Pyxus International (PYYX) Accumulated Expenses (2010 - 2026)
Pyxus International (PYYX) posted Accumulated Expenses of $131.51 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), up 26.3% from $104.16 million a year earlier and up 14.6% from the prior quarter.
Pyxus International (PYYX) Accumulated Expenses (2010 - 2026) Analysis & Trends
At the end of FY2026 (ended Mar 31, 2026), Pyxus International's Accumulated Expenses came in at $114.76 million, up 26.2% from FY2025.
- Annual Accumulated Expenses shows a five-year compound annual growth rate of 9.9% (FY2021 to FY2026).
- In prior fiscal years, Pyxus International's Accumulated Expenses was $90.91 million in FY2025 (-6.2%), $96.95 million in FY2024 (+4.6%), $92.69 million in FY2023 (+12.7%) and $82.24 million in FY2022 (+14.8%).
- The fiscal Q1 2027 figure stands as the highest quarterly Accumulated Expenses since fiscal Q1 2011.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last five quarters, with growth averaging 15.1% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was fiscal Q3 2025, with growth of 33.2%; the weakest was fiscal Q3 2024, with a decline of 17.9%.
- According to Business Quant data, Accumulated Expenses for the three prior fiscal quarters was $114.76 million (Q4 2026), $125.79 million (Q3 2026) and $109.24 million (Q2 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Archer-Daniels-Midland | 39.75 Bn | 36.05 Bn | 1.94 Bn |
| 2 | Bunge Global | 20.62 Bn | 18.13 Bn | 1.68 Bn |
| 3 | Tyson Foods | 18.20 Bn | 14.55 Bn | 921.00 Mn |
| 4 | Jbs | 13.21 Bn | -19.90 Bn | 2.59 Bn |
| 5 | Darling Ingredients | 9.91 Bn | 9.50 Bn | 503.37 Mn |
| 6 | Smithfield Foods | 7.38 Bn | 2.33 Bn | 478.00 Mn |
| 7 | Pilgrims Pride | 6.66 Bn | 4.49 Bn | 339.75 Mn |
| 8 | Ingredion | 6.11 Bn | 2.29 Bn | 426.00 Mn |
| 9 | Seaboard | 3.85 Bn | -964.27 Mn | 221.00 Mn |
| 10 | Pyxus International | 68.66 Mn | -463.80 Mn | 61.41 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 131.51 Mn |
| Mar 31, 2026 | 114.76 Mn |
| Dec 31, 2025 | 125.79 Mn |
| Sep 30, 2025 | 109.24 Mn |
| Jun 30, 2025 | 104.16 Mn |
| Mar 31, 2025 | 90.91 Mn |
| Dec 31, 2024 | 104.18 Mn |
| Sep 30, 2024 | 103.39 Mn |
| Jun 30, 2024 | 99.05 Mn |
| Mar 31, 2024 | 96.95 Mn |
| Dec 31, 2023 | 78.23 Mn |
| Sep 30, 2023 | 93.98 Mn |
| Jun 30, 2023 | 94.36 Mn |
| Mar 31, 2023 | 92.69 Mn |
| Dec 31, 2022 | 95.31 Mn |
| Sep 30, 2022 | 75.99 Mn |
| Jun 30, 2022 | 91.05 Mn |
| Mar 31, 2022 | 82.24 Mn |
| Dec 31, 2021 | 79.58 Mn |
| Sep 30, 2021 | 72.57 Mn |
Pyxus International 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=PYYX&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "PYYX", "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=PYYX&period=max&api_key=YOUR_API_KEY");
const data = await res.json();