Kun Peng International (KPEA) Total Liabilities (2011 - 2026)
Kun Peng International's Total Liabilities was $9.99 million in fiscal Q3 2026 (quarter ended Jun 30, 2026), up 14.9% from $8.7 million a year earlier and up 2.7% from the prior quarter.
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Analysis
Kun Peng International (KPEA) Total Liabilities (2011 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 30, 2025), Total Liabilities at Kun Peng International came in at $9.03 million, up 4.2% from FY2024.
- Total Liabilities has now increased for five consecutive fiscal years, with a five-year compound annual growth rate of 54.8% (FY2020 to FY2025).
- In earlier fiscal years, Total Liabilities was $8.67 million in FY2024 (+38.0%), $6.28 million in FY2023 (+15.6%), $5.44 million in FY2022 (+3.7%) and $5.24 million in FY2021 (+416.6%).
- The fiscal Q3 2026 figure marks the highest quarterly Total Liabilities in data going back to fiscal Q3 2011.
- Compared with a year earlier, Total Liabilities has increased for 17 straight quarters, with growth averaging 16.9% over the last eight quarters.
- Across the past five years, year-over-year growth in Total Liabilities ran from 3.7% in fiscal Q4 2022 to 783.1% in fiscal Q1 2022.
- Per Business Quant data, KPEA's Total Liabilities in the three fiscal quarters before Q3 2026 was $9.73 million (Q2 2026), $9.61 million (Q1 2026) and $9.03 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,654.24 Bn | 2,170.93 Bn | 104.83 Bn | 544.07 Bn |
| 2 | Home Depot | 289.19 Bn | 282.43 Bn | 16.12 Bn | 92.77 Bn |
| 3 | Tjx Companies | 143.39 Bn | 120.94 Bn | 5.07 Bn | 26.46 Bn |
| 4 | Lowes Companies | 105.29 Bn | 98.25 Bn | 8.58 Bn | 63.32 Bn |
| 5 | Ross Stores | 75.79 Bn | 58.72 Bn | 2.12 Bn | 9.24 Bn |
| 6 | Target | 72.00 Bn | 66.59 Bn | 8.94 Bn | 43.39 Bn |
| 7 | O Reilly Automotive | 70.61 Bn | 69.69 Bn | 2.52 Bn | 19.22 Bn |
| 8 | Carvana | 66.52 Bn | 58.12 Bn | 1.38 Bn | 9.41 Bn |
| 9 | Autozone | 47.57 Bn | 46.47 Bn | 2.52 Bn | 23.70 Bn |
| 10 | Kun Peng International | 9.60 Mn | 9.52 Mn | -5,644.00 | 9.99 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 9.99 Mn |
| Mar 31, 2026 | 9.73 Mn |
| Dec 31, 2025 | 9.61 Mn |
| Sep 30, 2025 | 9.03 Mn |
| Jun 30, 2025 | 8.70 Mn |
| Mar 31, 2025 | 8.66 Mn |
| Dec 31, 2024 | 8.69 Mn |
| Sep 30, 2024 | 8.67 Mn |
| Jun 30, 2024 | 8.16 Mn |
| Mar 31, 2024 | 7.18 Mn |
| Dec 31, 2023 | 6.80 Mn |
| Sep 30, 2023 | 6.28 Mn |
| Jun 30, 2023 | 7.83 Mn |
| Mar 31, 2023 | 6.32 Mn |
| Dec 31, 2022 | 5.98 Mn |
| Sep 30, 2022 | 5.44 Mn |
| Jun 30, 2022 | 4.62 Mn |
| Mar 31, 2022 | 5.04 Mn |
| Dec 31, 2021 | 5.35 Mn |
| Sep 30, 2021 | 5.24 Mn |
API Access
Kun Peng International 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=KPEA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "KPEA", "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=KPEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();