This dataset contains a comprehensive collection of historical data for the Nifty 50 stocks, a diversified stock market index in India. The data covers the period from January 2018 to August 2023, providing valuable insights into the performance of the Indian stock market over the years.

Features: - Stock Symbol: The unique stock symbol of the company listed in the Nifty 50 index - Date: The date of the stock market data. - Open: The opening price of the stock on the given date. - High: The highest price reached by the stock during the trading session. - Low: The lowest price reached by the stock during the trading session. - Close: The closing price of the stock on the given date. - Volume: The trading volume of the stock on the given date.

Context

NIFTY 500 is India’s first broad-based stock market index of the Indian stock market. It contains the top 500 listed companies on the NSE. The NIFTY 500 index represents about 96.1% of free-float market capitalization and 96.5% of the total turnover on the National Stock Exchange (NSE).

NIFTY 500 companies are disaggregated into 72 industry indices. Industry weights in the index reflect industry weights in the market. For example, if the banking sector has a 5% weight in the universe of stocks traded on the NSE, banking stocks in the index would also have an approximate representation of 5% in the index. NIFTY 500 can be used for a variety of purposes such as benchmarking fund portfolios, launching index funds, ETFs, and other structured products.

• Other Notable Indices -
  • NIFTY 50: Top 50 listed companies on the NSE. A diversified 50-stock index accounting for 13 sectors of the Indian economy.
  • NIFTY Next 50: Also called NIFTY Juniors. Represents 50 companies from NIFTY 100 after excluding the NIFTY 50 companies.
  • NIFTY 100: Diversified 100 stock index representing major sectors of the economy. NIFTY 100 represents the top 100 companies based on full market capitalization from NIFTY 500.
  • NIFTY 200: Designed to reflect the behavior and performance of large and mid-market capitalization companies.

Content

The dataset comprises various parameters and features for each of the NIFTY 500 Stocks, including Company Name, Symbol, Industry, Series, Open, High, Low, Previous Close, Last Traded Price, Change, Percentage Change, Share Volume, Value in Indian Rupee, 52 Week High, 52 Week Low, 365 Day Percentage Change, and 30 Day Percentage Change.

Dataset Glossary (Column-Wise)

Company Name: Name of the Company.

Symbol: A stock symbol is a unique series of letters assigned to a security for trading purposes.

Industry: Name of the industry to which the stock belongs.

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

Open: It is the price at which the financial security opens in the market when trading begins. It may or may not be different from the previous day's closing price. The security may open at a higher price than the closing price due to excess demand for the security.

High: It is the highest price at which a stock is traded during the course of the trading day and is typically higher than the closing or equal to the opening price.

Low: Today's low is a security's intraday low trading price. Today's low is the lowest price at which a stock trades over the course of a trading day.

Previous Close: The previous close almost always refers to the prior day's final price of a security when the market officially closes for the day. It can apply to a stock, bond, commodity, futures or option co-contract, market index, or any other security.

Last Traded Price: The last traded price (LTP) usually differs from the closing price of the day. This is because the closing price of the day on NSE is the weighted average price of the last 30 mins of trading. The last traded price of the day is the actual last traded price.

Change: For a stock or bond quote, change is the difference between the current price and the last trade of the previous day. For interest rates, change is benchmarked against a major market rate (e.g., LIBOR) and may only be updated as infrequently as once a quarter.

Percentage Change: Take the selling price and subtract the initial purchase price. The result is the gain or loss. Take the gain or loss from the investment and divide it by the original amount or purchase price of the investment. Finally, multiply the result by 100 to arrive at the percentage change in the investment.

Share Volume: Volume is an indicator that means the total number of shares that have been bought or sold in a specific period of time or during the trading day. It will also involve the buying and selling of every share during a specific time period.

Value (Indian Rupee): Market value—also known as market cap—is calculated by multiplying a company's outstanding shares by its current market price.

52-Week High: A 52-week high is the highest share price that a stock has traded at during a passing year. Many market aficionados view the 52-week high as an important factor in determining a stock's current value and predicting future price movement. 52-week High prices are adjusted for Bonus, Split & Rights Corporate actions.

52-Week Low: A 52-week low is the lowest ...

India's main stock market index, the SENSEX, rose to 82445 points on June 9, 2025, gaining 0.31% from the previous session. Over the past month, the index has climbed 0.02% and is up 7.79% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from India. BSE SENSEX Stock Market Index - values, historical data, forecasts and news - updated on June of 2025.

Techsalerator's Corporate Actions Dataset in India offers a comprehensive collection of data fields related to corporate actions, providing valuable insights for investors, traders, and financial institutions. This dataset includes crucial information about the various financial instruments of all 5000 companies traded on the BSE Ltd. (XBOM).

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Top 5 used data fields in the Corporate Actions Dataset for India:

• Dividend Declaration Date: The date on which a company's board of directors announces the dividend payout to its shareholders. This information is crucial for investors who rely on dividends as a source of income.

• Stock Split Ratio: The ratio by which a company's shares are split to increase liquidity and affordability. This field is essential for understanding changes in share structure.

• Merger Announcement Date: The date on which a company officially announces its intention to merge with another entity. This field is crucial for investors assessing the impact of potential mergers on their investments.

• Rights Issue Record Date: The date on which shareholders must be on the company's books to be eligible for participating in a rights issue. This data helps investors plan their participation in fundraising events.

• Bonus Issue Ex-Date: The date on which a company's shares start trading without the value of the bonus issue. This information is vital for investors to adjust their portfolios accordingly.

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Top 5 corporate actions in India:

Mergers and Acquisitions (M&A): Corporate actions related to mergers, acquisitions, and corporate restructuring have been significant in India's business landscape, leading to consolidation and expansion across various sectors.

Initial Public Offerings (IPOs): India's IPO market has been active, with companies across sectors going public to raise capital. Corporate actions related to IPOs contribute to the growth of India's capital markets.

Digital Transformation and Tech Investments: Corporate actions involving technology investments, digitalization efforts, and partnerships contribute to India's digital transformation and emerging tech ecosystem.

Infrastructure Development: Corporate actions related to infrastructure projects, such as transportation networks, energy, and smart cities, support India's economic growth and urbanization.

Sustainable Initiatives and ESG Focus: Corporate actions focusing on environmental, social, and governance (ESG) practices, as well as investments in sustainable projects and businesses, align with India's commitment to sustainability.

Top 5 financial instruments with corporate action Data in India

Bombay Stock Exchange (BSE) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Bombay Stock Exchange. This index would provide insights into the performance of the Indian stock market.

Bombay Stock Exchange (BSE) Foreign Company Index: The index that tracks the performance of foreign companies listed on the Bombay Stock Exchange, if foreign listings were present. This index would give an overview of foreign business involvement in India.

IndiaMart: An India-based online marketplace with operations in multiple regions. IndiaMart focuses on connecting buyers and sellers and contributing to the growth of e-commerce in India.

FinServe India: A financial services provider in India with a focus on promoting financial inclusion and access to banking services, particularly among underserved communities.

AgriTech India: A company dedicated to advancing agricultural technology in India, focusing on optimizing crop yields and improving food security to support the country's agricultural sector.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for India, 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.

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Data fields included:

Dividend Declaration Date Stock Split Ratio Merger Announcement Date Rights Issue Record Date Bonus Issue Ex-Date Stock Buyback Date Spin-Off Announcement Date Dividend Record Date Merger Effective Date Rights Issue Subscription Price ‍

Q&A:

How much does the Corporate Actions Dataset cost in India?

The cost of the Corporate Actions 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.

How complete is the Corporate Actions Dataset coverage in India?

Techsalerator provides comprehensive coverage of Corporate Actions Data for various companies and securities traded on the India Stock Exchange. The datase...

The dataset shows average of Share Price Indices and Market Capitalisation

Note: 1. Market capitalisation data are as at end-December up to 1987-88 and at end-March from 1988-89 onwards. 2. Compilation of RBI index was discontinued by the Reserve Bank of India since 1999-2000. Similarly, the compilation of data on the All-India market capitalisation was discontinued by Bombay Stock Exchange Limited (BSE), since 1999-2000. 3. BSE 100 Index introduced from October 14, 1996 was previously known as BSE National Index. BSE National Index (Base: 1983-84 = 100) comprised 100 stocks listed at five major stock exchanges in India - Mumbai, Calcutta, Delhi, Ahmedabad and Madras, while BSE 100 index into account only the prices of stocks listed at BSE. 4. BSE 100 index has been re-based as 1983-84=58 with effect from June 04, 2012. Since 2009-10, data is based on re-based index value of 58.

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.

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

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

Context

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

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

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

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

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

Content

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

Important Note

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

Acknowledgements

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

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

This comprehensive dataset provides detailed stock market information for the top 100 companies listed on the Bombay Stock Exchange (BSE). It includes:

Minute-by-minute data for the past year. Week-by-week data spanning 10 years. Month-by-month data covering nearly 24 years. This extensive dataset is ideal for researchers, analysts, and traders seeking in-depth insights into the performance and trends of BSE100 stocks.

Nigeria's main stock market index, the NSE-All Share, rose to 114617 points on June 5, 2025, gaining 1.63% from the previous session. Over the past month, the index has climbed 5.77% and is up 15.62% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Nigeria. Nigeria Stock Market NSE - values, historical data, forecasts and news - updated on June of 2025.

Analysis of ‘Nifty IT Index daily data 2011 to 2022’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/abhijeetbhilare/nifty-it-index-daily-data-2011-to-2022 on 13 February 2022.

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

Context

IT is one of the biggest revenue making industry in India. Around 8% of India's GDP is contributed by IT sector. This dataset shows how Top 10 IT companies of India are performing on daily basis.

Content

Dataset contains Daily performance of Top 10 IT companies of India listed on Nifty stock Exchange. Below are the brief In-sites about each column. 1. Date - Date of trading 2. Open - At what price trading started 3. High - Day's high traded price 4. Low - Day's low traded price 5. Close - At what price trading ended 6. Shares Traded - Volume of shares traded 7. Turnover - Turnover in Rupees (Cr.)

Acknowledgements

This dataset is taken from NSE site

Inspiration

Lets analyze Nifty IT sector and forcast how it will perform in future

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

The Nifty 50 is an index that represents the performance of the top 50 companies listed on the National Stock Exchange (NSE) in India. The dataset you mentioned includes 3-minute interval data for the Nifty 50 index from January 2015 to October 2022, with the date and time combined in a single "Date" column.

Each entry in the dataset represents a 3-minute interval and includes the following information:

1. date: The specific date and time corresponding to the 3-minute interval.
2. open: The opening price of the Nifty 50 index during that 3-minute period.
3. high: The highest price reached by the Nifty 50 index during that 3-minute period.
4. low: The lowest price reached by the Nifty 50 index during that 3-minute period.
5. close: The closing price of the Nifty 50 index during that 3-minute period. 6.volume: NA

This dataset with combined date and time information in a single "Date" column can still be utilized for scalping strategies and general analysis purposes. Traders and analysts can analyze the open, high, low, and close prices at each 3-minute interval, along with the associated date and time, to identify short-term trends, measure volatility, and determine potential entry and exit points for trades.

Additionally, traders and analysts can perform technical analysis, identify patterns, and develop trading strategies based on this dataset. They can apply various technical indicators, such as moving averages, oscillators, and trend lines, to gain insights into market dynamics and make informed trading decisions, considering the combined date and time information for each 3-minute interval.

By studying the Nifty 50 3-minute dataset, traders and analysts can gain a deeper understanding of the price behavior of the top 50 companies in the Indian stock market. The dataset spans from January 2015 to October 2022, allowing for comprehensive analysis of historical trends, patterns, and market movements. The combined date and time information in the "Date" column provides a reference for each 3-minute interval, enabling traders and analysts to refine their trading strategies, enhance decision-making processes, and potentially extract valuable insights for successful trading.

China's main stock market index, the SHANGHAI, rose to 3385 points on June 6, 2025, gaining 0.04% from the previous session. Over the past month, the index has climbed 1.28% and is up 10.95% 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 June of 2025.

Turkey's main stock market index, the BIST 100, rose to 9487 points on June 5, 2025, gaining 0.12% from the previous session. Over the past month, the index has climbed 3.85%, though it remains 7.72% lower than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Turkey. Turkey Stock Market - values, historical data, forecasts and news - updated on June of 2025.

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

Context

nifty50.csv The NIFTY 50 index is National Stock Exchange of India's benchmark stock market index for Indian equity market. It is a well diversified 50 stock index accounting for 22 sectors of the economy. It is used for a variety of purposes such as bench-marking fund portfolios, index based derivatives and index funds.

banknifty.csv Bank Nifty represents the 12 most liquid and large capitalized stocks from the banking sector which trade on the National Stock Exchange (NSE). It provides investors and market intermediaries a benchmark that captures the capital market performance of Indian banking sector.

Content

A data frame with 8 variables: index, date, time, open, high, low, close and id. For each year from 2013 to 2016, the number of trading data of each minute of given each date. The currency of the price is Indian Rupee (INR).

• index : market id
• date: numerical value (Ex. 20121203- to be converted to 2012/12/03)
• time: factor (Ex. 09:16)
• open: numeric (opening price)
• high: numeric (high price)
• low: numeric (low price)
• close: numeric (closing price)

Inspiration

Initial raw data sets are very complex and mixed datatypes. These are processed properly using R libraries like dplyr, stringr and other data munging packages. The desired outputs are then converted into a CSV format to use for further analysis.

Pakistan's main stock market index, the KSE 100, fell to 121641 points on June 5, 2025, losing 0.13% from the previous session. Over the past month, the index has climbed 7.11% and is up 64.68% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Pakistan. Pakistan Stock Market (KSE100) - values, historical data, forecasts and news - updated on June of 2025.

The Measurable AI Temu & Fast Fashion E-Receipt Dataset is a leading source of email receipts and transaction data, offering data collected directly from users via Proprietary Consumer Apps, with millions of opt-in users.

We source our email receipt consumer data panel via two consumer apps which garner the express consent of our end-users (GDPR compliant). We then aggregate and anonymize all the transactional data to produce raw and aggregate datasets for our clients.

Use Cases Our clients leverage our datasets to produce actionable consumer insights such as: - Market share analysis - User behavioral traits (e.g. retention rates) - Average order values - Promotional strategies used by the key players. Several of our clients also use our datasets for forecasting and understanding industry trends better.

Coverage - Asia (Japan, Thailand, Malaysia, Vietnam, Indonesia, Singapore, Hong Kong, Phillippines) - EMEA (Spain, United Arab Emirates, Saudi, Qatar) - Latin America (Brazil, Mexico, Columbia, Argentina)

Granular Data Itemized, high-definition data per transaction level with metrics such as - Order value - Items ordered - No. of orders per user - Delivery fee - Service fee - Promotions used - Geolocation data and more - Email ID (can work out user overlap with peers and loyalty)

Aggregate Data - Weekly/ monthly order volume - Revenue delivered in aggregate form, with historical data dating back to 2018.

Most of our clients are fast-growing Tech Companies, Financial Institutions, Buyside Firms, Market Research Agencies, Consultancies and Academia.

Our dataset is GDPR compliant, contains no PII information and is aggregated & anonymized with user consent. Contact business@measurable.ai for a data dictionary and to find out our volume in each country.

Browse LSEG's I/B/E/S Estimates, discover our range of data, indices & benchmarks. Our Data Catalogue offers unrivalled data and delivery mechanisms.

This dataset contains daily OHLCV data for ~ 2000 Indian Stocks listed on the National Stock Exchange for all time. The columns are multi-index columns, so this needs to be taken into account when reading and using the data. Source : Yahoo Finance Type: All files are CSV format. Currency : INR

All the tickers have been collected from here : https://www.nseindia.com/market-data/securities-available-for-trading

If using pandas, the following function is a utility to read any of the CSV files: ``` import pandas as pd def read_ohlcv(filename): "read a given ohlcv data file downloaded from yfinance" return pd.read_csv( filename, skiprows=[0, 1, 2], # remove the multiindex rows that cause trouble names=["Date", "Close", "High", "Low", "Open", "Volume"], index_col="Date", parse_dates=["Date"], )

dataset = read_ohlcv("ABCAPITAL.NS.csv")

The stocks of goods held by firms in India increased by 897.01 INR Billion in the first quarter of 2025. This dataset provides - India Changes in Inventories - actual values, historical data, forecast, chart, statistics, economic calendar and news.