Japan's main stock market index, the JP225, fell to 39570 points on July 11, 2025, losing 0.19% from the previous session. Over the past month, the index has climbed 3.66%, though it remains 3.94% lower than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on July of 2025.

Prices for Japan Stock Market Index (JP225) including live quotes, historical charts and news. Japan Stock Market Index (JP225) was last updated by Trading Economics this July 12 of 2025.

The Nikkei 225 Index reached an all-time high of ********* on *************. This was the highest value since the index peaked at ********* in 1989. The Nikkei 225 is a price-weighted stock market index that has been calculated by the Nihon Keizai Shimbun (Nikkei) newspaper since 1950. It comprises 225 constituents listed on the Prime Market of the Tokyo Stock Exchange (TSE).

Graph and download economic data for Nikkei Stock Average, Nikkei 225 (NIKKEI225) from 1949-05-16 to 2025-07-11 about stocks, stock market, Japan, and indexes.

The Nikkei Stock Average (Nikkei 225) closed at ********* points in June 2025. In February 2024, the index surpassed an all-time high recorded in 1989. The Nikkei 225 is a price-weighted stock market index that has been calculated by the Nihon Keizai Shimbun (Nikkei) newspaper since 1950. It comprises 225 constituents listed on the Prime Market of the Tokyo Stock Exchange (TSE).

In 2024, the Nikkei 225 index closed at ********* points. The index surpassed a 34-year-old record in February and reached a new all-time high in July 2024. The Nikkei 225 is a price-weighted stock market index that has been calculated by the Nihon Keizai Shimbun (Nikkei) newspaper since 1950. It comprises 225 constituents listed on the Prime Market of the Tokyo Stock Exchange.

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.

Will the Nikkei 225 Index Recover?

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

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: Rising Tide or Ticking Time Bomb?

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

Japan OSE: Open Interest: Nikkei 225 Options data was reported at 2,254,097.000 Unit in Oct 2018. This records an increase from the previous number of 2,113,535.000 Unit for Sep 2018. Japan OSE: Open Interest: Nikkei 225 Options data is updated monthly, averaging 560,663.000 Unit from Jun 1989 (Median) to Oct 2018, with 353 observations. The data reached an all-time high of 4,746,092.000 Unit in May 2013 and a record low of 12,962.000 Unit in Jun 1989. Japan OSE: Open Interest: Nikkei 225 Options data remains active status in CEIC and is reported by Japan Exchange Group. The data is categorized under Global Database’s Japan – Table JP.Z016: Osaka Exchange Inc: Futures and Options.

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 Target Price Prediction

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

Predictions indicate a sustained upward trend for the Nikkei 225 index. Positive global economic conditions, strong corporate earnings, and government stimulus measures are expected to support growth. However, potential risks include geopolitical tensions, interest rate hikes, and supply chain disruptions, which could lead to volatility and a slowdown in growth.

Nikkei 225 Futures: Trading Val: Purchases: Brokerage data was reported at 5,709,267.240 JPY mn in 16 Jul 2018. This records a decrease from the previous number of 8,177,573.299 JPY mn for 09 Jul 2018. Nikkei 225 Futures: Trading Val: Purchases: Brokerage data is updated weekly, averaging 6,753,366.406 JPY mn from Jan 2014 (Median) to 16 Jul 2018, with 237 observations. The data reached an all-time high of 26,349,900.540 JPY mn in 24 Aug 2015 and a record low of 1,721,668.953 JPY mn in 28 Dec 2015. Nikkei 225 Futures: Trading Val: Purchases: Brokerage data remains active status in CEIC and is reported by Japan Exchange Group. The data is categorized under Global Database’s Japan – Table JP.Z033: Nikkei 225 Futures: Trading by Type of Investor.

Japan OSE: Open Interest: Nikkei 225 Futures data was reported at 430,092.000 Unit in Oct 2018. This records an increase from the previous number of 420,954.000 Unit for Sep 2018. Japan OSE: Open Interest: Nikkei 225 Futures data is updated monthly, averaging 288,782.000 Unit from Sep 1988 (Median) to Oct 2018, with 362 observations. The data reached an all-time high of 567,770.000 Unit in May 2013 and a record low of 13,506.000 Unit in Sep 1988. Japan OSE: Open Interest: Nikkei 225 Futures data remains active status in CEIC and is reported by Japan Exchange Group. The data is categorized under Global Database’s Japan – Table JP.Z016: Osaka Exchange Inc: Futures and Options.

Tick (trades only) sample data for Nikkei 225 - OSE JNK timestamped in Chicago time

Intraday 1 minute sample data for Mini Nikkei 225 - OSE MJNK 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.

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

Download Historical Nikkei 225 Index Indicies Data. CQG daily, 1 minute, tick, and level 1 data from 1899.

Nikkei 225 Futures: Trading Vol: Balance: Fin Inst: Ins Cos data was reported at 2.000 Unit in 16 Jul 2018. This records a decrease from the previous number of 61.000 Unit for 09 Jul 2018. Nikkei 225 Futures: Trading Vol: Balance: Fin Inst: Ins Cos data is updated weekly, averaging 160.000 Unit from Jan 2014 (Median) to 16 Jul 2018, with 237 observations. The data reached an all-time high of 16,394.000 Unit in 05 Sep 2016 and a record low of 0.000 Unit in 25 Jun 2018. Nikkei 225 Futures: Trading Vol: Balance: Fin Inst: Ins Cos data remains active status in CEIC and is reported by Japan Exchange Group. The data is categorized under Global Database’s Japan – Table JP.Z033: Nikkei 225 Futures: Trading by Type of Investor.

Nikkei 225 Futures: Trading Val: Balance: Fin Inst: City&Reg Banks data was reported at 162,601.526 JPY mn in 19 Nov 2018. This records a decrease from the previous number of 220,186.513 JPY mn for 12 Nov 2018. Nikkei 225 Futures: Trading Val: Balance: Fin Inst: City&Reg Banks data is updated weekly, averaging 126,637.910 JPY mn from Jan 2014 (Median) to 19 Nov 2018, with 255 observations. The data reached an all-time high of 435,836.873 JPY mn in 07 Nov 2016 and a record low of 2,210.850 JPY mn in 29 Dec 2014. Nikkei 225 Futures: Trading Val: Balance: Fin Inst: City&Reg Banks data remains active status in CEIC and is reported by Japan Exchange Group. The data is categorized under Global Database’s Japan – Table JP.Z033: Nikkei 225 Futures: Trading by Type of Investor.

Japan Nikkei 225 Futures: Trading Val: Sales: Fin Inst: Other Fin Inst data was reported at 4,155.910 JPY mn in 16 Jul 2018. This records a decrease from the previous number of 9,118.240 JPY mn for 09 Jul 2018. Japan Nikkei 225 Futures: Trading Val: Sales: Fin Inst: Other Fin Inst data is updated weekly, averaging 2,116.460 JPY mn from Jan 2014 (Median) to 16 Jul 2018, with 237 observations. The data reached an all-time high of 20,705.430 JPY mn in 07 Nov 2016 and a record low of 0.000 JPY mn in 26 Sep 2016. Japan Nikkei 225 Futures: Trading Val: Sales: Fin Inst: Other Fin Inst data remains active status in CEIC and is reported by Japan Exchange Group. The data is categorized under Global Database’s Japan – Table JP.Z033: Nikkei 225 Futures: Trading by Type of Investor.