 (a decline of 66.2%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $10.38 million (Q2 2026), $10.23 million (Q1 2026) and $15.34 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 165.62 Bn | 160.44 Bn | 6.42 Bn |
| 2 | Starbucks | 108.79 Bn | 96.42 Bn | - |
| 3 | Chipotle Mexican Grill | 40.35 Bn | 36.33 Bn | - |
| 4 | Yum Brands | 37.59 Bn | 34.48 Bn | 1.47 Bn |
| 5 | Restaurant Brands International | 24.96 Bn | 22.07 Bn | 1.38 Bn |
| 6 | Darden Restaurants | 22.28 Bn | 21.39 Bn | -113.70 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn |
| 8 | Yum China Holdings | 14.08 Bn | 8.44 Bn | 537.00 Mn |
| 9 | Texas Roadhouse | 10.31 Bn | 9.67 Bn | - |
| 10 | Good Times Restaurants | 15.63 Mn | 4.15 Mn | - |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 12.08 Mn |
| Mar 31, 2026 | 10.38 Mn |
| Dec 30, 2025 | 10.23 Mn |
| Sep 30, 2025 | 15.34 Mn |
| Jul 1, 2025 | 16.62 Mn |
| Apr 1, 2025 | 23.19 Mn |
| Dec 31, 2024 | 25.25 Mn |
| Sep 24, 2024 | 27.93 Mn |
| Jun 25, 2024 | 23.71 Mn |
| Mar 26, 2024 | 23.76 Mn |
| Dec 26, 2023 | 25.73 Mn |
| Sep 26, 2023 | 30.47 Mn |
| Jun 27, 2023 | 36.23 Mn |
| Mar 28, 2023 | 25.77 Mn |
| Dec 27, 2022 | 21.97 Mn |
| Sep 27, 2022 | 19.16 Mn |
| Jun 28, 2022 | 26.50 Mn |
| Mar 29, 2022 | 39.42 Mn |
| Dec 28, 2021 | 48.95 Mn |
| Sep 28, 2021 | 56.71 Mn |
Good Times Restaurants Enterprise Value 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=enterprise-value&ticker=GTIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "enterprise-value", "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=enterprise-value&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();