Dingdong (Cayman) (DDL) Accumulated Expenses (2020 - 2026)
Dingdong (Cayman) (DDL) posted Accumulated Expenses of $1.93 million for the quarter ended Jun 30, 2026, down 98.2% from $105.47 million a year earlier but up 8.7% from the prior quarter.
Dingdong (Cayman) (DDL) Accumulated Expenses (2020 - 2026) Analysis & Trends
As of Dec 31, 2025, Dingdong (Cayman)'s Accumulated Expenses came in at $108.77 million, up 3.5% from the prior year.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of -2.6% (years ended Dec 2020 to Dec 2025).
- In prior years, Dingdong (Cayman)'s Accumulated Expenses was $105.09 million in the year ended Dec 31, 2024 (-99.9%), $92.45 billion in the year ended Dec 31, 2023 (-21.4%), $117.58 billion in the year ended Dec 31, 2022 (+14.7%) and $102.51 billion in the year ended Dec 31, 2021.
- Quarterly Accumulated Expenses has run from a low of $657,589 in the quarter ended Dec 31, 2025 to a high of $138.98 million in the quarter ended Sep 30, 2021 over five years.
- On a year-over-year basis, Accumulated Expenses has declined in each of the last four quarters, with an average decline of 29.6% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was the quarter ended Sep 30, 2024, with growth of 26.3%; the weakest was the quarter ended Dec 31, 2025, with a decline of 99.4%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $1.78 million (quarter ended Mar 31, 2026), $657,589 (quarter ended Dec 31, 2025) and $106.76 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Walmart | 824.47 Bn | 787.18 Bn | 49.13 Bn |
| 2 | Costco Wholesale | 403.75 Bn | 333.05 Bn | 9.01 Bn |
| 3 | Sysco | 37.36 Bn | 31.61 Bn | 4.13 Bn |
| 4 | Kroger | 34.63 Bn | 20.79 Bn | 7.86 Bn |
| 5 | Dollar General | 26.38 Bn | 21.06 Bn | 3.68 Bn |
| 6 | Caseys General Stores | 22.49 Bn | 20.48 Bn | 1.24 Bn |
| 7 | Dollar Tree | 21.40 Bn | 18.02 Bn | 2.10 Bn |
| 8 | US Foods Holding | 19.94 Bn | 19.74 Bn | 1.92 Bn |
| 9 | Tractor Supply | 16.33 Bn | 15.49 Bn | 1.68 Bn |
| 10 | Dingdong (Cayman) | 1.39 Bn | 114.26 Mn | 1.64 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.93 Mn |
| Mar 31, 2026 | 1.78 Mn |
| Dec 31, 2025 | 657,589.49 |
| Sep 30, 2025 | 106.76 Mn |
| Jun 30, 2025 | 105.47 Mn |
| Mar 31, 2025 | 105.43 Mn |
| Dec 31, 2024 | 106.79 Mn |
| Sep 30, 2024 | 110.56 Mn |
| Jun 30, 2024 | 95.40 Mn |
| Mar 31, 2024 | 97.24 Mn |
| Dec 31, 2023 | 91.17 Mn |
| Sep 30, 2023 | 87.54 Mn |
| Jun 30, 2023 | 88.05 Mn |
| Mar 31, 2023 | 95.13 Mn |
| Dec 31, 2022 | 114.02 Mn |
| Sep 30, 2022 | 98.15 Mn |
| Jun 30, 2022 | 104.47 Mn |
| Mar 31, 2022 | 107.50 Mn |
| Dec 31, 2021 | 102.18 Mn |
| Sep 30, 2021 | 138.98 Mn |
Dingdong (Cayman) Accumulated Expenses 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=accumulated-expenses&ticker=DDL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "DDL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=DDL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();