Coty (COTY) Operating Expenses (2012 - 2026)
Coty's Operating Expenses came in at $741.3 million for fiscal Q4 2026 (quarter ended Jun 30, 2026), up 3.2% from $718.6 million a year earlier and up 2.0% from the prior quarter.
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Analysis
Coty (COTY) Operating Expenses (2012 - 2026) Analysis & Trends
For FY2026 (ended Jun 30, 2026), Coty's Operating Expenses was $3.11 billion, down 2.2% from FY2025.
- Operating Expenses carries a five-year compound annual growth rate of 5.1% (FY2021 to FY2026).
- Going back by fiscal year, Operating Expenses was $3.18 billion in FY2025 (-0.6%), $3.2 billion in FY2024 (+13.8%), $2.81 billion in FY2023 (-2.2%) and $2.87 billion in FY2022 (+18.5%).
- The five-year range for quarterly Operating Expenses is $652.5 million (fiscal Q3 2022) to $854.1 million (fiscal Q3 2025).
- Year-over-year, Operating Expenses increased in four of the last eight quarters, with an average decline of 1.2%.
- The fastest year-over-year change in Operating Expenses over five years came in fiscal Q1 2022 (growth of 28.6%), and the weakest in fiscal Q1 2023 (a decline of 15.1%).
- Business Quant data shows COTY's Operating Expenses at $726.6 million (Q3 2026), $848.3 million (Q2 2026) and $792.5 million (Q1 2026) in the three fiscal quarters before Q4 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Procter & Gamble | 371.53 Bn | 327.28 Bn | 10.28 Bn | 6.33 Bn |
| 2 | Colgate Palmolive | 75.49 Bn | 70.22 Bn | 3.30 Bn | 2.13 Bn |
| 3 | Estee Lauder Companies | 38.41 Bn | 26.49 Bn | 2.74 Bn | 2.78 Bn |
| 4 | Kenvue | 37.04 Bn | 32.65 Bn | 2.30 Bn | 1.60 Bn |
| 5 | Kimberly Clark | 35.98 Bn | 33.18 Bn | 1.60 Bn | - |
| 6 | Church & Dwight | 25.05 Bn | 23.58 Bn | 693.90 Mn | 252.20 Mn |
| 7 | Clorox | 10.64 Bn | 8.92 Bn | 804.00 Mn | 330.00 Mn |
| 8 | e.l.f. Beauty | 6.78 Bn | 5.75 Bn | 398.84 Mn | 280.32 Mn |
| 9 | Reynolds Consumer Products | 4.84 Bn | 4.50 Bn | 245.00 Mn | 107.00 Mn |
| 10 | Coty | 2.82 Bn | 1.69 Bn | 772.70 Mn | 741.30 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 741.30 Mn |
| Mar 31, 2026 | 726.60 Mn |
| Dec 31, 2025 | 848.30 Mn |
| Sep 30, 2025 | 792.50 Mn |
| Jun 30, 2025 | 718.60 Mn |
| Mar 31, 2025 | 854.10 Mn |
| Dec 31, 2024 | 798.70 Mn |
| Sep 30, 2024 | 808.70 Mn |
| Jun 30, 2024 | 792.70 Mn |
| Mar 31, 2024 | 771.50 Mn |
| Dec 31, 2023 | 839.10 Mn |
| Sep 30, 2023 | 795.80 Mn |
| Jun 30, 2023 | 671.80 Mn |
| Mar 31, 2023 | 719.10 Mn |
| Dec 31, 2022 | 751.40 Mn |
| Sep 30, 2022 | 669.50 Mn |
| Jun 30, 2022 | 718.80 Mn |
| Mar 31, 2022 | 652.50 Mn |
| Dec 31, 2021 | 714.80 Mn |
| Sep 30, 2021 | 788.70 Mn |
API Access
Coty 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=COTY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "COTY", "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=COTY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();