Newmarket (NEU) Accumulated Expenses (2009 - 2026)
Newmarket's (NEU) quarterly Accumulated Expenses came in at $95.2 million in Q2 2026, up 22.73% year-over-year from $77.6 million in Q2 2025, and little changed quarter-over-quarter from $94.8 million in Q1 2026.
Newmarket (NEU) Accumulated Expenses (2009 - 2026) Analysis & Trends
Newmarket has disclosed Accumulated Expenses across 18 years of filings, most recently posting $95.2 million for Q2 2026.
- In Q2 2026, Accumulated Expenses rose 22.73% year-over-year to $95.2 million; the TTM figure through Jun 2026 stood at $95.2 million (up 22.73% YoY), while the FY2025 annual figure was $109.8 million, up 22.96% from the prior year.
- Accumulated Expenses came in at $95.2 million for Q2 2026 at Newmarket, roughly flat from $94.8 million in the prior quarter.
- In the past five years, Accumulated Expenses ranged from a high of $109.8 million in Q4 2025 to a low of $70.5 million in Q1 2025.
- Average Accumulated Expenses over 5 years is $82.2 million, with a median of $80.0 million recorded in 2024.
- Year-over-year, Accumulated Expenses declined 15.49% in 2023 and soared 34.57% in 2026.
- Over 5 years, Accumulated Expenses stood at $89.5 million in 2022, then slipped by 14.48% to $76.5 million in 2023, then increased by 16.63% to $89.3 million in 2024, then gained by 22.96% to $109.8 million in 2025, then fell by 13.28% to $95.2 million in 2026.
- Per Business Quant data, the three most recent Accumulated Expenses figures were $95.2 million in Q2 2026, $94.8 million in Q1 2026, and $109.8 million in Q4 2025.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Asml Holding | 647.47 Bn | 631.49 Bn | 5.90 Bn |
| 2 | General Electric | 325.83 Bn | 316.71 Bn | 6.95 Bn |
| 3 | Astrazeneca | 257.75 Bn | 252.54 Bn | 12.86 Bn |
| 4 | Citigroup | 221.04 Bn | -2,078.84 Bn | 24.75 Bn |
| 5 | Bhp | 219.16 Bn | 200.62 Bn | - |
| 6 | Diageo | 208.21 Bn | 208.26 Bn | - |
| 7 | Rio Tinto | 188.09 Bn | 183.71 Bn | - |
| 8 | Ferrari | 151.21 Bn | 149.46 Bn | 1.18 Bn |
| 9 | Unilever | 134.81 Bn | 130.23 Bn | - |
| 10 | Newmarket | 8.20 Bn | 8.11 Bn | 242.43 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 95.20 Mn |
| Mar 31, 2026 | 94.82 Mn |
| Dec 31, 2025 | 109.77 Mn |
| Sep 30, 2025 | 83.23 Mn |
| Jun 30, 2025 | 77.57 Mn |
| Mar 31, 2025 | 70.46 Mn |
| Dec 31, 2024 | 89.28 Mn |
| Sep 30, 2024 | 82.36 Mn |
| Jun 30, 2024 | 85.11 Mn |
| Mar 31, 2024 | 72.67 Mn |
| Dec 31, 2023 | 76.55 Mn |
| Sep 30, 2023 | 72.30 Mn |
| Jun 30, 2023 | 72.92 Mn |
| Mar 31, 2023 | 72.34 Mn |
| Dec 31, 2022 | 89.51 Mn |
| Sep 30, 2022 | 85.55 Mn |
| Jun 30, 2022 | 76.18 Mn |
| Mar 31, 2022 | 73.40 Mn |
| Dec 31, 2021 | 85.10 Mn |
| Sep 30, 2021 | 86.68 Mn |
Newmarket 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=NEU&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "NEU", "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=NEU&period=max&api_key=YOUR_API_KEY");
const data = await res.json();