SRX Global (SRXH) Total Liabilities (2009 - 2026)
SRX Global (SRXH) posted Total Liabilities of $23.53 million for fiscal Q4 2025 (quarter ended Dec 31, 2025), down 70.4% from $79.47 million a year earlier but up 194.3% from the prior quarter.
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Analysis
SRX Global (SRXH) Total Liabilities (2009 - 2026) Analysis & Trends
Since fiscal Q4 2011, SRX Global has reported Total Liabilities for 55 quarters.
- Annual Total Liabilities shows a five-year compound annual growth rate of -21.6% (FY2020 to FY2025).
- In prior fiscal years, SRX Global's Total Liabilities was $79.47 million in FY2024 (+476.3%), $13.79 million in FY2023 (-19.6%), $17.15 million in FY2022 (+2.2%) and $16.79 million in FY2021 (-78.8%).
- Quarterly Total Liabilities has run from a low of $8 million in fiscal Q3 2025 to a high of $88.88 million in fiscal Q3 2024 over five years.
- On a year-over-year basis, Total Liabilities increased in five of the last eight quarters, with growth averaging 128.9%.
- The strongest year-over-year quarter for Total Liabilities in the past five years was fiscal Q4 2024, with growth of 476.3%; the weakest was fiscal Q3 2025, with a decline of 91.0%.
- According to Business Quant data, Total Liabilities for the three prior fiscal quarters was $8 million (Q3 2025), $79.87 million (Q2 2025) and $74.02 million (Q1 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Unilever | 144.95 Bn | 98.82 Bn | - | 69.38 Bn |
| 2 | Mondelez International | 84.23 Bn | 77.29 Bn | 3.92 Bn | 45.12 Bn |
| 3 | Hershey | 34.99 Bn | 31.72 Bn | 1.51 Bn | 9.02 Bn |
| 4 | Kraft Heinz | 28.72 Bn | 16.47 Bn | 1.99 Bn | 36.15 Bn |
| 5 | General Mills | 18.50 Bn | 16.16 Bn | 1.49 Bn | 22.81 Bn |
| 6 | J M Smucker | 14.27 Bn | 14.05 Bn | 979.60 Mn | 10.45 Bn |
| 7 | Mccormick | 12.58 Bn | 12.23 Bn | 794.90 Mn | 9.06 Bn |
| 8 | Hormel Foods | 12.22 Bn | 8.90 Bn | 471.52 Mn | 5.43 Bn |
| 9 | Chewy | 9.17 Bn | 6.46 Bn | 1.01 Bn | 3.37 Bn |
| 10 | SRX Global | 10.85 Mn | -69.75 Mn | 904,000.00 | 2.37 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 2.37 Mn |
| Mar 31, 2026 | 25.08 Mn |
| Dec 31, 2025 | 23.53 Mn |
| Sep 30, 2025 | 8.00 Mn |
| Jun 30, 2025 | 79.87 Mn |
| Mar 31, 2025 | 74.02 Mn |
| Dec 31, 2024 | 79.47 Mn |
| Sep 30, 2024 | 88.88 Mn |
| Jun 30, 2024 | 34.77 Mn |
| Mar 31, 2024 | 14.35 Mn |
| Dec 31, 2023 | 13.79 Mn |
| Sep 30, 2023 | 64.83 Mn |
| Jun 30, 2023 | 14.18 Mn |
| Mar 31, 2023 | 16.24 Mn |
| Dec 31, 2022 | 17.15 Mn |
| Sep 30, 2022 | 19.33 Mn |
| Jun 30, 2022 | 18.64 Mn |
| Mar 31, 2022 | 19.82 Mn |
| Dec 31, 2021 | 16.79 Mn |
| Sep 30, 2021 | 16.13 Mn |
API Access
SRX Global 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=SRXH&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "SRXH", "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=SRXH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();