71 datasets found
  1. Private Company Financials Dataset | S&P Global Marketplace

    • marketplace.spglobal.com
    Updated Aug 2, 2020
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    S&P Global (2020). Private Company Financials Dataset | S&P Global Marketplace [Dataset]. https://www.marketplace.spglobal.com/en/datasets/private-company-financials-(30)
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    Dataset updated
    Aug 2, 2020
    Dataset authored and provided by
    S&P Globalhttps://www.spglobal.com/
    Description

    Standardized financial data on over 12 million global private companies.

  2. S&P Capital IQ Financials Dataset | S&P Global Marketplace

    • marketplace.spglobal.com
    Updated Aug 2, 2020
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    S&P Global (2020). S&P Capital IQ Financials Dataset | S&P Global Marketplace [Dataset]. https://www.marketplace.spglobal.com/en/datasets/s-p-capital-iq-financials-(10)
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    Dataset updated
    Aug 2, 2020
    Dataset authored and provided by
    S&P Globalhttps://www.spglobal.com/
    Description

    Standardized and As Reported financial data for global public companies as well as thousands of private companies and private companies with public debt.

  3. a

    S.Korea Financial statements datasets

    • aiceltech.com
    Updated Jun 28, 2024
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    KED Aicel (2024). S.Korea Financial statements datasets [Dataset]. https://www.aiceltech.com/datasets/financial-statements
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    Dataset updated
    Jun 28, 2024
    Dataset authored and provided by
    KED Aicel
    License

    https://www.aiceltech.com/termshttps://www.aiceltech.com/terms

    Time period covered
    2016 - 2024
    Area covered
    South Korea
    Description

    Korean Companies’ Financial Data provides important information to analyze a company’s financial status and performance. This data includes financial indicators such as revenue, expenses, assets, and liabilities. Collected from corporate financial reports and stock market data, it helps investors evaluate financial health and discover investment opportunities, essential for valuing Korean companies.

  4. d

    FirstRate Data - US Fundamental Data (Historical Financial Data for 30 Years...

    • datarade.ai
    .xls
    Updated Dec 20, 2020
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    FirstRate Data (2020). FirstRate Data - US Fundamental Data (Historical Financial Data for 30 Years Quarterly Financials for 5500 Tickers) [Dataset]. https://datarade.ai/data-products/us-fundamental-data-30-years-quarterly-financials-for-5500-tickers-firstrate-data
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    .xlsAvailable download formats
    Dataset updated
    Dec 20, 2020
    Dataset authored and provided by
    FirstRate Data
    Area covered
    United States of America
    Description
    • Data from Dec 1989 to Dec 2020.
    • Includes Income Statement, Balance Sheet, and Cashflow statement.
    • Adjusted for restatements.
    • Includes valuation metrics such as enterprise valuation and market capitalization.
    • Over 30 ratios such as p/e ratio, EBITDA/sales, gross margin etc..
    • Standardized categories for comparison between companies.
  5. Compustat® Financials Dataset | S&P Global Marketplace

    • marketplace.spglobal.com
    Updated Aug 2, 2020
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    S&P Global (2020). Compustat® Financials Dataset | S&P Global Marketplace [Dataset]. https://www.marketplace.spglobal.com/en/datasets/compustat-financials-(8)
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    Dataset updated
    Aug 2, 2020
    Dataset authored and provided by
    S&P Globalhttps://www.spglobal.com/
    Description

    Standardized North American and global company financials and market data for active and inactive publicly-traded companies.

  6. F

    Quarterly Financial Report: U.S. Corporations: All Information: Capital...

    • fred.stlouisfed.org
    json
    Updated Mar 24, 2025
    + more versions
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    (2025). Quarterly Financial Report: U.S. Corporations: All Information: Capital Stock and Other Capital (Less Treasury Stock) [Dataset]. https://fred.stlouisfed.org/series/QFRD326INFUSNO
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    jsonAvailable download formats
    Dataset updated
    Mar 24, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Quarterly Financial Report: U.S. Corporations: All Information: Capital Stock and Other Capital (Less Treasury Stock) (QFRD326INFUSNO) from Q4 2009 to Q4 2024 about stocks, information, finance, capital, Treasury, corporate, industry, and USA.

  7. SNL Financial Institutions Regulatory Data Dataset | S&P Global Marketplace

    • marketplace.spglobal.com
    Updated Aug 2, 2020
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    S&P Global (2020). SNL Financial Institutions Regulatory Data Dataset | S&P Global Marketplace [Dataset]. https://www.marketplace.spglobal.com/en/datasets/snl-financial-institutions-regulatory-data-(37)
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    Dataset updated
    Aug 2, 2020
    Dataset authored and provided by
    S&P Globalhttps://www.spglobal.com/
    Description

    Financial statement filings from banks and credit unions.

  8. F

    Quarterly Financial Report: U.S. Corporations: All Information: Total Cash...

    • fred.stlouisfed.org
    json
    Updated Dec 10, 2024
    + more versions
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    (2024). Quarterly Financial Report: U.S. Corporations: All Information: Total Cash on Hand and in U.S. Banks [Dataset]. https://fred.stlouisfed.org/series/QFRTCASHINFUSNO
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    jsonAvailable download formats
    Dataset updated
    Dec 10, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    United States
    Description

    Graph and download economic data for Quarterly Financial Report: U.S. Corporations: All Information: Total Cash on Hand and in U.S. Banks (QFRTCASHINFUSNO) from Q4 2009 to Q3 2024 about cash, information, finance, corporate, banks, depository institutions, industry, and USA.

  9. d

    U.S. P&C Insurance Ratings of Business Quality & Operational Efficiency by...

    • datarade.ai
    Updated May 3, 2021
    + more versions
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    Hoeg & Company (2021). U.S. P&C Insurance Ratings of Business Quality & Operational Efficiency by Hoeg & Company [Dataset]. https://datarade.ai/data-products/u-s-p-c-insurance-ratings-of-business-quality-operational-efficiency-by-hoeg-company-hoeg-company
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    .xml, .csv, .xls, .txtAvailable download formats
    Dataset updated
    May 3, 2021
    Dataset authored and provided by
    Hoeg & Company
    Area covered
    United States of America
    Description

    What sets Hoeg & Company’s Ratings apart from other measures of business efficiency and quality is that they take into account the nature of each financial institution’s underlying book of business in determining operational efficiency. Data from financial statements issued by banks (call reports) and insurers (statutory financial statements) to regulators (FDIC & State Departments of Insurance) is used in our analysis to assure integrity and consistency. The data is analyzed to determine how well the resources of each entity are used to acquire customers, provide service and manage operations. In addition, the analysis indicates those business portfolios that best facilitate maximizing profitability and contribute to financial strength.
    The analysis is based on the “efficient frontier” concept used in investment portfolio theory to identify best performance in investment management. Companies are compared to the best performance level in their industry segment for how effectively and efficiently they manage their core business. Hoeg & Company transforms complex financial data into focused, accurate and actionable business information about financial institutions. Clients get a precise set of measures of how efficiently and effectively each firm in a selected industry segment operates.

  10. d

    Vision Private Equity Data for Deal Sourcing | US Consumer Transaction Data...

    • datarade.ai
    .csv, .xls
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    Consumer Edge, Vision Private Equity Data for Deal Sourcing | US Consumer Transaction Data | 100M Accounts, 12K Merchants, 800+ Companies, 600 Tickers [Dataset]. https://datarade.ai/data-products/consumer-edge-vision-private-equity-data-for-deal-sourcing-consumer-edge
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    .csv, .xlsAvailable download formats
    Dataset authored and provided by
    Consumer Edge
    Area covered
    United States of America
    Description

    Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. CE Transact Signal is an aggregated transaction feed that includes consumer transaction data on 100M+ credit and debit cards, including 14M+ active monthly users. Capturing online, offline, and 3rd-party consumer spending on public and private companies, data covers 12K+ merchants and deep demographic and geographic breakouts. Track detailed consumer behavior patterns, including retention, purchase frequency, and cross shop in addition to total spend, transactions, and dollars per transaction.

    Consumer Edge’s consumer transaction datasets offer insights into industries across consumer and discretionary spend such as: • Apparel, Accessories, & Footwear • Automotive • Beauty • Commercial – Hardlines • Convenience / Drug / Diet • Department Stores • Discount / Club • Education • Electronics / Software • Financial Services • Full-Service Restaurants • Grocery • Ground Transportation • Health Products & Services • Home & Garden • Insurance • Leisure & Recreation • Limited-Service Restaurants • Luxury • Miscellaneous Services • Online Retail – Broadlines • Other Specialty Retail • Pet Products & Services • Sporting Goods, Hobby, Toy & Game • Telecom & Media • Travel

    This data sample illustrates how Consumer Edge data can be used by private investors for deal sourcing, providing daily spend for 12,000 brands by channel.

    Inquire about a CE subscription to perform more complex, near real-time deal sourcing, diligence, and portfolio monitoring analysis functions on public tickers and private brands like: • Screen fast-growing brands in any consumer industry or subindustry • Search for lagging companies open to capital discussions

    Consumer Edge offers a variety of datasets covering the US and Europe (UK, Austria, France, Germany, Italy, Spain), with subscription options serving a wide range of business needs.

    Use Case: Deal Sourcing & Diligence

    Problem A $35B Private Equity company focused on growth & venture, credit, and public equity investing in later-stage companies was looking for a data solution to enable them to source and vet the health of potential investments vs. their peers and their industry. With limited visibility, they were seeking a data solution that would seamlessly and easily provide concrete data and analytics for their assessments.

    Solution The firm leveraged CE data to monitor and report weekly on: • Sourcing: With the support of Consumer Edge’s Insight team, the firm set up dashboard views to find and track the struggling firms that are open to capital needs. • Diligence: The firm vetted the health of a potential investment target vs. their peers and their industry by monitoring key metrics such as YoY growth, spend amount % growth, transactions, and of transactions % growth.

    Impact The diligence team able to: • Identify three target acquisition companies based on historic performance • Set benchmarks vs. competition and monitor growth trends • Develop growth plans for post-acquisition strategy

    Corporate researchers and consumer insights teams use CE Vision for:

    Corporate Strategy Use Cases • Ecommerce vs. brick & mortar trends • Real estate opportunities • Economic spending shifts

    Marketing & Consumer Insights • Total addressable market view • Competitive threats & opportunities • Cross-shopping trends for new partnerships • Demo and geo growth drivers • Customer loyalty & retention

    Investor Relations • Shareholder perspective on brand vs. competition • Real-time market intelligence • M&A opportunities

    Most popular use cases for private equity and venture capital firms include: • Deal Sourcing • Live Diligences • Portfolio Monitoring

    Public and private investors can leverage insights from CE’s synthetic data to assess investment opportunities, while consumer insights, marketing, and retailers can gain visibility into transaction data’s potential for competitive analysis, understanding shopper behavior, and capturing market intelligence.

    Most popular use cases among public and private investors from quant and systematic funds to quantamental and fundamental funds include: • Track Key KPIs to Company-Reported Figures • Understanding TAM for Focus Industries • Competitive Analysis • Evaluating Public, Private, and Soon-to-be-Public Companies • Ability to Explore Geographic & Regional Differences • Cross-Shop & Loyalty • Drill Down to SKU Level & Full Purchase Details • Customer lifetime value • Earnings predictions • Uncovering macroeconomic trends • Analyzing market share • Performance benchmarking • Understanding share of wallet • Seeing subscription trends

    Fields Include: • Day • Merchant • Subindustry • Industry • Spend • Transactions • Spend per Transaction (derivable) • Cardholder State • Cardholder CBSA • Cardholder CSA • Age • Income • Wealth •...

  11. d

    Finhubb Stock API - Datasets

    • search.dataone.org
    • dataverse.harvard.edu
    Updated Nov 8, 2023
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    M, K (2023). Finhubb Stock API - Datasets [Dataset]. http://doi.org/10.7910/DVN/PVEM40
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    Dataset updated
    Nov 8, 2023
    Dataset provided by
    Harvard Dataverse
    Authors
    M, K
    Description

    Finnhub is the ultimate stock api in the market, providing real-time and historical price for global stocks with Rest API and websocket. We also support a tons of other financial data like stock fundamentals, analyst estimates, fundamental data and more. Download the file to access balance sheet of Amazon.

  12. f

    Five number summary of the 13 financial ratios.

    • figshare.com
    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Wilson Tsakane Mongwe; Rendani Mbuvha; Tshilidzi Marwala (2023). Five number summary of the 13 financial ratios. [Dataset]. http://doi.org/10.1371/journal.pone.0261245.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wilson Tsakane Mongwe; Rendani Mbuvha; Tshilidzi Marwala
    License

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

    Description

    Note that mil represents million. Q1 and Q3 are the lower and upper quartiles. More information can be found in Mongwe and Malan [6].

  13. Data from: SEC Filings

    • kaggle.com
    zip
    Updated Jun 5, 2020
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    Google BigQuery (2020). SEC Filings [Dataset]. https://www.kaggle.com/bigquery/sec-filings
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    zip(0 bytes)Available download formats
    Dataset updated
    Jun 5, 2020
    Dataset provided by
    Googlehttp://google.com/
    BigQueryhttps://cloud.google.com/bigquery
    Authors
    Google BigQuery
    Description

    In the U.S. public companies, certain insiders and broker-dealers are required to regularly file with the SEC. The SEC makes this data available online for anybody to view and use via their Electronic Data Gathering, Analysis, and Retrieval (EDGAR) database. The SEC updates this data every quarter going back to January, 2009. For more information please see this site.

    To aid analysis a quick summary view of the data has been created that is not available in the original dataset. The quick summary view pulls together signals into a single table that otherwise would have to be joined from multiple tables and enables a more streamlined user experience.

    DISCLAIMER: The Financial Statement and Notes Data Sets contain information derived from structured data filed with the Commission by individual registrants as well as Commission-generated filing identifiers. Because the data sets are derived from information provided by individual registrants, we cannot guarantee the accuracy of the data sets. In addition, it is possible inaccuracies or other errors were introduced into the data sets during the process of extracting the data and compiling the data sets. Finally, the data sets do not reflect all available information, including certain metadata associated with Commission filings. The data sets are intended to assist the public in analyzing data contained in Commission filings; however, they are not a substitute for such filings. Investors should review the full Commission filings before making any investment decision.

  14. Data from: Sample screening.

    • plos.figshare.com
    xls
    Updated Mar 7, 2024
    + more versions
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    Ruixue Bao; Li Wei (2024). Sample screening. [Dataset]. http://doi.org/10.1371/journal.pone.0299643.t001
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    xlsAvailable download formats
    Dataset updated
    Mar 7, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Ruixue Bao; Li Wei
    License

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

    Description

    We collect Chinese A-share listed companies from 2013 to 2022 as samples and use the multi-period difference-in-difference model (DID) to study the impact of multilingual ESG report disclosure on the enthusiasm of foreign investors. We find that Chinese companies disclose ESG reports in both Chinese and English stimulate the enthusiasm of foreign investors to hold shares. The main manifestations are the expansion of the company’s foreign shareholding quota and the increase in the number of shareholders. Further research show that disclosure of multilingual ESG reports makes up for the readability of company annual reports for foreign investors. In the case of companies with poor analyst attention and comparability of accounting information, and companies that hire non-big four auditing firms to audit financial reports, multilingual ESG report disclosures are more positive for foreign shareholdings. The participation of the central investor service center in corporate governance is weak, the degree of regional cultural integration is low, and the disclosure of English ESG reports by Chinese enterprises is conducive to promoting the enthusiasm of foreign shareholding. The research conclusions provide theoretical guidance and empirical reference for enterprises to expand information disclosure methods to foreign investors and attract overseas capital investment.

  15. F

    Life Insurance Companies, General Accounts; Total Liabilities (Balance...

    • fred.stlouisfed.org
    json
    Updated Mar 13, 2025
    + more versions
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    (2025). Life Insurance Companies, General Accounts; Total Liabilities (Balance Sheet), Level [Dataset]. https://fred.stlouisfed.org/series/BOGZ1FL544190073Q
    Explore at:
    jsonAvailable download formats
    Dataset updated
    Mar 13, 2025
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Description

    Graph and download economic data for Life Insurance Companies, General Accounts; Total Liabilities (Balance Sheet), Level (BOGZ1FL544190073Q) from Q4 1945 to Q4 2024 about general accounts, life, balance sheet, insurance, liabilities, and USA.

  16. Share of Americans investing money in the stock market 1999-2024

    • statista.com
    Updated Oct 8, 2024
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    Statista (2024). Share of Americans investing money in the stock market 1999-2024 [Dataset]. https://www.statista.com/statistics/270034/percentage-of-us-adults-to-have-money-invested-in-the-stock-market/
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    Dataset updated
    Oct 8, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    1999 - 2024
    Area covered
    United States
    Description

    In 2024, 62 percent of adults in the United States invested in the stock market. This figure has remained steady over the last few years, and is still below the levels before the Great Recession, when it peaked in 2007 at 65 percent. What is the stock market? The stock market can be defined as a group of stock exchanges, where investors can buy shares in a publicly traded company. In more recent years, it is estimated an increasing number of Americans are using neobrokers, making stock trading more accessible to investors. Other investments A significant number of people think stocks and bonds are the safest investments, while others point to real estate, gold, bonds, or a savings account. Since witnessing the significant one-day losses in the stock market during the Financial Crisis, many investors were turning towards these alternatives in hopes for more stability, particularly for investments with longer maturities. This could explain the decrease in this statistic since 2007. Nevertheless, some speculators enjoy chasing the short-run fluctuations, and others see value in choosing particular stocks.

  17. f

    Area under the receiver operating curve (AUC) and accuracy of the MCMC...

    • plos.figshare.com
    xls
    Updated Jun 1, 2023
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    Wilson Tsakane Mongwe; Rendani Mbuvha; Tshilidzi Marwala (2023). Area under the receiver operating curve (AUC) and accuracy of the MCMC methods. [Dataset]. http://doi.org/10.1371/journal.pone.0261245.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wilson Tsakane Mongwe; Rendani Mbuvha; Tshilidzi Marwala
    License

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

    Description

    The results were averaged over 10 runs of each algorithm.

  18. Discover Financial Services: SWOT, PESTLE & Banking Trends

    • quaintel.com
    Updated Mar 14, 2025
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    Quaintel Research Solutions (2025). Discover Financial Services: SWOT, PESTLE & Banking Trends [Dataset]. https://quaintel.com/public/store/report/discover-financial-services-company-profile-swot-pestle-value-chain-analysis
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    Dataset updated
    Mar 14, 2025
    Dataset provided by
    Quaintel Research
    Authors
    Quaintel Research Solutions
    License

    https://quaintel.com/privacy-policyhttps://quaintel.com/privacy-policy

    Area covered
    Global
    Description

    Discover Financial Services report covers SWOT, PESTLE, value chain, financial insights & ESG strategies for credit card, banking & payment service market expansion.: “ Read More

  19. c

    Corporate strategies on the example of a German calico factory in...

    • datacatalogue.cessda.eu
    • search.gesis.org
    • +2more
    Updated Oct 19, 2024
    + more versions
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    Bloemer (2024). Corporate strategies on the example of a German calico factory in Wuerttemberg on it´s way from a family enterprise to an incorporated company during the period from 1754 to 1966. Employees, wages, production, investment, balance sheet figures. [Dataset]. http://doi.org/10.4232/1.11355
    Explore at:
    Dataset updated
    Oct 19, 2024
    Dataset provided by
    Vera Rosemarie
    Authors
    Bloemer
    Time period covered
    1754 - 1984
    Area covered
    Germany
    Description

    The enterprise, it’s top management as well as it’s contacts to other enterprises is the subject of interest of economic and company history. The aim is to analyze complex historical developments and processes using the example of real events, i.e. of the history and experiences of real single enterprises. The focus of the study at hand is the historical development of the enterprise itself, to find out how the businessmen do react on Situations like social, political and technical changes. „Es gilt herauszufinden, wie Unternehmer/Unternehmen auf bestimmte Situationen bzw. allgemeine, soziale, politische und technische Entwicklungen reagiert haben.“ (S. 15).

    The calico factory in the town Heidenheim (abbreviation: WCM) serves as an example and as object of investigation for the study. The enterprise was founded in 1754 and produced until 1966. The factory started as a traditional family-run company. In 1856 WCM was transformed to a stock corporation and was listed on the stock exchange in Stuttgart. After 1966 the production was stopped and the corporation serves as financial institution and management company only. WCM is listed on the stock exchange in Stuttgart until today. „Die vorliegende Arbeit befasst sich mit der Württembergischen Cattunmanufaktur (WCM), einem Textilveredelungsunternehmen Württembergs, das 1754 gegründet wurde und bis 1966 produzierte. Bis heute wird das Unternehmen an der Stuttgarter Börse notiert, es dient wechselnden Eigentümern als Finanzierungs- und Verwaltungsgesellschaft.“ (S. 15)

    The analyisis of the material, which covers more than twohundred years, serves to provide a detailed description of the company’s development, it’s foundation, the consolidation period, the company’s heyday, the war periods and the years after the two world wars, and finally it’s transformation into a corporation in times of economic prosperity. The development of the corporation’s market value is described until 1984.

    Main-issue of the study is the company’s policy and the implementation of formulated objectives, i.e. the strategies of the entrepreneurs and the top management of the calico factory. The company itself is the result of decisionmaking and implementation of strategies, which are the steps of the development from a so called „entrepreneurial enterprise“ to a so called „managerial enterprise“ . The following questions are discussed: - How does the entrepreneur cope with special situations and changes? - Which networks have been developed between the decision makers (entrepreneurs and managers) and the company? - Which networks have been developed between the company itself and it’s surroundings (location, state, economic market)?

    Datatables in the search- and downloadsystem HISTAT (Subject: entrepreneurial history. In German: Thema: Unternehmensgeschichte):

    A. Die Sulzer Cattunmanufaktur, das Unternehmen der Familie Meebold (1754-1855) (The Sulzer calicu factory, the enterprise of the Meebold-Family, from 1754 to 1855) - Beschäftigte; Anzahl der Dampfmaschinen; Produktion; Entrichtete Zollbeträge (Datatable: employees; number of steam-engines; Production-figures; payed customs)

    B. Die Württembergische Cattunmanufaktur AG (1856-1966) (The calicu factory in Wuerttemberg as corporation, 1856 to 1966)

    B.1 Ausgewählte Daten zu Kapital, Löhne, Investitionen und Anleihen (Datatable B.1: selected data on capital, earnings, investments and loans) B.2 Lange Reihen zu Bilanzen, Kennzahlen und Bewertungszahlen des börsennotierten Unternehmens WCM AG (Datatable B.2: long series on financial statements, key figures, and valuation figures of the stock exchange listed company WCM AG)

    C. Die WCM AG nach 1966 (The time after production of WCM AG – 1966 until today) - Aktiva und Passiva (Datatable: assets and liabilities)

  20. FPT Securities Joint Stock Company SWOT and Financial Analysis

    • quaintel.com
    Updated Mar 4, 2025
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    Quaintel Research Solutions (2025). FPT Securities Joint Stock Company SWOT and Financial Analysis [Dataset]. https://quaintel.com/public/store/report/fpt-securities-joint-stock-company-profile-swot-pestle-value-chain-analysis
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    Dataset updated
    Mar 4, 2025
    Dataset provided by
    Quaintel Research
    Authors
    Quaintel Research Solutions
    License

    https://quaintel.com/privacy-policyhttps://quaintel.com/privacy-policy

    Area covered
    Global
    Description

    FPT Securities Joint Stock Company Company Profile, Opportunities, Challenges and Risk (SWOT, PESTLE and Value Chain); Corporate and ESG Strategies; Competitive Intelligence; Financial KPI’s; Operational KPI’s; Recent Trends: “ Read More

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S&P Global (2020). Private Company Financials Dataset | S&P Global Marketplace [Dataset]. https://www.marketplace.spglobal.com/en/datasets/private-company-financials-(30)
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Private Company Financials Dataset | S&P Global Marketplace

SPGlobal

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Dataset updated
Aug 2, 2020
Dataset authored and provided by
S&P Globalhttps://www.spglobal.com/
Description

Standardized financial data on over 12 million global private companies.

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