Prices for DXY Dollar Index including live quotes, historical charts and news. DXY Dollar Index was last updated by Trading Economics this August 2 of 2025.

USD index is expected to strengthen in the near term due to persistent safe-haven demand amid global economic uncertainties. The risk associated with this prediction is the potential for a correction if risk appetite improves or the Federal Reserve signals a dovish pivot.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

US Dollar Index: Bullish Break or Bearish Trap?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Graph and download economic data for Nominal Broad U.S. Dollar Index (DTWEXBGS) from 2006-01-02 to 2025-07-25 about trade-weighted, broad, exchange rate, currency, goods, services, rate, indexes, and USA.

The US dollar index of February 2025 was higher than it was in 2024, although below the peak in late 2022. This reveals itself in a historical graphic on the past 50 years, measuring the relative strength of the U.S. dollar. This metric is different from other FX graphics that compare the U.S. dollar against other currencies. By July 15, 2025, the DXY index was around 98.01 points. The history of the DXY Index The index shown here – often referred to with the code DXY, or USDX – measures the value of the U.S. dollar compared to a basket of six other foreign currencies. This basket includes the euro, the Swiss franc, the Japanese yen, the Canadian dollar, the British pound, and the Swedish króna. The index was created in 1973, after the arrival of the petrodollar and the dissolution of the Bretton Woods Agreement. Today, most of these currencies remain connected to the United States' largest trade partners. The relevance of the DXY Index The index focuses on trade and the strength of the U.S. dollar against specific currencies. It less on inflation or devaluation, which is measured in alternative metrics like the Big Mac Index. Indeed, as the methodology behind the DXY Index has only been updated once – when the euro arrived in 1999 – some argue this composition is not accurate to the current state of the world. The price development of the U.S. dollar affects many things, including commodity prices in general.

The DXY exchange rate rose to 99.9812 on August 1, 2025, up 0.01% from the previous session. Over the past month, the United States Dollar has strengthened 3.31%, but it's down by 3.13% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on August of 2025.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Dollar Index (Live)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The average for 2022 based on 7 countries was 6218.31 billion U.S. dollars. The highest value was in the USA: 40297.98 billion U.S. dollars and the lowest value was in Bermuda: 0.21 billion U.S. dollars. The indicator is available from 1975 to 2022. Below is a chart for all countries where data are available.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Dollars and Sense: The Correlation Between US Total Reserves and the Dollar Index

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The U.S. dollar was the most common currency in foreign exchange reserves in 2023, comprising more than three times the amount of the euro in global reserves that year. This total peaked in 2015, partly due to the strength of the dollar during the Eurozone crisis. The share of the U.S. dollar has lost since to the Japanese yen and euro, as well as other currencies. Why do foreign exchange reserves matter? When countries with different currencies export goods, they must agree on a currency for payment. As a result, countries hold currency reserves worth trillions of U.S. dollars. After World War II, the U.S. dollar itself became the international currency in the Bretton Woods Agreement and is thus the most common currency for international payments. The United States Treasury is also seen by most as risk-free, giving the country a low-risk premium. For this reason, countries hold U.S. dollars in reserve because the currency holds value relatively well eventually. China and currency reserves Since 2016, the International Monetary Fund has included the Chinese renminbi (yuan) as part of the Special Drawing Rights (SDR) basket. This decision recognized the influence of the renminbi as a reserve currency, particularly in several Asian countries. China also holds significant foreign exchange reserves itself, funded by its large positive trade balance.

United States US: Stocks Traded: Total Value data was reported at 39,785.881 USD bn in 2017. This records a decrease from the previous number of 42,071.330 USD bn for 2016. United States US: Stocks Traded: Total Value data is updated yearly, averaging 17,934.293 USD bn from Dec 1984 (Median) to 2017, with 34 observations. The data reached an all-time high of 47,245.496 USD bn in 2008 and a record low of 1,108.421 USD bn in 1984. United States US: Stocks Traded: Total Value data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

The euro and U.S. dollar made up more than ***** of 10 SWIFT payments worldwide in 2025, outperforming many other currencies. This is according to a monthly report meant to track the market share of China's yuan renminbi within the international bank transfer system SWIFT. Although China holds the largest forex reserves in the world, the yuan ranked as the ******-used currency in international payments. The figures concern customer-initiated and institutional payments and exclude trade. Discussions on the potential weakening role of the U.S. dollar especially touch world trade and forex. For example, the share of the USD in forex reserves declined visibly against the euro and Japanese yen in 2024. What sparked this de-dollarization trend, and will it continue? Trade sanctions and de-dollarization De-dollarization in 2024 is mentioned mostly alongside trade and the BRICS countries - an informal name given to Brazil, Russia, India, China, and South Africa. The combined GDP of BRICS is about ** percent of the world's economy. After the start of the Ukraine war and Russia received economic sanctions, the BRICS slowly evolved into a trading bloc. The group increasingly wanted its own currency to settle payments within the trade bloc, to avoid using the U.S. dollar. In August 2024, BRICS will gather in South Africa to discuss the creation of such a new joint currency. Additionally, ** countries - including Argentina, Algeria, Egypt, Saudi Arabia, Turkey, and Yemen - expressed interest in joining the BRICS group. CBDC, or projects into a digital payment settlement A factor of future uncertainty for the U.S. dollar is how central bank digital currencies (CBDC) develop in emerging countries. Several projects exist between individual countries that specifically target cross-border interbank payments. A cooperation between Thailand and Hong Kong, Inthanon-Lionrock, ranks as the most advanced of these projects. CBDC does not require the U.S. dollar to function. Tangible such as commodities or gold can back them. The value of transactions processed with CBDC is to grow by ******* percent between 2024 and 2030.

Key information about United States Market Capitalization

• United States Market Capitalization accounted for 40,297.980 USD bn in Dec 2022, compared with a percentage of 48,548.538 USD bn in the previous year
• US Market Capitalization is updated yearly, available from Dec 1975 to Dec 2022
• The data reached an all-time high of 48,548.538 USD bn in Dec 2021 and a record low of 703.800 USD bn in Dec 1975

The World Bank provides annual Market Capitalization in USD. Market Capitalization includes domestic companies listed at the end of the year and excludes investment companies, mutual funds and other collective investment vehicles.

Prices for TRYUSD Turkish Lira US Dollar including live quotes, historical charts and news. TRYUSD Turkish Lira US Dollar was last updated by Trading Economics this August 2 of 2025.

The value of global domestic equity market increased from ***** trillion U.S. dollars in 2013 to ****** trillion U.S. dollars in 2024. The United States was by far the leading country with the largest share of total world stocks as of 2024. Global market capitalization in different regions The market capitalization of domestic companies listed varied across different regions of the world. As of Decmber 2024, the Americas region had the largest domestic equity market, totaling ** trillion U.S. dollars. This region is home to the NYSE and Nasdaq, which are the two largest stock exchange operators in the world. The market capitalization of these two exchanges alone exceeded ** billion U.S. dollars as of January 2025, larger than the total market capitalization in the Asia-Pacific, and in the EMEA regions in the same period. Largest Stock Exchanges in Latin America As of December 2024, the B3 (Brasil Bolsa Balcao) was the biggest stock exchange in Latin America in terms of market capitalization and the second-largest in terms of number of listed companies. Following the B3 were the Mexican Stock Exchange and the Santiago Stock Exchange in Chile. The most valuable company in Latin America is listed on the Mexican Stock Exchange: Fomento Económico Mexicano, a multinational beverage and retail company headquartered in Monterrey, had a market cap of *** billion U.S. dollars as of March 2025.

As of May 2025, the combined average monthly turnover of the three main U.S. equities market operators - the New York Stock Exchange (NYSE), the Nasdaq, and Chicago Board Options Exchange (CBOE) Global Markets - amounted to around *** trillion U.S. dollars. However, the largest share of total equity trades in the United States was held by off-exchange transactions.

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

[Video] US Dollar Index: Charting a New Course?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Prices for USDJPY US Dollar Japanese Yen including live quotes, historical charts and news. USDJPY US Dollar Japanese Yen was last updated by Trading Economics this July 31 of 2025.

Ukraine: Stock market capitalization, billion USD: The latest value from 2018 is 4.42 billion U.S. dollars, a decline from 5.2 billion U.S. dollars in 2017. In comparison, the world average is 894.42 billion U.S. dollars, based on data from 76 countries. Historically, the average for Ukraine from 2010 to 2018 is 14.83 billion U.S. dollars. The minimum value, 4.42 billion U.S. dollars, was reached in 2018 while the maximum of 38.9 billion U.S. dollars was recorded in 2010.

Armenia: Stock market capitalization, billion USD: The latest value from 2022 is 0.25 billion U.S. dollars, an increase from 0.03 billion U.S. dollars in 2021. In comparison, the world average is 1244.55 billion U.S. dollars, based on data from 74 countries. Historically, the average for Armenia from 2018 to 2022 is 0.08 billion U.S. dollars. The minimum value, 0.03 billion U.S. dollars, was reached in 2020 while the maximum of 0.25 billion U.S. dollars was recorded in 2022.