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.
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Analysis
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 Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | FX Effect (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,173.87 Bn | 3,931.39 Bn | 73.85 Bn | -31.00 Mn |
| 2 | Meta Platforms | 1,849.67 Bn | 1,552.19 Bn | 49.47 Bn | -7.00 Mn |
| 3 | Netflix | 279.23 Bn | 239.43 Bn | 6.52 Bn | -19.63 Mn |
| 4 | Alibaba Group Holding | 245.86 Bn | 63.73 Bn | 15.11 Bn | -224.00 Mn |
| 5 | Shopify | 196.08 Bn | 173.27 Bn | 1.71 Bn | -4.00 Mn |
| 6 | Uber Technologies | 138.90 Bn | 110.88 Bn | 6.38 Bn | 54.00 Mn |
| 7 | Booking Holdings | 119.48 Bn | 52.53 Bn | - | -111.00 Mn |
| 8 | PDD Holdings | 107.30 Bn | -144.64 Bn | 9.45 Bn | 182.40 Mn |
| 9 | Spotify Technology | 97.33 Bn | 54.56 Bn | 1.86 Bn | 26.73 Mn |
| 10 | NetEase | 74.83 Bn | 32.10 Bn | 3.13 Bn | -27.67 Mn |
Historic Data
Download Data
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 |
API Access
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_KEYimport 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();