G Willi Food International (WILCF) Exchange Rate Effect (2011 - 2026)
G Willi Food International (WILCF) posted Exchange Rate Effect of $46.33 million for the quarter ended Jun 30, 2026, up 46.8% from $31.56 million a year earlier.
G Willi Food International (WILCF) Exchange Rate Effect (2011 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Exchange Rate Effect at G Willi Food International was $15.19 million, up 313.5% year-over-year; for the year ended Dec 31, 2025, it was $519,000, up 222.4% from the prior year.
- In prior years, G Willi Food International's Exchange Rate Effect was $161,000 in the year ended Dec 31, 2024 (-13.0%), $185,000 in the year ended Dec 31, 2023, -$2.86 million in the year ended Dec 31, 2022 and $1.4 million in the year ended Dec 31, 2021.
- The figure for the quarter ended Jun 30, 2026 stands as the highest quarterly Exchange Rate Effect since the quarter ended Jun 30, 2021.
- On a year-over-year basis, Exchange Rate Effect increased in two of the last five quarters, with an average decline of 19.9%.
- The strongest year-over-year quarter for Exchange Rate Effect in the past five years was the quarter ended Jun 30, 2026, with growth of 46.8%; the weakest was the quarter ended Jun 30, 2022, with a decline of 98.7%.
- According to Business Quant data, Exchange Rate Effect for the three prior quarters was $22,000 (quarter ended Mar 31, 2026), $148,000 (quarter ended Dec 31, 2025) and -$31.31 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | FX Effect (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 862.64 Bn | 825.34 Bn | 49.13 Bn | 398.00 Mn |
| 2 | Costco Wholesale | 409.33 Bn | 338.62 Bn | 9.01 Bn | -16.00 Mn |
| 3 | Sysco | 37.65 Bn | 31.90 Bn | 4.13 Bn | -9.00 Mn |
| 4 | Kroger | 35.26 Bn | 21.42 Bn | 7.86 Bn | - |
| 5 | Dollar General | 27.43 Bn | 22.11 Bn | 3.68 Bn | - |
| 6 | Caseys General Stores | 22.41 Bn | 20.40 Bn | 1.24 Bn | - |
| 7 | Dollar Tree | 21.77 Bn | 18.40 Bn | 2.10 Bn | -600,000.00 |
| 8 | US Foods Holding | 20.27 Bn | 20.06 Bn | 1.92 Bn | - |
| 9 | Tractor Supply | 16.74 Bn | 15.90 Bn | 1.68 Bn | - |
| 10 | G Willi Food International | 359.40 Mn | 193.80 Mn | 18.94 Mn | 46.33 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 46.33 Mn |
| Mar 31, 2026 | 22,000.00 |
| Dec 31, 2025 | 148,000.00 |
| Sep 30, 2025 | -31.31 Mn |
| Jun 30, 2025 | 31.56 Mn |
| Mar 31, 2025 | 113,000.00 |
| Dec 31, 2024 | 654,000.00 |
| Sep 30, 2024 | -28.66 Mn |
| Jun 30, 2024 | 28.05 Mn |
| Mar 31, 2024 | 114,000.00 |
| Dec 31, 2023 | 15,000.00 |
| Sep 30, 2023 | 298,000.00 |
| Jun 30, 2023 | 59,000.00 |
| Mar 31, 2023 | -187,000.00 |
| Dec 31, 2022 | -5.65 Mn |
| Sep 30, 2022 | 420,000.00 |
| Jun 30, 2022 | 979,000.00 |
| Mar 31, 2022 | 1.39 Mn |
| Dec 31, 2021 | -60.41 Mn |
| Sep 30, 2021 | -11.20 Mn |
G Willi Food International 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=WILCF&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "exchange-rate-effect", "ticker": "WILCF", "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=WILCF&period=max&api_key=YOUR_API_KEY");
const data = await res.json();