Simulations Plus (SLP) Cash & Equivalents (2010 - 2026)
Simulations Plus' Cash & Equivalents came in at $35.32 million for fiscal Q3 2026 (quarter ended May 31, 2026), up 31.1% from $26.95 million a year earlier and up 37.3% from the prior quarter.
Simulations Plus (SLP) Cash & Equivalents (2010 - 2026) Analysis & Trends
At the end of FY2025 (ended Aug 31, 2025), Simulations Plus' Cash & Equivalents was $30.85 million, up 199.2% from FY2024.
- Cash & Equivalents carries a five-year compound annual growth rate of -8.9% (FY2020 to FY2025).
- Going back by fiscal year, Cash & Equivalents was $10.31 million in FY2024 (-82.1%), $57.52 million in FY2023 (+11.6%), $51.57 million in FY2022 (+39.4%) and $36.98 million in FY2021 (-24.8%).
- The fiscal Q3 2026 figure represents the highest quarterly Cash & Equivalents since fiscal Q3 2024.
- Year-over-year, Cash & Equivalents has increased for four consecutive quarters, with growth averaging 55.0% over the last eight quarters.
- The fastest year-over-year change in Cash & Equivalents over five years came in fiscal Q1 2026 (growth of 387.9%), and the weakest in fiscal Q1 2025 (a decline of 84.5%).
- Business Quant data shows SLP's Cash & Equivalents at $25.73 million (Q2 2026), $30.19 million (Q1 2026) and $30.85 million (Q4 2025) in the three fiscal quarters before Q3 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | - |
| 2 | Veeva Systems | 44.24 Bn | 16.49 Bn | 695.95 Mn | 1.81 Bn |
| 3 | Samsara | 24.06 Bn | 20.83 Bn | 392.58 Mn | 291.39 Mn |
| 4 | Toast | 17.18 Bn | 9.85 Bn | 516.00 Mn | 1.02 Bn |
| 5 | Ptc | 15.95 Bn | 14.76 Bn | 490.47 Mn | 351.45 Mn |
| 6 | Duolingo | 13.49 Bn | 8.67 Bn | 216.74 Mn | 1.18 Bn |
| 7 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 214.40 Mn |
| 8 | Manhattan Associates | 11.90 Bn | 10.90 Bn | 168.33 Mn | 186.11 Mn |
| 9 | Costar | 11.09 Bn | 5.06 Bn | 728.00 Mn | 1.27 Bn |
| 10 | Simulations Plus | 374.00 Mn | 214.14 Mn | 15.13 Mn | 35.32 Mn |
Historic Data
| Date | Value |
|---|---|
| May 31, 2026 | 35.32 Mn |
| Feb 28, 2026 | 25.73 Mn |
| Nov 30, 2025 | 30.19 Mn |
| Aug 31, 2025 | 30.85 Mn |
| May 31, 2025 | 26.95 Mn |
| Feb 28, 2025 | 10.99 Mn |
| Nov 30, 2024 | 6.19 Mn |
| Aug 31, 2024 | 10.31 Mn |
| May 31, 2024 | 109.09 Mn |
| Feb 29, 2024 | 37.03 Mn |
| Nov 30, 2023 | 39.79 Mn |
| Aug 31, 2023 | 57.52 Mn |
| May 31, 2023 | 55.13 Mn |
| Feb 28, 2023 | 39.29 Mn |
| Nov 30, 2022 | 49.39 Mn |
| Aug 31, 2022 | 51.57 Mn |
| May 31, 2022 | 42.35 Mn |
| Feb 28, 2022 | 60.37 Mn |
| Nov 30, 2021 | 41.68 Mn |
| Aug 31, 2021 | 36.98 Mn |
Simulations Plus Cash & Equivalents 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=cash-and-equivalents&ticker=SLP&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "ticker": "SLP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=cash-and-equivalents&ticker=SLP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();