e.l.f. Beauty (ELF) Change in Accured Expenses (2015 - 2026)
e.l.f. Beauty (ELF) reported Change in Accured Expenses of -$2.43 million for fiscal Q1 2027 (quarter ended Jun 30, 2026), compared with -$1.54 million a year earlier.
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Analysis
e.l.f. Beauty (ELF) Change in Accured Expenses (2015 - 2026) Analysis & Trends
Over the twelve months ended Jun 30, 2026, e.l.f. Beauty's Change in Accured Expenses came in at $74.4 million; for FY2026 (ended Mar 31, 2026), it was $75.29 million.
- Change in Accured Expenses has a five-year compound annual growth rate of 33.9% (FY2021 to FY2026).
- By fiscal year, Change in Accured Expenses came in at -$23.4 million in FY2025, $81.22 million in FY2024 (+88.9%), $43 million in FY2023 and $1.5 million in FY2022 (-91.4%).
- Five-year quarterly Change in Accured Expenses spans a low of -$17.71 million in fiscal Q4 2025 and a high of $65.48 million in fiscal Q4 2026.
- The high point for year-over-year Change in Accured Expenses in five years was fiscal Q4 2023 (growth of 831.2%); the low point was fiscal Q2 2025 (a decline of 80.8%).
- Per Business Quant data, the three fiscal quarters before Q1 2027 came in at $65.48 million (Q4 2026), -$14.55 million (Q3 2026) and $25.9 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Procter & Gamble | 334.70 Bn | 290.68 Bn | 10.28 Bn | - |
| 2 | Colgate Palmolive | 67.39 Bn | 62.44 Bn | 3.30 Bn | 135.00 Mn |
| 3 | Kenvue | 33.10 Bn | 28.72 Bn | 2.30 Bn | 197.00 Mn |
| 4 | Estee Lauder Companies | 32.68 Bn | 20.76 Bn | 2.74 Bn | - |
| 5 | Kimberly Clark | 31.38 Bn | 28.70 Bn | 1.60 Bn | - |
| 6 | Church & Dwight | 22.32 Bn | 20.85 Bn | 693.90 Mn | 26.10 Mn |
| 7 | Clorox | 9.75 Bn | 8.19 Bn | 804.00 Mn | 50.00 Mn |
| 8 | e.l.f. Beauty | 6.14 Bn | 5.11 Bn | 398.84 Mn | -2.43 Mn |
| 9 | Reynolds Consumer Products | 4.62 Bn | 4.29 Bn | 245.00 Mn | 50.00 Mn |
| 10 | Interparfums | 3.58 Bn | 3.39 Bn | 223.53 Mn | -3.71 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -2.43 Mn |
| Mar 31, 2026 | 65.48 Mn |
| Dec 31, 2025 | -14.55 Mn |
| Sep 30, 2025 | 25.90 Mn |
| Jun 30, 2025 | -1.54 Mn |
| Mar 31, 2025 | -17.71 Mn |
| Dec 31, 2024 | -10.88 Mn |
| Sep 30, 2024 | 8.30 Mn |
| Jun 30, 2024 | -3.11 Mn |
| Mar 31, 2024 | -3.52 Mn |
| Dec 31, 2023 | 39.62 Mn |
| Sep 30, 2023 | 43.10 Mn |
| Jun 30, 2023 | 2.01 Mn |
| Mar 31, 2023 | 20.39 Mn |
| Dec 31, 2022 | 15.81 Mn |
| Sep 30, 2022 | 10.24 Mn |
| Jun 30, 2022 | -3.44 Mn |
| Mar 31, 2022 | 2.19 Mn |
| Dec 31, 2021 | 5.19 Mn |
| Sep 30, 2021 | 1.54 Mn |
API Access
e.l.f. Beauty Change in Accured 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=change-in-accured-expenses&ticker=ELF&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "ELF", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=ELF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();