Browse LSEG's MSCI Global Equity Indexes and gain extensive equity market coverage for over 75 countries in the developed, emerging and frontier markets.

United States New York Stock Exchange: Index: MSCI US Real Estate Index data was reported at 232.090 NA in May 2024. This stayed constant from the previous number of 232.090 NA for Apr 2024. United States New York Stock Exchange: Index: MSCI US Real Estate Index data is updated monthly, averaging 217.340 NA from Dec 2012 (Median) to May 2024, with 138 observations. The data reached an all-time high of 333.710 NA in Dec 2021 and a record low of 159.970 NA in Aug 2013. United States New York Stock Exchange: Index: MSCI US Real Estate Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: MSCI: Monthly.

"ESG-Risikoeinstufungen, Scores, Informationen zur geschäftlichen Einbindung und zum Produktinvolvement sowie Kontroversen über Unternehmen und Staaten werden von Asset und Wealth Managern verwendet. Dieses Datenpaket entspricht dem Basispaket von MSCI. Diese Informationen helfen unseren Kunden, ESG-Aspekte in ihre Anlageentscheidungen miteinzubeziehen, Nachhaltigkeitsrisiken in Anlageportfolios zu überwachen und Anlegern über ESG-Aspekte zu berichten. Dieser von MSCI bezogene ESG Datensatz erweitert das ESG RegRisk und andere SIX ESG Datenangebote. Dieses Paket entspricht dem MSCI ESG Fund Metrics-Paket, liefert aber anstelle von Fondsdaten Unternehmensdaten."

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

United States New York Stock Exchange: Index: MSCI US Gross Total Return data was reported at 25,491.880 NA in Apr 2025. This records a decrease from the previous number of 25,623.120 NA for Mar 2025. United States New York Stock Exchange: Index: MSCI US Gross Total Return data is updated monthly, averaging 11,158.379 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 27,650.960 NA in Jan 2025 and a record low of 4,706.759 NA in Jan 2012. United States New York Stock Exchange: Index: MSCI US Gross Total Return data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: MSCI: Monthly.

MSCI World index is predicted to experience a moderate increase. The predicted range for the index is between a slight increase and a significant increase. The risk associated with this prediction is moderate, as there are some factors that could potentially impact the index's performance.

MSCI Barra Models are leading risk models backed by over 40 years of factor data and now leverage Systematic Equity Strategy factors. Get access via LSEG.

Msci reported 38.72 in PE Price to Earnings for its fiscal quarter ending in March of 2025. Data for Msci | MSCI - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last July in 2025.

There is an increasing demand for high quality data on the UN 17 Sustainable Development Goals (SDGs) to report to clients, or to address clients' demands to support investments aligned with these goals. SIX offers the MSCI SDG/Impact Data, which is designed to provide a holistic view of companies’ net contribution, both positive and negative, towards addressing each of the 17 UN SDGs, and to support clients' unique impact investing goals and priorities.

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.

MSCI World Index Forecast: Mixed Outlook

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

United States New York Stock Exchange: Index: MSCI US REIT Index data was reported at 1,271.220 NA in Apr 2025. This records a decrease from the previous number of 1,306.750 NA for Mar 2025. United States New York Stock Exchange: Index: MSCI US REIT Index data is updated monthly, averaging 1,147.546 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 1,577.230 NA in Dec 2021 and a record low of 835.504 NA in Feb 2012. United States New York Stock Exchange: Index: MSCI US REIT Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: MSCI: Monthly.

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.

MSCI World: Where Will it Take Us?

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

Msci reported $4.55B in Debt for its fiscal quarter ending in March of 2025. Data for Msci | MSCI - Debt including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Msci reported $4 in EPS Earnings Per Share for its fiscal quarter ending in March of 2025. Data for Msci | MSCI - EPS Earnings Per Share including historical, tables and charts were last updated by Trading Economics this last July in 2025.

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.

MSCI World: Reflecting Global Economic Trends or Inflated Valuations?

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

Browse MSCI World NTR (EUR) Index Futures (ESI) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

ICE Futures US iMpact is the primary data feed for ICE Futures US and covers the majority of trading in agricultural commodities, including sugar, coffee, cotton, and cocoa futures and options. This comprehensive market data feed also includes financial products such as equity indexes, currencies, and US Treasury futures contracts. The dataset provides complete market depth information across all listed outrights, spreads, options, and options combinations for every expiration month. ICE Futures US represents one of the most significant exchanges for US-based agricultural and financial derivatives, offering essential price discovery and risk management tools for global market participants.

Asset class: Futures, Options

Origin: Captured at Aurora DC3 with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP

Supported data encodings: DBN, CSV, JSON (Learn more)

Supported market data schemas: MBO, MBP-1, MBP-10, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics (Learn more)

Resolution: Immediate publication, nanosecond-resolution timestamps

As of 2024, Sustainalytics was the third most popular source for Environmental, Social, and Governance (ESG) data among institutional investors. Bloomberg ranked second, with ** percent of survey respondents stating they used this source for ESG data. MSCI was the leading source among institutional investors surveyed, with ** percent of investors having a preference for this source.

Download Historical MSCI Singapore Stock Index Futures Data. CQG daily, 1 minute, tick, and level 1 data from 1899.

The Environmental Sustainability Materiality Map dataset is a structured and curated collection of data derived from the MSCI Industry Materiality Map. MSCI ESG Ratings evaluate companies' resilience to long-term, financially relevant environmental, social, and governance (ESG) risks. The MSCI ESG Industry Materiality Map is a visual representation of the current ESG Key Issues and their significance to companies' ESG Ratings. This map is part of MSCI's ESG Ratings transparency initiatives, which aim to make ESG Ratings of companies and funds accessible to the public. The dataset includes structured data collected from the MSCI Materiality Map, showcasing the most relevant ESG Key Issues for each industry and their contribution to companies' overall ESG Ratings. This dataset aims to provide researchers, investors, and policymakers with valuable insights into the social sustainability aspects of various industries and the factors that contribute to their ESG Ratings. Data Collection Process: The data for the Environmental Sustainability Materiality Map dataset was collected from the publicly available MSCI Industry Materiality Map. The information was then structured and organized to create a comprehensive dataset that highlights the most relevant ESG Key Issues for each industry and their contribution to companies' ESG Ratings. Link: MSCI Industry Materiality Map

United States New York Stock Exchange: Index: MSCI US Growth Index Net Total Return data was reported at 24,589.422 NA in Apr 2025. This records an increase from the previous number of 23,991.494 NA for Mar 2025. United States New York Stock Exchange: Index: MSCI US Growth Index Net Total Return data is updated monthly, averaging 8,873.335 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 27,433.036 NA in Jan 2025 and a record low of 3,519.068 NA in Jan 2012. United States New York Stock Exchange: Index: MSCI US Growth Index Net Total Return data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: MSCI: Monthly.