Landstar System (LSTR) Accumulated Expenses (2010 - 2026)
Landstar System's (LSTR) quarterly Accumulated Expenses came in at $59.0 million in Q2 2026, up 60.39% year-over-year from $36.8 million in Q2 2025, and up 3.92% quarter-over-quarter from $56.8 million in Q1 2026.
Landstar System (LSTR) Accumulated Expenses (2010 - 2026) Analysis & Trends
Landstar System has disclosed Accumulated Expenses across 17 years of filings, most recently posting $59.0 million for Q2 2026.
- In Q2 2026, Accumulated Expenses rose 60.39% year-over-year to $59.0 million; the TTM figure through Jun 2026 stood at $59.0 million (up 60.39% YoY), while the FY2025 annual figure was $87.3 million, up 115.6% from the prior year.
- Accumulated Expenses came in at $59.0 million for Q2 2026 at Landstar System, up from $56.8 million in the prior quarter.
- In the past five years, Accumulated Expenses ranged from a high of $87.3 million in Q4 2025 to a low of $36.8 million in Q2 2025.
- Average Accumulated Expenses over 5 years is $49.3 million, with a median of $45.3 million recorded in 2023.
- Year-over-year, Accumulated Expenses declined 21.7% in 2023 and soared 115.6% in 2025.
- Over 5 years, Accumulated Expenses stood at $50.8 million in 2022, then retreated by 17.73% to $41.8 million in 2023, then retreated by 3.14% to $40.5 million in 2024, then soared by 115.6% to $87.3 million in 2025, then plunged by 32.43% to $59.0 million in 2026.
- Per Business Quant data, the three most recent Accumulated Expenses figures were $59.0 million in Q2 2026, $56.8 million in Q1 2026, and $87.3 million in Q4 2025.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Copart | 27.11 Bn | 23.77 Bn | 732.88 Mn |
| 2 | Expeditors International Of Washington | 24.83 Bn | 23.80 Bn | 1.09 Bn |
| 3 | C. H. Robinson Worldwide | 17.92 Bn | 17.76 Bn | 1.11 Bn |
| 4 | Rb Global | 15.40 Bn | 14.87 Bn | 935.50 Mn |
| 5 | Ryder System | 9.14 Bn | 9.14 Bn | 1.45 Bn |
| 6 | Landstar System | 5.78 Bn | 5.43 Bn | 308.86 Mn |
| 7 | GXO Logistics | 5.27 Bn | 4.53 Bn | 508.00 Mn |
| 8 | Rxo | 3.34 Bn | 3.32 Bn | 302.00 Mn |
| 9 | Hub | 1.98 Bn | 1.89 Bn | 250.84 Mn |
| 10 | Cryoport | 862.04 Mn | 465.34 Mn | 22.82 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 27, 2026 | 59.02 Mn |
| Mar 28, 2026 | 56.79 Mn |
| Dec 27, 2025 | 87.34 Mn |
| Sep 27, 2025 | 43.89 Mn |
| Jun 28, 2025 | 36.80 Mn |
| Mar 29, 2025 | 37.64 Mn |
| Dec 28, 2024 | 40.51 Mn |
| Sep 28, 2024 | 43.37 Mn |
| Jun 29, 2024 | 42.68 Mn |
| Mar 30, 2024 | 40.68 Mn |
| Dec 30, 2023 | 41.83 Mn |
| Sep 30, 2023 | 45.52 Mn |
| Jul 1, 2023 | 45.16 Mn |
| Apr 1, 2023 | 50.06 Mn |
| Dec 31, 2022 | 50.84 Mn |
| Sep 24, 2022 | 58.13 Mn |
| Jun 25, 2022 | 53.97 Mn |
| Mar 26, 2022 | 52.64 Mn |
| Dec 25, 2021 | 46.90 Mn |
| Sep 25, 2021 | 64.96 Mn |
Landstar System 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=LSTR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "LSTR", "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=LSTR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();