Dine Brands Global (DIN) Selling, General & Administrative (2010 - 2026)
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Analysis
Dine Brands Global (DIN) Selling, General & Administrative (2010 - 2026) Analysis & Trends
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | SG&A (Qtr) |
|---|---|---|---|---|---|
| 1 | Mcdonalds | 195.98 Bn | 190.80 Bn | 6.42 Bn | 817.00 Mn |
| 2 | Starbucks | 120.13 Bn | 107.76 Bn | - | 598.80 Mn |
| 3 | Yum Brands | 44.36 Bn | 41.25 Bn | 1.47 Bn | 324.00 Mn |
| 4 | Chipotle Mexican Grill | 43.92 Bn | 40.41 Bn | - | 185.23 Mn |
| 5 | Restaurant Brands International | 27.10 Bn | 22.88 Bn | 1.40 Bn | 183.00 Mn |
| 6 | Darden Restaurants | 25.62 Bn | 24.72 Bn | 1.68 Bn | 134.80 Mn |
| 7 | Restaurant Brands International Limited Partnership | 24.67 Bn | 20.46 Bn | 1.40 Bn | 183.00 Mn |
| 8 | Yum China Holdings | 17.38 Bn | 11.04 Bn | 537.00 Mn | 139.00 Mn |
| 9 | Texas Roadhouse | 12.08 Bn | 11.42 Bn | - | 72.41 Mn |
| 10 | Dine Brands Global | 428.34 Mn | 7.34 Mn | 84.70 Mn | 51.60 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 27, 2026 | 51.60 Mn |
| Jun 28, 2026 | 55.60 Mn |
| Mar 29, 2026 | 53.10 Mn |
| Dec 28, 2025 | 51.49 Mn |
| Sep 30, 2025 | 50.20 Mn |
| Jun 29, 2025 | 50.80 Mn |
| Mar 30, 2025 | 51.30 Mn |
| Dec 29, 2024 | 52.27 Mn |
| Sep 30, 2024 | 45.39 Mn |
| Jun 30, 2024 | 46.86 Mn |
| Mar 31, 2024 | 52.19 Mn |
| Dec 31, 2023 | 50.56 Mn |
| Sep 30, 2023 | 48.62 Mn |
| Jun 30, 2023 | 47.84 Mn |
| Mar 31, 2023 | 51.09 Mn |
| Dec 31, 2022 | 58.80 Mn |
| Sep 30, 2022 | 46.34 Mn |
| Jun 30, 2022 | 44.06 Mn |
| Mar 31, 2022 | 41.55 Mn |
| Dec 31, 2021 | 48.95 Mn |
API Access
Dine Brands Global Selling, General & Administrative 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=selling-general-and-administrative&ticker=DIN&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "selling-general-and-administrative", "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=selling-general-and-administrative&ticker=DIN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();