Telecom Argentina (TEO) Exchange Rate Effect (2013 - 2026)
Telecom Argentina (TEO) posted Exchange Rate Effect of -$8.26 billion for the quarter ended Jun 30, 2026, compared with $20.91 billion a year earlier.
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Analysis
Telecom Argentina (TEO) Exchange Rate Effect (2013 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Exchange Rate Effect at Telecom Argentina was -$40.3 billion; for the year ended Dec 31, 2025, it came in at $63.12 billion.
- Annual Exchange Rate Effect shows a five-year compound annual growth rate of 74.4% (years ended Dec 2020 to Dec 2025).
- In prior years, Telecom Argentina's Exchange Rate Effect was -$68.5 billion in the year ended Dec 31, 2024, $238.05 billion in the year ended Dec 31, 2023, -$8.05 billion in the year ended Dec 31, 2022 and -$33.46 billion in the year ended Dec 31, 2021.
- Quarterly Exchange Rate Effect has run from a low of -$103.41 billion in the quarter ended Mar 31, 2024 to a high of $235.12 billion in the quarter ended Dec 31, 2023 over five years.
- On a year-over-year basis, Exchange Rate Effect increased in two of the last five quarters, with growth averaging 112.5%.
- According to Business Quant data, Exchange Rate Effect for the three prior quarters was -$85.24 billion (quarter ended Mar 31, 2026), $27.06 billion (quarter ended Dec 31, 2025) and $26.13 billion (quarter ended Sep 30, 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | FX Effect (Qtr) |
|---|---|---|---|---|---|
| 1 | Verizon Communications | 191.08 Bn | 155.48 Bn | 27.03 Bn | - |
| 2 | T-Mobile US | 175.17 Bn | 159.92 Bn | 14.76 Bn | - |
| 3 | At&T | 167.81 Bn | 115.76 Bn | 25.82 Bn | - |
| 4 | Grupo Televisa, S.A.B | 146.22 Bn | 134.85 Bn | 318.12 Mn | - |
| 5 | Comcast | 76.40 Bn | 40.65 Bn | - | 2.00 Mn |
| 6 | Chunghwa Telecom | 35.35 Bn | 31.20 Bn | 728.80 Mn | - |
| 7 | EchoStar | 26.08 Bn | 17.22 Bn | 1.65 Bn | 259,000.00 |
| 8 | AST SpaceMobile | 23.11 Bn | 23.62 Bn | 7.95 Mn | -1.42 Mn |
| 9 | Bce | 18.79 Bn | 17.12 Bn | - | - |
| 10 | Telecom Argentina | 5.24 Bn | 5,485.56 Bn | - | -8.26 Bn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | -8.26 Bn |
| Mar 31, 2026 | -85.24 Bn |
| Dec 31, 2025 | 27.06 Bn |
| Sep 30, 2025 | 26.13 Bn |
| Jun 30, 2025 | 20.91 Bn |
| Mar 31, 2025 | -10.98 Bn |
| Dec 31, 2024 | 5.15 Bn |
| Sep 30, 2024 | 7.05 Bn |
| Jun 30, 2024 | 22.71 Bn |
| Mar 31, 2024 | -103.41 Bn |
| Dec 31, 2023 | 235.12 Bn |
| Sep 30, 2023 | 9.78 Bn |
| Jun 30, 2023 | -905.00 Mn |
| Mar 31, 2023 | -5.95 Bn |
| Dec 31, 2022 | -973.00 Mn |
| Sep 30, 2022 | -7.07 Bn |
| Jun 30, 2022 | -1.44 Bn |
| Mar 31, 2022 | -2.82 Bn |
| Dec 31, 2021 | -29.38 Bn |
| Sep 30, 2021 | -9.74 Bn |
API Access
Telecom Argentina 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=TEO&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "exchange-rate-effect", "ticker": "TEO", "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=TEO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();