Liquidity Services (LQDT) Accumulated Expenses (2010 - 2026)
Liquidity Services (LQDT) posted Accumulated Expenses of $29.6 million for fiscal Q3 2026 (quarter ended Jun 30, 2026), up 16.7% from $25.36 million a year earlier and up 18.3% from the prior quarter.
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Analysis
Liquidity Services (LQDT) Accumulated Expenses (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Sep 30, 2025), Liquidity Services' Accumulated Expenses came in at $30.58 million, up 8.2% from FY2024.
- Annual Accumulated Expenses has increased for three consecutive fiscal years, with a five-year compound annual growth rate of 9.8% (FY2020 to FY2025).
- In prior fiscal years, Liquidity Services' Accumulated Expenses was $28.26 million in FY2024 (+18.7%), $23.81 million in FY2023 (+2.2%), $23.3 million in FY2022 (-10.3%) and $25.98 million in FY2021 (+35.8%).
- Quarterly Accumulated Expenses has run from a low of $17.41 million in fiscal Q1 2024 to a high of $37.95 million in fiscal Q2 2022 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last four quarters, with growth averaging 9.2% over the last eight quarters.
- The strongest year-over-year quarter for Accumulated Expenses in the past five years was fiscal Q1 2022, with growth of 105.1%; the weakest was fiscal Q1 2023, with a decline of 39.4%.
- According to Business Quant data, Accumulated Expenses for the three prior fiscal quarters was $25.03 million (Q2 2026), $23.26 million (Q1 2026) and $30.58 million (Q4 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Alphabet | 3,462.85 Bn | 3,197.75 Bn | 76.16 Bn |
| 2 | Meta Platforms | 1,559.43 Bn | 1,223.94 Bn | 51.23 Bn |
| 3 | Netflix | 262.12 Bn | 223.42 Bn | 6.80 Bn |
| 4 | Alibaba Group Holding | 253.57 Bn | 67.20 Bn | 15.16 Bn |
| 5 | Shopify | 191.77 Bn | 170.57 Bn | 1.78 Bn |
| 6 | Uber Technologies | 139.89 Bn | 110.71 Bn | 6.42 Bn |
| 7 | AppLovin | 130.31 Bn | 118.84 Bn | 1.94 Bn |
| 8 | Spotify Technology | 123.80 Bn | 80.72 Bn | 1.89 Bn |
| 9 | Booking Holdings | 120.61 Bn | 54.35 Bn | - |
| 10 | Liquidity Services | 1.36 Bn | 557.38 Mn | 63.84 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 29.60 Mn |
| Mar 31, 2026 | 25.03 Mn |
| Dec 31, 2025 | 23.26 Mn |
| Sep 30, 2025 | 30.58 Mn |
| Jun 30, 2025 | 25.36 Mn |
| Mar 31, 2025 | 23.52 Mn |
| Dec 31, 2024 | 22.76 Mn |
| Sep 30, 2024 | 28.26 Mn |
| Jun 30, 2024 | 27.80 Mn |
| Mar 31, 2024 | 23.72 Mn |
| Dec 31, 2023 | 17.41 Mn |
| Sep 30, 2023 | 23.81 Mn |
| Jun 30, 2023 | 20.54 Mn |
| Mar 31, 2023 | 24.76 Mn |
| Dec 31, 2022 | 21.63 Mn |
| Sep 30, 2022 | 23.30 Mn |
| Jun 30, 2022 | 24.80 Mn |
| Mar 31, 2022 | 37.95 Mn |
| Dec 31, 2021 | 35.71 Mn |
| Sep 30, 2021 | 25.98 Mn |
API Access
Liquidity Services 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=accumulated-expenses&ticker=LQDT&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "LQDT", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=LQDT&period=max&api_key=YOUR_API_KEY");
const data = await res.json();