Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The DXY exchange rate fell to 97.6499 on September 1, 2025, down 0.12% from the previous session. Over the past month, the United States Dollar has weakened 1.15%, and is down by 3.95% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on September of 2025.
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
https://www.ademcetinkaya.com/p/legal-disclaimer.htmlhttps://www.ademcetinkaya.com/p/legal-disclaimer.html
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The EUR/USD exchange rate rose to 1.1708 on September 1, 2025, up 0.21% from the previous session. Over the past month, the Euro US Dollar Exchange Rate - EUR/USD has strengthened 1.07%, and is up by 5.79% over the last 12 months. Euro US Dollar Exchange Rate - EUR/USD - values, historical data, forecasts and news - updated on September of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The USD/TWD exchange rate rose to 30.7630 on September 2, 2025, up 0.44% from the previous session. Over the past month, the Taiwanese Dollar has weakened 2.89%, but it's up by 4.17% over the last 12 months. Taiwanese Dollar - values, historical data, forecasts and news - updated on September of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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 September of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The EUR/USD exchange rate rose to 1.1715 on September 1, 2025, up 0.28% from the previous session. Over the past month, the Euro US Dollar Exchange Rate - EUR/USD has strengthened 1.13%, and is up by 5.86% over the last 12 months. Euro US Dollar Exchange Rate - EUR/USD - values, historical data, forecasts and news - updated on September of 2025.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The USD/CAD exchange rate rose to 1.3745 on September 1, 2025, up 0.08% from the previous session. Over the past month, the Canadian Dollar has strengthened 0.17%, but it's down by 1.83% over the last 12 months. Canadian Dollar - values, historical data, forecasts and news - updated on September of 2025.
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Russia MED Forecast: Foreign Exchange Rate: Year Average: US Dollar: Conservative 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: Conservative Scenario data is updated yearly, averaging 71.279 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: Conservative 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.
https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html
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.
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)
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)
Stock price prediction
Portfolio optimization
Algorithmic trading
Market sentiment analysis
Risk management
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
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
Between 2025 and 2028, the U.S. dollar to Polish zloty exchange rate in Poland will maintain a stable value of ****** zloty for one U.S. dollar.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Russia MED Forecast: Foreign Exchange Rate: Year Average: US Dollar: Target data was reported at 67.397 RUB/USD in 2020. This records an increase from the previous number of 65.974 RUB/USD for 2019. Russia MED Forecast: Foreign Exchange Rate: Year Average: US Dollar: Target data is updated yearly, averaging 64.239 RUB/USD from Dec 2016 (Median) to 2020, with 5 observations. The data reached an all-time high of 67.397 RUB/USD in 2020 and a record low of 58.014 RUB/USD in 2017. Russia MED Forecast: Foreign Exchange Rate: Year Average: US Dollar: Target 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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The AUD/USD exchange rate rose to 0.6552 on September 1, 2025, up 0.32% from the previous session. Over the past month, the Australian Dollar has strengthened 1.21%, but it's down by 3.46% over the last 12 months. Australian Dollar - values, historical data, forecasts and news - updated on September of 2025.
https://www.technavio.com/content/privacy-noticehttps://www.technavio.com/content/privacy-notice
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.
Major Market Trends & Insights
Europe dominated the market and accounted for a 47% growth during the forecast period.
By the Type - Reporting dealers segment was valued at USD 278.60 billion in 2023
By the Trade Finance Instruments - Currency swaps segment accounted for the largest market revenue share in 2023
Market Size & Forecast
Market Opportunities: USD 118.14 billion
Market Future Opportunities: USD 582.00 billion
CAGR : 10.6%
Europe: Largest market in 2023
Market Summary
The Foreign Exchange (Forex) market, a global financial platform for exchanging one currency for another, is a dynamic and continuously evolving ecosystem. According to the Bank for International Settlements, daily trading volumes reached approximately USD6 trillion in April 2020, representing a significant portion of the world's financial transactions. This market's importance is underscored by its role in facilitating international trade, investment, and tourism. The Forex market's decentralized nature allows for 24/7 trading opportunities, making it an attractive proposition for businesses and investors seeking to manage currency risk or capitalize on price fluctuations. Despite the market's complexity, advanced technologies, such as machine learning and artificial intelligence, are increasingly being adopted to enhance trading strategies and improve risk management.
One significant trend is the increasing use of money transfer agencies, venture capital investments, and mutual funds in foreign exchange transactions. These tools enable real-time analysis of market trends and help forecast exchange rates, providing valuable insights for businesses operating in multiple currencies. The Forex market's influence extends beyond traditional financial sectors, with applications in various industries, including tourism, import/export, and international business. As businesses expand their global footprint and economies continue to interconnect, the role and significance of the Forex market are set to grow further.
What will be the Size of the Foreign Exchange Market during the forecast period?
Explore market size, adoption trends, and growth potential for foreign exchange market Request Free Sample
The market, a vital component of the global financial system, operates without fail, facilitating the conversion of one currency into another. According to recent data, approximately 6% of daily global trading volume is attributed to this market. Looking ahead, growth is projected to reach over 5% annually. Consider the following comparison: the average daily trading volume in the forex market exceeds that of the New York Stock Exchange by a significant margin. In 2020, the former recorded around USD 6 trillion, while the latter saw approximately USD 136 billion. This disparity underscores the market's immense scale and influence.
Moreover, the forex market's liquidity depth enables efficient price discovery, minimizing transaction security concerns and market impact costs. Automated trading bots and order book depth analysis are essential tools for market participants, allowing for effective backtesting strategies and fraud detection systems. Leverage ratios, transaction fees, and margin requirements are essential factors influencing market accessibility and profitability. High-frequency trading and the presence of liquidity providers contribute to market efficiency and statistical arbitrage opportunities. Regulatory compliance and brokerage services further ensure a secure trading environment. Despite payment processing fees and order flow imbalance, risk tolerance levels remain a crucial consideration for participants.
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 intricate financial ecosystem where businesses and investors transact in various currencies to manage internationa
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The DXY exchange rate fell to 97.6499 on September 1, 2025, down 0.12% from the previous session. Over the past month, the United States Dollar has weakened 1.15%, and is down by 3.95% over the last 12 months. United States Dollar - values, historical data, forecasts and news - updated on September of 2025.