Daily nominal effective exchange rate of the euro
The nominal effective exchange rate (NEER) of the euro is a weighted average of nominal bilateral rates between the euro and a basket of foreign currencies. It is an indicator of the external values of the euro vis-à-vis the currencies of selected euro area’s trading partners.
If this index rate goes up, more foreign currency can be obtained, on average, for €1. It therefore becomes more expensive, on average, for those who want to exchange foreign currency for euro. Likewise, if this index rate goes down, less foreign currency can be obtained, on average, for €1 and, in turn, it becomes less expensive to exchange foreign currency into euro.
The nominal effective exchange rates of the euro are calculated by the European Central Bank (ECB).
They are based on weighted averages of bilateral euro exchange rates against 40 trading partners of the euro area.
The weights capture third-market effects and are based on trade in manufactured goods and services with the euro area’s trading partners in the periods 1995-97, 1998-2000, 2001-03, 2004-06, 2007-09, 2010-12, 2013-15, 2016-18, 2019-21 and 2022-24 with the indices being chain-linked at the end of each three-year period.
1 January 2026: updated trade weights data underlying the EERs and HCIs
Daily nominal effective exchange rate of the euro
Related information
Two additional sets of daily nominal indices, considering 12 and 17 trading partners are also available in the ECB Data Portal.
Weights of trading partner countries in the EER-40 indices based on different reference periods
| Euro area trading partner | 1995-1997 |
1998-2000 |
2001-2003 |
2004-2006 |
2007-2009 |
2010-2012 |
2013-2015 |
2016-2018 |
2019-2021 |
2022-2024 |
|---|---|---|---|---|---|---|---|---|---|---|
|
Algeria |
0.4 | 0.3 | 0.4 | 0.3 | 0.4 | 0.4 | 0.4 | 0.3 | 0.2 | 0.2 |
|
Argentina |
0.6 |
0.5 | 0.3 | 0.3 | 0.4 | 0.4 | 0.4 | 0.3 | 0.2 |
0.2 |
| Australia | 0.8 | 0.7 | 0.7 |
0.8 | 0.8 | 0.9 | 0.8 | 0.8 | 0.8 |
0.8 |
| Brazil | 1.3 | 1.2 |
1.1 |
1.2 | 1.4 | 1.6 | 1.3 | 1.1 | 1.0 | 1.1 |
| Canada | 1.5 | 1.6 | 1.6 | 1.6 | 1.5 | 1.4 |
1.4 | 1.4 | 1.4 | 1.5 |
| Chile | 0.3 |
0.3 | 0.3 | 0.4 | 0.4 | 0.4 | 0.3 | 0.3 | 0.3 | 0.2 |
| China | 3.4 | 4.0 | 5.7 | 8.3 | 10.9 | 13.2 |
13.9 |
13.9 |
15.8 | 15.4 |
| Colombia | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 | 0.2 |
| Czech Republic | 1.9 | 2.1 | 2.5 |
3.0 | 3.4 | 3.4 | 3.3 | 3.6 | 3.5 |
3.6 |
| Denmark | 2.6 | 2.3 | 2.4 | 2.4 |
2.3 | 2.0 |
1.9 | 1.9 |
1.9 | 2.0 |
| Hong Kong | 3.0 | 3.1 | 3.2 | 2.9 | 2.5 |
2.3 | 2.2 | 2.1 | 2.0 |
1.7 |
| Hungary | 1.3 | 1.8 | 2.0 | 2.3 | 2.3 | 2.0 | 2.1 | 2.2 | 2.3 |
2.2 |
| Iceland | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 |
| India | 1.1 | 1.2 | 1.3 | 1.8 | 2.3 | 2.6 | 2.6 | 2.8 |
3.1 |
3.4 |
| Indonesia | 0.8 | 0.6 | 0.6 | 0.5 | 0.5 | 0.6 | 0.6 | 0.6 | 0.5 | 0.5 |
| Israel | 1.0 |
1.0 | 0.9 | 0.8 | 0.7 | 0.8 | 0.8 | 0.9 | 1.0 | 1.1 |
| Japan | 8.2 | 7.5 | 6.5 | 5.8 | 5.0 | 4.6 | 3.8 | 3.8 | 3.7 | 3.1 |
|
Malaysia |
1.1 | 1.0 | 1.0 | 1.0 | 1.0 |
1.0 |
0.9 | 0.9 |
0.8 |
0.8 |
| Mexico | 0.8 | 1.1 | 1.2 | 1.1 | 1.0 | 1.1 | 1.2 | 1.3 | 1.3 | 1.4 |
| Morocco | 0.5 | 0.6 | 0.6 | 0.6 | 0.7 | 0.6 | 0.6 |
0.7 | 0.7 | 0.8 |
| New Zealand | 0.2 | 0.1 | 0.2 | 0.2 | 0.1 | 0.1 | 0.2 | 0.2 |
0.1 | 0.1 |
| Norway | 1.4 | 1.3 | 1.2 | 1.3 | 1.4 | 1.2 | 1.1 | 1.0 | 0.9 | 1.0 |
| Peru | 0.1 | 0.1 | 0.1 | 0.1 | 0.1 | 0.2 | 0.1 |
0.1 |
0.1 |
0.1 |
| Philippines | 0.4 | 0.4 | 0.4 | 0.4 | 0.3 | 0.3 | 0.4 | 0.4 | 0.4 | 0.4 |
| Poland | 2.1 | 2.4 | 2.8 | 3.5 | 4.4 | 4.4 | 4.6 | 5.0 | 5.6 | 5.9 |
| Romania | 0.6 | 0.6 |
0.9 | 1.2 | 1.5 |
1.5 | 1.7 |
1.9 |
1.9 |
1.9 |
| Russia | 2.3 | 1.8 | 2.1 |
2.7 |
3.2 |
3.3 | 3.0 |
2.5 | 2.3 | 1.1 |
| Saudi Arabia | 0.5 | 0.4 | 0.5 | 0.6 | 0.7 | 0.7 | 0.8 | 0.8 | 0.6 |
0.8 |
| Singapore | 2.0 | 1.8 | 1.9 |
1.4 |
1.7 | 1.9 |
2.0 |
2.1 |
2.2 |
2.4 |
| South Africa | 0.9 | 0.9 | 0.9 | 1.0 | 0.9 | 0.9 | 0.8 | 0.7 | 0.7 | 0.6 |
| South Korea | 2.4 | 2.2 | 2.3 | 2.7 | 2.7 | 2.6 |
2.5 |
2.5 |
2.4 | 2.4 |
| Sweden | 4.2 | 4.0 | 3.6 | 3.7 | 3.5 | 3.3 | 3.1 |
3.1 |
3.0 | 3.0 |
| Switzerland | 8.0 | 7.1 |
6.9 | 6.4 | 6.4 | 6.7 |
6.6 |
6.2 | 6.1 |
6.0 |
| Taiwan | 1.8 | 1.9 | 1.7 | 1.5 | 1.3 | 1.3 | 1.2 | 1.2 | 1.3 | 1.4 |
| Thailand | 1.1 | 0.9 | 0.9 | 0.9 | 1.0 | 1.0 | 1.0 | 1.0 | 0.9 | 0.9 |
| Turkey | 2.0 | 2.1 | 2.1 | 2.7 |
2.7 |
2.7 | 2.8 |
2.7 |
2.6 |
3.0 |
| Ukraine | 0.4 | 0.4 | 0.4 | 0.6 | 0.7 | 0.6 | 0.4 | 0.4 | 0.5 |
0.4 |
| United Arab Emirates | 0.5 | 0.5 | 0.6 | 0.8 | 0.9 | 1.0 | 1.1 | 1.2 | 1.0 | 1.2 |
| United Kingdom | 18.7 | 18.4 | 17.7 | 16.2 | 13.5 |
12.1 | 12.3 | 11.9 | 10.5 |
9.7 |
| United States | 19.1 | 21.5 |
20.2 |
16.7 |
15.2 |
14.6 | 15.5 |
15.9 | 16.1 |
17.4 |
| Total | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 | 100.0 |
- The ECB’s enhanced effective exchange rates and harmonised competitiveness indicators, by Martin Schmitz, Andreas Dietrich and Rémy Brisson (ECB Statistics Paper No 49, June 2024)
- The ECB’s enhanced effective exchange rate measures (ECB Economic Bulletin, Issue 6/2020)
- Revised trade weights for the effective exchange rates of the euro reflect the increasing importance of emerging market economies (ECB Economic Bulletin, Issue 6/2015 – Box 5)
- Revisiting the effective exchange rates of the Euro, by Martin Schmitz, Maarten De Clercq, Michael Fidora, Bernadette Lauro and Cristina Pinheiro (ECB Occasional Paper No. 134, June 2012)
- The effective exchange rates of the euro - revised trade weights in the light of global economic integration (ECB Monthly Bulletin, March 2012, pp. 17-21)
- The effective exchange rates of the euro following the recent euro area and EU enlargements (ECB Monthly Bulletin, March 2007, pp. 77-79)
- The update of the euro effective exchange rates (ECB, September 2004)
- The effective exchange rates of the euro, by Luca Buldorini, Stelios Makrydakis and Christian Thimann (ECB Occasional Paper No.2, February 2002)