Pangaea Logistics Solutions (PANL) Operating Expenses (2014 - 2026)
Pangaea Logistics Solutions' Operating Expenses was $165.77 million in Q2 2026, up 8.3% from $153.04 million a year earlier and up 3.5% from the prior quarter.
Pangaea Logistics Solutions (PANL) Operating Expenses (2014 - 2026) Analysis & Trends
On a trailing twelve-month basis, Pangaea Logistics Solutions' Operating Expenses was $644.07 million through Jun 30, 2026, up 18.5% year-over-year; for FY2025, it came in at $591.1 million, up 21.1% from FY2024.
- Operating Expenses shows a five-year compound annual growth rate of 10.2% (FY2020 to FY2025).
- In earlier years, Operating Expenses was $488.09 million in FY2024 (+7.4%), $454.65 million in FY2023 (-23.5%), $594.2 million in FY2022 (-7.0%) and $639.23 million in FY2021 (+76.0%).
- Quarterly Operating Expenses has moved between $93.72 million (Q1 2024) and $203.8 million (Q4 2021) over five years.
- Compared with a year earlier, Operating Expenses has increased for nine straight quarters, with growth averaging 19.7% over the last eight quarters.
- The best year-over-year quarter for Operating Expenses over five years was Q3 2021 (growth of 99.9%); the worst was Q4 2022 (a decline of 46.4%).
- Per Business Quant data, PANL's Operating Expenses in the three quarters before Q2 2026 was $160.11 million (Q1 2026), $166.44 million (Q4 2025) and $151.75 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Union Pacific | 162.85 Bn | 157.37 Bn | - | 4.10 Bn |
| 2 | Csx | 86.62 Bn | 82.84 Bn | - | 2.43 Bn |
| 3 | Canadian Pacific Kansas City | 76.11 Bn | 75.83 Bn | - | 1.95 Bn |
| 4 | United Parcel Service | 70.66 Bn | 47.58 Bn | - | 21.90 Bn |
| 5 | Norfolk Southern | 70.32 Bn | 64.96 Bn | - | 2.34 Bn |
| 6 | Fedex | 68.53 Bn | 34.48 Bn | - | 23.46 Bn |
| 7 | Delta Air Lines | 55.25 Bn | 37.43 Bn | - | 17.89 Bn |
| 8 | Old Dominion Freight Line | 36.69 Bn | 35.95 Bn | - | 1.09 Bn |
| 9 | Ryanair Holdings | 28.78 Bn | 12.78 Bn | 3.13 Bn | 4.43 Bn |
| 10 | Pangaea Logistics Solutions | 524.44 Mn | 178.00 Mn | - | 165.77 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 165.77 Mn |
| Mar 31, 2026 | 160.11 Mn |
| Dec 31, 2025 | 166.44 Mn |
| Sep 30, 2025 | 151.75 Mn |
| Jun 30, 2025 | 153.04 Mn |
| Mar 31, 2025 | 119.88 Mn |
| Dec 31, 2024 | 132.37 Mn |
| Sep 30, 2024 | 138.11 Mn |
| Jun 30, 2024 | 123.88 Mn |
| Mar 31, 2024 | 93.72 Mn |
| Dec 31, 2023 | 121.30 Mn |
| Sep 30, 2023 | 115.90 Mn |
| Jun 30, 2023 | 110.22 Mn |
| Mar 31, 2023 | 107.20 Mn |
| Dec 31, 2022 | 109.20 Mn |
| Sep 30, 2022 | 154.10 Mn |
| Jun 30, 2022 | 159.20 Mn |
| Mar 31, 2022 | 171.80 Mn |
| Dec 31, 2021 | 203.80 Mn |
| Sep 30, 2021 | 187.50 Mn |
Pangaea Logistics Solutions Operating 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=operating-expenses&ticker=PANL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "PANL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=PANL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();