China Foods Holdings (CFOO) Total Liabilities (2010 - 2026)
China Foods Holdings (CFOO) reported Total Liabilities of $1.63 million for Q2 2026, up 15.8% from $1.41 million a year earlier and up 5.2% from the prior quarter.
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Analysis
China Foods Holdings (CFOO) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, China Foods Holdings posted Total Liabilities of $1.49 million, up 15.9% from FY2024.
- Total Liabilities has increased for three consecutive years, with a five-year compound annual growth rate of 16.4% (FY2020 to FY2025).
- By year, Total Liabilities came in at $1.29 million in FY2024 (+70.1%), $755,996 in FY2023 (+14.2%), $661,779 in FY2022 (-43.5%) and $1.17 million in FY2021 (+68.0%).
- The Q2 2026 figure ranks as the highest quarterly Total Liabilities in data going back to Q4 2010.
- Year over year, Total Liabilities has now increased in each of the last 11 quarters, with growth averaging 44.3% over the last eight quarters.
- The high point for year-over-year Total Liabilities in five years was Q3 2021 (growth of 104.0%); the low point was Q4 2022 (a decline of 43.5%).
- Per Business Quant data, the three quarters before Q2 2026 came in at $1.55 million (Q1 2026), $1.49 million (Q4 2025) and $1.43 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Procter & Gamble | 346.43 Bn | 302.42 Bn | 10.28 Bn | 72.21 Bn |
| 2 | Colgate Palmolive | 69.04 Bn | 64.10 Bn | 3.30 Bn | 16.22 Bn |
| 3 | Estee Lauder Companies | 34.63 Bn | 22.70 Bn | 2.74 Bn | 15.96 Bn |
| 4 | Kenvue | 34.35 Bn | 29.97 Bn | 2.30 Bn | 16.18 Bn |
| 5 | Kimberly Clark | 32.85 Bn | 30.17 Bn | 1.60 Bn | 16.68 Bn |
| 6 | Church & Dwight | 22.69 Bn | 21.21 Bn | 693.90 Mn | 4.76 Bn |
| 7 | Clorox | 9.84 Bn | 8.28 Bn | 804.00 Mn | 7.54 Bn |
| 8 | e.l.f. Beauty | 6.00 Bn | 4.97 Bn | 398.84 Mn | 1.29 Bn |
| 9 | Reynolds Consumer Products | 4.65 Bn | 4.32 Bn | 245.00 Mn | 2.77 Bn |
| 10 | China Foods Holdings | 21.26 Mn | 21.15 Mn | 2.00 | 1.63 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.63 Mn |
| Mar 31, 2026 | 1.55 Mn |
| Dec 31, 2025 | 1.49 Mn |
| Sep 30, 2025 | 1.43 Mn |
| Jun 30, 2025 | 1.41 Mn |
| Mar 31, 2025 | 1.42 Mn |
| Dec 31, 2024 | 1.29 Mn |
| Sep 30, 2024 | 966,078.00 |
| Jun 30, 2024 | 828,131.00 |
| Mar 31, 2024 | 726,743.00 |
| Dec 31, 2023 | 755,996.00 |
| Sep 30, 2023 | 740,181.00 |
| Jun 30, 2023 | 688,143.00 |
| Mar 31, 2023 | 648,060.00 |
| Dec 31, 2022 | 661,779.00 |
| Sep 30, 2022 | 948,341.00 |
| Jun 30, 2022 | 1.01 Mn |
| Mar 31, 2022 | 1.11 Mn |
| Dec 31, 2021 | 1.17 Mn |
| Sep 30, 2021 | 1.09 Mn |
API Access
China Foods Holdings 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=CFOO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "CFOO", "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=CFOO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();