American Electric Power (AEP) Operating Expenses (2009 - 2026)
American Electric Power's Operating Expenses came in at $5.78 billion for fiscal Q3 2016 (quarter ended Sep 30, 2016), up 66.5% from $3.47 billion a year earlier and up 91.0% from the prior quarter.
American Electric Power (AEP) Operating Expenses (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Sep 30, 2016, American Electric Power reported Operating Expenses of $15.11 billion, up 13.1% year-over-year; for FY2015 (ended Dec 31, 2015), it was $13.12 billion, down 1.0% from FY2014.
- Operating Expenses carries a five-year compound annual growth rate of 2.2% (FY2010 to FY2015).
- Going back by fiscal year, Operating Expenses was $13.25 billion in FY2014 (+10.5%), $11.99 billion in FY2013 (-2.4%) and $12.29 billion in FY2012.
- The fiscal Q3 2016 figure represents the highest quarterly Operating Expenses in data going back to fiscal Q1 2009.
- Year-over-year, Operating Expenses increased in four of the last eight quarters, with growth averaging 9.6%.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q3 2016 (growth of 66.5%), and the weakest in fiscal Q4 2013 (a decline of 23.2%).
- Business Quant data shows AEP's Operating Expenses at $3.03 billion (Q2 2016), $3.15 billion (Q1 2016) and $3.15 billion (Q4 2015) in the three fiscal quarters before Q3 2016.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Enel Chile | 285.66 Bn | 285.66 Bn | 890.00 Mn | -140.00 Mn |
| 2 | Nextera Energy | 159.27 Bn | 160.17 Bn | - | 5.29 Bn |
| 3 | Southern | 96.02 Bn | 87.08 Bn | 5.92 Bn | 5.20 Bn |
| 4 | Duke Energy | 88.50 Bn | 87.10 Bn | 6.74 Bn | 6.84 Bn |
| 5 | National Grid | 78.31 Bn | 59.83 Bn | - | - |
| 6 | American Electric Power | 65.19 Bn | 63.57 Bn | 3.84 Bn | 4.20 Bn |
| 7 | Dominion Energy | 53.46 Bn | 56.14 Bn | - | 4.15 Bn |
| 8 | Sempra | 51.03 Bn | 50.16 Bn | 2.89 Bn | 1.35 Bn |
| 9 | Entergy | 46.86 Bn | 36.05 Bn | - | 2.67 Bn |
| 10 | Xcel Energy | 44.05 Bn | 38.96 Bn | - | 2.41 Bn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.20 Bn |
| Mar 31, 2026 | 4.66 Bn |
| Dec 31, 2025 | 4.20 Bn |
| Sep 30, 2025 | 4.49 Bn |
| Jun 30, 2025 | 3.69 Bn |
| Mar 31, 2025 | 4.18 Bn |
| Dec 31, 2024 | 3.60 Bn |
| Sep 30, 2024 | 4.07 Bn |
| Jun 30, 2024 | 3.90 Bn |
| Mar 31, 2024 | 3.85 Bn |
| Dec 31, 2023 | 3.95 Bn |
| Sep 30, 2023 | 3.99 Bn |
| Jun 30, 2023 | 3.50 Bn |
| Mar 31, 2023 | 3.99 Bn |
| Dec 31, 2022 | 4.32 Bn |
| Sep 30, 2022 | 4.60 Bn |
| Jun 30, 2022 | 3.64 Bn |
| Mar 31, 2022 | 3.60 Bn |
| Dec 31, 2021 | 3.38 Bn |
| Sep 30, 2021 | 3.52 Bn |
American Electric Power 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=AEP&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "AEP", "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=AEP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();