Interparfums (IPAR) Total Liabilities (2010 - 2026)
Interparfums' Total Liabilities was $399.41 million in Q2 2026, down 20.9% from $505 million a year earlier and down 7.2% from the prior quarter.
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Analysis
Interparfums (IPAR) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Total Liabilities at Interparfums came in at $481.22 million, up 2.7% from FY2024.
- Total Liabilities shows a five-year compound annual growth rate of 20.7% (FY2020 to FY2025).
- In earlier years, Total Liabilities was $468.62 million in FY2024 (-1.8%), $477.16 million in FY2023 (-8.3%), $520.4 million in FY2022 (+27.9%) and $407.03 million in FY2021 (+116.9%).
- The Q2 2026 figure marks the lowest quarterly Total Liabilities since Q3 2022.
- Compared with a year earlier, Total Liabilities was higher in two of the last eight quarters, with an average decline of 3.1%.
- The best year-over-year quarter for Total Liabilities over five years was Q3 2021 (growth of 127.9%); the worst was Q2 2026 (a decline of 20.9%).
- Per Business Quant data, IPAR's Total Liabilities in the three quarters before Q2 2026 was $430.23 million (Q1 2026), $481.22 million (Q4 2025) and $460.16 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Procter & Gamble | 337.81 Bn | 293.80 Bn | 10.28 Bn | 72.21 Bn |
| 2 | Colgate Palmolive | 68.01 Bn | 63.06 Bn | 3.30 Bn | 16.22 Bn |
| 3 | Kenvue | 33.93 Bn | 29.54 Bn | 2.30 Bn | 16.18 Bn |
| 4 | Estee Lauder Companies | 33.63 Bn | 21.70 Bn | 2.74 Bn | 15.96 Bn |
| 5 | Kimberly Clark | 32.41 Bn | 29.73 Bn | 1.60 Bn | 16.68 Bn |
| 6 | Church & Dwight | 22.35 Bn | 20.88 Bn | 693.90 Mn | 4.76 Bn |
| 7 | Clorox | 9.80 Bn | 8.24 Bn | 804.00 Mn | 7.54 Bn |
| 8 | e.l.f. Beauty | 5.95 Bn | 4.92 Bn | 398.84 Mn | 1.29 Bn |
| 9 | Reynolds Consumer Products | 4.56 Bn | 4.22 Bn | 245.00 Mn | 2.77 Bn |
| 10 | Interparfums | 3.55 Bn | 3.36 Bn | 223.53 Mn | 399.41 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 399.41 Mn |
| Mar 31, 2026 | 430.23 Mn |
| Dec 31, 2025 | 481.22 Mn |
| Sep 30, 2025 | 460.16 Mn |
| Jun 30, 2025 | 505.00 Mn |
| Mar 31, 2025 | 433.01 Mn |
| Dec 31, 2024 | 468.62 Mn |
| Sep 30, 2024 | 495.47 Mn |
| Jun 30, 2024 | 462.79 Mn |
| Mar 31, 2024 | 441.29 Mn |
| Dec 31, 2023 | 477.16 Mn |
| Sep 30, 2023 | 517.53 Mn |
| Jun 30, 2023 | 504.73 Mn |
| Mar 31, 2023 | 519.72 Mn |
| Dec 31, 2022 | 520.40 Mn |
| Sep 30, 2022 | 381.05 Mn |
| Jun 30, 2022 | 379.45 Mn |
| Mar 31, 2022 | 403.97 Mn |
| Dec 31, 2021 | 407.03 Mn |
| Sep 30, 2021 | 366.76 Mn |
API Access
Interparfums Total Liabilities 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=total-liabilities&ticker=IPAR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "IPAR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=IPAR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();