Wayfair (W) Exchange Rate Effect (2013 - 2026)
Wayfair (W) recorded Exchange Rate Effect of $1 million in Q2 2026, compared with -$19 million a year earlier and down 75.0% from the prior quarter.
Wayfair (W) Exchange Rate Effect (2013 - 2026) Analysis & Trends
On a TTM basis, Wayfair's Exchange Rate Effect came in at $3 million as of Jun 30, 2026; for FY2025, it was -$30 million.
- Across earlier years, Exchange Rate Effect came in at $8 million in FY2024 (+300.0%), $2 million in FY2023 (+100.0%), $1 million in FY2022 and -$16 million in FY2021.
- Quarterly Exchange Rate Effect has ranged from -$19 million in Q2 2025 to $14 million in Q4 2024 over the past five years.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | FX Effect (Qtr) |
|---|---|---|---|---|---|
| 1 | Amazon Com | 2,653.16 Bn | 2,653.16 Bn | - | 72.00 Mn |
| 2 | Home Depot | 338.76 Bn | 332.00 Bn | 16.12 Bn | -16.00 Mn |
| 3 | Tjx Companies | 155.97 Bn | 133.51 Bn | 5.07 Bn | -26.00 Mn |
| 4 | Lowes Companies | 121.83 Bn | 114.80 Bn | 8.58 Bn | - |
| 5 | O Reilly Automotive | 74.90 Bn | 74.90 Bn | 2.68 Bn | -244,000.00 |
| 6 | Ross Stores | 73.46 Bn | 56.38 Bn | 2.12 Bn | - |
| 7 | Target | 72.26 Bn | 66.85 Bn | 8.94 Bn | - |
| 8 | Autozone | 53.81 Bn | 52.66 Bn | 3.52 Bn | 11.91 Mn |
| 9 | Carvana | 51.56 Bn | 41.15 Bn | 1.52 Bn | - |
| 10 | Wayfair | 14.96 Bn | 9.98 Bn | 1.05 Bn | 1.00 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.00 Mn |
| Mar 31, 2026 | 4.00 Mn |
| Dec 31, 2025 | -2.00 Mn |
| Jun 30, 2025 | -19.00 Mn |
| Mar 31, 2025 | -9.00 Mn |
| Dec 31, 2024 | 14.00 Mn |
| Sep 30, 2024 | -6.00 Mn |
| Jun 30, 2024 | 1.00 Mn |
| Mar 31, 2024 | -1.00 Mn |
| Dec 31, 2023 | -1.00 Mn |
| Mar 31, 2023 | 3.00 Mn |
| Dec 31, 2022 | 9.00 Mn |
| Sep 30, 2022 | -1.00 Mn |
| Jun 30, 2022 | -3.00 Mn |
| Mar 31, 2022 | -4.00 Mn |
| Dec 31, 2021 | -9.00 Mn |
| Jun 30, 2021 | 1.00 Mn |
| Mar 31, 2021 | -8.00 Mn |
| Dec 31, 2020 | 5.54 Mn |
| Sep 30, 2020 | 3.55 Mn |
Wayfair 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=W&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "exchange-rate-effect", "ticker": "W", "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=W&period=max&api_key=YOUR_API_KEY");
const data = await res.json();