Village Super Market (VLGEA) Total Liabilities (2011 - 2026)
Village Super Market's Total Liabilities came in at $507.58 million for fiscal Q4 2026 (quarter ended Jul 25, 2026), down 0.8% from $511.75 million a year earlier but up 2.8% from the prior quarter.
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Analysis
Village Super Market (VLGEA) Total Liabilities (2011 - 2026) Analysis & Trends
Going back to fiscal Q4 2011, Village Super Market's Total Liabilities data covers 60 quarters.
- Total Liabilities has declined in each of the last three fiscal years, with a five-year compound annual growth rate of -1.5% (FY2021 to FY2026).
- Going back by fiscal year, Total Liabilities was $511.75 million in FY2025 (-4.2%), $534.11 million in FY2024 (-4.2%), $557.54 million in FY2023 (+0.9%) and $552.34 million in FY2022 (+0.9%).
- The five-year range for quarterly Total Liabilities is $493.54 million (fiscal Q3 2026) to $568.15 million (fiscal Q1 2023).
- Year-over-year, Total Liabilities has declined for 12 consecutive quarters, with an average decline of 3.6% over the last eight quarters.
- The fastest year-over-year change in Total Liabilities over five years came in fiscal Q1 2023 (growth of 5.0%), and the weakest in fiscal Q1 2026 (a decline of 5.6%).
- Business Quant data shows VLGEA's Total Liabilities at $493.54 million (Q3 2026), $510.58 million (Q2 2026) and $503.19 million (Q1 2026) in the three fiscal quarters before Q4 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 961.60 Bn | 918.03 Bn | 49.13 Bn | 189.41 Bn |
| 2 | Costco Wholesale | 451.41 Bn | 374.69 Bn | 12.19 Bn | 53.24 Bn |
| 3 | Kroger | 41.07 Bn | 27.22 Bn | 7.86 Bn | 43.65 Bn |
| 4 | Sysco | 40.11 Bn | 34.36 Bn | 4.13 Bn | 25.73 Bn |
| 5 | Dollar General | 30.55 Bn | 25.23 Bn | 3.68 Bn | 22.88 Bn |
| 6 | Caseys General Stores | 26.34 Bn | 24.34 Bn | 1.24 Bn | 5.03 Bn |
| 7 | Dollar Tree | 24.96 Bn | 21.58 Bn | 2.10 Bn | 10.60 Bn |
| 8 | US Foods Holding | 22.77 Bn | 22.57 Bn | 1.92 Bn | 10.06 Bn |
| 9 | Tractor Supply | 18.16 Bn | 17.32 Bn | 1.68 Bn | 9.53 Bn |
| 10 | Village Super Market | 654.29 Mn | 116.98 Mn | - | 507.58 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 25, 2026 | 507.58 Mn |
| Apr 25, 2026 | 493.54 Mn |
| Jan 24, 2026 | 510.58 Mn |
| Oct 25, 2025 | 503.19 Mn |
| Jul 26, 2025 | 511.75 Mn |
| Apr 26, 2025 | 515.89 Mn |
| Jan 25, 2025 | 530.15 Mn |
| Oct 26, 2024 | 532.88 Mn |
| Jul 27, 2024 | 534.11 Mn |
| Apr 27, 2024 | 534.00 Mn |
| Jan 27, 2024 | 541.28 Mn |
| Oct 28, 2023 | 557.48 Mn |
| Jul 29, 2023 | 557.54 Mn |
| Apr 29, 2023 | 549.01 Mn |
| Jan 28, 2023 | 557.02 Mn |
| Oct 29, 2022 | 568.15 Mn |
| Jul 30, 2022 | 552.34 Mn |
| Apr 30, 2022 | 552.20 Mn |
| Jan 29, 2022 | 542.05 Mn |
| Oct 30, 2021 | 541.06 Mn |
API Access
Village Super Market 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=VLGEA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "VLGEA", "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=VLGEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();