9 datasets found
  1. T

    Japan Stock Market Index (JP225) Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    Japan Stock Market Index (JP225) Data [Dataset]. https://tradingeconomics.com/japan/stock-market
    Explore at:
    excel, csv, xml, jsonAvailable download formats
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 5, 1965 - Jul 14, 2025
    Area covered
    Japan
    Description

    Japan's main stock market index, the JP225, fell to 39432 points on July 14, 2025, losing 0.35% from the previous session. Over the past month, the index has climbed 2.93%, though it remains 4.47% 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.

  2. Opinion on the possibility of major stock markets crashing Japan 2020

    • statista.com
    Updated Jul 11, 2025
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    Statista (2024). Opinion on the possibility of major stock markets crashing Japan 2020 [Dataset]. https://www.statista.com/statistics/1045611/japan-likelihood-major-stock-markets-crash/
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    Dataset updated
    Jul 11, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Nov 26, 2019 - Dec 6, 2019
    Area covered
    Japan
    Description

    According to a survey conducted by Ipsos on predictions for global issues, approximately ** percent of Japanese respondents believed it was likely that major stock markets around the world would crash in 2020. The results of the survey showed that about ** percent of respondents worldwide thought that the crash of major global stock markets was likely in 2020.

  3. J

    Japan Stock market capitalization, in dollars - data, chart |...

    • theglobaleconomy.com
    csv, excel, xml
    Updated Nov 20, 2016
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    Globalen LLC (2016). Japan Stock market capitalization, in dollars - data, chart | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/Japan/stock_market_capitalization_dollars/
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    xml, excel, csvAvailable download formats
    Dataset updated
    Nov 20, 2016
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1975 - Dec 31, 2022
    Area covered
    Japan
    Description

    Japan: Stock market capitalization, billion USD: The latest value from 2022 is 5380.48 billion U.S. dollars, a decline from 6544.3 billion U.S. dollars in 2021. In comparison, the world average is 1244.55 billion U.S. dollars, based on data from 74 countries. Historically, the average for Japan from 1975 to 2022 is 3052.32 billion U.S. dollars. The minimum value, 21.53 billion U.S. dollars, was reached in 1977 while the maximum of 6718.22 billion U.S. dollars was recorded in 2020.

  4. D

    Data from: Scale-Dependent Inverse Temperature Features Associated with...

    • researchdata.ntu.edu.sg
    Updated Feb 17, 2025
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    DR-NTU (Data) (2025). Scale-Dependent Inverse Temperature Features Associated with Crashes in the US and Japanese Stock Markets [Dataset]. http://doi.org/10.21979/N9/6RNYM0
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    txt(120), txt(80), txt(610), txt(1702), txt(12258), txt(580), txt(570), txt(11992), txt(11991), txt(14620), txt(12201), application/x-ipynb+json(6940), rtf(1036), text/x-matlab(2694), txt(2541), text/x-matlab(17159), txt(12367), txt(730), txt(12852), text/x-matlab(1788), text/x-matlab(3283), text/x-matlab(3305), txt(12315), text/x-matlab(17900)Available download formats
    Dataset updated
    Feb 17, 2025
    Dataset provided by
    DR-NTU (Data)
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Area covered
    United States
    Dataset funded by
    Ministry of Education (MOE)
    Description

    Paper accepted by the Complexity Journal.

  5. H

    The Japanese Economy in Crises: A Time Series Segmentation Study [Dataset]

    • dataverse.harvard.edu
    Updated Oct 30, 2013
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    Ann Ann Cheong; Robert Paulo Fornia; Gladys Hui Ting Lee; Jun Liang Kok; Woei Shyr Yim; Danny Yuan Xu; Yiting Zhang (2013). The Japanese Economy in Crises: A Time Series Segmentation Study [Dataset] [Dataset]. http://doi.org/10.7910/DVN/LOGDTV
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Oct 30, 2013
    Dataset provided by
    Harvard Dataverse
    Authors
    Ann Ann Cheong; Robert Paulo Fornia; Gladys Hui Ting Lee; Jun Liang Kok; Woei Shyr Yim; Danny Yuan Xu; Yiting Zhang
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Time period covered
    1996 - 2010
    Area covered
    Japan
    Description

    We performed a comprehensive time series segmentation study on the 36 Nikkei Jap anese industry indices from 1 January 1996 to 11 June 2010. From the temporal distributions of the clustered segments, we found that the Japanese economy never fully recovered from the extended 1997–2003 crisis, and responded to the most recent global financial crisis in five stages. Of these, the second and main stage affecting 21 industries lasted only 27 days, in contrast to the two-and-a-half-years across-the-board recovery from the 1997–2003 financial crisis. We constructed the minimum spanning trees (MSTs) to visualize the Pearson cross correlations between Japanese industries over five macroeconomic periods: (i) 1997–1999 (Asian Financial Crisis), (ii) 2000–2002 (Technology Bubble Crisis), (iii) 2003–2006 (economic growth), (iv) 2007–2008 (Subprime Crisis), and (iv) 2008–2010 (Lehman Brothers Crisis). In these MSTs, the Chemicals and Electric Machinery industries are consistently hubs. Finally, we present evidence from the segment-to-segment MSTs for flights to quality within the Japanese stock market.

  6. f

    Data_Sheet_1_Research on the dynamic spillover of stock markets under...

    • figshare.com
    zip
    Updated Jun 1, 2023
    + more versions
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    Baicheng Zhou; Qingshu Yin; Shu Wang; Tianye Li (2023). Data_Sheet_1_Research on the dynamic spillover of stock markets under COVID-19—Taking the stock markets of China, Japan, and South Korea as an example.ZIP [Dataset]. http://doi.org/10.3389/fpubh.2022.1008348.s001
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Frontiers
    Authors
    Baicheng Zhou; Qingshu Yin; Shu Wang; Tianye Li
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    South Korea, China, Japan
    Description

    Examining stock market interactions between China (mainland China and Hong Kong), Japan, and South Korea, this study employs a framework that includes 239 economic variables to identify the spillover effects among these three countries, and empirically simulates the dynamic time-varying non-linear relationship between the stock markets of different countries. The findings are that in recent decades, China's stock market relied on Hong Kong's as a window to the exchange of price information with Japan and South Korea. More recently, the China stock market's spillover effect on East Asia has expanded. The spread of the crisis has strengthened co-movement between the stock markets of China, Japan, and South Korea.

  7. f

    S1 Data -

    • plos.figshare.com
    xlsx
    Updated Jan 25, 2024
    + more versions
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    Xiaoyang Wang; Hui Guo; Muhammad Waris; Badariah Haji Din (2024). S1 Data - [Dataset]. http://doi.org/10.1371/journal.pone.0296712.s001
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    xlsxAvailable download formats
    Dataset updated
    Jan 25, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Xiaoyang Wang; Hui Guo; Muhammad Waris; Badariah Haji Din
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The growing trend of interdependence between the international stock markets indicated the amalgamation of risk across borders that plays a significant role in portfolio diversification by selecting different assets from the financial markets and is also helpful for making extensive economic policy for the economies. By applying different methodologies, this study undertakes the volatility analysis of the emerging and OECD economies and analyzes the co-movement pattern between them. Moreover, with that motive, using the wavelet approach, we provide strong evidence of the short and long-run risk transfer over different time domains from Malaysia to its trading partners. Our findings show that during the Asian financial crisis (1997–98), Malaysia had short- and long-term relationships with China, Germany, Japan, Singapore, the UK, and Indonesia due to both high and low-frequency domains. Meanwhile, after the Global financial crisis (2008–09), it is being observed that Malaysia has long-term and short-term synchronization with emerging (China, India, Indonesia), OECD (Germany, France, USA, UK, Japan, Singapore) stock markets but Pakistan has the low level of co-movement with Malaysian stock market during the global financial crisis (2008–09). Moreover, it is being seen that Malaysia has short-term at both high and low-frequency co-movement with all the emerging and OECD economies except Japan, Singapore, and Indonesia during the COVID-19 period (2020–21). Japan, Singapore, and Indonesia have long-term synchronization relationships with the Malaysian stock market at high and low frequencies during COVID-19. While in a leading-lagging relationship, Malaysia’s stock market risk has both leading and lagging behavior with its trading partners’ stock market risk in the selected period; this behavior changes based on the different trade and investment flow factors. Moreover, DCC-GARCH findings shows that Malaysian market has both short term and long-term synchronization with trading partners except USA. Conspicuously, the integration pattern seems that the cooperation development between stock markets matters rather than the regional proximity in driving the cointegration. The study findings have significant implications for investors, governments, and policymakers around the globe.

  8. f

    Data_Sheet_4_Research on the dynamic spillover of stock markets under...

    • frontiersin.figshare.com
    zip
    Updated Jun 9, 2023
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    Baicheng Zhou; Qingshu Yin; Shu Wang; Tianye Li (2023). Data_Sheet_4_Research on the dynamic spillover of stock markets under COVID-19—Taking the stock markets of China, Japan, and South Korea as an example.ZIP [Dataset]. http://doi.org/10.3389/fpubh.2022.1008348.s004
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 9, 2023
    Dataset provided by
    Frontiers
    Authors
    Baicheng Zhou; Qingshu Yin; Shu Wang; Tianye Li
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    South Korea, Japan, China
    Description

    Examining stock market interactions between China (mainland China and Hong Kong), Japan, and South Korea, this study employs a framework that includes 239 economic variables to identify the spillover effects among these three countries, and empirically simulates the dynamic time-varying non-linear relationship between the stock markets of different countries. The findings are that in recent decades, China's stock market relied on Hong Kong's as a window to the exchange of price information with Japan and South Korea. More recently, the China stock market's spillover effect on East Asia has expanded. The spread of the crisis has strengthened co-movement between the stock markets of China, Japan, and South Korea.

  9. T

    USDJPY US Dollar Japanese Yen - Currency Exchange Rate Live Price Chart

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 28, 2017
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    TRADING ECONOMICS (2017). USDJPY US Dollar Japanese Yen - Currency Exchange Rate Live Price Chart [Dataset]. https://tradingeconomics.com/usdjpy:cur
    Explore at:
    csv, xml, json, excelAvailable download formats
    Dataset updated
    May 28, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2000 - Jul 14, 2025
    Area covered
    Japan
    Description

    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 14 of 2025.

  10. Not seeing a result you expected?
    Learn how you can add new datasets to our index.

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Japan Stock Market Index (JP225) Data [Dataset]. https://tradingeconomics.com/japan/stock-market

Japan Stock Market Index (JP225) Data

Japan Stock Market Index (JP225) - Historical Dataset (1965-01-05/2025-07-14)

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13 scholarly articles cite this dataset (View in Google Scholar)
excel, csv, xml, jsonAvailable download formats
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jan 5, 1965 - Jul 14, 2025
Area covered
Japan
Description

Japan's main stock market index, the JP225, fell to 39432 points on July 14, 2025, losing 0.35% from the previous session. Over the past month, the index has climbed 2.93%, though it remains 4.47% 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.

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