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 98.4741 on July 18, 2025, down 0.18% from the previous session. Over the past month, the United States Dollar has weakened 0.44%, and is down by 5.65% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on July of 2025.

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.

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.

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

Browse MSCI Japan NTR USD Index Daily Futures (DMS) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

ICE Futures US iMpact is the primary data feed for ICE Futures US and covers the majority of trading in agricultural commodities, including sugar, coffee, cotton, and cocoa futures and options. This comprehensive market data feed also includes financial products such as equity indexes, currencies, and US Treasury futures contracts. The dataset provides complete market depth information across all listed outrights, spreads, options, and options combinations for every expiration month. ICE Futures US represents one of the most significant exchanges for US-based agricultural and financial derivatives, offering essential price discovery and risk management tools for global market participants.

Asset class: Futures, Options

Origin: Captured at Aurora DC3 with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP

Supported data encodings: DBN, CSV, JSON (Learn more)

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics (Learn more)

Resolution: Immediate publication, nanosecond-resolution timestamps

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

The EUR/USD exchange rate rose to 1.1657 on July 18, 2025, up 0.36% from the previous session. Over the past month, the Euro US Dollar Exchange Rate - EUR/USD has strengthened 1.40%, and is up by 7.13% over the last 12 months. Euro US Dollar Exchange Rate - EUR/USD - values, historical data, forecasts and news - updated on July of 2025.

Browse MSCI Philippines NTR (USD) Index Futures (MPH) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

ICE Europe Financials is sourced from ICE’s proprietary iMpact feed and delivers all financial futures and options listed on ICE Futures Europe. It captures full order book depth for derivatives used to manage risk across European yield curves and major equity benchmarks.

This dataset covers a broad range of interest rate products, such as short-term interest rate futures (STIRs), benchmark contracts like Euribor, SONIA, and SOFR, Swapnote contracts, and government bond futures, including Long, Medium, and Short Term Gilts. It also offers equity index derivatives like FTSE 100 futures and London Stock Exchange options.

ICE Europe Financials provides all listed outrights, spreads, options, and option combinations across every expiration month. Commodity derivatives from ICE Futures Europe are available in the ICE Europe Commodities dataset.

Asset class: Futures, Options

Origin: Captured at Aurora DC3 with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP

Supported data encodings: DBN, CSV, JSON (Learn more)

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics (Learn more)

Resolution: Immediate publication, nanosecond-resolution timestamps

Browse MSCI World Health Care Net TR USD Index Futures (M55) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

ICE Europe Financials is sourced from ICE’s proprietary iMpact feed and delivers all financial futures and options listed on ICE Futures Europe. It captures full order book depth for derivatives used to manage risk across European yield curves and major equity benchmarks.

This dataset covers a broad range of interest rate products, such as short-term interest rate futures (STIRs), benchmark contracts like Euribor, SONIA, and SOFR, Swapnote contracts, and government bond futures, including Long, Medium, and Short Term Gilts. It also offers equity index derivatives like FTSE 100 futures and London Stock Exchange options.

ICE Europe Financials provides all listed outrights, spreads, options, and option combinations across every expiration month. Commodity derivatives from ICE Futures Europe are available in the ICE Europe Commodities dataset.

Asset class: Futures, Options

Origin: Captured at Aurora DC3 with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP

Supported data encodings: DBN, CSV, JSON (Learn more)

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics (Learn more)

Resolution: Immediate publication, nanosecond-resolution timestamps

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

The USD/CNY exchange rate fell to 7.1806 on July 18, 2025, down 0.04% from the previous session. Over the past month, the Chinese Yuan has strengthened 0.08%, and is up by 1.42% over the last 12 months. Chinese Yuan - values, historical data, forecasts and news - updated on July of 2025.