Prices for DXY Dollar Index including live quotes, historical charts and news. DXY Dollar Index was last updated by Trading Economics this March 27 of 2025.

Long term historical dataset of the broad price-adjusted U.S. dollar index published by the Federal Reserve. The index is adjusted for the aggregated home inflation rates of all included currencies. The price adjustment is especially important with our Asian and South American trading partners due to their significant inflation episodes of the 80s and 90s.

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 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. 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 decreased 0.1629 or 0.16% to 104.3841 on Thursday March 27 from 104.5470 in the previous trading session. United States Dollar - values, historical data, forecasts and news - updated on March 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.

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 2025-03-21 about trade-weighted, broad, exchange rate, currency, goods, services, rate, indexes, and USA.

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 faces uncertain future amid economic headwinds

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 official currency of Puerto Rico is the US Dollar. This dataset displays a chart with historical values for the US Dollar Index. United States Dollar - values, historical data, forecasts and news - updated on March 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.

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 statistic shows the development of the MSCI World USD Index from 1986 to 2024. The 2024 year-end value of the MSCI World USD index amounted to 3,707.84 points. MSCI World USD index – additional information The MSCI World Index, developed by Morgan Stanley Capital International (MSCI), is one of the most important stock indices. It includes stocks from developed countries all over the world and is regarded as benchmark of global stock market. According to MSCI, this index covers about 88 percent of the free float-adjusted market capitalization in each country. As seen on the statistics above, in 2024, MSCI World USD index reported its highest value since 1986 amounting, a threefold increase from the figure recorded in 2013, when the year-end value of the MSCI World index was equal to 1,161.07. Along with the S&P Global Broad Market, the MSCI World is one of the most important global stock market performance indexes. Aside of including markets around the globe, these two indexes are global in a sense that they disregard where the companies are domiciled or traded, whereas other important indexes such as the Dow Jones Industrial Average, the Japanese index Nikkei 225, Wilshire 5000, the NASDAQ 100 index, have different approaches.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

The main stock market index in Japan (JP225) decreased 2147 points or 5.38% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on March of 2025.

Graph and download economic data for CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-03-24 about VIX, volatility, stock market, and USA.

The main stock market index in Hong Kong (HK50) increased 3587 points or 17.88% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on March of 2025.

The main stock market index in Indonesia (JCI) decreased 608 points or 8.58% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Indonesia. Indonesia Stock Market (JCI) - values, historical data, forecasts and news - updated on March of 2025.

Long term historical dataset of the daily U.S. Dollar - Chinese Yuan (USDCNY) exchange rate back to 1981.

The main stock market index in Germany (DE40) increased 2823 points or 14.18% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Germany. Germany Stock Market Index (DE40) - values, historical data, forecasts and news - updated on March of 2025.

The main stock market index in Turkey (BIST 100) decreased 220 points or 2.24% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks this benchmark index from Turkey. Turkey Stock Market - values, historical data, forecasts and news - updated on March of 2025.

Baltic Dry increased 637 points or 63.89% since the beginning of 2025, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Baltic Exchange Dry Index - values, historical data, forecasts and news - updated on March of 2025.