Euroseas (ESEA) Accumulated Expenses (2009 - 2026)
Euroseas (ESEA) posted Accumulated Expenses of $12.87 million for the quarter ended Jun 30, 2026, up 102.7% from $6.35 million a year earlier and up 20.0% from the prior quarter.
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Analysis
Euroseas (ESEA) Accumulated Expenses (2009 - 2026) Analysis & Trends
As of Dec 31, 2025, Euroseas' Accumulated Expenses came in at $9.04 million, up 101.6% from the prior year.
- Annual Accumulated Expenses has increased for four consecutive years, though with a five-year compound annual growth rate of -90.7% (years ended Dec 2020 to Dec 2025).
- In prior years, Euroseas' Accumulated Expenses was $4.48 million in the year ended Dec 31, 2024 (+140.3%), $1.87 million in the year ended Dec 31, 2023 (+6.2%), $1.76 million in the year ended Dec 31, 2022 (+3.1%) and $1.7 million in the year ended Dec 31, 2021 (-100.0%).
- The figure for the quarter ended Jun 30, 2026 stands as the highest quarterly Accumulated Expenses since the quarter ended Dec 31, 2020.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last 11 quarters, with growth averaging 95.3% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was the quarter ended Mar 31, 2024, with growth of 234.5%; the weakest was the quarter ended Dec 31, 2021, with a decline of 100.0%.
- According to Business Quant data, Accumulated Expenses for the three prior quarters was $10.73 million (quarter ended Mar 31, 2026), $9.04 million (quarter ended Dec 31, 2025) and $8.92 million (quarter ended Sep 30, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Union Pacific | 161.62 Bn | 156.15 Bn | - |
| 2 | Csx | 86.16 Bn | 82.37 Bn | - |
| 3 | Canadian Pacific Kansas City | 74.78 Bn | 74.50 Bn | - |
| 4 | United Parcel Service | 70.01 Bn | 46.94 Bn | - |
| 5 | Norfolk Southern | 69.45 Bn | 64.09 Bn | - |
| 6 | Fedex | 67.46 Bn | 33.40 Bn | - |
| 7 | Delta Air Lines | 54.88 Bn | 37.06 Bn | - |
| 8 | Old Dominion Freight Line | 36.07 Bn | 35.33 Bn | - |
| 9 | Ryanair Holdings | 28.71 Bn | 12.72 Bn | 3.13 Bn |
| 10 | Euroseas | 503.23 Mn | -118.36 Mn | 113.38 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 12.87 Mn |
| Mar 31, 2026 | 10.73 Mn |
| Dec 31, 2025 | 9.04 Mn |
| Sep 30, 2025 | 8.92 Mn |
| Jun 30, 2025 | 6.35 Mn |
| Mar 31, 2025 | 5.85 Mn |
| Dec 31, 2024 | 4.48 Mn |
| Sep 30, 2024 | 5.15 Mn |
| Jun 30, 2024 | 2.76 Mn |
| Mar 31, 2024 | 5.66 Mn |
| Dec 31, 2023 | 1.87 Mn |
| Sep 30, 2023 | 2.26 Mn |
| Jun 30, 2023 | 1.29 Mn |
| Mar 31, 2023 | 1.69 Mn |
| Dec 31, 2022 | 1.76 Mn |
| Sep 30, 2022 | 3.50 Mn |
| Jun 30, 2022 | 1.72 Mn |
| Mar 31, 2022 | 1.45 Mn |
| Dec 31, 2021 | 1.70 Mn |
| Sep 30, 2021 | 2.19 Mn |
API Access
Euroseas 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=ESEA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "ESEA", "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=ESEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();