Dine Brands Global (DIN) Cash & Equivalents (2009 - 2026)
Dine Brands Global (DIN) reported Cash & Equivalents of $97.5 million for Q2 2026, down 6.4% from the prior quarter.
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Analysis
Dine Brands Global (DIN) Cash & Equivalents (2009 - 2026) Analysis & Trends
At the end of FY2025, Dine Brands Global posted Cash & Equivalents of $128.2 million, down 31.3% from FY2024.
- Cash & Equivalents has a five-year compound annual growth rate of -19.7% (FY2020 to FY2025).
- By year, Cash & Equivalents came in at $186.7 million in FY2024 (+27.8%), $146.03 million in FY2023 (-45.9%), $269.7 million in FY2022 (-25.4%) and $361.41 million in FY2021 (-5.7%).
- The Q2 2026 figure ranks as the lowest quarterly Cash & Equivalents since Q2 2018.
- Year over year, Cash & Equivalents gained in two of the last four quarters, with growth averaging 17.1%.
- The high point for year-over-year Cash & Equivalents in five years was Q3 2024 (growth of 72.7%); the low point was Q3 2023 (a decline of 72.4%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $104.2 million (Q1 2026), $128.2 million (Q4 2025) and $168 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 164.07 Bn | 158.89 Bn | 6.42 Bn | 822.00 Mn |
| 2 | Starbucks | 108.16 Bn | 95.79 Bn | - | 3.45 Bn |
| 3 | Chipotle Mexican Grill | 40.91 Bn | 36.89 Bn | - | 228.20 Mn |
| 4 | Yum Brands | 37.32 Bn | 34.20 Bn | 1.47 Bn | 674.00 Mn |
| 5 | Restaurant Brands International | 24.36 Bn | 21.46 Bn | 1.38 Bn | 1.06 Bn |
| 6 | Darden Restaurants | 22.52 Bn | 21.62 Bn | -113.70 Mn | 219.50 Mn |
| 7 | Restaurant Brands International Limited Partnership | 17.01 Bn | 12.57 Bn | 1.38 Bn | 1.06 Bn |
| 8 | Yum China Holdings | 14.14 Bn | 8.50 Bn | 537.00 Mn | 485.00 Mn |
| 9 | Texas Roadhouse | 10.28 Bn | 9.64 Bn | - | 202.43 Mn |
| 10 | Dine Brands Global | 359.48 Mn | -138.42 Mn | 91.20 Mn | 97.50 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 28, 2026 | 97.50 Mn |
| Mar 29, 2026 | 104.20 Mn |
| Dec 28, 2025 | 128.20 Mn |
| Sep 30, 2025 | 168.00 Mn |
| Dec 29, 2024 | 186.70 Mn |
| Sep 30, 2024 | 169.64 Mn |
| Jun 30, 2024 | 153.53 Mn |
| Mar 31, 2024 | 145.00 Mn |
| Dec 31, 2023 | 146.03 Mn |
| Sep 30, 2023 | 98.20 Mn |
| Jun 30, 2023 | 98.00 Mn |
| Mar 31, 2023 | 181.61 Mn |
| Dec 31, 2022 | 269.70 Mn |
| Sep 30, 2022 | 355.30 Mn |
| Jun 30, 2022 | 263.54 Mn |
| Mar 31, 2022 | 294.74 Mn |
| Dec 31, 2021 | 361.41 Mn |
| Sep 30, 2021 | 304.20 Mn |
| Jun 30, 2021 | 259.50 Mn |
| Mar 31, 2021 | 179.60 Mn |
API Access
Dine Brands Global Cash & Equivalents 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=cash-and-equivalents&ticker=DIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "ticker": "DIN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=cash-and-equivalents&ticker=DIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();