Dine Brands Global (DIN) Dividends Paid - Common and Preferred (2010 - 2026)
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Analysis
Dine Brands Global (DIN) Dividends Paid - Common and Preferred (2010 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Div Paid (Total) (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 195.98 Bn | 190.80 Bn | 6.42 Bn | 1.32 Bn |
| 2 | Starbucks | 120.13 Bn | 107.76 Bn | - | 706.60 Mn |
| 3 | Yum Brands | 44.36 Bn | 41.25 Bn | 1.47 Bn | 206.00 Mn |
| 4 | Chipotle Mexican Grill | 43.92 Bn | 40.41 Bn | - | - |
| 5 | Restaurant Brands International | 27.10 Bn | 22.88 Bn | 1.40 Bn | 296.00 Mn |
| 6 | Darden Restaurants | 25.62 Bn | 24.72 Bn | 1.68 Bn | 184.20 Mn |
| 7 | Restaurant Brands International Limited Partnership | 24.67 Bn | 20.46 Bn | 1.40 Bn | 296.00 Mn |
| 8 | Yum China Holdings | 17.38 Bn | 11.04 Bn | 537.00 Mn | 101.00 Mn |
| 9 | Texas Roadhouse | 12.08 Bn | 11.42 Bn | - | 49.26 Mn |
| 10 | Dine Brands Global | 428.34 Mn | 7.34 Mn | 84.70 Mn | 2.40 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 27, 2026 | 2.40 Mn |
| Jun 28, 2026 | 2.30 Mn |
| Mar 29, 2026 | 2.50 Mn |
| Dec 28, 2025 | 7.40 Mn |
| Sep 30, 2025 | 7.80 Mn |
| Mar 30, 2025 | 7.80 Mn |
| Dec 29, 2024 | 7.80 Mn |
| Sep 30, 2024 | 7.80 Mn |
| Jun 30, 2024 | 7.90 Mn |
| Mar 31, 2024 | 7.70 Mn |
| Dec 31, 2023 | -40,000.00 |
| Sep 30, 2023 | 15.77 Mn |
| Jun 30, 2023 | -1,000.00 |
| Mar 31, 2023 | 16.00 Mn |
| Sep 30, 2022 | 16.18 Mn |
| Mar 31, 2022 | 14.59 Mn |
| Dec 31, 2020 | 466,000.00 |
| Jun 30, 2020 | 12.48 Mn |
| Mar 31, 2020 | 11.45 Mn |
| Dec 31, 2019 | 12.63 Mn |
API Access
Dine Brands Global Dividends Paid - Common and Preferred 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=dividends-paid-common-and-prefferd&ticker=DIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "dividends-paid-common-and-prefferd", "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=dividends-paid-common-and-prefferd&ticker=DIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();