Luckin Coffee (LKNCY) Selling, General & Administrative (2018 - 2026)
Analysis
Luckin Coffee (LKNCY) Selling, General & Administrative (2018 - 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 | Luckin Coffee | 10.86 Bn | 5.95 Bn | 1.64 Bn | 160.23 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 160.23 Mn |
| Jun 30, 2026 | 144.91 Mn |
| Mar 31, 2026 | 123.10 Mn |
| Dec 31, 2025 | 120.78 Mn |
| Sep 30, 2025 | 111.24 Mn |
| Jun 30, 2025 | 102.64 Mn |
| Mar 31, 2025 | 93.80 Mn |
| Dec 31, 2024 | 87.36 Mn |
| Sep 30, 2024 | 90.81 Mn |
| Jun 30, 2024 | 81.15 Mn |
| Mar 31, 2024 | 77.08 Mn |
| Dec 31, 2023 | 79.16 Mn |
| Sep 30, 2023 | 65.97 Mn |
| Jun 30, 2023 | 58.69 Mn |
| Mar 31, 2023 | 52.54 Mn |
| Dec 31, 2022 | 59.65 Mn |
| Sep 30, 2022 | 53.91 Mn |
| Jun 30, 2022 | 51.08 Mn |
| Mar 31, 2022 | 50.95 Mn |
| Dec 31, 2021 | 61.05 Mn |
API Access
Luckin Coffee 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=LKNCY&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "selling-general-and-administrative", "ticker": "LKNCY", "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=LKNCY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();