16 datasets found
  1. Annual development of the Bloomberg Barclays MSCI Global Green Bond Index...

    • statista.com
    Updated Aug 21, 2024
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    Statista (2024). Annual development of the Bloomberg Barclays MSCI Global Green Bond Index 2015-2023 [Dataset]. https://www.statista.com/statistics/1109189/bloomberg-barclays-msci-global-green-bond-index-development/
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    Dataset updated
    Aug 21, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Green bond indices make it easier for investors to track the performance of green bonds and compare it with other investments. Bloomberg Barclays MSCI Global Green Bond Index was launched in 2014 with the aim provide a benchmark for the green bonds market. Between 2015 and 2020, the Bloomberg Barclays MSCI Global Green Bond Index saw an overall increase, reaching a value of 121.91 as of the end of 2020. By the end of 2022, however, the index value fell to 86.94, before increasing again to 96.09 by the end of 2023.

  2. 500 Richest People 2021

    • kaggle.com
    Updated May 13, 2021
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    Firat Gonen (2021). 500 Richest People 2021 [Dataset]. https://www.kaggle.com/frtgnn/500-richest-people-2021/discussion
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    May 13, 2021
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Firat Gonen
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Based on Bloomberg's Billionaires index...

    The Bloomberg Billionaires Index is a daily ranking of the world's richest people. In calculating net worth, Bloomberg News strives to provide the most transparent calculations available, and each individual billionaire profile contains a detailed analysis of how that person's fortune is tallied.

    The index is a dynamic measure of personal wealth based on changes in markets, the economy and Bloomberg reporting. Each net worth figure is updated every business day after the close of trading in New York. Stakes in publicly traded companies are valued using the share's most recent closing price. Valuations are converted to U.S. dollars at current exchange rates.

    Closely held companies are valued in several ways, such as by comparing the enterprise value-to-Ebitda or price-to-earnings ratios of similar public companies or by using comparable transactions. Calculations of closely held company debt -- if net debt cannot be determined -- are based on the net debt-to-Ebitda ratios of comparable peers. The value of closely held companies adjusts daily based on market moves for peer companies or by applying the market movement of a relevant industry index. The criteria used to choose peer companies is based on the closely held asset's industry and size.

    When ownership of closely held assets cannot be verified, they aren't included in the calculations. The specific valuation methodology for each closely held company is included in the net worth analysis section of a billionaire's profile. Additional details included in the valuation notes for each asset are available to subscribers of the Bloomberg Professional Service.

    A standard liquidity discount of 5 percent is applied to most closely held companies where assets may be hard to sell. When a different percentage is used an explanation is given. No liquidity discounts are applied to the values of public stakes. In some instances, a country risk discount is also applied based on a person's concentration of assets and ease of selling them in a given geography. A country's risk is assessed based on Standard & Poor's sovereign debt ratings.

    If a billionaire has pledged as collateral shares he or she holds in a public company, the value of those shares or the value of a loan taken against them is removed from the net worth calculation. If reliable information can be obtained about the ultimate use of those borrowed funds, that value is added back into the calculation.

    Hedge fund businesses are valued using the average market capitalization-to-assets under management ratios of the most comparable publicly traded funds. Fee income is not considered because it cannot be uniformly verified. Personal funds invested along with outside capital are not included in the calculation. A "key man" risk discount of 25 percent is applied to funds whose performance is tied to a single individual. Assets under management are updated using ADV forms filed with the federal government and news reports, and returns are factored when sourced to reports from credible news outfits, the HFRI Index and industry analysts.

    Net worth calculations include dividend income paid and proceeds from the sale of public and closely held shares. Taxes are deducted based on prevailing income, dividend and capital gains tax rates in a billionaire's country of residence. Taxes are applied at the highest rate unless there is evidence to support a lower percentage, in which case an explanation is given in the net worth summary. For calculations of cash and other investable assets, a hybrid return based on holdings in cash, government bonds, equities and commodities is applied.

    No assumptions are made about personal debt. Family members often hold a portion of a billionaire's assets. Such transfers don't change the nature of who ultimately controls the fortune. As a result, Bloomberg News operates under the rule that all billionaire fortunes are inherently family fortunes and credit family fortunes to the founders or ranking family members who are determined to have direct control over the assets. When individual stakes can be verified and adult family members have an active role in a business, the value is credited to each individual.

    Each billionaire -- or a representative -- is given an opportunity to respond to questions regarding the net worth calculation, including assets and liabilities.

    Bloomberg News editorial policy is to not cover Bloomberg L.P. As a result, Michael Bloomberg, the founder and majority owner of Bloomberg L.P., isn't considered for this ranking.

    Because calculating net worth requires a degree of estimation, bull and bear case scenarios that would make a person's fortune higher or lower than the Bloomberg Billionaires Index valuation are included on the Bloomberg Professional Service. A confidence rating also is included on each profile:

  3. n

    Keyphrase Metrics for Bloomberg Billionaires Index

    • newsletterscan.com
    Updated Jan 24, 2025
    + more versions
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    (2025). Keyphrase Metrics for Bloomberg Billionaires Index [Dataset]. https://newsletterscan.com/topic/bloomberg-billionaires-index
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    Dataset updated
    Jan 24, 2025
    Variables measured
    Mentions, Growth Rate, Growth Category
    Description

    A dataset of mentions, growth rate, and total volume of the keyphrase 'Bloomberg Billionaires Index' over time.

  4. Top Tech Companies Stock Price

    • kaggle.com
    Updated Nov 24, 2020
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    Tomas Mantero (2020). Top Tech Companies Stock Price [Dataset]. https://www.kaggle.com/datasets/tomasmantero/top-tech-companies-stock-price
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Nov 24, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Tomas Mantero
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    Context

    In this dataset you can find the Top 100 companies in the technology sector. You can also find 5 of the most important and used indices in the financial market as well as a list of all the companies in the S&P 500 index and in the technology sector.

    The Global Industry Classification Standard also known as GICS is the primary financial industry standard for defining sector classifications. The Global Industry Classification Standard was developed by index providers MSCI and Standard and Poor’s. Its hierarchy begins with 11 sectors which can be further delineated to 24 industry groups, 69 industries, and 158 sub-industries.

    You can read the definition of each sector here.

    The 11 broad GICS sectors commonly used for sector breakdown reporting include the following: Energy, Materials, Industrials, Consumer Discretionary, Consumer Staples, Health Care, Financials, Information Technology, Telecommunication Services, Utilities and Real Estate.

    In this case we will focuse in the Technology Sector. You can see all the sectors and industry groups here.

    To determine which companies, correspond to the technology sector, we use Yahoo Finance, where we rank the companies according to their “Market Cap”. After having the list of the Top 100 best valued companies in the sector, we proceeded to download the historical data of each of the companies using the NASDAQ website.

    Regarding to the indices, we searched various sources to find out which were the most used and determined that the 5 most frequently used indices are: Dow Jones Industrial Average (DJI), S&P 500 (SPX), NASDAQ Composite (IXIC), Wilshire 5000 Total Market Inde (W5000) and to specifically view the technology sector SPDR Select Sector Fund - Technology (XLK). Historical data for these indices was also obtained from the NASDQ website.

    Content

    In total there are 107 files in csv format. They are composed as follows:

    • 100 files contain the historical data of tech companies.
    • 5 files contain the historical data of the most used indices.
    • 1 file contain the list of all the companies in the S&P 500 index.
    • 1 file contain the list of all the companies in the technology sector.

    Column Description

    Every company and index file has the same structure with the same columns:

    Date: It is the date on which the prices were recorded. High: Is the highest price at which a stock traded during the course of the trading day. Low: Is the lowest price at which a stock traded during the course of the trading day. Open: Is the price at which a stock started trading when the opening bell rang. Close: Is the last price at which a stock trades during a regular trading session. Volume: Is the number of shares that changed hands during a given day. Adj Close: The adjusted closing price factors in corporate actions, such as stock splits, dividends, and rights offerings.

    The two other files have different columns names:

    List of S&P 500 companies

    Symbol: Ticker symbol of the company. Name: Name of the company. Sector: The sector to which the company belongs.

    Technology Sector Companies List

    Symbol: Ticker symbol of the company. Name: Name of the company. Price: Current price at which a stock can be purchased or sold. (11/24/20) Change: Net change is the difference between closing prices from one day to the next. % Change: Is the difference between closing prices from one day to the next in percentage. Volume: Is the number of shares that changed hands during a given day. Avg Vol: Is the daily average of the cumulative trading volume during the last three months. Market Cap (Billions): Is the total value of a company’s shares outstanding at a given moment in time. It is calculated by multiplying the number of shares outstanding by the price of a single share. PE Ratio: Is the ratio of a company's share (stock) price to the company's earnings per share. The ratio is used for valuing companies and to find out whether they are overvalued or undervalued.

    Acknowledgements

    SEC EDGAR | Company Filings NASDAQ | Historical Quotes Yahoo Finance | Technology Sector Wikipedia | List of S&P 500 companies S&P Dow Jones Indices | S&P 500 [S&P Dow Jones Indices | DJI](https://www.spglobal.com/spdji/en/i...

  5. h

    stock-market-tweets-data

    • huggingface.co
    Updated Dec 16, 2023
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    Stephan Akkerman (2023). stock-market-tweets-data [Dataset]. https://huggingface.co/datasets/StephanAkkerman/stock-market-tweets-data
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Dec 16, 2023
    Authors
    Stephan Akkerman
    License

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

    Description

    Stock Market Tweets Data

      Overview
    

    This dataset is the same as the Stock Market Tweets Data on IEEE by Bruno Taborda.

      Data Description
    

    This dataset contains 943,672 tweets collected between April 9 and July 16, 2020, using the S&P 500 tag (#SPX500), the references to the top 25 companies in the S&P 500 index, and the Bloomberg tag (#stocks).

      Dataset Structure
    

    created_at: The exact time this tweet was posted. text: The text of the tweet, providing… See the full description on the dataset page: https://huggingface.co/datasets/StephanAkkerman/stock-market-tweets-data.

  6. F

    CBOE Emerging Markets ETF Volatility Index

    • fred.stlouisfed.org
    json
    Updated Jul 30, 2025
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    (2025). CBOE Emerging Markets ETF Volatility Index [Dataset]. https://fred.stlouisfed.org/series/VXEEMCLS
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    jsonAvailable download formats
    Dataset updated
    Jul 30, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-citation-requiredhttps://fred.stlouisfed.org/legal/#copyright-citation-required

    Description

    Graph and download economic data for CBOE Emerging Markets ETF Volatility Index (VXEEMCLS) from 2011-03-16 to 2025-07-29 about ETF, VIX, emerging markets, volatility, stock market, and USA.

  7. u

    Analysis of volatility spillovers in the stock, currency and goods market...

    • researchdata.up.ac.za
    xlsx
    Updated May 31, 2023
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    Chevaughn van der Westhuizen; Reneé van Eyden; Goodness C. Aye (2023). Analysis of volatility spillovers in the stock, currency and goods market and the monetary policy efficiency within different uncertainty states in these markets [Dataset]. http://doi.org/10.25403/UPresearchdata.22187701.v1
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    xlsxAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    University of Pretoria
    Authors
    Chevaughn van der Westhuizen; Reneé van Eyden; Goodness C. Aye
    License

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

    Description

    South African monthly The FTSE/JSE All Share Index data was procured from Bloomberg and the nominal effective exchange rate (NEER) from South African Reserve Bank (SARB) database, where the data has been seasonally adjusted specifying 2015 as the base year. Volatility measures in these markets are generated through a multivaraite EGARCH model in the WinRATS software. South African monthly consumer price index (CPI) data was procured from the International Monetary Fund’s International Financial Statistics (IFS) database, where the data has been seasonally adjusted, specifying 2010 as the base year. The inflation rate is constructed by taking the year-on-year changes in the monthly CPI figures. Inflation uncertainty was generated through the GARCH model in Eviews software. The following South African macroeconomic variables were procured from the SARB: real industrial production (IP), which is used as a proxy for real GDP, real investment (I), real consumption (C), inflation (CPI), broad money (M3), the 3-month treasury bill rate (TB3) and the policy rate (R), a measure of U.S. EPU developed by Baker et al. (2016) to account for global developments available at http://www.policyuncertainty.com/us_monthly.html.

  8. T

    CRB Commodity Index - Price Data

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +12more
    csv, excel, json, xml
    Updated May 27, 2017
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    TRADING ECONOMICS (2017). CRB Commodity Index - Price Data [Dataset]. https://tradingeconomics.com/commodity/crb
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    csv, json, excel, xmlAvailable download formats
    Dataset updated
    May 27, 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 3, 1994 - Jul 29, 2025
    Area covered
    World
    Description

    CRB Index rose to 377.14 Index Points on July 29, 2025, up 0.83% from the previous day. Over the past month, CRB Index's price has risen 3.27%, and is up 16.45% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. CRB Commodity Index - values, historical data, forecasts and news - updated on July of 2025.

  9. w

    Global Commodity Index Funds Market Research Report: By Investment Objective...

    • wiseguyreports.com
    Updated Jul 19, 2024
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    wWiseguy Research Consultants Pvt Ltd (2024). Global Commodity Index Funds Market Research Report: By Investment Objective (Diversification, Inflation Hedging, Performance Enhancement), By Asset Class (Broad Commodity Index Funds, Sector-Specific Commodity Index Funds, Single Commodity Index Funds), By Index Provider (S&P GSCI, Bloomberg Commodity Index (BCI), Thomson Reuters/CoreCommodity CRB Index), By Investment Style (Active Commodity Index Funds, Passive Commodity Index Funds), By Investor Profile (Institutional Investors, Accredited Investors, Retail Investors) and By Regional (North America, Europe, South America, Asia Pacific, Middle East and Africa) - Forecast to 2032. [Dataset]. https://www.wiseguyreports.com/reports/commodity-index-funds-market
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    Dataset updated
    Jul 19, 2024
    Dataset authored and provided by
    wWiseguy Research Consultants Pvt Ltd
    License

    https://www.wiseguyreports.com/pages/privacy-policyhttps://www.wiseguyreports.com/pages/privacy-policy

    Time period covered
    Jan 7, 2024
    Area covered
    Global
    Description
    BASE YEAR2024
    HISTORICAL DATA2019 - 2024
    REPORT COVERAGERevenue Forecast, Competitive Landscape, Growth Factors, and Trends
    MARKET SIZE 2023377.63(USD Billion)
    MARKET SIZE 2024401.23(USD Billion)
    MARKET SIZE 2032651.97(USD Billion)
    SEGMENTS COVEREDInvestment Objective ,Asset Class ,Index Provider ,Investment Style ,Investor Profile ,Regional
    COUNTRIES COVEREDNorth America, Europe, APAC, South America, MEA
    KEY MARKET DYNAMICSIncreased demand for alternative investments Growing popularity of passive investing Rise in commodity prices Geopolitical uncertainty Technological advancements
    MARKET FORECAST UNITSUSD Billion
    KEY COMPANIES PROFILEDiShares MSCI Commodity Swap Index Fund ,Rogers International Commodity Index ,S&P GSCI ,MSCI Commodity Index ,UBS Bloomberg Constant Maturity Commodity Index ,PowerShares DB Commodity Tracking Fund ,Bloomberg Commodity Index ,DB Commodity Index ,Solactive Commodity Index ,Thomson Reuters/CoreCommodity CRB Index ,Invesco DB Commodity Index Tracking Fund ,CRB Commodity Index ,Dow Jones Commodity Index ,ETFS Physical Swiss Gold Shares ,WisdomTree Enhanced Commodity Tracking Fund
    MARKET FORECAST PERIOD2024 - 2032
    KEY MARKET OPPORTUNITIESGrowing demand for diversification Increased investor interest in commodities Technological advancements
    COMPOUND ANNUAL GROWTH RATE (CAGR) 6.25% (2024 - 2032)
  10. T

    Baltic Exchange Dry Index - Price Data

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated May 26, 2017
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    TRADING ECONOMICS (2017). Baltic Exchange Dry Index - Price Data [Dataset]. https://tradingeconomics.com/commodity/baltic
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    csv, excel, xml, jsonAvailable download formats
    Dataset updated
    May 26, 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 4, 1985 - Jul 30, 2025
    Area covered
    World
    Description

    Baltic Dry fell to 1,995 Index Points on July 30, 2025, down 5.41% from the previous day. Over the past month, Baltic Dry's price has risen 36.83%, and is up 16.80% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Baltic Exchange Dry Index - values, historical data, forecasts and news - updated on July of 2025.

  11. Gold Prices Recover as Investors Eye Federal Reserve's Rate Decision - News...

    • indexbox.io
    doc, docx, pdf, xls +1
    Updated Jul 1, 2025
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    IndexBox Inc. (2025). Gold Prices Recover as Investors Eye Federal Reserve's Rate Decision - News and Statistics - IndexBox [Dataset]. https://www.indexbox.io/blog/gold-prices-rebound-amid-federal-reserve-rate-decision-anticipation/
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    pdf, doc, docx, xlsx, xlsAvailable download formats
    Dataset updated
    Jul 1, 2025
    Dataset provided by
    IndexBox
    Authors
    IndexBox Inc.
    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, 2012 - Jul 1, 2025
    Area covered
    World
    Variables measured
    Market Size, Market Share, Tariff Rates, Average Price, Export Volume, Import Volume, Demand Elasticity, Market Growth Rate, Market Segmentation, Volume of Production, and 4 more
    Description

    Gold prices recover after consecutive weekly losses, trading above $3,260 an ounce as investors await the Federal Reserve's rate decision. Market dynamics shift amid global trade uncertainties.

  12. m

    Data for: Nuclear hazard and asset prices: Implications of nuclear disasters...

    • data.mendeley.com
    Updated Nov 16, 2020
    + more versions
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    Ana Belén Alonso-Conde (2020). Data for: Nuclear hazard and asset prices: Implications of nuclear disasters in the cross-sectional behavior of stock returns [Dataset]. http://doi.org/10.17632/wv94fj59t4.3
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    Dataset updated
    Nov 16, 2020
    Authors
    Ana Belén Alonso-Conde
    License

    Attribution-NonCommercial 3.0 (CC BY-NC 3.0)https://creativecommons.org/licenses/by-nc/3.0/
    License information was derived automatically

    Description

    Using all stocks listed on the Japanese equity market and macroeconomic data for Japan, the dataset comprises the following series:

    1. Japan_25_Portfolios_MV_PTBV: Monthly returns for 25 size-book-to-market equity portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
    2. Japan_25_Portfolios_MV_PE: Monthly returns for 25 size-PE portfolios, following the Fama and French (1993) methodology. (Raw data source: Datastream database)
    3. Japan_50_Portfolios_SECTOR: Monthly returns for 50 industry portfolios. (Raw data source: Datastream database)
    4. Japan_3 Factors: Fama and French three-factors (RM, SMB and HML), following the Fama and French (1993) methodology. (Raw data source: Datastream database)
    5. Japan_5 Factors: Fama and French five-factors (RM, SMB, HML, RMW, and CMA), following the Fama and French (2015) methodology. (Raw data source: Datastream database)
    6. Japan_NUCLEAR_Y: Instrument in years with a value of 1 when a nuclear disaster has occurred somewhere in the world and 0 otherwise. (Raw data source: Bloomberg and BBC News)
    7. Japan_NUCLEAR_M: Instrument in months with a value of 1 when a nuclear disaster has occurred somewhere in the world and 0 otherwise. (Raw data source: Bloomberg and BBC News)
    8. Japan_RF_M: Three-month interest rate of the Treasury Bill for Japan. (Raw data source: OECD)
    9. Company data: Names and general data of the companies that constitute the sample. (Raw data source: Datastream database)
    10. Number of stocks in portfolios: Number of stocks included each year in Japan_25_Portfolios_MV_PTBV, Japan_25_Portfolios_MV_PE and Japan_50_Portfolios_SECTOR. (Raw data source: Datastream database)

    We have produced all return series using the following data from Datastream: (i) total return index (RI series), (ii) market value (MV series), (iii) market-to-book equity (PTBV series), (iv) total assets (WC02999 series), (v) return on equity (WC08301 series), (vi) price-to-earnings ratio (PE series), and (vii) industry (SECTOR series). We have used the generic rules suggested by Griffin, Kelly, & Nardari (2010) for excluding non-common equity securities from Datastream data. We also exclude stocks with less than twelve observations. Accordingly, our sample comprises a total number of 5,212 stocks.

    REFERENCES:

    Fama, E. F. and French, K. R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3–56. Fama, E. F. and French, K. R. (2015). A five-factor asset pricing model. Journal of Financial Economics, 116, 1–22. Griffin, J. M., Kelly, P., and Nardari, F. (2010). Do market efficiency measures yield correct inferences? A comparison of developed and emerging markets. Review of Financial Studies, 23, 3225–3277.

  13. Innovativste Länder der Welt nach dem Bloomberg Innovation Index 2021

    • de.statista.com
    Updated Feb 15, 2021
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    Statista (2021). Innovativste Länder der Welt nach dem Bloomberg Innovation Index 2021 [Dataset]. https://de.statista.com/statistik/daten/studie/1089357/umfrage/innovativste-laender-der-welt-nach-dem-bloomberg-innovation-index/
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    Dataset updated
    Feb 15, 2021
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2021
    Area covered
    Weltweit
    Description

    Südkorea ist im Jahr 2021 das innovativste Land der Welt nach dem Bloomberg Innovation Index 2021. Südkorea verdrängt mit einem Indexwert von ***** Punkten den Vorjahressieger Deutschland von der Spitzenposition. Deutschland erreicht mit einem Indexwert von ***** Punkten den vierten Platz im Bloomberg Innovation Ranking 2021. Der Bloomberg Innovation Index kann Werte zwischen 0 bis 100 annehmen und basiert auf den sieben gleichgewichteten Kategorien R&D Intensity (F&E-Intensität), Manufacturing value-added (Wertschöpfung in der Fertigung), Productivity (Produktivität), High-tech density (Zahl der Hightech-Unternehmen), Tertiary Efficiency (Effizienz des tertiären Bildungsbereichs, z.B. Immatrikulationen, Abschlussquoten, Absolventen), Researcher Concentration (Forscher im F&E-Bereich) und Patent Activity (Patentanmeldungen). Weitere Kennzahlen zur Bestimmung der Innovationskraft eines Landes sind unter anderem der Global Innovation Index oder der Innovationsindikator.

  14. Net worth and its YTD change of the richest Russians 2025

    • statista.com
    Updated Jun 3, 2025
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    Statista (2025). Net worth and its YTD change of the richest Russians 2025 [Dataset]. https://www.statista.com/statistics/1293568/richest-russians-financial-losses-due-to-the-war-with-ukraine/
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    Dataset updated
    Jun 3, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Russia
    Description

    The fortunes of most of the 10 wealthiest Russians increased from the start of the year as of June 3, 2025. Russia's richest man, Vladimir Potanin, saw his net worth grow by 3.85 billion U.S. dollars from January 1, 2025. Thus, his net worth reached 31.7 billion U.S. dollars. Potanin ranked 58th worldwide in the Bloomberg Billionaires Index as of that date.

  15. T

    Coffee - Price Data

    • tradingeconomics.com
    • de.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Jul 30, 2025
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    TRADING ECONOMICS (2025). Coffee - Price Data [Dataset]. https://tradingeconomics.com/commodity/coffee
    Explore at:
    csv, json, excel, xmlAvailable download formats
    Dataset updated
    Jul 30, 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
    Aug 16, 1972 - Jul 30, 2025
    Area covered
    World
    Description

    Coffee fell to 292.65 USd/Lbs on July 30, 2025, down 1.60% from the previous day. Over the past month, Coffee's price has fallen 0.76%, but it is still 28.08% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Coffee - values, historical data, forecasts and news - updated on July of 2025.

  16. T

    Cocoa - Price Data

    • tradingeconomics.com
    • ru.tradingeconomics.com
    • +14more
    csv, excel, json, xml
    Updated Jul 31, 2025
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    TRADING ECONOMICS (2025). Cocoa - Price Data [Dataset]. https://tradingeconomics.com/commodity/cocoa
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    csv, json, xml, excelAvailable download formats
    Dataset updated
    Jul 31, 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
    Jul 1, 1959 - Jul 31, 2025
    Area covered
    World
    Description

    Cocoa rose to 8,390.48 USD/T on July 31, 2025, up 2.24% from the previous day. Over the past month, Cocoa's price has fallen 4.01%, but it is still 11.20% higher than a year ago, according to trading on a contract for difference (CFD) that tracks the benchmark market for this commodity. Cocoa - values, historical data, forecasts and news - updated on July of 2025.

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Statista (2024). Annual development of the Bloomberg Barclays MSCI Global Green Bond Index 2015-2023 [Dataset]. https://www.statista.com/statistics/1109189/bloomberg-barclays-msci-global-green-bond-index-development/
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Annual development of the Bloomberg Barclays MSCI Global Green Bond Index 2015-2023

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2 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Aug 21, 2024
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

Green bond indices make it easier for investors to track the performance of green bonds and compare it with other investments. Bloomberg Barclays MSCI Global Green Bond Index was launched in 2014 with the aim provide a benchmark for the green bonds market. Between 2015 and 2020, the Bloomberg Barclays MSCI Global Green Bond Index saw an overall increase, reaching a value of 121.91 as of the end of 2020. By the end of 2022, however, the index value fell to 86.94, before increasing again to 96.09 by the end of 2023.

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