Good Times Restaurants (GTIM) Accounts Payables (2010 - 2026)
Good Times Restaurants (GTIM) reported Accounts Payables of $2.66 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 2.3% from $2.73 million a year earlier and down 9.7% from the prior quarter.
Good Times Restaurants (GTIM) Accounts Payables (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 30, 2025), Good Times Restaurants posted Accounts Payables of $2.61 million, down 14.8% from FY2024.
- Accounts Payables has a five-year compound annual growth rate of 0.2% (FY2020 to FY2025).
- By fiscal year, Accounts Payables came in at $3.06 million in FY2024 (+18.3%), $2.59 million in FY2023 (+311.6%), $628,000 in FY2022 (-58.0%) and $1.5 million in FY2021 (-42.0%).
- Five-year quarterly Accounts Payables spans a low of $593,000 in fiscal Q1 2022 and a high of $3.13 million in fiscal Q2 2025.
- Year over year, Accounts Payables gained in three of the last eight quarters, with growth averaging 2.4%.
- The high point for year-over-year Accounts Payables in five years was fiscal Q4 2023 (growth of 311.6%); the low point was fiscal Q3 2022 (a decline of 65.2%).
- Per Business Quant data, the three fiscal quarters before Q3 2026 came in at $2.95 million (Q2 2026), $3.05 million (Q1 2026) and $2.61 million (Q4 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Accounts Payables (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 163.51 Bn | 158.34 Bn | 6.42 Bn | 1.11 Bn |
| 2 | Starbucks | 107.11 Bn | 94.75 Bn | - | 1.78 Bn |
| 3 | Chipotle Mexican Grill | 40.42 Bn | 36.40 Bn | - | 255.13 Mn |
| 4 | Yum Brands | 37.23 Bn | 34.12 Bn | 1.47 Bn | 1.19 Bn |
| 5 | Restaurant Brands International | 24.82 Bn | 21.92 Bn | 1.38 Bn | 884.00 Mn |
| 6 | Darden Restaurants | 22.06 Bn | 21.17 Bn | -113.70 Mn | 427.70 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 884.00 Mn |
| 8 | Yum China Holdings | 14.18 Bn | 8.54 Bn | 537.00 Mn | 2.26 Bn |
| 9 | Texas Roadhouse | 10.25 Bn | 9.62 Bn | - | 179.04 Mn |
| 10 | Good Times Restaurants | 15.84 Mn | 4.36 Mn | - | 2.66 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.66 Mn |
| Mar 31, 2026 | 2.95 Mn |
| Dec 30, 2025 | 3.05 Mn |
| Sep 30, 2025 | 2.61 Mn |
| Jul 1, 2025 | 2.73 Mn |
| Apr 1, 2025 | 3.13 Mn |
| Dec 31, 2024 | 2.62 Mn |
| Sep 24, 2024 | 3.06 Mn |
| Jun 25, 2024 | 2.88 Mn |
| Mar 26, 2024 | 2.75 Mn |
| Dec 26, 2023 | 2.64 Mn |
| Sep 26, 2023 | 2.59 Mn |
| Jun 27, 2023 | 1.02 Mn |
| Mar 28, 2023 | 2.38 Mn |
| Dec 27, 2022 | 951,000.00 |
| Sep 27, 2022 | 628,000.00 |
| Jun 28, 2022 | 753,000.00 |
| Mar 29, 2022 | 705,000.00 |
| Dec 28, 2021 | 593,000.00 |
| Sep 28, 2021 | 1.50 Mn |
Good Times Restaurants Accounts Payables 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=accounts-payables&ticker=GTIM&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accounts-payables", "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=accounts-payables&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();