Good Times Restaurants (GTIM) Change in Property, Plant and Equipment (2010 - 2026)
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Analysis
Good Times Restaurants (GTIM) Change in Property, Plant and Equipment (2010 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change in PP&E (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 175.84 Bn | 170.66 Bn | 6.42 Bn | -768.00 Mn |
| 2 | Starbucks | 114.91 Bn | 102.54 Bn | - | -291.40 Mn |
| 3 | Yum Brands | 40.85 Bn | 37.73 Bn | 1.47 Bn | -99.00 Mn |
| 4 | Chipotle Mexican Grill | 34.81 Bn | 30.79 Bn | - | -217.27 Mn |
| 5 | Restaurant Brands International | 26.32 Bn | 23.42 Bn | 1.38 Bn | -39.00 Mn |
| 6 | Darden Restaurants | 24.03 Bn | 23.12 Bn | 1.68 Bn | -171.30 Mn |
| 7 | Restaurant Brands International Limited Partnership | 16.93 Bn | 12.49 Bn | 1.38 Bn | -39.00 Mn |
| 8 | Yum China Holdings | 15.37 Bn | 9.73 Bn | 537.00 Mn | -127.00 Mn |
| 9 | Texas Roadhouse | 10.86 Bn | 10.23 Bn | - | -98.68 Mn |
| 10 | Good Times Restaurants | 13.73 Mn | 2.25 Mn | - | -123,000.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -123,000.00 |
| Mar 31, 2026 | -320,000.00 |
| Dec 30, 2025 | -187,000.00 |
| Sep 30, 2025 | -302,000.00 |
| Jul 1, 2025 | -530,000.00 |
| Apr 1, 2025 | -816,000.00 |
| Dec 31, 2024 | -1.34 Mn |
| Sep 24, 2024 | -860,000.00 |
| Jun 25, 2024 | -1.22 Mn |
| Mar 26, 2024 | -615,000.00 |
| Dec 26, 2023 | -448,000.00 |
| Sep 26, 2023 | -1.55 Mn |
| Jun 27, 2023 | -1.76 Mn |
| Mar 28, 2023 | -700,000.00 |
| Dec 27, 2022 | -719,000.00 |
| Sep 27, 2022 | -1.76 Mn |
| Jun 28, 2022 | -446,000.00 |
| Mar 29, 2022 | -940,000.00 |
| Dec 28, 2021 | -237,000.00 |
| Sep 28, 2021 | -1.10 Mn |
API Access
Good Times Restaurants Change in Property, Plant and Equipment 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-property-plant-and-equipment&ticker=GTIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-property-plant-and-equipment", "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=change-in-property-plant-and-equipment&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();