Fatpipe (FATN) Exchange Rate Effect (2024 - 2026)
Fatpipe's Exchange Rate Effect came in at -$130,138 for fiscal Q1 2027 (quarter ended Jun 30, 2026), compared with -$55,759 a year earlier.
Fatpipe (FATN) Exchange Rate Effect (2024 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Fatpipe reported Exchange Rate Effect of -$266,409; for FY2026 (ended Mar 31, 2026), it came in at -$192,030.
- Going back by fiscal year, Exchange Rate Effect was -$153,822 in FY2025 and $211,952 in FY2024.
- The fiscal Q1 2027 figure represents the lowest quarterly Exchange Rate Effect since fiscal Q4 2025.
- Business Quant data shows FATN's Exchange Rate Effect at -$50,729 (Q4 2026), -$12,803 (Q3 2026) and -$72,739 (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | FX Effect (Qtr) |
|---|---|---|---|---|---|
| 1 | Apple | 5,090.84 Bn | 4,836.31 Bn | 54.82 Bn | - |
| 2 | Cisco Systems | 390.99 Bn | 326.92 Bn | 11.06 Bn | 28.00 Mn |
| 3 | Arista Networks | 240.45 Bn | 189.65 Bn | 2.33 Bn | 100,000.00 |
| 4 | Dell Technologies | 219.04 Bn | 174.80 Bn | 9.83 Bn | -22.00 Mn |
| 5 | Sony | 158.27 Bn | 38.21 Bn | - | - |
| 6 | Sandisk | 129.40 Bn | 114.23 Bn | 9.38 Bn | 4.00 Mn |
| 7 | Seagate Technology Holdings | 114.31 Bn | 109.16 Bn | 2.43 Bn | - |
| 8 | Western Digital | 105.81 Bn | 95.63 Bn | 2.53 Bn | - |
| 9 | Hewlett Packard Enterprise | 63.81 Bn | 41.69 Bn | 4.93 Bn | -30.00 Mn |
| 10 | Fatpipe | 61.46 Mn | 42.67 Mn | 4.35 Mn | -8,306.00 |
Historic Data
| Date | Value |
|---|---|
| Sep 30, 2026 | -8,306.00 |
| Jun 30, 2026 | -130,138.00 |
| Mar 31, 2026 | -50,729.00 |
| Dec 31, 2025 | -12,803.00 |
| Sep 30, 2025 | -72,739.00 |
| Jun 30, 2025 | -55,759.00 |
| Mar 31, 2025 | -470,712.00 |
| Dec 31, 2024 | 304,188.00 |
| Sep 30, 2024 | 99,958.00 |
| Jun 30, 2024 | -87,256.00 |
Fatpipe Exchange Rate Effect 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=exchange-rate-effect&ticker=FATN&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "exchange-rate-effect", "ticker": "FATN", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=exchange-rate-effect&ticker=FATN&period=max&api_key=YOUR_API_KEY");
const data = await res.json();