Formula Systems (1985) (FORTY) Cash & Equivalents (2009 - 2026)
Formula Systems (1985)'s Cash & Equivalents came in at $863.79 million for Q2 2026, up 119.7% from $393.19 million a year earlier but down 26.9% from the prior quarter.
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Analysis
Formula Systems (1985) (FORTY) Cash & Equivalents (2009 - 2026) Analysis & Trends
At the end of FY2025, Formula Systems (1985)'s Cash & Equivalents was $1.28 billion, up 152.1% from FY2024.
- Cash & Equivalents carries a five-year compound annual growth rate of 20.6% (FY2020 to FY2025).
- Going back by year, Cash & Equivalents was $507.8 million in FY2024 (-6.7%), $544.34 million in FY2023 (unchanged), $544.34 million in FY2022 (+8.5%) and $501.65 million in FY2021 (unchanged).
- The five-year range for quarterly Cash & Equivalents is $985,000 (Q3 2025) to $1.28 billion (Q4 2025).
- Year-over-year, Cash & Equivalents has increased for three consecutive quarters, with growth averaging 45.3% over the last eight quarters.
- The fastest year-over-year change in Cash & Equivalents over five years came in Q1 2026 (growth of 155.9%), and the weakest in Q3 2025 (a decline of 99.8%).
- Business Quant data shows FORTY's Cash & Equivalents at $1.18 billion (Q1 2026), $1.28 billion (Q4 2025) and $985,000 (Q3 2025) in the three quarters before Q2 2026.
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Cash & Equiv. (Qtr) |
|---|---|---|---|---|---|
| 1 | Infosys | 50.59 Bn | 37.09 Bn | 1.60 Bn | 2.29 Bn |
| 2 | Cognizant Technology Solutions | 32.87 Bn | 26.04 Bn | 1.83 Bn | 1.04 Bn |
| 3 | Wipro | 22.10 Bn | 17.25 Bn | 745.00 Mn | 992.00 Mn |
| 4 | Cdw | 20.94 Bn | 18.92 Bn | 1.32 Bn | 361.80 Mn |
| 5 | Td Synnex | 19.62 Bn | 13.78 Bn | 1.43 Bn | 749.30 Mn |
| 6 | Cgi | 18.25 Bn | 16.05 Bn | - | 440.31 Mn |
| 7 | Arrow Electronics | 10.72 Bn | 9.67 Bn | 1.13 Bn | 244.63 Mn |
| 8 | Avnet | 7.23 Bn | 6.41 Bn | 865.03 Mn | 155.40 Mn |
| 9 | EPAM Systems | 7.08 Bn | 2.72 Bn | 429.57 Mn | 789.40 Mn |
| 10 | Formula Systems (1985) | 1.79 Bn | -1.56 Bn | 158.43 Mn | 863.79 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 863.79 Mn |
| Mar 31, 2026 | 1.18 Bn |
| Dec 31, 2025 | 1.28 Bn |
| Sep 30, 2025 | 985,000.00 |
| Jun 30, 2025 | 393.19 Mn |
| Mar 31, 2025 | 461.81 Mn |
| Dec 31, 2024 | 507.80 Mn |
| Sep 30, 2024 | 469.71 Mn |
| Jun 30, 2024 | 408.26 Mn |
| Mar 31, 2024 | 436.79 Mn |
| Dec 31, 2023 | 451.95 Mn |
| Sep 30, 2023 | 392.30 Mn |
| Jun 30, 2023 | 386.00 Mn |
| Mar 31, 2023 | 447.89 Mn |
| Dec 31, 2022 | 544.34 Mn |
| Sep 30, 2022 | 470.46 Mn |
| Jun 30, 2022 | 412.10 Mn |
| Mar 31, 2022 | 532.82 Mn |
| Dec 31, 2021 | 485.39 Mn |
| Sep 30, 2021 | 453.28 Mn |
API Access
Formula Systems (1985) 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=FORTY&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "cash-and-equivalents", "ticker": "FORTY", "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=FORTY&period=max&api_key=YOUR_API_KEY");
const data = await res.json();