The EUR/USD exchange rate rose to 1.1708 on September 1, 2025, up 0.21% from the previous session. Over the past month, the Euro US Dollar Exchange Rate - EUR/USD has strengthened 1.07%, and is up by 5.79% over the last 12 months. Euro US Dollar Exchange Rate - EUR/USD - values, historical data, forecasts and news - updated on September of 2025.

Tick (Bids | Asks | Trades | Settle) sample data for Forex - EURUSD Euro/United States IEURUSD timestamped in Chicago time

Prices for EURUSD Euro US Dollar including live quotes, historical charts and news. EURUSD Euro US Dollar was last updated by Trading Economics this September 2 of 2025.

Prices for Euro Area Stock Market Index (EU600) including live quotes, historical charts and news. Euro Area Stock Market Index (EU600) was last updated by Trading Economics this September 1 of 2025.

Tick (Bids | Asks | Trades | Settle) sample data for E-Micro Euro FX M6E timestamped in Chicago time

Daily bulletin time series available since 2/1/2002, for the Euro, and since 28/11/1984, for the other currencies. For the American Dollar, this data set shows administered rates until March, 1990 and free rates from then on (Resolution 1690/1990). Administered rates are those set by the Central Bank of Brazil; from March, 1992, this rate started being called Ptax rate (close). Until 30/6/2011, this rate was calculated as the average rate, weighed by volume, of all interbank operations traded on that day. Starting on 1/7/2011 (Circular 3506/2010), the Ptax rate calculation corresponds to the arithmetic average of four daily quotes provided by Central Bank of Brazil’s foreign exchange dealers; the quotes must reflect market conditions at that time. Parities of the other currencies against the American Dollar (USD) are obtained from information agencies. Currencies rates against the Brazilian currency are calculated dividing the Brazilian currency rate against the American Dollar by the parities against the American Dollar for type A currencies, and multiplying the Brazilian currency rate against the American Dollar by the parities against the American Dollar for type B currencies. Available currencies: Danish Krone (DKK) Type A Norwegian Krone (NOK) Type A Swedish Krona (SEK) Type A American Dollar (USD) Type A Australian Dollar (AUD) Type B Canadian Dollar (CAD) Type A Euro (EUR) Type B Swiss Franc (CHF) Type A Japanese Yen (JPY) Type A British Pound (GBP) Type B Unit of measure: Type A currencies: Parity (American Dollar): quantity in the currency per one unit of American Dollar (USD); Rates (Brazilian currency): quantity in the Brazilian currency per one unit of the currency Type B currencies: Parity (American Dollar): quantity in American Dollars (USD) per one unit of the currency; Rates (Brazilian currency): quantity in the Brazilian currency per one unit of the currency Example of how to calculate type A currencies rates in the Brazilian currency, considering the Real (BRL) as the domestic currency and the Canadian Dollar (CAD) as the foreign currency: CADBRL bid rate = USDBRL bid rate ÷ USDCAD offer parity CADBRL offer rate = USDBRL offer rate ÷ USDCAD bid parity Example of how to calculate type B currencies rates in the Brazilian currency, considering the Real (BRL) as the domestic currency and the Euro (EUR) as the foreign currency: EURBRL bid rate = EURUSD bid parity × USDBRL bid rate EURBRL offer rate = EURUSD offer parity × USDBRL offer rate Source: Refinitiv, except for USDBRL The Central Bank assumes no responsibility whatsoever for non-simultaneity or any lack of information, as well as for possible errors in currency parities or any other errors, except the parity of the United States dollar in relation to the Real. The institution also assumes no responsibilty for delays or the unavailability of telecommunications services, interruptions, failures or imprecisions in the providing of the services or information. The Central Bank likewise assumes no responsibility for any losses or damages consequent upon such interruptions, delays, failings or imperfections, as well as for the inadequate use of the information contained in the transaction. af829095-9d8c-4c1d-a77f-48e4d51f7a71 exchange-rates-daily-bulletins

Tick (Bids | Asks | Trades | Settle) sample data for Euro FX (Settlement) EU timestamped in Chicago time

Prices for Euro Area Stock Market Index (EU350) including live quotes, historical charts and news. Euro Area Stock Market Index (EU350) was last updated by Trading Economics this September 1 of 2025.

Prices for Euro Stoxx 50 Volatility EUR Price Index including live quotes, historical charts and news. Euro Stoxx 50 Volatility EUR Price Index was last updated by Trading Economics this September 2 of 2025.

Futures data can be ordered as full month ranges. To control costs it is possible to order Nearest to Expiry (NTE) data with overlap between expiring future and the next future in the month of expiry or with overlap over more than 1 month is needed. Of course you can also select all active expiries if required.

The data is available at tick level with millisecond resolution as well as at regular intervals of 1 Min, 5 Min and so on.

Data is priced separately for Trades (Tx) and Quotes (Qt).

Tick level Tx data consists of a millisecond timestamp and trade price Tx with an option to include the Volume field. Tick level Qt data consists of millisecond timestamp and quote Qt with a flag to indicate whether it is a Bid or an Ask and optionally the Qt size field can be added.

Regular interval data is usually supplied as one of these sets: CloseTx CloseBid, CloseAsk OpenTx, HighTx, LowTx, CloseTx OpenBid, HighBid, LowBid, CloseBid OpenAsk, HighAsk, LowAsk, CloseAsk

Additional Fields: IntervalTxVolume, CloseBidSize, CloseAskSize and some others are available if required.

Timestamps are by default in GMT but data can be in any Time Zone requested.

Pricing depends on frequency and number of fields.

100s of papers in finance and economics have been written since 1986 onwards using our data and several reputed banks and hedge funds use our data for back testing and risk management.

Prices for USDEUR US Dollar Euro including live quotes, historical charts and news. USDEUR US Dollar Euro was last updated by Trading Economics this September 2 of 2025.

Tick (Bids | Asks | Trades | Settle) sample data for Euro FX (All Sessions) EUA timestamped in Chicago time

Prices for CZKEUR Czech Republic Koruna Euro including live quotes, historical charts and news. CZKEUR Czech Republic Koruna Euro was last updated by Trading Economics this September 2 of 2025.

Tick (Bids | Asks | Trades | Settle) sample data for Euro/British Pound EB timestamped in Chicago time

Tick (Bids | Asks | Trades | Settle) sample data for Forex - EURJPY Euro/Japan IEURJPY timestamped in Chicago time

Europäische Unions Quote Mindestreserve belief sich im 2025-02 auf 1.0 %. Dies stellt keine Veränderung im Vergleich zu den vorherigen Zahlen von 1.0 % für 2025-01 dar. Europäische Unions Quote Mindestreserve werden monatlich aktualisiert, mit einem Durchschnitt von 1.0 % von 1999-01 bis 2025-02, mit 314 Beobachtungen. Die Daten erreichten ein Allzeithoch in Höhe von 2.0 % im 2011-12 und ein Rekordtief in Höhe von 1.0 % im 2025-02. Europäische Unions Quote Mindestreserve Daten behalten den Aktiv-Status in CEIC und werden von European Central Bank gemeldet. Die Daten werden unter Global Databases Europäische Union – Table EU.KA006: European Central Bank: Reserve Requirements Ratio kategorisiert.

Tick (Bids | Asks | Trades | Settle) sample data for Euro Swiss (3 month) (Pit) QN timestamped in Chicago time

P-values of two samples Kolmogorov-Smirnov test comparing real data distribution with q normal distribution for individual stocks and the whole WIG 30 index (independent fit of left and right tail is performed).

Tick (Bids | Asks | Trades | Settle) sample data for Euro/Swiss Franc FR timestamped in Chicago time

Introduction: Quotebank is a dataset of 178 million unique, speaker-attributed quotations that were extracted from 196 million English news articles crawled from over 377 thousand web domains between August 2008 and April 2020. The quotations were extracted and attributed using Quobert, a distantly and minimally supervised end-to-end, language-agnostic framework for quotation attribution. For further details, please refer to the description below and to the original paper:Timoté Vaucher, Andreas Spitz, Michele Catasta, and Robert West"Quotebank: A Corpus of Quotations from a Decade of News"Proceedings of the 14th International ACM Conference on Web Search and Data Mining (WSDM), 2021.https://doi.org/10.1145/3437963.3441760When using the dataset, please cite the above paper. Dataset summaryThe dataset consists of two versions:Quotation-centric version (quotes-YYYY.json.bz2). An aggregated set of unique quotations with the most likely speaker. Each unique quotation occurs only once in this version of the data and the probabilities of the candidate speakers to which the quotation can be attributed are aggregated over all occurrences of the quotation. This version of the data is a minimal - but complete - list of attributed quotations that is aimed at users who only require quotation-speaker attributions, but no individual contexts for these quotations from the original articles.Article-centric version (quotebank-YYYY.json.bz2). A complete set of all individual quotation mentions with associated speaker as well as the article context in which they are mentioned. This larger version contains one entry per article in the news data. Each entry contains all speakers that appear in the news article as well as the (attributed) quotations, alongside a context window surrounding the quotations. Both versions are split into 13 files (one per year) for ease of downloading and handling. Dataset detailsThe following formatting applies to both versions of the dataset:All data is made available in JSON format that has been compressed using bzip2;The data is split per year (i.e., one file exists for each calendar year);The offsets of quotations, contexts, and speaker annotations are given in units of Penn TreeBank Tokenizer tokens; Offsets are zero-based and are computed from the start of the article; When pairs of offsets are provided, the end offset is non-inclusive (e.g. in Python you can call tokens[start:end] without having to do end+1). Version 1: Quotation-centric dataIn this version of the dataset, the quotations are aggregated across all their occurrences in the news article data, and assigned a probability for each speaker candidate. We consider two quotations to be equivalent and suitable for aggregation if they are identical after lower-casing and removing punctuation.Quotation-centric data |-- quoteID: Primary key of the quotation (format: "YYYY-MM-DD-{increasing int:06d}") |-- quotation: Text of the longest encountered original form of the quotation |-- date: Earliest occurrence date of any version of the quotation |-- phase: Corresponding phase of the data in which the quotation first occurred (A-E) |-- probas: Array representing the probabilities of each speaker having uttered the quotation. The probabilities across different occurrences of the same quotation are summed for each distinct candidate speaker and then normalized |-- proba: Probability for a given speaker |-- speaker: Most frequent surface form for a given speaker in the articles where the quotation occurred |-- speaker: Selected most likely speaker. This matches the the first speaker entry in probas |-- qids: Wikidata IDs of all aliases that match the selected speaker |-- numOccurrences: Number of time this quotation occurs in the articles |-- urls: List of links to the original articles containing the quotation Version 2: Article-centric dataIn this data set, individual quotations are not aggregated. For each article, one JSON entry contains all speakers that appear in the news article, the (attributed) quotations, and the text within a context window surrounding each of the quotations.Article-centric data |-- articleID: Primary key |-- articleLength: Length of the article in PTB tokens |-- date: Publication date of the article |-- phase: Corresponding phase in which the article appeared (A-E) |-- title: Title of the article |-- url: Link to the original article |-- names: List of all extracted speakers that occur in the article |-- name: Surface form of the first occurrence of each speaker in the article |-- ids: List of Wikidata IDs that have name as a possible alias |-- offsets: List of pairs of start/end offset, signifying positions at which the speaker occurs in the article (full and partial mention of the speaker) |-- quotations: List of all the quotations that appear in the article |-- quoteID: Foreign key of the quotation (from the quotation-centric dataset) |-- quotation: Text of the quotation as it occurs in this article |-- quotationOffset: Index where the quotation starts in the article |-- leftContext: Text in the left context window of the quotation (used for the attribution) |-- rightContext: Text in the right context window (used for the attribution) |-- globalProbas: Array representing the probabilities of each speaker having uttered the quote at the aggregated level. Same as probas for a given quoteID |-- globalTopSpeaker: Most probable speaker at the aggregated level. Same as speaker for a given quoteID |-- localProbas: Array representing the probabilities of each speaker having said the quote given this article context. |-- proba: Probability for a given speaker |-- speaker: Name of the speaker as it first occurs in this article |-- localTopSpeaker: Selected speaker. Same name as the first entry in localProbas |-- numOccurrences: Number of times this quotation occurs in any article Code repositoryThe code of Quobert that was used for the extraction and attribution of this data set is available and managed in a Github repository, which you can find here.