Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Key information about Russia RTS
The statistic shows the annual development of the MOEX (RUB) Russia index from 2013 to 2023. MOEX (Moscow Interbank Currency Exchange) is the leading Russian Stock Exchange index, reflecting the performance of the 50 largest and most liquid companies traded on the Moscow Stock Exchange. The year-end value of IMOEX amounted to 2,883.04 in 2024 - below the value registered at the end of the previous year.
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Stock market index in Russia, June, 2025 The most recent value is 190.94 points as of June 2025, no change compared to the previous value of 190.94 points. Historically, the average for Russia from September 1997 to June 2025 is 91.33 points. The minimum of 1.51 points was recorded in August 1998, while the maximum of 250.66 points was reached in October 2021. | TheGlobalEconomy.com
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Russia Equity Market Index: USD data was reported at 25.554 2010=100 in Apr 2025. This records a decrease from the previous number of 26.532 2010=100 for Mar 2025. Russia Equity Market Index: USD data is updated monthly, averaging 38.826 2010=100 from Sep 1995 (Median) to Apr 2025, with 356 observations. The data reached an all-time high of 196.583 2010=100 in May 2008 and a record low of 4.863 2010=100 in Jan 1999. Russia Equity Market Index: USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.GEM: Equity Market Index. Local equity market index valued in US$ terms
https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required
Graph and download economic data for Financial Market: Share Prices for Russia (SPASTT01RUQ661N) from Q4 1997 to Q1 2025 about Russia and stock market.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
El índice principal del mercado de valores de Rusia, el MOEX, subió a 2760 puntos el 23 de junio de 2025, aumentando un 0.31% con respecto a la sesión anterior. En el último mes, el índice ha subido un 2.22%, aunque sigue siendo un 11.20% más bajo que hace un año, según la negociación en un contrato por diferencia (CFD) que sigue este índice de referencia de Rusia. Los valores actuales, los datos históricos, las previsiones, estadísticas, gráficas y calendario económico - Rusia - Mercado de acciones.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Key information about Russia Market Capitalization
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.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
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.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Russia Equity Market Index: Local Currency data was reported at 71.537 2010=100 in Apr 2025. This records a decrease from the previous number of 76.685 2010=100 for Mar 2025. Russia Equity Market Index: Local Currency data is updated monthly, averaging 68.584 2010=100 from Sep 1995 (Median) to Apr 2025, with 356 observations. The data reached an all-time high of 156.306 2010=100 in May 2008 and a record low of 3.360 2010=100 in Oct 1998. Russia Equity Market Index: Local Currency data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Russian Federation – Table RU.World Bank.GEM: Equity Market Index. Local equity market index valued in local currency unit (LCU) terms
In 2019, Gazprom accounted for over one quarter of the total contribution to the growth of the Russian stock market, or Russian Trading Index (RTS). The second leading contributor was Sberbank.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
The dataset contains statistics on trading volume and capitalization of Russian companies from the value of shares of the Moscow Exchange Index in 2015-2025.Датасет содержит статистику объема торгов и капитализации российских компаний от стоимости акций Индекса Мосбиржи в 2015-2025 гг.
https://deepfo.com/documentacion.php?idioma=enhttps://deepfo.com/documentacion.php?idioma=en
russian stock indexes. name, image, weighting method, type, date Foundation, Country, continent, Stock Market, Market capitalization, Website, legal entity
https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required
Graph and download economic data for Financial Market: Real Effective Exchange Rates: CPI Based for Russia (CCRETT01RUQ661N) from Q1 1993 to Q1 2025 about Russia, exchange rate, currency, CPI, manufacturing, real, rate, price index, indexes, and price.
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://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required
Graph and download economic data for Financial Market: Real Effective Exchange Rates: CPI Based for Russia (CCRETT01RUA661N) from 1993 to 2024 about Russia, exchange rate, currency, CPI, manufacturing, real, rate, price index, indexes, and price.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Russia: Financial markets development: The latest value from 2021 is 0.439 index points, a decline from 0.44 index points in 2020. In comparison, the world average is 0.239 index points, based on data from 158 countries. Historically, the average for Russia from 1984 to 2021 is 0.432 index points. The minimum value, 0 index points, was reached in 1984 while the maximum of 0.683 index points was recorded in 2009.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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.