United States U.S. Dollar Index: Futures: Volume data was reported at 36,443.810 Unit in Apr 2025. This records an increase from the previous number of 26,125.524 Unit for Mar 2025. United States U.S. Dollar Index: Futures: Volume data is updated monthly, averaging 3,678.275 Unit from Nov 1985 (Median) to Apr 2025, with 474 observations. The data reached an all-time high of 77,809.773 Unit in Mar 2015 and a record low of 210.783 Unit in Oct 1986. United States U.S. Dollar Index: Futures: Volume data remains active status in CEIC and is reported by Barchart.com, Inc.. The data is categorized under Global Database’s United States – Table US.M036: US Dollar Index.

United States U.S. Dollar Index: Futures: High data was reported at 101.014 Mar1973=100 in Apr 2025. This records a decrease from the previous number of 104.350 Mar1973=100 for Mar 2025. United States U.S. Dollar Index: Futures: High data is updated monthly, averaging 93.879 Mar1973=100 from Nov 1985 (Median) to Apr 2025, with 474 observations. The data reached an all-time high of 126.365 Mar1973=100 in Dec 1985 and a record low of 72.793 Mar1973=100 in Apr 2008. United States U.S. Dollar Index: Futures: High data remains active status in CEIC and is reported by Barchart.com, Inc.. The data is categorized under Global Database’s United States – Table US.M036: US Dollar Index.

United States U.S. Dollar Index: Futures: Open Interest data was reported at 28,716.190 Unit in Apr 2025. This records a decrease from the previous number of 34,969.952 Unit for Mar 2025. United States U.S. Dollar Index: Futures: Open Interest data is updated monthly, averaging 22,840.175 Unit from Nov 1985 (Median) to Apr 2025, with 474 observations. The data reached an all-time high of 129,685.045 Unit in Mar 2015 and a record low of 1,125.000 Unit in Nov 1985. United States U.S. Dollar Index: Futures: Open Interest data remains active status in CEIC and is reported by Barchart.com, Inc.. The data is categorized under Global Database’s United States – Table US.M036: US Dollar Index.

Download Historical U.S. Dollar Index (Settlement) Futures Data. CQG daily, 1 minute, tick, and level 1 data from 1899.

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.

WTI Futures x3 Leveraged USD Index: The Next Big Play?

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

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.

United States U.S. Dollar Index: Futures: Open data was reported at 100.690 Mar1973=100 in Apr 2025. This records a decrease from the previous number of 104.086 Mar1973=100 for Mar 2025. United States U.S. Dollar Index: Futures: Open data is updated monthly, averaging 93.525 Mar1973=100 from Nov 1985 (Median) to Apr 2025, with 474 observations. The data reached an all-time high of 126.074 Mar1973=100 in Dec 1985 and a record low of 72.360 Mar1973=100 in Apr 2008. United States U.S. Dollar Index: Futures: Open data remains active status in CEIC and is reported by Barchart.com, Inc.. The data is categorized under Global Database’s United States – Table US.M036: US Dollar Index.

The DXY exchange rate fell to 98.4660 on July 21, 2025, down 0.02% from the previous session. Over the past month, the United States Dollar has weakened 0.46%, and is down by 5.60% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on July 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 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 July of 2025.

United States U.S. Dollar Index: Futures: Low data was reported at 99.955 Mar1973=100 in Apr 2025. This records a decrease from the previous number of 103.664 Mar1973=100 for Mar 2025. United States U.S. Dollar Index: Futures: Low data is updated monthly, averaging 93.156 Mar1973=100 from Nov 1985 (Median) to Apr 2025, with 474 observations. The data reached an all-time high of 125.701 Mar1973=100 in Dec 1985 and a record low of 72.031 Mar1973=100 in Apr 2008. United States U.S. Dollar Index: Futures: Low data remains active status in CEIC and is reported by Barchart.com, Inc.. The data is categorized under Global Database’s United States – Table US.M036: US Dollar Index.

Daily sample data for U.S. Dollar Index (ICE) DXE timestamped in Chicago time

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

The EUR/USD exchange rate rose to 1.1669 on July 21, 2025, up 0.41% from the previous session. Over the past month, the Euro US Dollar Exchange Rate - EUR/USD has strengthened 0.79%, and is up by 7.16% over the last 12 months. Euro US Dollar Exchange Rate - EUR/USD - values, historical data, forecasts and news - updated on July 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.

WTI Futures x3 Leveraged USD Index: Will it Soar or Sink?

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

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

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.

WTI Futures x3 Leveraged USD Index Forecast

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

Baltic Dry rose to 2,052 Index Points on July 18, 2025, up 1.08% from the previous day. Over the past month, Baltic Dry's price has risen 17.19%, and is up 7.89% compared to the same time last year, 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 July of 2025.

CRB Index rose to 376.85 Index Points on July 18, 2025, up 0.63% from the previous day. Over the past month, CRB Index's price has fallen 1.73%, but it is still 14.21% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on July of 2025.

Argentina Trading Value: BCBA: USD: Index Futures data was reported at 0.000 ARS mn in Feb 2021. This stayed constant from the previous number of 0.000 ARS mn for Jan 2021. Argentina Trading Value: BCBA: USD: Index Futures data is updated monthly, averaging 0.000 ARS mn from Jan 2000 (Median) to Feb 2021, with 254 observations. The data reached an all-time high of 35.488 ARS mn in May 2003 and a record low of 0.000 ARS mn in Feb 2021. Argentina Trading Value: BCBA: USD: Index Futures data remains active status in CEIC and is reported by Buenos Aires Stock Exchange. The data is categorized under Global Database’s Argentina – Table AR.Z003: Buenos Aires Stock Exchange: Trading Value (Discontinued).