One United States dollar was worth over ********* Indonesian rupiah in September 2025, the highest value in a comparison of over 50 different currencies worldwide. All countries and territories shown here are based on the Big Mac Index - a measurement of how much a single Big Mac is worth across different areas in the world. This exchange rate comparison reveals a strong position of the dollar in Asia and Latin America. Note, though, that several of the top currencies shown here do not rank among the most traded. The quarterly U.S. dollar exchange rate against the ten biggest forex currencies only contains the Korean won and the Japanese yen.

This dataset provides updated currency exchange rates for a variety of currencies against a base currency (typically the United States Dollar, USD).

Content:

Base Currency: USD

The dataset is primarily focused on exchange rates concerning the United States Dollar (USD). Currencies Included:

Exchange rates are provided for a comprehensive list of currencies, including but not limited to Euro (EUR), British Pound (GBP), Japanese Yen (JPY), and many others.

Currency Codes:

These currency codes are used to uniquely identify and represent different world currencies in international financial transactions, trade, and investment. They are commonly used to specify the currency in which monetary values are expressed, making it easier to conduct cross-border transactions and financial reporting.

In July 2025, the exchange rate of yuan to U.S. dollar was ****. In the past decades, the yuan has undergone a slow liberalization, being increasingly exposed to the international money market. FOREX history of the Renminbi After the Communist Party took control over China, it introduced a unified currency which has since then undergone many changes. During the planned economy, the yuan had a fixed exchange rate. At the time, the currency’s exchange rate was deliberately set high to support the industrial development, which relied on imports. After the country committed to opening its economy, the Renminbi was gradually exposed to the supply and demand of the global FOREX markets. Until 2005, the yuan remained pegged to the U.S. dollar. Currency manipulator, or not? As China manifested its role in the global economy, the country was repeatedly accused of manipulating the value of its currency. Especially, voices from the United States claimed that Beijing would intentionally keep the value of the yuan low. A cheap Renminbi would make products from China more attractive for foreign buyers which in turn would support the country’s export-driven economy. However, currency manipulation is difficult to make out and even harder to prove, which is why no significant actions have been taken.

This dataset was generated by parsing PDFs released by the US Treasury for foreign exchange. An edited version (quarterly-edited.csv) includes fixes for typos in the Treasury data.

Usage caveats from the documentation:

"Exceptions to using the reporting rates as shown in the report are: * collections and refunds to be valued at specified rates set by international agreements, * conversions of one foreign currency into another, * foreign currencies sold for dollars, and * other types of transactions affecting dollar appropriations. (See Volume I Treasury Financial Manual 2-3200 for further details.)

Since the exchange rates in this report are not current rates of exchange, they should not be used to value transactions affecting dollar appropriations."

Additional caveats:

This unified dataset should be used only for reference or ballpark estimation, and not for anything like automated valuation. The reason is because there's still a lot of messiness involving countries and changing units- when in doubt or if required, please do additional research to confirm the historical rates are indeed as stated.

Future plans:

• Clean this up so that it can indeed be used in an automated system for converting currencies
• Fill in the missing entries
• Standardize country names and currency names

Documentation

Source

The DXY exchange rate rose to 99.4202 on December 2, 2025, up 0.01% from the previous session. Over the past month, the United States Dollar has weakened 0.45%, and is down by 6.53% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on December of 2025.

The euro-to-dollar exchange rate fluctuated significantly in 2022, reaching its lowest recorded value since 2008 during that time. Figures were different later in the year, however, with a rate of 1.16 USD recorded at the end of November 14, 2025. The average (standardized) measure is based on the calculation of many observations throughout the period in question. It is therefore different from an annual measure at a point, which reflects concrete values as of end of the year.EstablishmentThe euro, which was established in 1992, introduced in non-physical form in 1999 and finally rolled out in 2002, is used by 19 of the 27 member states of the European Union. This group of countries is otherwise known as the eurozone or euro area. By 2018, the total value of euro currency in circulation was almost 1.2 trillion euros, or over 3.4 thousand euros per capita.Euro to USDBetween 2001 and 2008, the average annual exchange rate of the euro to the U.S. dollar noted a steep increase. In 2008, the euro to U.S. dollar annual average exchange rate was equal to 1.47, which meant that one euro could buy 1.47 U.S. dollars. By 2019, this value had decreased overall, to a value of 1.12 which meant that one euro could buy 1.12 U.S. dollars. Similar dynamics in the euro to U.S. dollar exchange rate were also reflected in the monthly exchange rate recently.

The EUR/USD exchange rate rose to 1.1619 on December 2, 2025, up 0.08% from the previous session. Over the past month, the Euro US Dollar Exchange Rate - EUR/USD has strengthened 0.86%, and is up by 10.57% over the last 12 months. Euro US Dollar Exchange Rate - EUR/USD - values, historical data, forecasts and news - updated on December of 2025.

Graph and download economic data for Canadian Dollars to U.S. Dollar Spot Exchange Rate (DEXCAUS) from 1971-01-04 to 2025-11-28 about Canada, exchange rate, currency, rate, and USA.

Graph and download economic data for Currency Conversions: US Dollar Exchange Rate: Average of Daily Rates: National Currency: USD for Turkey (CCUSMA02TRA618N) from 1957 to 2024 about Turkey, exchange rate, currency, and rate.

A graphic that displays the dollar performance against other currencies reveals that economic developments had mixed results on currency exchanges. The third quarter of 2023 marked a period of disinflation in the euro area, while China's projected growth was projected to go up. The United States economy was said to have a relatively strong performance in Q3 2023, although growing capital market interest rate and the resumption of student loan repayments might dampen this growth at the end of 2023. A relatively weak Japanese yen Q3 2023 saw pressure from investors towards Japanese authorities on how they would respond to the situation surrounding the Japanese yen. The USD/JPY rate was close to ***, whereas analysts suspected it should be around ** given the country's purchase power parity. The main reason for this disparity is said to be the differences in central bank interest rates between the United States, the euro area, and Japan. Any future aggressive changes from, especially the U.S. Fed might lower those differences. Financial markets responded somewhat disappoint when Japan did not announce major plans to tackle the situation. Potential rent decreases in 2024 Central bank rates peak in 2023, although it is expected that some of these will decline in early 2024. That said, analysts expect overall policies will remain restrictive. For example, the Bank of England's interest rate remained unchanged at **** percent in Q3 2023. It is believed the United Kingdom's central bank will ease its interest rate in 2024 but less than either the U.S. Fed or the European Central Bank. This should be a positive development for the pound compared to either the euro or the dollar.

Graph and download economic data for Currency Conversions: US Dollar Exchange Rate: Average of Daily Rates: National Currency: USD for Chile (CCUSMA02CLM618N) from Jan 1957 to Oct 2025 about Chile, exchange rate, currency, and rate.

A dataset containing exchange rate information in USD typically includes historical or real-time data about the conversion rates of various currencies to US dollars. The dataset may include information about different currency pairs, where one currency is denoted as USD (United States Dollar), and the other currency varies. For example, EUR/USD represents the exchange rate of euros to US dollars. The main component of the dataset is the exchange rate values themselves. These values represent the amount of the foreign currency required to purchase one US dollar at a specific point in time. Exchange rate values may be provided as floating-point numbers with a specific precision.

The USD/TWD exchange rate fell to 31.4070 on December 2, 2025, down 0.01% from the previous session. Over the past month, the Taiwanese Dollar has weakened 1.54%, but it's up by 3.52% over the last 12 months. Taiwanese Dollar - values, historical data, forecasts and news - updated on December of 2025.

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: North, South, Artibonite, Centre, South-East, Grande'Anse, North-East, West, North-West, Market Average

A ranked comparison of GBP to USD all-in rates, fees and delivered amounts for common transfer amounts.

This dataset contains monthly exchange rate data for four major global currencies: United States Dollar (USD), British Pound (GBP), Canadian Dollar (CAD), and Australian Dollar (AUD). The data spans multiple years, starting from January 1999, and is recorded on a monthly basis. It is structured in CSV format with five columns: Date, USD_Price, GBP_Price, CAD_Price, and AUD_Price. The Date column represents the timestamp of the recorded exchange rate in the YYYY-MM-DD format, while the remaining columns represent the exchange rates for their respective currencies.

This dataset can be used for various financial and economic analyses, including identifying long-term trends, studying fluctuations in exchange rates, and understanding periods of stability and volatility. It is particularly useful for researchers and analysts looking to examine historical currency trends and assess the factors influencing foreign exchange markets.

Financial professionals can leverage this data to build predictive models and apply machine learning techniques to estimate future exchange rates. By analyzing past trends, it is possible to gain insights into potential market movements and develop strategies for risk management and investment decision-making.

Economists can use the dataset to examine the impact of global economic events on currency values and study correlations between exchange rates and macroeconomic indicators such as inflation, interest rates, and trade balances. This can provide a deeper understanding of how economic policies and external shocks affect currency markets over time.

Additionally, the dataset is valuable for comparing currency movements with stock markets, commodity prices, and international trade patterns. It enables researchers to analyze how different currencies react to financial crises, policy changes, and economic shifts. By offering a comprehensive view of historical exchange rate fluctuations, this dataset serves as a foundation for financial forecasting, economic research, and market correlation studies.

The data shows the year-wise foreign exchange reserves in Indian currency and in US Dollar in the years between 2001 and 2017.

Note: 1. Gold has been valued close to international market price. 2. Conversion of FCA is done at current exchange rates and SDR in US dollars is done at exchange rates supplied by IMF. 3. Transactions with IMF are converted at respective SDR/$ rate. 4. FCA excludes: (i) Investment in foreign currency denominated bonds issued by IIFC (UK) since 2009, (ii) Amount lent under SAARC swap arrangements since 2013 and (iii) SDR transferred by Govt. of India to RBI since March 2014. 5. Gold includes Rupee 31,463 crore(US$ 6699 million) reflecting the purchase of 200 metric tonnes of Gold from IMF on November 3, 2009. 6. SDR includes SDR 3082.5 million allocated under general allocation and SDR 214.6 million allocated under special allocation by the IMF done on August 28,2009 and September 2009 respectively. 8. Above figures are as on 31st March of each year mentioned in years. 9. FCA implies Foreign Currency Assets, SDRs implies Special Drawing Rights and RTP implies Reserve Tranche Position in IMF.

Abstract

Currency exchange rate is an important metric to inform economic policy but traditional sources are often produced with delay during crises and only at an aggregate level. This may poorly reflect the actual rate trends in rural or poverty-stricken areas, where large populations reside in fragile situations. This data set includes currency exchange rate estimates and is intended to help gain insight in price developments beyond what can be formally measured by traditional methods. The estimates are generated using a machine-learning approach that imputes ongoing subnational price surveys, often with accuracy similar to direct measurement of prices. The data set provides new opportunities to investigate local price dynamics in areas where populations are sensitive to localized price shocks and where traditional data are not available.

Geographic coverage notes

The data cover the following sub-national areas: Aleppo, Dar'a, Quneitra, Homs, Deir-ez-Zor, Damascus, Ar-Raqqa, Al-Hasakeh, Hama, As-Sweida, Rural Damascus, Tartous, Idleb, Lattakia, Market Average

Number of U.S. Dollars per domestic currency unit for currencies used in Pacific Island Countries and Territories. Monthly and yearly values for end-of-period and period-average exchange rates since 1950 are based on data from IMF International Financial Statistics.

Find more Pacific data on PDH.stat.

This dataset offers a comprehensive view of daily currency exchange rates, from 2008 to 2023. Currency rates can be affected by various factors, including interest rates, inflation, political instability, economic performance, and global market developments. Understanding these rates over time can provide valuable insights into economic trends, market behaviors, and the impacts of global events on currency values.

The currency pairs included in this dataset are: USD to INR (INR=X) USD to JPY (JPY=X) USD to EUR (EUR=X) USD to GBP (GBP=X) USD to AUD (AUD=X) USD to CAD (CAD=X) USD to CHF (CHF=X) USD to CNY (CNY=X) USD to HKD (HKD=X) USD to SGD (SGD=X)

Each row in the dataset represents a single day and includes the following columns:

Ticker: The currency pair being represented. Date: The date in YYYY-MM-DD format. Open: The opening exchange rate of the day. High: The highest exchange rate of the day. Low: The lowest exchange rate of the day. Close: The closing exchange rate of the day. Adj Close: The adjusted closing exchange rate of the day. Volume: The volume of the currency traded on that day.

Usage: This dataset could be useful for a variety of purposes, including but not limited to:

Economic research: Analyze currency trends over time to understand economic behaviors. Financial modeling: Use historical data to forecast future currency rates. Machine learning: Develop predictive models for currency exchange rates. Teaching: An excellent resource for educators in finance and economics.