NetEase (NTES) Exchange Rate Effect (2009 - 2026)
NetEase's Exchange Rate Effect came in at -$27.67 million for the quarter ended Jun 30, 2026, compared with -$4.39 million a year earlier.
NetEase (NTES) Exchange Rate Effect (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, NetEase reported Exchange Rate Effect of -$118.15 million; for the year ended Dec 31, 2025, it came in at -$54.69 million.
- Going back by year, Exchange Rate Effect was $1.47 million in the year ended Dec 31, 2024, -$28.52 million in the year ended Dec 31, 2023, $16.01 million in the year ended Dec 31, 2022 and -$8.69 million in the year ended Dec 31, 2021.
- The five-year range for quarterly Exchange Rate Effect is -$49.21 million (the quarter ended Mar 31, 2026) to $15.84 million (the quarter ended Dec 31, 2024).
- Business Quant data shows NTES's Exchange Rate Effect at -$49.21 million (quarter ended Mar 31, 2026), -$24.8 million (quarter ended Dec 31, 2025) and -$16.47 million (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) | FX Effect (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 3,624.96 Bn | 3,359.86 Bn | 76.16 Bn | 45.00 Mn |
| 2 | Meta Platforms | 1,640.16 Bn | 1,304.68 Bn | 51.23 Bn | 8.00 Mn |
| 3 | Netflix | 255.21 Bn | 216.51 Bn | 6.80 Bn | 19.00 Mn |
| 4 | Alibaba Group Holding | 219.23 Bn | 41.30 Bn | 15.16 Bn | -224.00 Mn |
| 5 | Shopify | 189.29 Bn | 174.44 Bn | 1.78 Bn | 1.00 Mn |
| 6 | Uber Technologies | 142.08 Bn | 113.28 Bn | 6.42 Bn | -34.00 Mn |
| 7 | AppLovin | 135.54 Bn | 124.07 Bn | 1.94 Bn | -428,000.00 |
| 8 | Spotify Technology | 126.14 Bn | 83.06 Bn | 1.89 Bn | 14.96 Mn |
| 9 | Booking Holdings | 119.69 Bn | 53.43 Bn | - | -5.00 Mn |
| 10 | NetEase | 78.00 Bn | 36.89 Bn | 3.13 Bn | -27.67 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -27.67 Mn |
| Mar 31, 2026 | -49.21 Mn |
| Dec 31, 2025 | -24.80 Mn |
| Sep 30, 2025 | -16.47 Mn |
| Jun 30, 2025 | -4.39 Mn |
| Mar 31, 2025 | -7.83 Mn |
| Dec 31, 2024 | 15.84 Mn |
| Sep 30, 2024 | -9.51 Mn |
| Jun 30, 2024 | 1.14 Mn |
| Mar 31, 2024 | -6.03 Mn |
| Dec 31, 2023 | -24.20 Mn |
| Sep 30, 2023 | 580,230.20 |
| Jun 30, 2023 | -6.84 Mn |
| Mar 31, 2023 | 2.27 Mn |
| Dec 31, 2022 | 7.49 Mn |
| Sep 30, 2022 | 507,317.04 |
| Jun 30, 2022 | 11.36 Mn |
| Mar 31, 2022 | -3.34 Mn |
| Dec 31, 2021 | -12.62 Mn |
| Sep 30, 2021 | 2.23 Mn |
NetEase 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=NTES&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "exchange-rate-effect", "ticker": "NTES", "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=NTES&period=max&api_key=YOUR_API_KEY");
const data = await res.json();