Village Super Market (VLGEA) Other Accumulated Expenses (2011 - 2023)
Village Super Market (VLGEA) recorded Other Accumulated Expenses of $79.43 million in fiscal Q2 2023 (quarter ended Jan 28, 2023), up 0.4% from $79.09 million a year earlier but down 1.4% from the prior quarter.
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Analysis
Village Super Market (VLGEA) Other Accumulated Expenses (2011 - 2023) Analysis & Trends
At the end of FY2022 (ended Jul 30, 2022), Village Super Market reported Other Accumulated Expenses of $77.04 million, up 8.8% from FY2021.
- Annual Other Accumulated Expenses has a five-year compound annual growth rate of 5.3% (FY2017 to FY2022).
- Across earlier fiscal years, Other Accumulated Expenses came in at $70.79 million in FY2021 (-14.8%), $83.05 million in FY2020 (+25.6%), $66.13 million in FY2019 (+7.0%) and $61.8 million in FY2018 (+3.8%).
- Quarterly Other Accumulated Expenses has ranged from $56.86 million in fiscal Q3 2018 to $83.05 million in fiscal Q4 2020 over the past five years.
- On a year-over-year basis, Other Accumulated Expenses has increased for three consecutive quarters, with an average decline of 0.1% over the last eight quarters.
- Peak year-over-year performance for Other Accumulated Expenses in the last five years was growth of 25.6% in fiscal Q4 2020, against a decline of 14.8% in fiscal Q4 2021 at the low end.
- Per Business Quant, the preceding three fiscal quarters came in at $80.59 million (Q1 2023), $77.04 million (Q4 2022) and $72.59 million (Q3 2022).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Walmart | 827.17 Bn | 789.87 Bn | 49.13 Bn |
| 2 | Costco Wholesale | 408.32 Bn | 337.62 Bn | 9.01 Bn |
| 3 | Sysco | 37.11 Bn | 31.36 Bn | 4.13 Bn |
| 4 | Kroger | 34.86 Bn | 21.01 Bn | 7.86 Bn |
| 5 | Dollar General | 26.24 Bn | 20.91 Bn | 3.68 Bn |
| 6 | Caseys General Stores | 22.83 Bn | 20.83 Bn | 1.24 Bn |
| 7 | Dollar Tree | 21.05 Bn | 17.67 Bn | 2.10 Bn |
| 8 | US Foods Holding | 20.97 Bn | 20.76 Bn | 1.92 Bn |
| 9 | Tractor Supply | 16.22 Bn | 15.39 Bn | 1.68 Bn |
| 10 | Village Super Market | 663.46 Mn | 146.29 Mn | - |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jan 28, 2023 | 79.43 Mn |
| Oct 29, 2022 | 80.59 Mn |
| Jul 30, 2022 | 77.04 Mn |
| Apr 30, 2022 | 72.59 Mn |
| Jan 29, 2022 | 79.09 Mn |
| Oct 30, 2021 | 76.96 Mn |
| Jul 31, 2021 | 70.79 Mn |
| Apr 24, 2021 | 75.63 Mn |
| Jan 23, 2021 | 81.08 Mn |
| Oct 24, 2020 | 76.92 Mn |
| Jul 25, 2020 | 83.05 Mn |
| Apr 25, 2020 | 71.21 Mn |
| Jan 25, 2020 | 72.54 Mn |
| Oct 26, 2019 | 64.58 Mn |
| Jul 27, 2019 | 66.13 Mn |
| Apr 27, 2019 | 59.67 Mn |
| Jan 26, 2019 | 62.46 Mn |
| Oct 27, 2018 | 57.61 Mn |
| Jul 28, 2018 | 61.80 Mn |
| Apr 28, 2018 | 56.86 Mn |
API Access
Village Super Market Other Accumulated Expenses 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=other-accumulated-expenses&ticker=VLGEA&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "other-accumulated-expenses", "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=other-accumulated-expenses&ticker=VLGEA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();