Good Times Restaurants (GTIM) Market Capitalization (2010 - 2026)
Good Times Restaurants' Market Capitalization came in at $14.89 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 21.7% from $19.02 million a year earlier but up 20.5% from the prior quarter.
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Analysis
Good Times Restaurants (GTIM) Market Capitalization (2010 - 2026) Analysis & Trends
For FY2025 (ended Sep 30, 2025), Good Times Restaurants' Market Capitalization was $17.2 million, down 44.6% from FY2024.
- Market Capitalization carries a five-year compound annual growth rate of -0.8% (FY2020 to FY2025).
- Going back by fiscal year, Market Capitalization was $31.07 million in FY2024 (-9.2%), $34.23 million in FY2023 (+27.9%), $26.76 million in FY2022 (-58.5%) and $64.44 million in FY2021 (+259.8%).
- The five-year range for quarterly Market Capitalization is $12.35 million (fiscal Q2 2026) to $64.44 million (fiscal Q4 2021).
- Year-over-year, Market Capitalization has declined for ten consecutive quarters, with an average decline of 27.9% over the last eight quarters.
- The fastest year-over-year change in Market Capitalization over five years came in fiscal Q4 2021 (growth of 259.8%), and the weakest in fiscal Q4 2022 (a decline of 58.5%).
- Business Quant data shows GTIM's Market Capitalization at $12.35 million (Q2 2026), $12.78 million (Q1 2026) and $17.2 million (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Mcdonalds | 163.51 Bn | 158.34 Bn | 6.42 Bn |
| 2 | Starbucks | 107.11 Bn | 94.75 Bn | - |
| 3 | Chipotle Mexican Grill | 40.42 Bn | 36.40 Bn | - |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - |
| 10 | Good Times Restaurants | 15.84 Mn | 4.36 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 14.89 Mn |
| Mar 31, 2026 | 12.35 Mn |
| Dec 30, 2025 | 12.78 Mn |
| Sep 30, 2025 | 17.20 Mn |
| Jul 1, 2025 | 19.02 Mn |
| Apr 1, 2025 | 25.22 Mn |
| Dec 31, 2024 | 27.59 Mn |
| Sep 24, 2024 | 31.07 Mn |
| Jun 25, 2024 | 27.79 Mn |
| Mar 26, 2024 | 27.25 Mn |
| Dec 26, 2023 | 28.78 Mn |
| Sep 26, 2023 | 34.23 Mn |
| Jun 27, 2023 | 39.52 Mn |
| Mar 28, 2023 | 30.78 Mn |
| Dec 27, 2022 | 27.52 Mn |
| Sep 27, 2022 | 26.76 Mn |
| Jun 28, 2022 | 34.83 Mn |
| Mar 29, 2022 | 44.96 Mn |
| Dec 28, 2021 | 55.17 Mn |
| Sep 28, 2021 | 64.44 Mn |
API Access
Good Times Restaurants Market Capitalization 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=market-capitalization&ticker=GTIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "market-capitalization", "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=market-capitalization&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();