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: 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.

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

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

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: 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.

Prices for DXY Dollar Index including live quotes, historical charts and news. DXY Dollar Index was last updated by Trading Economics this September 1 of 2025.

Graph and download economic data for Nominal Broad U.S. Dollar Index (DTWEXBGS) from 2006-01-02 to 2025-08-22 about trade-weighted, broad, exchange rate, currency, goods, services, rate, indexes, and USA.

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.

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

Tick (trades only) sample data for U.S. Dollar Index (Settlement) DX 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.

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

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

Cotton futures are declining as the weekend approaches, influenced by mixed external factors such as changes in the US dollar index and crude oil futures. Current sales commitments and market insights provide a detailed overview of the situation.

Index Time Series for Invesco DB US Dollar Index Bullish Fund. The frequency of the observation is daily. Moving average series are also typically included. The fund invests in futures contracts in an attempt to track its index. The index is calculated to reflect the changes in market value over time, whether positive or negative, of long positions in DX Contracts.

Cotton futures face a decline due to market pressures, with significant drops in December contracts, a falling US dollar index, and reduced crude oil prices impacting the market.

Daily sample data for U.S. Dollar Index (Settlement) DX timestamped in Chicago time

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).

Cotton futures have risen significantly amid market fluctuations, influenced by a weakening US dollar and increased oil production by OPEC+. Discover the latest trends and data in the cotton market.

Cotton futures rose amid mixed market signals, with contracts up between 16 and 57 points. The U.S. dollar index climbed while crude oil futures edged up.