Prices for DXY Dollar Index including live quotes, historical charts and news. DXY Dollar Index was last updated by Trading Economics this July 13 of 2025.

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.

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 DXY exchange rate rose to 97.9584 on July 14, 2025, up 0.11% from the previous session. Over the past month, the United States Dollar has weakened 0.32%, and is down by 6.03% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on July 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.

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

Prices for BTCUSD Bitcoin US Dollar including live quotes, historical charts and news. BTCUSD Bitcoin US Dollar was last updated by Trading Economics this July 6 of 2025.

Prices for USDVND US Dollar Vietnamese Dong including live quotes, historical charts and news. USDVND US Dollar Vietnamese Dong was last updated by Trading Economics this July 14 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

At **** U.S. dollars, Switzerland has the most expensive Big Macs in the world, according to the January 2025 Big Mac index. Concurrently, the cost of a Big Mac was **** dollars in the U.S., and **** U.S. dollars in the Euro area. What is the Big Mac index? The Big Mac index, published by The Economist, is a novel way of measuring whether the market exchange rates for different countries’ currencies are overvalued or undervalued. It does this by measuring each currency against a common standard – the Big Mac hamburger sold by McDonald’s restaurants all over the world. Twice a year the Economist converts the average national price of a Big Mac into U.S. dollars using the exchange rate at that point in time. As a Big Mac is a completely standardized product across the world, the argument goes that it should have the same relative cost in every country. Differences in the cost of a Big Mac expressed as U.S. dollars therefore reflect differences in the purchasing power of each currency. Is the Big Mac index a good measure of purchasing power parity? Purchasing power parity (PPP) is the idea that items should cost the same in different countries, based on the exchange rate at that time. This relationship does not hold in practice. Factors like tax rates, wage regulations, whether components need to be imported, and the level of market competition all contribute to price variations between countries. The Big Mac index does measure this basic point – that one U.S. dollar can buy more in some countries than others. There are more accurate ways to measure differences in PPP though, which convert a larger range of products into their dollar price. Adjusting for PPP can have a massive effect on how we understand a country’s economy. The country with the largest GDP adjusted for PPP is China, but when looking at the unadjusted GDP of different countries, the U.S. has the largest economy.

Korea ImPI: USD: By SITC: Food & Live Animals data was reported at 174.710 2005=100 in Dec 2012. This records a decrease from the previous number of 176.260 2005=100 for Nov 2012. Korea ImPI: USD: By SITC: Food & Live Animals data is updated monthly, averaging 90.315 2005=100 from Jan 1971 (Median) to Dec 2012, with 504 observations. The data reached an all-time high of 188.260 2005=100 in Apr 2011 and a record low of 59.770 2005=100 in Jan 1971. Korea ImPI: USD: By SITC: Food & Live Animals data remains active status in CEIC and is reported by The Bank of Korea. The data is categorized under Global Database’s Korea – Table KR.I071: Import Price Index (USD Basis): 2005=100.

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 13 of 2025.

Taiwan ExPI: USD: SITC: Food and Live Animals Chiefly for Food data was reported at 133.520 2001=100 in Dec 2007. This records an increase from the previous number of 132.990 2001=100 for Nov 2007. Taiwan ExPI: USD: SITC: Food and Live Animals Chiefly for Food data is updated monthly, averaging 113.140 2001=100 from Jan 1981 (Median) to Dec 2007, with 324 observations. The data reached an all-time high of 182.620 2001=100 in Jun 1999 and a record low of 82.700 2001=100 in Nov 1982. Taiwan ExPI: USD: SITC: Food and Live Animals Chiefly for Food data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.I065: Export Price Index: 2001=100: USD.

Prices for USDIDR US Dollar Indonesian Rupiah including live quotes, historical charts and news. USDIDR US Dollar Indonesian Rupiah was last updated by Trading Economics this July 14 of 2025.

Stay informed with real-time charts of international precious metal prices. Monitor spot prices for Silver in USD, GBP, and EUR. Access live updates here >>

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

Taiwan ExPI: USD: SITC: Foods & Edible Live Animals data was reported at 153.240 2006=100 in Dec 2012. This records a decrease from the previous number of 166.330 2006=100 for Nov 2012. Taiwan ExPI: USD: SITC: Foods & Edible Live Animals data is updated monthly, averaging 94.245 2006=100 from Jan 1981 (Median) to Dec 2012, with 384 observations. The data reached an all-time high of 210.150 2006=100 in Feb 2012 and a record low of 64.210 2006=100 in Nov 1982. Taiwan ExPI: USD: SITC: Foods & Edible Live Animals data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.I067: Export Price Index: 2006=100: USD.

Interactive chart illustrating the performance of the Dow Jones Industrial Average (DJIA) market index over the last ten years. Each point of the stock market graph is represented by the daily closing price for the DJIA. Historical data can be downloaded via the red button on the upper left corner of the chart.

Taiwan ExPI: USD: Live Animals; Animal Products (AP) data was reported at 116.220 2016=100 in Jun 2018. This stayed constant from the previous number of 116.220 2016=100 for May 2018. Taiwan ExPI: USD: Live Animals; Animal Products (AP) data is updated monthly, averaging 77.485 2016=100 from Jan 1998 (Median) to Jun 2018, with 246 observations. The data reached an all-time high of 138.830 2016=100 in Feb 2012 and a record low of 49.620 2016=100 in Jan 2002. Taiwan ExPI: USD: Live Animals; Animal Products (AP) data remains active status in CEIC and is reported by Directorate-General of Budget, Accounting and Statistics, Executive Yuan. The data is categorized under Global Database’s Taiwan – Table TW.I063: Export Price Index: 2016=100: USD.

Thailand ImPI: USD: CA: Live Animal and Plant for Purebred Breeding data was reported at 113.600 2007=100 in Jan 2013. This records a decrease from the previous number of 113.900 2007=100 for Dec 2012. Thailand ImPI: USD: CA: Live Animal and Plant for Purebred Breeding data is updated monthly, averaging 99.400 2007=100 from Jan 2000 (Median) to Jan 2013, with 157 observations. The data reached an all-time high of 115.100 2007=100 in Apr 2012 and a record low of 84.200 2007=100 in Apr 2000. Thailand ImPI: USD: CA: Live Animal and Plant for Purebred Breeding data remains active status in CEIC and is reported by Bureau of Trade and Economic Indices. The data is categorized under Global Database’s Thailand – Table TH.I060: Export and Import Price Index: 2007=100.