The main stock market index of United States, the US500, rose to 6327 points on July 23, 2025, gaining 0.27% from the previous session. Over the past month, the index has climbed 3.85% and is up 16.57% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United States. United States Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

China's main stock market index, the SHANGHAI, rose to 3606 points on July 24, 2025, gaining 0.65% from the previous session. Over the past month, the index has climbed 4.33% and is up 24.91% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from China. China Shanghai Composite Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

The statistic shows the development of the MSCI World USD Index from 1986 to 2024. The 2024 year-end value of the MSCI World USD index amounted to ******** points. MSCI World USD index – additional information The MSCI World Index, developed by Morgan Stanley Capital International (MSCI), is one of the most important stock indices. It includes stocks from developed countries all over the world and is regarded as benchmark of global stock market. According to MSCI, this index covers about ** percent of the free float-adjusted market capitalization in each country. As seen on the statistics above, in 2024, MSCI World USD index reported its highest value since 1986 amounting, a threefold increase from the figure recorded in 2013, when the year-end value of the MSCI World index was equal to ********. Along with the S&P Global Broad Market, the MSCI World is one of the most important global stock market performance indexes. Aside of including markets around the globe, these two indexes are global in a sense that they disregard where the companies are domiciled or traded, whereas other important indexes such as the Dow Jones Industrial Average, the Japanese index Nikkei 225, Wilshire 5000, the NASDAQ 100 index, have different approaches.

The goal of this project is to quantify, at the National scale, the relative susceptibility of the Nation's coast to sea-level rise through the use of a coastal vulnerability index (CVI). This initial classification is based upon the variables geomorphology, regional coastal slope, tide range, wave height, relative sea-level rise and shoreline erosion and accretion rates. The combination of these variables and the association of these variables to each other furnish a broad overview of regions where physical changes are likely to occur due to sea-level rise.

Russia Actual Diffusion Index: Orders: Enterprises with Rising Indicator over 1 Month data was reported at 40.000 % in Dec 2018. This records an increase from the previous number of 34.000 % for Nov 2018. Russia Actual Diffusion Index: Orders: Enterprises with Rising Indicator over 1 Month data is updated monthly, averaging 45.000 % from Dec 1991 (Median) to Dec 2018, with 325 observations. The data reached an all-time high of 62.000 % in Mar 2007 and a record low of 18.000 % in Dec 2008. Russia Actual Diffusion Index: Orders: Enterprises with Rising Indicator over 1 Month data remains active status in CEIC and is reported by Institute of World Economy and International Relations. The data is categorized under Russia Premium Database’s Business and Economic Survey – Table RU.SB002: Russian Economic Barometer: Enterprises Diffusion Indices: Actual.

The annual average consumer price index in the Dominican Republic was approximately 128.45 points in 2024. Following a continuous upward trend, the index has risen by around 127.39 points since 1980. Between 2024 and 2030, the index will rise by around 34.38 points, continuing its consistent upward trajectory.As defined by the International Monetary Fund, this indicator measures inflation on the basis of the average consumer price index. This index measure expresses a country's average level of prices based on a typical basket of consumer goods and services during a certain year. Typically a reference year exists for which a value of 100 had been assigned.

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 BEL 20 Index stock expected to rise?

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

Russia Actual Diffusion Index: Wages: Enterprises with Rising Indicator over 1 Month data was reported at 56.000 % in Dec 2018. This records an increase from the previous number of 43.000 % for Nov 2018. Russia Actual Diffusion Index: Wages: Enterprises with Rising Indicator over 1 Month data is updated monthly, averaging 54.000 % from Dec 1991 (Median) to Dec 2018, with 325 observations. The data reached an all-time high of 94.000 % in Jan 1992 and a record low of 24.000 % in Jan 2009. Russia Actual Diffusion Index: Wages: Enterprises with Rising Indicator over 1 Month data remains active status in CEIC and is reported by Institute of World Economy and International Relations. The data is categorized under Russia Premium Database’s Business and Economic Survey – Table RU.SB002: Russian Economic Barometer: Enterprises Diffusion Indices: Actual.

India's main stock market index, the SENSEX, rose to 82727 points on July 23, 2025, gaining 0.66% from the previous session. Over the past month, the index has climbed 0.82% and is up 3.22% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from India. BSE SENSEX Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

Graph and download economic data for Consumer Price Index for All Urban Consumers: Services Less Energy Services in U.S. City Average (CUSR0000SASLE) from Jan 1967 to Jun 2025 about energy, urban, consumer, services, CPI, inflation, price index, indexes, price, and USA.

The Dow Jones U.S. Telecommunications index is poised for a period of sustained growth, driven by the increasing adoption of 5G technology and the associated rise in demand for data and telecommunications services. The index is expected to experience a 6% increase in value over the next 12 months, with potential risks including economic uncertainty and regulatory changes.

Bombay Stock Exchange: Index: S&P BSE: SENSEX: Average data was reported at 35,298.947 1978-1979=100 in Nov 2018. This records an increase from the previous number of 34,518.844 1978-1979=100 for Oct 2018. Bombay Stock Exchange: Index: S&P BSE: SENSEX: Average data is updated monthly, averaging 5,648.982 1978-1979=100 from Jan 1990 (Median) to Nov 2018, with 347 observations. The data reached an all-time high of 38,061.525 1978-1979=100 in Aug 2018 and a record low of 678.846 1978-1979=100 in Feb 1990. Bombay Stock Exchange: Index: S&P BSE: SENSEX: Average data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Financial Market – Table IN.ZA002: Bombay Stock Exchange: Indices (Monthly).

Spain's main stock market index, the ES35, rose to 14068 points on July 23, 2025, gaining 0.19% from the previous session. Over the past month, the index has climbed 0.23% and is up 25.49% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Spain. Spain Stock Market Index (ES35) - values, historical data, forecasts and news - updated on July of 2025.

France's main stock market index, the FR40, fell to 7744 points on July 22, 2025, losing 0.69% from the previous session. Over the past month, the index has climbed 2.74% and is up 1.92% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from France. France Stock Market Index (FR40) - values, historical data, forecasts and news - updated on July of 2025.

The data have been filtered, e.g. by removing null records.

In August 2024, the global consumer price index, excluding the United States, stood at *****, compared to ***** for the U.S. The data for the world and emerging economies are distorted by hyperinflation in Venezuela and may not accurately reflect the inflation rate of other countries. However, Russia's war in Ukraine caused a surge in prices globally through 2022 and 2023. The headline consumer price index tracks the changes in the price level of a basket of goods and services purchased by households. Economic challenges in Argentina While CPI increases have been significant globally, certain economies have experienced more dramatic increases than others. Argentina is a notable case of these increases, as the CPI has increased more than *** percent between 2020 and 2023. Currently, most of the Argentinian public considers inflation and low wages to be the biggest challenges facing the country. Consumer responses to price increases Globally, consumers are coping with price increases in many ways. In a May 2023 survey, ** percent respondents from over 14 countries indicated they were more conscious about prices than previously. In another survey from earlier that year, over ** percent of respondents indicated they were most concerned about inflation and had changed their consumption habits as a result.

Analysis of ‘NIFTY-50 Stocks Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/iamsouravbanerjee/nifty50-stocks-dataset on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

The NIFTY 50 is a benchmark Indian stock market index that represents the weighted average of 50 of the largest Indian companies listed on the National Stock Exchange. It is one of the two main stock indices used in India, the other being the BSE SENSEX.

Nifty 50 is owned and managed by NSE Indices (previously known as India Index Services & Products Limited), which is a wholly-owned subsidiary of the NSE Strategic Investment Corporation Limited. NSE Indices had a marketing and licensing agreement with Standard & Poor's for co-branding equity indices until 2013. The Nifty 50 index was launched on 22 April 1996, and is one of the many stock indices of Nifty.

The NIFTY 50 index has shaped up to be the largest single financial product in India, with an ecosystem consisting of exchange-traded funds (onshore and offshore), exchange-traded options at NSE, and futures and options abroad at the SGX. NIFTY 50 is the world's most actively traded contract. WFE, IOM, and FIA surveys endorse NSE's leadership position.

The NIFTY 50 index covers 13 sectors (as of 30 April 2021) of the Indian economy and offers investment managers exposure to the Indian market in one portfolio. Between 2008 & 2012, the NIFTY 50 index's share of NSE's market capitalization fell from 65% to 29% due to the rise of sectoral indices like NIFTY Bank, NIFTY IT, NIFTY Pharma, NIFTY SERV SECTOR, NIFTY Next 50, etc. The NIFTY 50 Index gives a weightage of 39.47% to financial services, 15.31% to Energy, 13.01% to IT, 12.38% to consumer goods, 6.11% to Automobiles a and 0% to the agricultural sector.

The NIFTY 50 index is a free-float market capitalization weighted index. The index was initially calculated on a full market capitalization methodology. On 26 June 2009, the computation was changed to a free-float methodology. The base period for the NIFTY 50 index is 3 November 1995, which marked the completion of one year of operations of the National Stock Exchange Equity Market Segment. The base value of the index has been set at 1000 and a base capital of ₹ 2.06 trillion.

Content

In this Dataset, we have records of all the NIFTY-50 stocks along with various parameters.

Important Note

• % change is calculated with respect to adjusted price on ex-date for Dividend, Bonus, Rights & Face Value Split.
• 52 weeks high & 52 week low prices are adjusted for Bonus, Split & Rights Corporate actions.
• 365 days % Change and 30 days % Change values are adjusted With respect to corporate actions.

Acknowledgements

For more, you can visit the website of the National Stock Exchange of India Limited (NSE): https://www1.nseindia.com/

--- Original source retains full ownership of the source dataset ---

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 happens to gold if CPI increases?

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