Pyxus International (PYYX) Accumulated Expenses (2009 - 2026)
Pyxus International (PYYX) posted Accumulated Expenses of $121.03 million for fiscal Q2 2027 (quarter ended Sep 30, 2026), up 10.8% from $109.24 million a year earlier but down 8.0% from the prior quarter.
Pyxus International (PYYX) Accumulated Expenses (2009 - 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%).
- Quarterly Accumulated Expenses has run from a low of $75.99 million in fiscal Q2 2023 to a high of $131.51 million in fiscal Q1 2027 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last six quarters, with growth averaging 15.2% 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 $131.51 million (Q1 2027), $114.76 million (Q4 2026) and $125.79 million (Q3 2026).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Archer-Daniels-Midland | 34.69 Bn | 31.46 Bn | 1.89 Bn |
| 2 | Tyson Foods | 20.70 Bn | 17.06 Bn | 921.00 Mn |
| 3 | Bunge Global | 19.53 Bn | 17.95 Bn | 1.33 Bn |
| 4 | Jbs | 13.49 Bn | -2.10 Bn | 2.41 Bn |
| 5 | Darling Ingredients | 8.67 Bn | 8.25 Bn | 477.54 Mn |
| 6 | Smithfield Foods | 7.56 Bn | 2.38 Bn | 313.00 Mn |
| 7 | Pilgrims Pride | 6.70 Bn | 4.20 Bn | 333.67 Mn |
| 8 | Ingredion | 5.86 Bn | 1.97 Bn | 399.00 Mn |
| 9 | Scotts Miracle-Gro | 3.71 Bn | 3.71 Bn | - |
| 10 | Pyxus International | 62.01 Mn | -468.26 Mn | 78.91 Mn |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | 121.03 Mn |
| 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 |
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();