Eqty Price Volume:

Historic Data of Equity Price Volume of all equities traded in

National Stock Exchange (NSE India)

It has data since 1994.

Indices Files:

indices_delta_01_BroadMarket

indices_delta_01_Sectoral

Historic Data of all Indices. It has broader market as well sector market.

indices_delta_01_BroadMarket has consolidate broader market data upto a certain date.

indices_delta_01_Sectoral has consolidate sectoral market data upto a certain date.

Eqty Dlvry Pos:

Historic Data of equity delivery position of each stock traded in NSE.

All three files has data upto 19th April, 2021

Should you require more data, please approach me or you shall get it directly from NSE.

Prices for NSE Nifty 50 Index including live quotes, historical charts and news. NSE Nifty 50 Index was last updated by Trading Economics this August 2 of 2025.

India's main stock market index, the SENSEX, fell to 80600 points on August 1, 2025, losing 0.72% from the previous session. Over the past month, the index has declined 3.37% and is down 0.47% 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 August of 2025.

This statistic represents the market capitalization of the National Stock Exchange (NSE) in India from fiscal year 2012 to fiscal year 2017. During the fiscal year 2016, the National Stock Exchange had a market capitalization just over ** trillion Indian rupees.

Context

Stock market data is widely analyzed for educational, business and personal interests.

Content

The data is the price history and trading volumes of the fifty stocks in the index NIFTY 50 from NSE (National Stock Exchange) India. All datasets are at a day-level with pricing and trading values split across .cvs files for each stock along with a metadata file with some macro-information about the stocks itself. The data spans from 1st January, 2000 to 30th April, 2021.

Update Frequency

Since new stock market data is generated and made available every day, in order to have the latest and most useful information, the dataset will be updated once a month.

Acknowledgements

NSE India: https://www.nseindia.com/
Thanks to NSE for providing all the data publicly.

Inspiration

Various machine learning techniques can be applied and explored to stock market data, especially for trading algorithms and learning time series models.

Gain access to LSEG's National Stock Exchange of India data, India's largest stock exchange with more than 180,000 terminals across 600 districts.

The number of companies listed in the National Stock Exchange in India was 1959 in financial year 2020, an increase by **** companies compared to the previous year. Out of these nearly ************ companies there is only *** foreign company listed at the NSE.

After some rigorous SQL queries and coding on python. I made this dataset. In this dataset, all stocks of the Indian Stock Market are present a total of 2435 stocks. The data is of 1-year rows represent stock name and column represent date and I have filled the table with closing price. Enjoy and do some stock price predictions.

Key information about India Market Capitalization

• India Market Capitalization accounted for 4,388.733 USD bn in Feb 2025, compared with a percentage of 4,899.710 USD bn in the previous month
• India Market Capitalization is updated monthly, available from Jan 1993 to Feb 2025
• The data reached an all-time high of 5,663.221 USD bn in Sep 2024 and a record low of 55.322 USD bn in Apr 1993

CEIC converts monthly Market Capitalization into USD. BSE Limited provides Market Capitalization in local currency. The Federal Reserve Board period end market exchange rate is used for currency conversions.

In financial year 2024, a total of around ***** companies were listed in the National Stock Exchange (NSE) and the Bombay Stock Exchange (BSE) across India. This was an increase compared to the previous year.

NSE India listed company Vedanta Limited (VEDL) stock price history from 01-01-1996 to 13-01-2023. Yahoo Finance helped create this dataset. Vedanta Ltd. is a company listed and operational in India.

The file contains RELIANCE - NSE Stock Data from 1-Jan-16 to 6-May-21 The data can be used to forecast the stock prices of the future Its a timeseries data from the national stock exchange of India

In financial year 2024, **** unique investors were registered on the National Stock Exchange of India. It was a significant increase from the previous year. That year, new registrations accounted for nearly **********.

Key information about India P/E ratio

• India SENSEX recorded a daily P/E ratio of 21.540 on 26 Mar 2025, compared with 21.740 from the previous day.
• India SENSEX P/E ratio is updated daily, with historical data available from Dec 1988 to Mar 2025.
• The P/E ratio reached an all-time high of 36.210 in Feb 2021 and a record low of 15.670 in Mar 2020.
• BSE Limited provides daily P/E Ratio.

In the latest reports, Sensitive 30 (Sensex) closed at 73,198.100 points in Feb 2025.

The file contains HCLTECH - NSE Stock Data from 1-Jan-16 to 10-May-21 The data can be used to forecast the stock prices of the future Its a timeseries data from the national stock exchange of India

Its for EQUITY division

The dataset used in this paper is the historical prices of stocks from ten thematic sectors listed on the NSE of India.

In 2023, the returns on Nifty 50 reported a rise of ***** percent compared to the year before. Furthermore, since 2016, Nifty 50 has consistently demonstrated a positive trend in annual returns. Nifty 50 is a benchmark Indian stock market index, representing the weighted average of 50 of the largest Indian companies listed on the National Stock Exchange (NSE).

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Is NSE NAM-INDIA Stock Expected to Go Up? (Stock Forecast)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

The Nifty 50 Index data provides a comprehensive overview of the performance of the top 50 actively traded stocks listed on the National Stock Exchange of India (NSE). This dataset encompasses a wide range of industries, including finance, technology, healthcare, and consumer goods, offering insights into the overall health and direction of the Indian stock market.

Included in the data are key metrics such as daily opening and closing prices, high and low prices, trading volume, and percentage changes. These metrics allow analysts and investors to track trends, identify patterns, and make informed decisions regarding investment strategies.

Additionally, the dataset may incorporate historical data, enabling users to conduct thorough analyses over specific time periods and assess the long-term performance of individual stocks or the index as a whole. Whether used for research, financial modeling, or investment decision-making, the Nifty 50 Index data serves as a valuable resource for understanding and navigating the dynamic landscape of the Indian stock market.

The Real-time Candlestick OHLC API provides current candlestick data that covers all major stock exchanges including NYSE, NASDAQ, LSE, Euronext to NSE of India, TSE, and a few more. Users can choose from candlestick data with 1 min, 2 min, 5 min, 15 min, 30 min, 1 hour, 4 hour, 1 day, 1 week, 1 month and 1 year interval. By using the real-time candlestick OHLC data, they can visualize data on candlestick charts and build financial products.