Moog (MOG-A) Accumulated Expenses (2009 - 2026)
Moog (MOG-A) posted Accumulated Expenses of $316.46 million for fiscal Q3 2026 (quarter ended Jun 27, 2026), down 0.5% from $318.04 million a year earlier but up 10.4% from the prior quarter.
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Analysis
Moog (MOG-A) Accumulated Expenses (2009 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 27, 2025), Moog's Accumulated Expenses came in at $320.08 million, up 2.1% from FY2024.
- Annual Accumulated Expenses has increased for four consecutive fiscal years, with a five-year compound annual growth rate of 7.7% (FY2020 to FY2025).
- In prior fiscal years, Moog's Accumulated Expenses was $313.37 million in FY2024 (+29.6%), $241.81 million in FY2023 (+12.3%), $215.38 million in FY2022 (+1.6%) and $212.01 million in FY2021 (-3.8%).
- Quarterly Accumulated Expenses has run from a low of $206.9 million in fiscal Q3 2023 to a high of $320.08 million in fiscal Q4 2025 over five years.
- On a year-over-year basis, Accumulated Expenses has declined in each of the last three quarters, with growth averaging 6.8% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was fiscal Q3 2024, with growth of 40.6%; the weakest was fiscal Q1 2022, with a decline of 11.7%.
- According to Business Quant data, Accumulated Expenses for the three prior fiscal quarters was $286.74 million (Q2 2026), $280.61 million (Q1 2026) and $320.08 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | General Electric | 321.31 Bn | 275.31 Bn | 4.68 Bn |
| 2 | Rtx | 248.97 Bn | 222.19 Bn | 5.13 Bn |
| 3 | Boeing | 152.99 Bn | 59.70 Bn | 2.41 Bn |
| 4 | Lockheed Martin | 116.67 Bn | 103.39 Bn | 2.45 Bn |
| 5 | Howmet Aerospace | 92.54 Bn | 88.15 Bn | 951.00 Mn |
| 6 | General Dynamics | 89.31 Bn | 76.42 Bn | 2.18 Bn |
| 7 | Motorola Solutions | 74.04 Bn | 70.40 Bn | 1.68 Bn |
| 8 | Northrop Grumman | 67.90 Bn | 57.15 Bn | 2.12 Bn |
| 9 | Honeywell International | 67.82 Bn | 20.27 Bn | 3.65 Bn |
| 10 | Moog | 11.17 Bn | 10.66 Bn | 347.25 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 316.46 Mn |
| Mar 28, 2026 | 286.74 Mn |
| Jan 3, 2026 | 280.61 Mn |
| Sep 27, 2025 | 320.08 Mn |
| Jun 28, 2025 | 318.04 Mn |
| Mar 29, 2025 | 297.64 Mn |
| Dec 28, 2024 | 301.46 Mn |
| Sep 28, 2024 | 313.37 Mn |
| Jun 29, 2024 | 290.82 Mn |
| Mar 30, 2024 | 281.74 Mn |
| Dec 30, 2023 | 253.14 Mn |
| Sep 30, 2023 | 241.81 Mn |
| Jul 1, 2023 | 206.90 Mn |
| Apr 1, 2023 | 212.27 Mn |
| Dec 31, 2022 | 209.62 Mn |
| Oct 1, 2022 | 215.38 Mn |
| Jul 2, 2022 | 211.77 Mn |
| Apr 2, 2022 | 217.78 Mn |
| Jan 1, 2022 | 207.38 Mn |
| Oct 2, 2021 | 212.01 Mn |
API Access
Moog 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=MOG-A&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "MOG-A", "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=MOG-A&period=max&api_key=YOUR_API_KEY");
const data = await res.json();