LPL Financial Holdings (LPLA) Change in Accured Expenses (2010 - 2026)
LPL Financial Holdings (LPLA) posted Change in Accured Expenses of $55.29 million for Q2 2026, down 25.7% from $74.43 million a year earlier.
LPL Financial Holdings (LPLA) Change in Accured Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Change in Accured Expenses at LPL Financial Holdings was $176.38 million, up 259.0% year-over-year; for FY2025, it came in at $161.29 million, up 336.2% from FY2024.
- In prior years, LPL Financial Holdings' Change in Accured Expenses was $36.98 million in FY2024 (+18.3%), $31.26 million in FY2023 (-38.3%), $50.66 million in FY2022 (+308.9%) and $12.39 million in FY2021.
- Quarterly Change in Accured Expenses has run from a low of -$115.13 million in Q1 2024 to a high of $143.2 million in Q3 2025 over five years.
- On a year-over-year basis, Change in Accured Expenses increased in three of the last six quarters, with growth averaging 109.5%.
- The strongest year-over-year quarter for Change in Accured Expenses in the past five years was Q3 2025, with growth of 680.9%; the weakest was Q3 2023, with a decline of 76.4%.
- According to Business Quant data, Change in Accured Expenses for the three prior quarters was -$72.59 million (Q1 2026), $50.49 million (Q4 2025) and $143.2 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Robinhood Markets | 101.35 Bn | 82.45 Bn | - | 67.00 Mn |
| 2 | Bank of New York Mellon | 98.65 Bn | 38.02 Bn | - | - |
| 3 | Cme | 94.54 Bn | 94.54 Bn | - | -70.30 Mn |
| 4 | Intercontinental Exchange | 84.23 Bn | 78.04 Bn | - | -77.00 Mn |
| 5 | Nasdaq | 50.77 Bn | 48.20 Bn | 1.50 Bn | 36.00 Mn |
| 6 | State Street | 48.31 Bn | 48.31 Bn | - | - |
| 7 | Interactive Brokers | 39.79 Bn | 33.24 Bn | - | 364.00 Mn |
| 8 | Northern Trust | 31.37 Bn | 31.37 Bn | - | -55.70 Mn |
| 9 | Cboe Global Markets | 28.34 Bn | 20.00 Bn | 731.60 Mn | 69.70 Mn |
| 10 | LPL Financial Holdings | 24.92 Bn | 20.24 Bn | - | 55.29 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 55.29 Mn |
| Mar 31, 2026 | -72.59 Mn |
| Dec 31, 2025 | 50.49 Mn |
| Sep 30, 2025 | 143.20 Mn |
| Jun 30, 2025 | 74.43 Mn |
| Mar 31, 2025 | -106.82 Mn |
| Dec 31, 2024 | 63.18 Mn |
| Sep 30, 2024 | 18.34 Mn |
| Jun 30, 2024 | 70.58 Mn |
| Mar 31, 2024 | -115.13 Mn |
| Dec 31, 2023 | 79.51 Mn |
| Sep 30, 2023 | 13.36 Mn |
| Jun 30, 2023 | 28.40 Mn |
| Mar 31, 2023 | -90.01 Mn |
| Dec 31, 2022 | -77.83 Mn |
| Sep 30, 2022 | 56.68 Mn |
| Jun 30, 2022 | 89.06 Mn |
| Mar 31, 2022 | -17.24 Mn |
| Dec 31, 2021 | 8.94 Mn |
| Sep 30, 2021 | 52.61 Mn |
LPL Financial Holdings Change in Accured 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=change-in-accured-expenses&ticker=LPLA&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-expenses", "ticker": "LPLA", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=change-in-accured-expenses&ticker=LPLA&period=max&api_key=YOUR_API_KEY");
const data = await res.json();