62 datasets found
  1. T

    Russia Stock Market Index MOEX CFD Data

    • tradingeconomics.com
    • ko.tradingeconomics.com
    • +12more
    csv, excel, json, xml
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    TRADING ECONOMICS, Russia Stock Market Index MOEX CFD Data [Dataset]. https://tradingeconomics.com/russia/stock-market
    Explore at:
    json, csv, excel, xmlAvailable 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
    Sep 22, 1997 - Jul 11, 2025
    Area covered
    Russia
    Description

    Russia's main stock market index, the MOEX, fell to 2642 points on July 11, 2025, losing 3.31% from the previous session. Over the past month, the index has declined 3.94% and is down 11.21% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Russia. Russia Stock Market Index MOEX CFD - values, historical data, forecasts and news - updated on July of 2025.

  2. T

    Moscow Exchange | MOEX - Stock Price | Live Quote | Historical Chart

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 28, 2017
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    TRADING ECONOMICS (2017). Moscow Exchange | MOEX - Stock Price | Live Quote | Historical Chart [Dataset]. https://tradingeconomics.com/moex:rm
    Explore at:
    json, xml, csv, 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
    Description

    Moscow Exchange stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

  3. Weekly MOEX performance Russia 2020-2025

    • statista.com
    Updated Jan 30, 2025
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    Statista (2025). Weekly MOEX performance Russia 2020-2025 [Dataset]. https://www.statista.com/statistics/1254381/weekly-performance-moex/
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    Dataset updated
    Jan 30, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 5, 2020 - Jan 26, 2025
    Area covered
    Russia
    Description

    The MOEX index, the most prominent ruble-denominated index of stocks listed on the Moscow Stock Exchange, fell by nearly one third of its value between February 13 and February 20, 2022, following the Russian invasion of Ukraine. It has since fluctuated significantly and stood at 2,953.2 as of January 26, 2025. The MOEX index is considered the primary index for domestic investors in Russia. It contains the same components as the RTS index, however the latter is denominated in U.S. dollars and therefore preferred by many international investors.

  4. T

    Moscow Exchange | MOEX - PE Price to Earnings

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 15, 2024
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    TRADING ECONOMICS (2024). Moscow Exchange | MOEX - PE Price to Earnings [Dataset]. https://tradingeconomics.com/moex:rm:pe
    Explore at:
    xml, json, excel, csvAvailable download formats
    Dataset updated
    Jun 15, 2024
    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
    Description

    Moscow Exchange reported 7.46 in PE Price to Earnings for its fiscal quarter ending in June of 2024. Data for Moscow Exchange | MOEX - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last July in 2025.

  5. Will MOEX Index Continue its Ascent? (Forecast)

    • kappasignal.com
    Updated Sep 2, 2024
    + more versions
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    KappaSignal (2024). Will MOEX Index Continue its Ascent? (Forecast) [Dataset]. https://www.kappasignal.com/2024/09/will-moex-index-continue-its-ascent.html
    Explore at:
    Dataset updated
    Sep 2, 2024
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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 MOEX Index Continue its Ascent?

    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

  6. k

    Is MOEX Russia Index a Buy? (Forecast)

    • kappasignal.com
    Updated Sep 3, 2022
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    KappaSignal (2022). Is MOEX Russia Index a Buy? (Forecast) [Dataset]. https://www.kappasignal.com/2022/09/is-moex-russia-index-buy.html
    Explore at:
    Dataset updated
    Sep 3, 2022
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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.

    Is MOEX Russia Index a Buy?

    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

  7. T

    MOEX - Aktienkurs

    • de.tradingeconomics.com
    csv, excel, json, xml
    Updated Jul 15, 2025
    + more versions
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    TRADING ECONOMICS (2025). MOEX - Aktienkurs [Dataset]. https://de.tradingeconomics.com/indexcf:ind
    Explore at:
    json, csv, xml, excelAvailable download formats
    Dataset updated
    Jul 15, 2025
    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 15, 2025
    Area covered
    Russia
    Description

    Prices for MOEX - Aktienkurs including live quotes, historical charts and news. MOEX - Aktienkurs was last updated by Trading Economics this July 15 of 2025.

  8. What is MOEX Russia Index stock prediction? (Forecast)

    • kappasignal.com
    Updated Sep 6, 2022
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    KappaSignal (2022). What is MOEX Russia Index stock prediction? (Forecast) [Dataset]. https://www.kappasignal.com/2022/09/what-is-moex-russia-index-stock.html
    Explore at:
    Dataset updated
    Sep 6, 2022
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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.

    What is MOEX Russia Index stock 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

  9. T

    Moscow Exchange | MOEX - Dividend Yield

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Oct 15, 2024
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    TRADING ECONOMICS (2024). Moscow Exchange | MOEX - Dividend Yield [Dataset]. https://tradingeconomics.com/moex:rm:dy
    Explore at:
    xml, csv, excel, jsonAvailable download formats
    Dataset updated
    Oct 15, 2024
    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
    Description

    Moscow Exchange reported 7.23 in Dividend Yield for its fiscal quarter ending in October of 2024. Data for Moscow Exchange | MOEX - Dividend Yield including historical, tables and charts were last updated by Trading Economics this last July in 2025.

  10. T

    Moscow Exchange | MOEX - Assets

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Sep 15, 2024
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    TRADING ECONOMICS (2024). Moscow Exchange | MOEX - Assets [Dataset]. https://tradingeconomics.com/moex:rm:assets
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    Sep 15, 2024
    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 15, 2025
    Description

    Moscow Exchange reported RUB9.2T in Assets for its fiscal quarter ending in September of 2024. Data for Moscow Exchange | MOEX - Assets including historical, tables and charts were last updated by Trading Economics this last July in 2025.

  11. MOEX index forecast: Slight Volatility Predicted (Forecast)

    • kappasignal.com
    Updated Dec 22, 2024
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    KappaSignal (2024). MOEX index forecast: Slight Volatility Predicted (Forecast) [Dataset]. https://www.kappasignal.com/2024/12/moex-index-forecast-slight-volatility.html
    Explore at:
    Dataset updated
    Dec 22, 2024
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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.

    MOEX index forecast: Slight Volatility Predicted

    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

  12. T

    Moscow Exchange | MOEX - Market Capitalization

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Feb 11, 2018
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    TRADING ECONOMICS (2018). Moscow Exchange | MOEX - Market Capitalization [Dataset]. https://tradingeconomics.com/moex:rm:market-capitalization
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    Feb 11, 2018
    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 16, 2025
    Description

    Moscow Exchange reported RUB389.9B in Market Capitalization this July of 2025, considering the latest stock price and the number of outstanding shares.Data for Moscow Exchange | MOEX - Market Capitalization including historical, tables and charts were last updated by Trading Economics this last July in 2025.

  13. k

    MOEX: Rising Tide or Stormy Waters? (Forecast)

    • kappasignal.com
    Updated Mar 19, 2024
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    KappaSignal (2024). MOEX: Rising Tide or Stormy Waters? (Forecast) [Dataset]. https://www.kappasignal.com/2024/03/moex-rising-tide-or-stormy-waters.html
    Explore at:
    Dataset updated
    Mar 19, 2024
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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.

    MOEX: Rising Tide or Stormy Waters?

    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

  14. MOEX Rebounds Anticipated Following Recent Dip: Analyst Forecasts (Forecast)...

    • kappasignal.com
    Updated May 7, 2025
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    KappaSignal (2025). MOEX Rebounds Anticipated Following Recent Dip: Analyst Forecasts (Forecast) [Dataset]. https://www.kappasignal.com/2025/05/moex-rebounds-anticipated-following.html
    Explore at:
    Dataset updated
    May 7, 2025
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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.

    MOEX Rebounds Anticipated Following Recent Dip: Analyst Forecasts

    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

  15. MOEX: Where Will It Go Next? (Forecast)

    • kappasignal.com
    Updated Mar 24, 2024
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    KappaSignal (2024). MOEX: Where Will It Go Next? (Forecast) [Dataset]. https://www.kappasignal.com/2024/03/moex-where-will-it-go-next.html
    Explore at:
    Dataset updated
    Mar 24, 2024
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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.

    MOEX: Where Will It Go Next?

    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

  16. T

    Moscow Exchange | MOEX - Cost Of Sales

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Sep 15, 2021
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    TRADING ECONOMICS (2021). Moscow Exchange | MOEX - Cost Of Sales [Dataset]. https://tradingeconomics.com/moex:rm:cost-of-sales
    Explore at:
    json, xml, excel, csvAvailable download formats
    Dataset updated
    Sep 15, 2021
    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 16, 2025
    Description

    Moscow Exchange reported RUB207.5M in Cost of Sales for its fiscal quarter ending in September of 2021. Data for Moscow Exchange | MOEX - Cost Of Sales including historical, tables and charts were last updated by Trading Economics this last July in 2025.

  17. T

    Moscow Exchange | MOEX - Trade Creditors

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Sep 15, 2024
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    TRADING ECONOMICS (2024). Moscow Exchange | MOEX - Trade Creditors [Dataset]. https://tradingeconomics.com/moex:rm:trade-creditors
    Explore at:
    xml, excel, csv, jsonAvailable download formats
    Dataset updated
    Sep 15, 2024
    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 15, 2025
    Description

    Moscow Exchange reported RUB3.1B in Trade Creditors for its fiscal quarter ending in September of 2024. Data for Moscow Exchange | MOEX - Trade Creditors including historical, tables and charts were last updated by Trading Economics this last July in 2025.

  18. How do you predict if a stock will go up or down? (MOEX Russia Index Stock...

    • kappasignal.com
    Updated Oct 25, 2022
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    KappaSignal (2022). How do you predict if a stock will go up or down? (MOEX Russia Index Stock Prediction) (Forecast) [Dataset]. https://www.kappasignal.com/2022/10/how-do-you-predict-if-stock-will-go-up_97.html
    Explore at:
    Dataset updated
    Oct 25, 2022
    Dataset authored and provided by
    KappaSignal
    License

    https://www.kappasignal.com/p/legal-disclaimer.htmlhttps://www.kappasignal.com/p/legal-disclaimer.html

    Description

    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.

    How do you predict if a stock will go up or down? (MOEX Russia Index Stock 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

  19. T

    Moscow Exchange | MOEX - Ebit

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Jun 15, 2023
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    TRADING ECONOMICS (2023). Moscow Exchange | MOEX - Ebit [Dataset]. https://tradingeconomics.com/moex:rm:ebit
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Jun 15, 2023
    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 15, 2025
    Description

    Moscow Exchange reported RUB15.37B in EBIT for its fiscal quarter ending in June of 2023. Data for Moscow Exchange | MOEX - Ebit including historical, tables and charts were last updated by Trading Economics this last July in 2025.

  20. T

    Moscow Exchange | MOEX - Net Income

    • tradingeconomics.com
    csv, excel, json, xml
    Updated Sep 15, 2024
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    TRADING ECONOMICS (2024). Moscow Exchange | MOEX - Net Income [Dataset]. https://tradingeconomics.com/moex:rm:net-income
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Sep 15, 2024
    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
    Description

    Moscow Exchange reported RUB23.03B in Net Income for its fiscal quarter ending in September of 2024. Data for Moscow Exchange | MOEX - Net Income including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Share
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TwitterTwitter
Email
Click to copy link
Link copied
Close
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TRADING ECONOMICS, Russia Stock Market Index MOEX CFD Data [Dataset]. https://tradingeconomics.com/russia/stock-market

Russia Stock Market Index MOEX CFD Data

Russia Stock Market Index MOEX CFD - Historical Dataset (1997-09-22/2025-07-11)

Explore at:
7 scholarly articles cite this dataset (View in Google Scholar)
json, csv, excel, xmlAvailable 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
Sep 22, 1997 - Jul 11, 2025
Area covered
Russia
Description

Russia's main stock market index, the MOEX, fell to 2642 points on July 11, 2025, losing 3.31% from the previous session. Over the past month, the index has declined 3.94% and is down 11.21% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Russia. Russia Stock Market Index MOEX CFD - values, historical data, forecasts and news - updated on July of 2025.

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