The DXY exchange rate rose to 96.9135 on July 1, 2025, up 0.04% from the previous session. Over the past month, the United States Dollar has weakened 1.82%, and is down by 8.30% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on July of 2025.

Sweden NIER Forecast: Exchange Rate: US Dollar data was reported at 7.500 SEK/USD in 2028. This records a decrease from the previous number of 7.600 SEK/USD for 2027. Sweden NIER Forecast: Exchange Rate: US Dollar data is updated yearly, averaging 7.400 SEK/USD from Dec 1971 (Median) to 2028, with 58 observations. The data reached an all-time high of 10.300 SEK/USD in 2001 and a record low of 4.200 SEK/USD in 1980. Sweden NIER Forecast: Exchange Rate: US Dollar data remains active status in CEIC and is reported by National Institute of Economic Research. The data is categorized under Global Database’s Sweden – Table SE.M020: Foreign Exchange Rate: Forecast: National Institute of Economic Research.

The EUR/USD exchange rate was unchanged at 1.1786 on July 1, 2025. Over the past month, the Euro US Dollar Exchange Rate - EUR/USD has strengthened 3.02%, and is up by 9.66% over the last 12 months. Euro US Dollar Exchange Rate - EUR/USD - 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.

BMF Forecast: Foreign Exchange Rate: US Dollar: Annual Average data was reported at 1.100 USD/EUR in 2027. This stayed constant from the previous number of 1.100 USD/EUR for 2026. BMF Forecast: Foreign Exchange Rate: US Dollar: Annual Average data is updated yearly, averaging 1.100 USD/EUR from Dec 2016 (Median) to 2027, with 12 observations. The data reached an all-time high of 1.200 USD/EUR in 2022 and a record low of 1.100 USD/EUR in 2027. BMF Forecast: Foreign Exchange Rate: US Dollar: Annual Average data remains active status in CEIC and is reported by Federal Ministry of Finance. The data is categorized under Global Database’s Austria – Table AT.M007: Foreign Exchange Rate: US Dollar: Forecast.

Snapshot img

Foreign Exchange Market Size 2025-2029

The foreign exchange market size is forecast to increase by USD 582 billion, at a CAGR of 10.6% between 2024 and 2029.

The Foreign Exchange Market is segmented by type (reporting dealers, financial institutions, non-financial customers), trade finance instruments (currency swaps, outright forward and FX swaps, FX options), trading platforms (electronic trading, over-the-counter (OTC), mobile trading), and geography (North America: US, Canada; Europe: Germany, Switzerland, UK; Middle East and Africa: UAE; APAC: China, India, Japan; South America: Brazil; Rest of World). This segmentation reflects the market's global dynamics, driven by institutional trading, increasing digital adoption through electronic trading and mobile trading, and regional economic activities, with APAC markets like India and China showing significant growth alongside traditional hubs like the US and UK.
The market is experiencing significant shifts driven by the escalating trends of urbanization and digitalization. These forces are creating 24x7 trading opportunities, enabling greater accessibility and convenience for market participants. However, the market's dynamics are not without challenges. The uncertainty of future exchange rates poses a formidable obstacle for businesses and investors alike, necessitating robust risk management strategies. As urbanization continues to expand and digital technologies reshape the trading landscape, market players must adapt to remain competitive. One significant trend is the increasing use of money transfer agencies, venture capital investments, and mutual funds in foreign exchange transactions. Companies seeking to capitalize on these opportunities must navigate the challenges effectively, ensuring they stay abreast of exchange rate fluctuations and implement agile strategies to mitigate risk.
The ability to adapt and respond to these market shifts will be crucial for success in the evolving market.

What will be the Size of the Foreign Exchange Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free Sample

In the dynamic and intricate realm of the market, entities such as algorithmic trading, order book, order management systems, and liquidity risk intertwine, shaping the ever-evolving market landscape. The market's continuous unfolding is characterized by the integration of various components, including sentiment analysis, Fibonacci retracement, mobile trading, and good-for-the-day orders. Market activities are influenced by factors like political stability, monetary policy, and market liquidity, which in turn impact economic growth and trade settlement. Technical analysis, with its focus on chart patterns and moving averages, plays a crucial role in informing trading decisions. The market's complexity is further amplified by the presence of entities like credit risk, counterparty risk, and operational risk.

Central bank intervention, order execution, clearing and settlement, and trade confirmation are essential components of the market's infrastructure, ensuring a seamless exchange of currencies. Geopolitical risk, currency correlation, and inflation rates contribute to currency volatility, necessitating hedging strategies and risk management. Market risk, interest rate differentials, and commodity currencies influence trading strategies, while cross-border payments and brokerage services facilitate international trade. The ongoing evolution of the market is marked by the emergence of advanced trading platforms, automated trading, and real-time data feeds, enabling traders to make informed decisions in an increasingly interconnected and complex global economy.

How is this Foreign Exchange Industry segmented?

The foreign exchange industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Reporting dealers
  Financial institutions
  Non-financial customers


Trade Finance Instruments

  Currency swaps
  Outright forward and FX swaps
  FX options


Trading Platforms

  Electronic Trading
  Over-the-Counter (OTC)
  Mobile Trading


Geography

  North America

    US
    Canada


  Europe

    Germany
    Switzerland
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The reporting dealers segment is estimated to witness significant growth during the forecast period.

The market is a dynamic and complex ecosystem where various entities interplay to manage currency risks and facilitate international trade. Reporting dealers, as key participants,

Russia MED Forecast: Foreign Exchange Rate: Year Average: US Dollar: Baseline Scenario data was reported at 75.156 RUB/USD in 2036. This records an increase from the previous number of 74.739 RUB/USD for 2035. Russia MED Forecast: Foreign Exchange Rate: Year Average: US Dollar: Baseline Scenario data is updated yearly, averaging 69.636 RUB/USD from Dec 2016 (Median) to 2036, with 21 observations. The data reached an all-time high of 75.156 RUB/USD in 2036 and a record low of 58.335 RUB/USD in 2017. Russia MED Forecast: Foreign Exchange Rate: Year Average: US Dollar: Baseline Scenario data remains active status in CEIC and is reported by Ministry of Economic Development of the Russian Federation. The data is categorized under Global Database’s Russian Federation – Table RU.ME002: Foreign Exchange Rate: Year Average: US Dollar: Forecast: Ministry of Economic Development.

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

Mexico BDM Forecast: Exchange Rate against US$: Average: Current Month data was reported at 19.260 MXN/USD in Mar 2019. This records an increase from the previous number of 19.210 MXN/USD for Feb 2019. Mexico BDM Forecast: Exchange Rate against US$: Average: Current Month data is updated monthly, averaging 17.645 MXN/USD from Dec 1999 (Median) to Mar 2019, with 76 observations. The data reached an all-time high of 21.420 MXN/USD in Jan 2017 and a record low of 9.560 MXN/USD in Dec 1999. Mexico BDM Forecast: Exchange Rate against US$: Average: Current Month data remains active status in CEIC and is reported by Bank of Mexico. The data is categorized under Global Database’s Mexico – Table MX.M006: Foreign Exchange Rates: Forecast.

The euro-to-dollar exchange rate fluctuated significantly in 2022, reaching its lowest recorded value since 2008 during that time. Figures were different later in the year, however, with a rate of 1.17 USD recorded at the end of June 27, 2025. The average (standardized) measure is based on the calculation of many observations throughout the period in question. It is therefore different from an annual measure at a point, which reflects concrete values as of end of the year. Establishment The euro, which was established in 1992, introduced in non-physical form in 1999 and finally rolled out in 2002, is used by 19 of the 27 member states of the European Union. This group of 19 countries is otherwise known as the eurozone or euro area. By 2018, the total value of euro currency in circulation was almost 1.2 trillion euros, or over 3.4 thousand euros per capita. Euro to USD Between 2001 and 2008, the average annual exchange rate of the euro to the U.S. dollar noted a steep increase. In 2008, the euro to U.S. dollar annual average exchange rate was equal to 1.47, which meant that one euro could buy 1.47 U.S. dollars. By 2019, this value had decreased overall, to a value of 1.12 which meant that one euro could buy 1.12 U.S. dollars. Similar dynamics in the euro to U.S. dollar exchange rate were also reflected in the monthly exchange rate recently.

The USD/MXN exchange rate fell to 18.7371 on July 1, 2025, down 0.07% from the previous session. Over the past month, the Mexican Peso has strengthened 2.51%, but it's down by 2.59% over the last 12 months. Mexican Peso - values, historical data, forecasts and news - updated on July of 2025.

Graph and download economic data for Canadian Dollars to U.S. Dollar Spot Exchange Rate (DEXCAUS) from 1971-01-04 to 2025-06-27 about Canada, exchange rate, currency, rate, and USA.

Interactive chart of historical data showing 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.

The euro-to-dollar exchange rate fluctuated significantly in 2022, reaching its lowest recorded value since 2008 during that time. Figures were different later in the year, however, with a rate of 1.13 USD recorded at the end of May 2, 2025. The average (standardized) measure is based on the calculation of many observations throughout the period in question. It is therefore different from an annual measure at a point, which reflects concrete values as of end of the year. Establishment The euro, which was established in 1992, introduced in non-physical form in 1999 and finally rolled out in 2002, is used by 19 of the 27 member states of the European Union. This group of 19 countries is otherwise known as the eurozone or euro area. By 2018, the total value of euro currency in circulation was almost 1.2 trillion euros, or over 3.4 thousand euros per capita. Euro to USD Between 2001 and 2008, the average annual exchange rate of the euro to the U.S. dollar noted a steep increase. In 2008, the euro to U.S. dollar annual average exchange rate was equal to 1.47, which meant that one euro could buy 1.47 U.S. dollars. By 2019, this value had decreased overall, to a value of 1.12 which meant that one euro could buy 1.12 U.S. dollars. Similar dynamics in the euro to U.S. dollar exchange rate were also reflected in the monthly exchange rate recently.

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

Luxembourg STATEC Forecast: Foreign Exchange Rate: US Dollar data was reported at 1.180 USD/EUR in 2018. This records an increase from the previous number of 1.130 USD/EUR for 2017. Luxembourg STATEC Forecast: Foreign Exchange Rate: US Dollar data is updated yearly, averaging 1.155 USD/EUR from Dec 2017 (Median) to 2018, with 2 observations. The data reached an all-time high of 1.180 USD/EUR in 2018 and a record low of 1.130 USD/EUR in 2017. Luxembourg STATEC Forecast: Foreign Exchange Rate: US Dollar data remains active status in CEIC and is reported by The Portal of Statistics of Luxembourg. The data is categorized under Global Database’s Luxembourg – Table LU.M009: Foreign Exchange Rate: Forecast: The Portal of Statistics of Luxembourg.

Between 2025 and 2028, the U.S. dollar to Polish zloty exchange rate in Poland will maintain a stable value of 3.8453 zloty for one U.S. dollar.

Forecast: Currency Handling Machines Sales in the US 2024 - 2028 Discover more data with ReportLinker!

Money Supply M0 in the United States decreased to 5648600 USD Million in May from 5732900 USD Million in April of 2025. This dataset provides - United States Money Supply M0 - actual values, historical data, forecast, chart, statistics, economic calendar and news.

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