The USD/JPY exchange rate fell to 149.4030 on September 26, 2025, down 0.26% from the previous session. Over the past month, the Japanese Yen has weakened 1.40%, and is down by 5.07% over the last 12 months. Japanese Yen - values, historical data, forecasts and news - updated on September of 2025.

Japan JP: Exchange Rate: National Currency per USD data was reported at 155.830 USD/JPY in Dec 2026. This stayed constant from the previous number of 155.830 USD/JPY for Sep 2026. Japan JP: Exchange Rate: National Currency per USD data is updated quarterly, averaging 138.131 USD/JPY from Mar 1960 (Median) to Dec 2026, with 268 observations. The data reached an all-time high of 362.802 USD/JPY in Sep 1963 and a record low of 77.324 USD/JPY in Dec 2011. Japan JP: Exchange Rate: National Currency per USD data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Japan – Table JP.OECD.EO: Exchange Rate: Forecast: OECD Member: Quarterly. EXCHUD - Exchange rate, national currency per USD

Prices for SGDJPY Singapore Dollar Japanese Yen including live quotes, historical charts and news. SGDJPY Singapore Dollar Japanese Yen was last updated by Trading Economics this September 28 of 2025.

New Zealand ANZ Forecast: Foreign Exchange Rate: Japan Yen data was reported at 58.900 NZD/JPY in Jun 2020. This records a decrease from the previous number of 59.500 NZD/JPY for Mar 2020. New Zealand ANZ Forecast: Foreign Exchange Rate: Japan Yen data is updated quarterly, averaging 74.400 NZD/JPY from Mar 2015 (Median) to Jun 2020, with 22 observations. The data reached an all-time high of 88.600 NZD/JPY in Jun 2015 and a record low of 58.900 NZD/JPY in Jun 2020. New Zealand ANZ Forecast: Foreign Exchange Rate: Japan Yen data remains active status in CEIC and is reported by ANZ Bank New Zealand. The data is categorized under Global Database’s New Zealand – Table NZ.M015: Foreign Exchange Rate: Forecast: ANZ Bank Ltd.

Sweden NIER Forecast: Exchange Rate: Japanese Yen data was reported at 7.300 SEK/100 JPY in 2023. This records a decrease from the previous number of 7.400 SEK/100 JPY for 2022. Sweden NIER Forecast: Exchange Rate: Japanese Yen data is updated yearly, averaging 6.300 SEK/100 JPY from Dec 1971 (Median) to 2023, with 53 observations. The data reached an all-time high of 8.500 SEK/100 JPY in 2012 and a record low of 1.400 SEK/100 JPY in 1975. Sweden NIER Forecast: Exchange Rate: Japanese Yen 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.

Prices for JPYIDR Japanese Yen Indonesian Rupiah including live quotes, historical charts and news. JPYIDR Japanese Yen Indonesian Rupiah was last updated by Trading Economics this September 27 of 2025.

The amount of Japanese yen that could be bought with USD kept increasing since September 2020. As of September 12, 2025, the exchange rate reached approximately 147.22 Japanese yen. 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 the end of the year.

Japan JP: Purchasing Power Parity: National Currency per USD data was reported at 94.927 USD/JPY in Dec 2026. This records an increase from the previous number of 94.884 USD/JPY for Sep 2026. Japan JP: Purchasing Power Parity: National Currency per USD data is updated quarterly, averaging 177.455 USD/JPY from Mar 1960 (Median) to Dec 2026, with 268 observations. The data reached an all-time high of 272.793 USD/JPY in Sep 1977 and a record low of 93.912 USD/JPY in Sep 2022. Japan JP: Purchasing Power Parity: National Currency per USD data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Japan – Table JP.OECD.EO: Exchange Rate: Forecast: OECD Member: Quarterly. PPP - Purchasing power parity, national currency per USD

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.

Japan's Nikkei Soars to 33-Year High on U.S. Debt Deal, Weak Yen

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

Prices for JPYTHB Japanese Yen Thai Baht including live quotes, historical charts and news. JPYTHB Japanese Yen Thai Baht was last updated by Trading Economics this September 28 of 2025.

In the fiscal year 2020, the value of the health technology market which is related to prevention and health control was forecast to reach around **** billion Japanese yen. The overall health technology market was forecast to increase to approximately *** billion yen by fiscal 2026. The digital healthcare market encompasses hardware, software, and services used for health, medical, and nursing care.

This dataset contains the predicted prices of Celo Japanese Yen for the upcoming years based on user-defined projections.

Prices for JPYPHP Japanese Yen Philippine Peso including live quotes, historical charts and news. JPYPHP Japanese Yen Philippine Peso was last updated by Trading Economics this September 28 of 2025.

Key information about Japan Exchange Rate against USD

• Japan Exchange Rate against USD averaged 137.053 (USD/JPY) in May 2023, compared with 133.475 USD/JPY in the previous month.
• Japan Exchange Rate against USD data is updated monthly, available from Jan 1957 to May 2023.
• The data reached an all-time high of 360.000 in Dec 1970 and a record low of 76.643 in Oct 2011.

• In the latest reports, Japan Short Term Interest Rate: Month End: TIBOR: Japanese Yen: 3 Months was reported at 0.075 % pa in May 2023.
• Its Long Term Interest Rate (Bonds Yield: Government Bonds: Newly Issued: 10 Years: Month End) was reported at 0.390 % pa in Apr 2023.
• The cash rate (Policy Rate: Month End: Japan: Complementary Deposit Facility Interest Rate) was set at -0.100 % pa in May 2023.

Forex: Monthly Avg: Singapore Dollars to Japanese Yen data was reported at 1.214 SGD/100 JPY in Nov 2018. This records a decrease from the previous number of 1.222 SGD/100 JPY for Oct 2018. Forex: Monthly Avg: Singapore Dollars to Japanese Yen data is updated monthly, averaging 1.368 SGD/100 JPY from Mar 1983 (Median) to Nov 2018, with 429 observations. The data reached an all-time high of 1.674 SGD/100 JPY in Apr 1995 and a record low of 0.866 SGD/100 JPY in Feb 1985. Forex: Monthly Avg: Singapore Dollars to Japanese Yen data remains active status in CEIC and is reported by Monetary Authority of Singapore. The data is categorized under Global Database’s Singapore – Table SG.M006: Foreign Exchange Rate.

Japan JP: Purchasing Power Parity: National Currency per USD: Single Hit Scenario data was reported at 103.079 USD/JPY in Dec 2021. This stayed constant from the previous number of 103.079 USD/JPY for Sep 2021. Japan JP: Purchasing Power Parity: National Currency per USD: Single Hit Scenario data is updated quarterly, averaging 184.999 USD/JPY from Mar 1960 (Median) to Dec 2021, with 248 observations. The data reached an all-time high of 272.344 USD/JPY in Sep 1977 and a record low of 101.103 USD/JPY in Sep 2013. Japan JP: Purchasing Power Parity: National Currency per USD: Single Hit Scenario data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Japan – Table JP.OECD.EO: Exchange Rate: Forecast: OECD Member: Quarterly. PPP - Purchasing power parity, national currency per USD

FocusEconomics' economic data is provided by official state statistical reporting agencies as well as our global network of leading banks, think tanks and consultancies. Our datasets provide not only historical data, but also Consensus Forecasts and individual forecasts from the aformentioned global network of economic analysts. This includes the latest forecasts as well as historical forecasts going back to 2010. Our global network consists of over 1000 world-renowned economic analysts from which we calculate our Consensus Forecasts. In this specific dataset you will find economic data for Japan Exchange Rate.

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.

Nikkei 225 Index Soars on Positive Economic Data and Weaker Yen

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 US Dollar Trading Signal dataset provides a near real-time assessment of market sentiment and trading direction for the U.S. dollar. The most recent update indicates a SELL signal with 85% confidence, driven by bearish developments over the last 24–48 hours. Key factors influencing this signal include: Macroeconomic weakness: U.S. consumer sentiment fell to a 15-month low while jobless claims rose, highlighting labour market softening. Monetary policy caution: The Federal Reserve’s restrained stance on interest rate cuts has added to investor uncertainty. Geopolitical pressures: Tariff announcements and ongoing tensions, alongside trade disruptions and sanctions, contributed to volatility. Cross-currency signals: The Japanese yen strengthened against the dollar, reinforcing bearish expectations. The dataset also categorises top themes—from political disruptions and sanctions, to monetary policy and employment data—and identifies influential events such as U.S.–Ukraine economic deals. For systematic traders, this data functions as a structured sentiment and event-driven input. It highlights how narratives around politics, economic releases, and central bank commentary can converge to produce leading indicators for FX strategy and risk management.

Philippines Forex: Month Average: Philippine Peso to Japanese Yen data was reported at 0.466 PHP/JPY in Nov 2018. This records a decrease from the previous number of 0.479 PHP/JPY for Oct 2018. Philippines Forex: Month Average: Philippine Peso to Japanese Yen data is updated monthly, averaging 0.346 PHP/JPY from Jan 1980 (Median) to Nov 2018, with 467 observations. The data reached an all-time high of 0.567 PHP/JPY in Jan 2012 and a record low of 0.030 PHP/JPY in Apr 1980. Philippines Forex: Month Average: Philippine Peso to Japanese Yen data remains active status in CEIC and is reported by Bangko Sentral ng Pilipinas. The data is categorized under Global Database’s Philippines – Table PH.M009: Foreign Exchange Rates.