Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 66 companies listed on the Nairobi Securities Exchange (XNAI) in Kenya. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for Kenya:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in Kenya:

Nairobi Securities Exchange All Share Index (NASI): The main index that tracks the performance of all companies listed on the Nairobi Securities Exchange (NSE). NASI provides insights into the overall market performance in Kenya.

Nairobi Securities Exchange 20 Share Index (NSE 20): An index that tracks the performance of the top 20 companies by market capitalization listed on the NSE. NSE 20 is an important benchmark for the Kenyan stock market.

Safaricom PLC: A leading telecommunications company in Kenya, offering mobile and internet services. Safaricom is one of the largest and most actively traded companies on the NSE.

Equity Group Holdings PLC: A prominent financial institution in Kenya, providing banking and financial services. Equity Group is a significant player in the Kenyan financial sector and is listed on the NSE.

KCB Group PLC: Another major financial institution in Kenya, offering banking and financial services. KCB Group is also listed on the NSE and is among the key players in the country's banking industry.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Kenya, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

‍

Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Kenya ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Kenya?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Kenya exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for this dataset?

Techsalerator accepts various payment methods, including credit cards, direct transfers, ACH, and wire transfers, facilitating a convenient and se...

NASDAQ (National Association of Securities Dealers Automated Quotation) is the world's second largest automated and electronic stock exchange and securities market in the United States, the first being the New York Stock Exchange, with more than 8,000 companies and corporations. It has more trading volume per hour than any other stock exchange in the world. More than 7,000 small and mid-cap stocks are traded on the NASDAQ. It is characterized by comprising high-tech companies in electronics, computers, telecommunications, biotechnology, and many others.

This dataset was created as a result of an automatic extraction of open & public data available in nasdaq.com, using web scraping techniques. The only purpose of creating it was for academic reasons

Context

The National Stock Exchange of India Ltd. (NSE) is an Indian stock exchange located at Mumbai, Maharashtra, India. National Stock Exchange (NSE) was established in 1992 as a demutualized electronic exchange. It was promoted by leading financial institutions on request of the Government of India. It is India’s largest exchange by turnover. In 1994, it launched electronic screen-based trading. Thereafter, it went on to launch index futures and internet trading in 2000, which were the first of its kind in the country.

With the help of NSE, you can trade in the following segments:

• Equities

• Indices

• Mutual Funds

• Exchange Traded Funds

• Initial Public Offerings

• Security Lending and Borrowing Scheme

https://cdn6.newsnation.in/images/2019/06/24/Sharemarket-164616041_6.jpg" alt="Stock image">

Companies on successful IPOs gets their Stocks traded over different Stock Exchnage platforms. NSE is one important platofrm in India. There are thousands of companies trading their stocks in NSE. But, I have chosen two popular and high rated IT service companies of India; TCS and INFOSYS. and the third one is the benchmark for Indian IT companies , i.e. NIFTY_IT_INDEX .

Content

The dataset contains three csv files. Each resembling to INFOSYS, NIFTY_IT_INDEX, and TCS, respectively. One can easily identify that by the name of CSV files.

Timeline of Data recording : 1-1-2015 to 31-12-2015.

Source of Data : Official NSE website.

Method : We have used the NSEpy api to fetch the data from NSE site. I have also mentioned my approach in this Kernel - "**WebScraper to download data for NSE**". Please go though that to better understand the nature of this dataset.

Shape of Dataset:

INFOSYS - 248 x 15 || NIFTY_IT_INDEX - 248 x 7 || **TCS - 248 x 15

• Colum Descriptors:

• Date: date on which data is recorded

• Symbol: NSE symbol of the stock

• Series: Series of that stock | EQ - Equity

OTHER SERIES' ARE:

EQ: It stands for Equity. In this series intraday trading is possible in addition to delivery.

BE: It stands for Book Entry. Shares falling in the Trade-to-Trade or T-segment are traded in this series and no intraday is allowed. This means trades can only be settled by accepting or giving the delivery of shares.

BL: This series is for facilitating block deals. Block deal is a trade, with a minimum quantity of 5 lakh shares or minimum value of Rs. 5 crore, executed through a single transaction, on the special “Block Deal window”. The window is opened for only 35 minutes in the morning from 9:15 to 9:50AM.

BT: This series provides an exit route to small investors having shares in the physical form with a cap of maximum 500 shares.

GC: This series allows Government Securities and Treasury Bills to be traded under this category.

IL: This series allows only FIIs to trade among themselves. Permissible only in those securities where maximum permissible limit for FIIs is not breached.

• Prev Close: Last day close point

• Open: current day open point

• High: current day highest point

• Low: current day lowest point

• Last: the final quoted trading price for a particular stock, or stock-market index, during the most recent day of trading.

• Close: Closing point for the current day

• VWAP: volume-weighted average price is the ratio of the value traded to total volume traded over a particular time horizon

• Volume: the amount of a security that was traded during a given period of time. For every buyer, there is a seller, and each transaction contributes to the count of total volume.

• Turnover: Total Turnover of the stock till that day

• Trades: Number of buy or Sell of the stock.

• Deliverable: Volumethe quantity of shares which actually move from one set of people (who had those shares in their demat account before today and are selling today) to another set of people (who have purchased those shares and will get those shares by T+2 days in their demat account).

• %Deliverble: percentage deliverables of that stock

Acknowledgements

I woul dlike to acknowledge all my sincere thanks to the brains behind NSEpy api, and in particular SWAPNIL JARIWALA , who is also maintaining an amazing open source github repo for this api.

Inspiration

I have also built a starter kernel for this dataset. You can find that right here .

I am so excited to see your magical approaches for the same dataset.

THANKS!

About this dataset

India's National Stock Exchange (NSE) has a total market capitalization of more than US$3.4 trillion, making it the world's 10th-largest stock exchange as of August 2021, with a trading volume of ₹8,998,811 crore (US$1.2 trillion) and more 2000 total listings.

NSE's flagship index, the NIFTY 50, is a 50 stock index is used extensively by investors in India and around the world as a barometer of the Indian capital market.

This dataset contains data of all company stocks listed in the NSE, allowing anyone to analyze and make educated choices about their investments, while also contributing to their countries economy.

How to use this dataset

• Create a time series regression model to predict NIFTY-50 value and/or stock prices.
• Explore the most the returns, components and volatility of the stocks.
• Identify high and low performance stocks among the list.

Highlighted Notebooks

• Your kernel can be featured here!
• Related Dataset: S&P 500 Stocks - daily updated
• More datasets

Acknowledgements

License

CC0: Public Domain

Splash banner

Stonks by unknown memer.

The dataset consists of companies listed in the S&P500, stock market index that measures the stock performance of 500 large companies listed on stock exchanges in the United State.

The S&P 500 stock market index, maintained by S&P Dow Jones Indices, comprises 505 common stocks issued by 500 large-cap companies and traded on American stock exchanges (including the 30 companies that compose the Dow Jones Industrial Average)

The S&P500 or SPX is the most commonly followed equity index, it covers about 80 percent of the American equity market by capitalization.

The index constituents and the constituent weights are updated regularly using rules published by S&P Dow Jones Indices. Although called the S&P 500, the index contains 505 stocks

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 54 companies listed on the Prague Stock Exchange (XPRA) in Czech Republic. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

‍

Top 5 used data fields in the End-of-Day Pricing Dataset for Czech Republic:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

‍

Top 5 financial instruments with End-of-Day Pricing Data in Czech Republic:

Prague Stock Exchange (PX) Main Market Index: The main index that tracks the performance of domestic companies listed on the Prague Stock Exchange. Monitoring this index provides insights into the overall trends and performance of the Czech stock market.

Prague Stock Exchange (PX) TOP 10 Index: The index that includes the top 10 largest and most liquid companies listed on the Prague Stock Exchange. This index provides a snapshot of the performance of the largest players in the Czech market.

Banking Group A: A major banking group based in the Czech Republic, offering a range of financial services including retail banking, corporate banking, and investment services. Monitoring the stock of this banking group is a key indicator of the financial sector's health.

Automotive Manufacturer B: A significant automotive manufacturer in the Czech Republic, contributing to the country's strong automotive industry. The stock of this company reflects trends in the manufacturing and export-oriented sectors.

Energy Company C: A major player in the energy sector in the Czech Republic, involved in electricity generation, distribution, or related services. Monitoring the stock of this company provides insights into the energy sector's dynamics.

‍

If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Czech Republic, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

‍

Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Czech Republic?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Czech Republic?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Czech Republic exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Tec...

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 14 companies listed on the Dominican Republic Stock Exchange (XBVR) in Dominican Republic. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

‍

Top 5 used data fields in the End-of-Day Pricing Dataset for Dominican Republic:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

‍

Top 5 financial instruments with End-of-Day Pricing Data in Dominican Republic:

Dow Jones Dominican Republic Index: The Dow Jones Dominican Republic Index represents the performance of companies listed on the Dominican Republic Stock Exchange (Bolsa de Valores de la República Dominicana). It serves as a benchmark for tracking the overall market performance in the country.

Banco Popular Dominicano: Banco Popular Dominicano is one of the largest banks in the Dominican Republic, offering a range of banking and financial services to individuals and businesses. The securities of Banco Popular Dominicano are actively traded on the Dominican Republic Stock Exchange.

Grupo Financiero BHD León: Grupo Financiero BHD León is a financial group that operates in the Dominican Republic, providing banking, insurance, and financial services. The securities of Grupo Financiero BHD León are listed and traded on the Dominican Republic Stock Exchange.

Banco de Reservas de la República Dominicana: Banco de Reservas, also known as Banreservas, is the state-owned bank of the Dominican Republic. It offers a wide range of banking and financial services to customers. The securities of Banreservas are listed on the Dominican Republic Stock Exchange.

Altice Dominicana: Altice Dominicana is a subsidiary of Altice Group, a multinational telecommunications company. Altice Dominicana provides telecommunication services in the Dominican Republic. The securities of Altice Dominicana are listed and traded on the Dominican Republic Stock Exchange.

‍

If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Dominican Republic, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

‍

Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Dominican Republic ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Dominican Republic?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Dominican Republic exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments...

This dataset contains daily stock prices and trading volume for the Adani group of companies listed on the National Stock Exchange (NSE) from January 1, 2023 onwards.

The Adani Group is a large company based in India that works in many different areas, such as transportation, logistics, agribusiness, power generation, renewable energy and more. It was started by Gautam Adani in 1988. It's worth noting that in September 2020, he was become the third richest man in the world.

But due to certain allegations from Hindenburg Research report in January 2023, there are huge fluctuations in the stock prices of Adani's companies. Please note that the Hindenburg report and its allegations are not confirmed and may not necessarily be indicative of the Adani group's actual financial performance or prospects. This dataset is provided for informational purposes only and does not constitute financial or investment advice. Users should conduct their own research and seek professional advice before making any investment decisions.

The Adani Group has seven companies that are listed on the National Stock Exchange (NSE) in India, including: Adani Enterprises Ltd (ADANIENT) Adani Green Energy Ltd (ADANIGREEN) Adani Ports and Special Economic Zone Ltd (ADANIPORTS) Adani Power Ltd (ADANIPOWER) Adani Transmission Ltd (ADANITRANS) Adani Total Gas Ltd (ATGL) Adani Wilmar Ltd (AWL)

Content : This dataset includes the daily closing price, opening price, highest price, lowest price, and trading volume, highest and lowest price of stocks in past 52 week, number of trades etc. for all the seven registered companies of Adani Group - Open - open value of the index on that day - High - highest value of the index on that day - Low - lowest value of the index on that day - PREV. CLOSE - Previous Close Value - LTP - Last Traded Price - VWAP - Volume Weighted Average Price - 52W H - 52 Week High price - 52W L - 52 Week Lowest price - Volume - volume of transaction - Value - Turn over in lakhs - No. of trades

Acknowledgements : The data is obtained from NSE website This is just data from 1st Jan, 2023 to 23 March, 2023 is provided here, you will get vast and detailed real-time & historical data from the official website.

Image Credit : Angel One Website

China's main stock market index, the SHANGHAI, fell to 3560 points on August 1, 2025, losing 0.37% from the previous session. Over the past month, the index has climbed 3.04% and is up 22.53% 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 August of 2025.

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 ---

Annual reports Assessment Dataset

This dataset will help investors, merchant bankers, credit rating agencies, and the community of equity research analysts explore annual reports in a more automated way, saving them time.

Following Sub Dataset(s) are there :

a) pdf and corresponding OCR text of 100 Indian annual reports These 100 annual reports are for the 100 largest companies listed on the Bombay Stock Exchange. The total number of words in OCRed text is 12.25 million.

b) A Few Examples of Sentences with Corresponding Classes The author defined 16 widely used topics used in the investment community as classes like:

Accounting Standards

Accounting for Revenue Recognition

Corporate Social Responsbility

Credit Ratings

Diversity Equity and Inclusion

Electronic Voting

Environment and Sustainability

Hedging Strategy

Intellectual Property Infringement Risk

Litigation Risk

Order Book

Related Party Transaction

Remuneration

Research and Development

Talent Management

Whistle Blower Policy

These classes should help generate ideas and investment decisions, as well as identify red flags and early warning signs of trouble when everything appears to be proceeding smoothly.

ABOUT DATA ::

"scrips.json" is a json with name of companies "SC_CODE" is BSE Scrip Id "SC_NAME" is Listed Companies Name "NET_TURNOV" is Turnover on the day of consideration

"source_pdf" is folder containing both PDF and OCR Output from Tesseract "raw_pdf.zip" contains raw PDF and it can be used to try another OCR. "ocr.zip" contains json file (annual_report_content.json) containing OCR text for each pdf. "annual_report_content.json" is an array of 100 elements and each element is having two keys "file_name" and "content"

"classif_data_rank_freezed.json" is used for evaluation of results contains "sentence" and corresponding "class"

Analysis of ‘United HealthCare Stock data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/kalilurrahman/united-healthcare-stock-data on 13 February 2022.

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

https://upload.wikimedia.org/wikipedia/commons/thumb/f/f3/UnitedHealth_Group_logo.svg/330px-UnitedHealth_Group_logo.svg.png" alt=""> https://www.pngkit.com/png/full/944-9444695_united-healthcare-graphic-design.png" alt=""> UHG is a very big market cap player.

UnitedHealth Group Incorporated is an American multinational managed healthcare and insurance company based in Minnetonka, Minnesota. It offers health care products and insurance services. UnitedHealth Group is the world's eighth-largest company by revenue and second-largest healthcare company behind CVS Health by revenue, and the largest insurance company by net premiums. UnitedHealthcare revenues comprise 80% of the Group's overall revenue

The company is ranked 8th on the 2021 Fortune Global 500. UnitedHealth Group has a market capitalization of $400.7 billion as of March 31, 2021.

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

Dataset

This dataset was created by Siddharth Shrivastava

Released under Apache 2.0

Contents

The indicator measures the share of female board members and executives in the largest publicly listed companies. Publicly listed means that the shares of the company are traded on the stock exchange. The ‘largest’ companies are taken to be the members (max. 50) of the primary blue-chip index, which is an index maintained by the stock exchange and covers the largest companies by market capitalisation and/or market trades. Only companies which are registered in the country concerned are counted. Board members cover all members of the highest decision-making body in each company (i.e. chairperson, non-executive directors, senior executives and employee representatives, where present). Executives refer to senior executives in the two highest decision-making bodies of the largest (max. 50) nationally registered companies listed on the national stock exchange. The two highest decision-making bodies are usually referred to as the supervisory board and the management board (in case of a two-tier governance system) and the board of directors and executive/management committee (in a unitary system). The data comes from the Gender Statistics Database of the European Institute for Gender Equality (EIGE).

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.

Ebitda Time Series for UK Commercial Property Trust. UK Commercial Property REIT Limited ("UKCM") is a listed Real Estate Investment Trust (REIT) with a net asset value of £1.1 billion as at 30 June 2023. UKCM is one of the largest diversified REITs in the UK and is a component of the FTSE 250 index made up of the largest 350 companies with a primary listing on the London Stock Exchange.

We first selected numerical indicators of company performance and employment standards and created dimensions of performance for these indicators.We then collected data for these dimensions from publicly available sources.We cleaned and organised the data to make them comparable and meaningful within and across dimensions.We ranked companies according to each dimension.We compiled composite rankings by grouping dimensions together.This database provides the underpinning research for a Knowledge Exchange (KE) and Impact project focusing on the employment standards of the largest listed South Korean companies within the Environment, Social and Governance (ESG) investment finance framework.We developed an original methodology for compiling a database of numerical indicators of employment standards. We call this our “Washing Line Methodology”.These data, dimensions, and rankings give us insights into South Korean companies’ relative performance in employment standards within the Social pillar of the ESG investment finance framework.Version 1 of the database is now Open Access and Shareable, since there is greater than a one year interval between its completion and the present. The Principle Investigator prefers that you discuss reuse with them; contact at peter.matanle@cantab.net.Data may be reused for non-commercial purposes if properly cited. Onward sharing of dimensional and methodological details outside of information publicly disclosed by the project participants is prohibited

Stock Analysis Software Market Outlook

The global stock analysis software market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.5 billion by 2032, growing at a compound annual growth rate (CAGR) of 12.5% during the forecast period. The growth of this market is driven by the increasing adoption of advanced analytics tools by individual investors and financial institutions to make informed investment decisions. The rising demand for automated trading systems and the integration of artificial intelligence (AI) and machine learning (ML) in stock analysis software are significant growth factors contributing to the market expansion.

One of the primary growth factors for the stock analysis software market is the increasing complexity and volume of financial data. With the exponential growth of data from various sources such as social media, news articles, and financial statements, investors and financial analysts require sophisticated tools to process and interpret this information accurately. Stock analysis software equipped with AI and ML algorithms can analyze vast datasets in real-time, providing valuable insights and predictive analytics that enhance investment strategies. Moreover, the growing trend of algorithmic trading, which relies heavily on high-speed data processing and automated decision-making, is further propelling the market growth.

Another crucial growth driver is the rising awareness and adoption of stock analysis software among individual investors. As more individuals seek to actively manage their investment portfolios, there is a growing demand for user-friendly and cost-effective stock analysis tools that offer comprehensive market analysis, technical indicators, and personalized investment recommendations. The proliferation of mobile applications and the increasing accessibility of cloud-based stock analysis solutions have made it easier for retail investors to access advanced analytical tools, thereby contributing to market expansion.

The integration of innovative technologies such as natural language processing (NLP) and sentiment analysis into stock analysis software is also a significant growth factor. These technologies enable the software to interpret and analyze unstructured data from news articles, social media, and other textual sources to gauge market sentiment and predict stock price movements. This capability is particularly valuable in today's fast-paced financial markets, where sentiment and news events can have a substantial impact on stock prices. The continuous advancements in AI and NLP technologies are expected to drive further innovations and improvements in stock analysis software, thereby boosting market growth.

In the evolving landscape of financial technology, Investor Relations Tools have become indispensable for companies seeking to maintain transparent and effective communication with their stakeholders. These tools facilitate seamless interaction between companies and their investors, providing real-time updates, financial reports, and strategic insights. By leveraging these tools, companies can enhance their investor engagement strategies, build trust, and foster long-term relationships with their shareholders. The integration of advanced analytics and AI-driven insights into Investor Relations Tools further empowers companies to tailor their communication strategies, ensuring that they meet the diverse needs of their investor base. As the demand for transparency and accountability in financial markets continues to grow, the adoption of sophisticated Investor Relations Tools is expected to rise, playing a crucial role in the broader ecosystem of stock analysis software.

From a regional perspective, North America is anticipated to hold the largest market share due to the high concentration of financial institutions, brokerage firms, and individual investors in the region. The presence of key market players and the early adoption of advanced technologies also contribute to the dominant position of North America in the global stock analysis software market. Additionally, the Asia Pacific region is expected to witness significant growth during the forecast period, driven by the increasing number of retail investors, rapid economic development, and the growing financial markets in countries such as China and India.

Component Analysis

This dataset is concerned with the development of networks of interlocking directorates among Dutch companies that have a link with Indonesia. For the year 1948, Nobel and Fennema identified a group of companies operating in Indonesia and a group of companies exporting to Indonesia. The first group contains all in Indonesia operating companies that were listed on the Amsterdam stock exchange with assets over 4 million guilder. The second group consists of the largest exporting companies to Indonesia by sector. They collected the names of directors of 141 selected companies for the years 1946, 1950, 1954, 1958, and 1962. The main sources for these data were annual reports and Van Oss’ Effectenboek. The database contains information about the name and function(s) of the directors, as well as the period in which a person is director at a particular company. The city were the company is located is included in the database as well. Between 1946 and 1962 there is a core of around 200 interlocking directors. Until 1958, the number of interlocks is around 1000, but after 1958 this number declines to 823.

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