Check Point Software Technologies (CHKP) Price to Earnings (2009 - 2026)
Check Point Software Technologies' Price to Earnings came in at 13.24 for the quarter ended Jun 30, 2026, down 52.6% from 27.94 a year earlier and down 7.2% from the prior quarter.
Check Point Software Technologies (CHKP) Price to Earnings (2009 - 2026) Analysis & Trends
For the year ended Dec 31, 2025, Check Point Software Technologies' Price to Earnings was 18.54, down 22.5% from the prior year.
- Going back by year, Price to Earnings was 23.92 in the year ended Dec 31, 2024 (+16.5%), 20.53 in the year ended Dec 31, 2023 (+7.4%), 19.12 in the year ended Dec 31, 2022 (+3.6%) and 18.45 in the year ended Dec 31, 2021 (-14.3%).
- The figure for the quarter ended Jun 30, 2026 represents the lowest quarterly Price to Earnings in data going back to the quarter ended Mar 31, 2009.
- Year-over-year, Price to Earnings has declined for four consecutive quarters, with an average decline of 3.5% over the last eight quarters.
- The fastest year-over-year change in Price to Earnings over five years came in the quarter ended Sep 30, 2024 (growth of 39.1%), and the weakest in the quarter ended Jun 30, 2026 (a decline of 52.6%).
- Business Quant data shows CHKP's Price to Earnings at 14.26 (quarter ended Mar 31, 2026), 18.54 (quarter ended Dec 31, 2025) and 22.20 (quarter ended Sep 30, 2025) in the three quarters before the quarter ended Jun 30, 2026.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 328.64 Bn | 313.71 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 276.50 Bn | 256.94 Bn | 1.10 Bn |
| 3 | Fortinet | 132.74 Bn | 118.67 Bn | 1.64 Bn |
| 4 | Snowflake | 120.19 Bn | 107.50 Bn | 1.04 Bn |
| 5 | Datadog | 99.51 Bn | 81.15 Bn | 881.34 Mn |
| 6 | Okta | 35.35 Bn | 25.44 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 33.58 Bn | 28.10 Bn | 546.45 Mn |
| 8 | Zscaler | 32.06 Bn | 18.18 Bn | - |
| 9 | MongoDB | 28.84 Bn | 19.30 Bn | 569.77 Mn |
| 10 | Check Point Software Technologies | 13.76 Bn | -2.25 Bn | 574.10 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 13.24 |
| Mar 31, 2026 | 14.26 |
| Dec 31, 2025 | 18.54 |
| Sep 30, 2025 | 22.20 |
| Jun 30, 2025 | 27.94 |
| Mar 31, 2025 | 28.97 |
| Dec 31, 2024 | 23.92 |
| Sep 30, 2024 | 26.00 |
| Jun 30, 2024 | 22.30 |
| Mar 31, 2024 | 22.04 |
| Dec 31, 2023 | 20.53 |
| Sep 30, 2023 | 18.69 |
| Jun 30, 2023 | 18.06 |
| Mar 31, 2023 | 19.34 |
| Dec 31, 2022 | 19.12 |
| Sep 30, 2022 | 18.38 |
| Jun 30, 2022 | 19.90 |
| Mar 31, 2022 | 22.25 |
| Dec 31, 2021 | 18.45 |
| Sep 30, 2021 | 18.75 |
Check Point Software Technologies Price to Earnings 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=price-to-earnings&ticker=CHKP&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "price-to-earnings", "ticker": "CHKP", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=price-to-earnings&ticker=CHKP&period=max&api_key=YOUR_API_KEY");
const data = await res.json();