Good Times Restaurants (GTIM) Receivables (2010 - 2026)
Good Times Restaurants (GTIM) posted Receivables of $833,000 for fiscal Q3 2026 (quarter ended Jun 30, 2026), down 2.3% from $853,000 a year earlier but up 15.1% from the prior quarter.
Powered by 
Analysis
Good Times Restaurants (GTIM) Receivables (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 30, 2025), Good Times Restaurants' Receivables came in at $795,000, down 10.7% from FY2024.
- Annual Receivables shows a five-year compound annual growth rate of 3.9% (FY2020 to FY2025).
- In prior fiscal years, Good Times Restaurants' Receivables was $890,000 in FY2024 (-42.1%), $1.54 million in FY2023 (+121.6%), $694,000 in FY2022 (+7.8%) and $644,000 in FY2021 (-1.8%).
- Quarterly Receivables has run from a low of $644,000 in fiscal Q4 2021 to a high of $603.6 million in fiscal Q2 2023 over five years.
- On a year-over-year basis, Receivables increased in two of the last eight quarters, with an average decline of 5.9%.
- The strongest year-over-year quarter for Receivables in the past five years was fiscal Q1 2022, with growth of 230.5%; the weakest was fiscal Q2 2024, with a decline of 99.9%.
- According to Business Quant data, Receivables for the three prior fiscal quarters was $724,000 (Q2 2026), $1.15 million (Q1 2026) and $795,000 (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Receivables (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 165.62 Bn | 160.44 Bn | 6.42 Bn | 2.49 Bn |
| 2 | Starbucks | 108.79 Bn | 96.42 Bn | - | 1.30 Bn |
| 3 | Chipotle Mexican Grill | 40.35 Bn | 36.33 Bn | - | 100.31 Mn |
| 4 | Yum Brands | 37.59 Bn | 34.48 Bn | 1.47 Bn | 623.00 Mn |
| 5 | Restaurant Brands International | 24.96 Bn | 22.07 Bn | 1.38 Bn | 800.00 Mn |
| 6 | Darden Restaurants | 22.28 Bn | 21.39 Bn | -113.70 Mn | 129.90 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 800.00 Mn |
| 8 | Yum China Holdings | 14.08 Bn | 8.44 Bn | 537.00 Mn | 115.00 Mn |
| 9 | Texas Roadhouse | 10.31 Bn | 9.67 Bn | - | 74.14 Mn |
| 10 | Good Times Restaurants | 15.63 Mn | 4.15 Mn | - | 833,000.00 |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 833,000.00 |
| Mar 31, 2026 | 724,000.00 |
| Dec 30, 2025 | 1.15 Mn |
| Sep 30, 2025 | 795,000.00 |
| Jul 1, 2025 | 853,000.00 |
| Apr 1, 2025 | 786,000.00 |
| Dec 31, 2024 | 1.05 Mn |
| Sep 24, 2024 | 890,000.00 |
| Jun 25, 2024 | 782,000.00 |
| Mar 26, 2024 | 862,000.00 |
| Dec 26, 2023 | 1.33 Mn |
| Sep 26, 2023 | 1.04 Mn |
| Jun 27, 2023 | 729,000.00 |
| Mar 28, 2023 | 603.60 Mn |
| Dec 27, 2022 | 1.12 Mn |
| Sep 27, 2022 | 694,000.00 |
| Jun 28, 2022 | 694,000.00 |
| Mar 29, 2022 | 1.42 Mn |
| Dec 28, 2021 | 2.35 Mn |
| Sep 28, 2021 | 644,000.00 |
API Access
Good Times Restaurants Receivables 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=receivables&ticker=GTIM&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "receivables", "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=receivables&ticker=GTIM&period=max&api_key=YOUR_API_KEY");
const data = await res.json();