Good Times Restaurants (GTIM) Long-Term Debt Issuances (2023 - 2025)
Good Times Restaurants' Long-Term Debt Issuances came in at $500,000 for fiscal Q1 2026 (quarter ended Dec 30, 2025), down 71.4% from $1.75 million a year earlier.
Good Times Restaurants (GTIM) Long-Term Debt Issuances (2023 - 2025) Analysis & Trends
For FY2025 (ended Sep 30, 2025), Good Times Restaurants' Long-Term Debt Issuances was $2.25 million, up 63.0% from FY2024.
- Going back by fiscal year, Long-Term Debt Issuances was $1.38 million in FY2024 (+84.0%) and $750,000 in FY2023.
- The five-year range for quarterly Long-Term Debt Issuances is $380,000 (fiscal Q3 2024) to $1.75 million (fiscal Q1 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | LT Debt Issuance (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 178.71 Bn | 173.54 Bn | 6.42 Bn | - |
| 2 | Starbucks | 116.18 Bn | 103.81 Bn | - | - |
| 3 | Yum Brands | 42.13 Bn | 39.01 Bn | 1.47 Bn | - |
| 4 | Chipotle Mexican Grill | 35.58 Bn | 31.56 Bn | - | - |
| 5 | Restaurant Brands International | 26.69 Bn | 23.79 Bn | 1.38 Bn | - |
| 6 | Darden Restaurants | 24.61 Bn | 23.71 Bn | 1.68 Bn | - |
| 7 | Restaurant Brands International Limited Partnership | 16.93 Bn | 12.49 Bn | 1.38 Bn | - |
| 8 | Yum China Holdings | 15.44 Bn | 9.80 Bn | 537.00 Mn | - |
| 9 | Texas Roadhouse | 11.33 Bn | 10.69 Bn | - | - |
| 10 | Good Times Restaurants | 13.83 Mn | 2.35 Mn | - | - |
Historic Data
| Date | Value |
|---|---|
| Dec 30, 2025 | 500,000.00 |
| Apr 1, 2025 | 500,000.00 |
| Dec 31, 2024 | 1.75 Mn |
| Jun 25, 2024 | 380,000.00 |
| Mar 26, 2024 | 500,000.00 |
| Dec 26, 2023 | 500,000.00 |
Good Times Restaurants Long-Term Debt Issuances 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=long-term-debt-issuances&ticker=GTIM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "long-term-debt-issuances", "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=long-term-debt-issuances&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();