India's main stock market index, the SENSEX, fell to 85138 points on December 2, 2025, losing 0.59% from the previous session. Over the past month, the index has climbed 1.38% and is up 5.31% 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 December of 2025.

Key information about India Sensitive 30 (Sensex)

• India Sensitive 30 (Sensex) closed at 85,706.7 points in Nov 2025, compared with 83,938.7 points at the previous month end
• India Equity Market Index: Month End: BSE: Sensitive 30 (Sensex) data is updated monthly, available from Apr 1979 to Nov 2025, with an average number of 2,987.7 points
• The data reached an all-time high of 85,706.7 points in Nov 2025 and a record low of 115.6 points in Nov 1979

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Further information about India Sensitive 30 (Sensex)

• In the latest reports, SENSEX recorded a daily P/E ratio of 23.2 in Dec 2025

India: Stock market capitalization, billion USD: The latest value from 2024 is 5131.4 billion U.S. dollars, an increase from 4340.13 billion U.S. dollars in 2023. In comparison, the world average is 1647.20 billion U.S. dollars, based on data from 68 countries. Historically, the average for India from 2000 to 2024 is 1822.81 billion U.S. dollars. The minimum value, 148.77 billion U.S. dollars, was reached in 2001 while the maximum of 5131.4 billion U.S. dollars was recorded in 2024.

The Indian Stock Market Dataset provides a comprehensive collection of stock market data sourced from secondary sources, primarily Google, offering insights into investment opportunities and trends within the Indian financial landscape. This dataset encompasses a wide array of information, with a primary focus on Return on Investment (ROI) metrics and the respective industry sectors in which investments are made.

With a reliability rating of 80%, this dataset offers valuable insights for investors, analysts, researchers, and enthusiasts seeking to understand and navigate the complexities of the Indian stock market. The dataset serves as a foundational resource for analyzing market performance, identifying lucrative investment opportunities, and making informed decisions in a dynamic financial environment.

Key features of the dataset include:

ROI Analysis: The dataset provides detailed ROI metrics, allowing stakeholders to assess the profitability of various investment avenues over specific timeframes. By analyzing ROI trends, investors can gauge the performance of individual stocks, portfolios, or entire industry sectors, facilitating strategic investment planning and risk management.

Industry Classification: Each investment entry in the dataset is categorized according to its respective industry sector. This classification enables users to explore investment opportunities within specific sectors such as technology, healthcare, finance, energy, consumer goods, and more. Understanding industry dynamics and market trends is essential for optimizing investment portfolios and diversifying risk exposure.

Historical Data: The dataset includes historical stock market data, offering insights into past performance trends and market behavior. By examining historical data, users can identify patterns, correlations, and anomalies that may impact future investment decisions. Historical analysis empowers investors to make informed predictions and adapt strategies in response to evolving market conditions.

Data Accuracy: While the dataset boasts an accuracy rate of 80%, users should exercise diligence and consider additional sources for validation and verification. While the majority of data points are reliable, occasional discrepancies or inaccuracies may exist, highlighting the importance of due diligence and comprehensive analysis in the investment process.

Accessibility: The Indian Stock Market Dataset is easily accessible and user-friendly, catering to a diverse audience ranging from seasoned investors to novices exploring the world of finance. The dataset can be utilized for various purposes, including academic research, financial modeling, algorithmic trading, and investment portfolio management.

In summary, the Indian Stock Market Dataset offers a valuable resource for analyzing ROI and industry trends within the Indian financial landscape. With a focus on accuracy, accessibility, and comprehensive data coverage, this dataset empowers stakeholders to make informed investment decisions, optimize portfolio performance, and navigate the complexities of the dynamic stock market environment. Whether you're a seasoned investor or a novice enthusiast, this dataset provides valuable insights for unlocking the potential of the Indian stock market.

Actual value and historical data chart for India Stock Market Return Percent Year On Year

NSE Stock Historical Price Data (Market Cap > 500 Cr)

Dataset Description

This dataset contains the historical closing price data for all stocks listed on the National Stock Exchange (NSE) of India with a market capitalization exceeding 500 crore INR. The dataset is ideal for analysts, researchers, and enthusiasts who wish to perform detailed analysis, develop trading algorithms, or study market trends of substantial companies within the Indian stock market.

Features

1. Stock Ticker: Unique symbol representing each stock.
2. Date: The specific trading date.
3. Closing Price: The price at which the stock closed on a given day.

Source

The data is sourced from official NSE records and includes all companies meeting the market capitalization criteria as of the latest update.

Applications

• Trend Analysis: Understand how stock prices of major companies have fluctuated over time.
• Algorithmic Trading: Develop and backtest trading algorithms using real historical data.
• Market Research: Study the performance of large-cap stocks to gain insights into market dynamics.
• Educational Use: Serve as a practical dataset for educational purposes in finance, economics, and data science courses.

Usage

The dataset can be used for various purposes including but not limited to: - Financial modeling and forecasting - Risk management and portfolio optimization - Academic research and projects - Machine learning and AI-driven stock prediction models

Stock market index in India, September, 2025 The most recent value is 297.41 points as of September 2025, an increase compared to the previous value of 295.41 points. Historically, the average for India from January 1960 to September 2025 is 40.36 points. The minimum of 0.29 points was recorded in June 1975, while the maximum of 304.47 points was reached in September 2024. | TheGlobalEconomy.com

Graph and download economic data for Financial Market: Share Prices for India (SPASTT01INA661N) from 1957 to 2024 about India and stock market.

Explore a comprehensive dataset of the Nifty 50, covering the period from 09 November 2015 to 12 July 2024. This dataset includes essential market variables such as Open, Close, High, Low, Shares Traded, and Turnover (₹ Cr) on a daily basis. Ideal for financial analysts, researchers, and machine learning enthusiasts, this data provides valuable insights into market trends, volatility, and trading patterns of India's benchmark stock index.

Tips:- - You can increase the number of features by using EMA_5/EMA_20 , SMA , RSI etc. - Need more Historical Data Click_me - You can even get data of Indian Bank , Mid Cap ... etc. from Click_me

Would like hear your Suggestion , Reviews and Usecase 😎

Thank You 😍

India: Stock market value traded, percent of GDP: The latest value from 2024 is 85.55 percent, an increase from 53.46 percent in 2023. In comparison, the world average is 44.48 percent, based on data from 33 countries. Historically, the average for India from 2000 to 2024 is 56.97 percent. The minimum value, 30.75 percent, was reached in 2013 while the maximum of 109.49 percent was recorded in 2000.

Description:

Explore the dynamic landscape of the Indian stock market with this extensive dataset featuring 4456 companies listed on both the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE). Gain insights into each company's financial performance, quarterly and yearly profit and loss statements, balance sheets, cash flow data, and essential financial ratios. Dive deep into the intricacies of shareholding patterns, tracking the movements of promoters, foreign and domestic institutional investors, and the public.

This dataset is a rich resource for financial analysts, investors, and data enthusiasts. Perform thorough company evaluations, sector-wise comparisons, and predictive modeling. With figures presented in crore rupees, leverage the dataset for in-depth exploratory data analysis, time series forecasting, and machine learning applications. Stay tuned for updates as we enrich this dataset for a deeper understanding of the Indian stock market landscape. Unlock the potential of data-driven decision-making with this comprehensive repository of financial information.

Folder Structure:

• 4492 NSE & BSE Companies
  • Main directory containing data for 4456 NSE and BSE registered companies.
  • Company_name folder
    • Individual folders for each company allowing for easy organization and retrieval.
    • Company_name.csv
      • General company information.
    • Quarterly_Profit_Loss.csv
      • Quarterly financial data.
    • Yearly_Profit_Loss.csv
      • Annual financial data.
    • Yearly_Balance_Sheet.csv
      • Annual balance sheet information.
    • Yearly_Cash_flow.csv
      • Annual cash flow data.
    • Ratios.csv.csv
      • Financial ratios over time.
    • Quarterly_Shareholding_Pattern.csv
      • Quarterly shareholding pattern.
    • Yearly_Shareholding_Pattern.csv
      • Annual shareholding pattern.

File Explanation:

Company_name.csv

- `Company_name`: Name of the company.
- `Sector`: Industry sector of the company.
- `BSE`: Bombay Stock Exchange code.
- `NSE`: National Stock Exchange code.
- `Market Cap`: Market capitalization of the company.
- `Current Price`: Current stock price.
- `High/Low`: Highest and lowest stock prices.
- `Stock P/E`: Price to earnings ratio.
- `Book Value`: Book value per share.
- `Dividend Yield`: Dividend yield percentage.
- `ROCE`: Return on capital employed percentage.
- `ROE`: Return on equity percentage.
- `Face Value`: Face value of the stock.
- `Price to Sales`: Price to sales ratio.
- `Sales growth (1, 3, 5, 7, 10 years)`: Sales growth percentage over different time periods.
- `Profit growth (1, 3, 5, 7, 10 years)`: Profit growth percentage over different time periods.
- `EPS`: Earnings per share.
- `EPS last year`: Earnings per share in the last year.
- `Debt (1, 3, 5, 7, 10 years)`: Debt of the company over different time periods.

Quarterly_Profit_Loss.csv

 - `Sales`: Revenue generated by the company.
 - `Expenses`: Total expenses incurred.
 - `Operating Profit`: Profit from core operations.
 - `OPM %`: Operating Profit Margin percentage.
 - `Other Income`: Additional income sources.
 - `Interest`: Interest paid.
 - `Depreciation`: Depreciation of assets.
 - `Profit before tax`: Profit before tax.
 - `Tax %`: Tax percentage.
 - `Net Profit`: Net profit after tax.
 - `EPS in Rs`: Earnings per share.

Yearly_Profit_Loss.csv

- Same as Quarterly_Profit_Loss.csv, but on a yearly basis.

Yearly_Balance_Sheet.csv

- `Equity Capital`: Capital raised through equity.
- `Reserves`: Company's retained earnings.
- `Borrowings`: Company's borrowings.
- `Other Liabilities`: Other financial obligations.
- `Total Liabilities`: Sum of all liabilities.
- `Fixed Assets`: Company's long-term assets.
- `CWIP`: Capital Work in Progress.
- `Investments`: Company's investments.
- `Other Assets`: Other non-current assets.
- `Total Assets`: Sum of all assets.

Yearly_Cash_flow.csv

- `Cash from Operating Activity`: Cash generated from core business operations.
- `Cash from Investing Activity`: Cash from investments.
- `Cash from Financing Activity`: Cash from financing (borrowing, stock issuance, etc.).
- `Net Cash Flow`: Overall net cash flow.

Ratios.csv.csv

- `Debtor Days`: Number of days it takes to collect receivables.
- `Inventory Days`: Number of days inventory is held.
- `Days Payable`: Number of days a company takes to pay its bills.
- `Cash Conversion Cycle`: Time taken to convert sales into cash.
- `Wor...

Last Update - 9th FEB 2025

Disclaimer!!! Data uploaded here are collected from the internet and some google drive. The sole purposes of uploading these data are to provide this Kaggle community with a good source of data for analysis and research. I don't own these datasets and am also not responsible for them legally by any means. I am not charging anything (either money or any favor) for this dataset. RESEARCH PURPOSE ONLY

THIS IS THE LARGEST DATASET ON NIFTY 100 STOCKS WITH EACH MINUTES AND DAILY DATA (2015 to 2025)

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 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 This dataset contains Nifty 100 historical daily prices. The historical data are retrieved from the NSE India website. Each stock in this Nifty 500 and are of 1 minute itraday data.

Every dataset contains the following fields. Open - Open price of the stock High - High price of the stock Low - Low price of the stock Close - Close price of the stock Volume - Volume traded of the stock in this time frame

Inspiration

• Data is uploaded for Research and Educational purposes.
• The data scientists and researchers can download and can build EDA, find Correlations, and perform Regression analysis on it.
• Quant researchers can build strategies and backtest their strategies with this dataset.

Stock Names

| ACC | ADANIENT | ADANIGREEN | ADANIPORTS | AMBUJACEM | | -- | -- | -- | -- | -- | | APOLLOHOSP | ASIANPAINT | AUROPHARMA | AXISBANK | BAJAJ-AUTO | | BAJAJFINSV | BAJAJHLDNG | BAJFINANCE | BANDHANBNK | BANKBARODA | | BERGEPAINT | BHARTIARTL | BIOCON | BOSCHLTD | BPCL | | BRITANNIA | CADILAHC | CHOLAFIN | CIPLA | COALINDIA | | COLPAL | DABUR | DIVISLAB | DLF | DMART | | DRREDDY | EICHERMOT | GAIL | GLAND | GODREJCP | | GRASIM | HAVELLS | HCLTECH | HDFC | HDFCAMC | | HDFCBANK | HDFCLIFE | HEROMOTOCO | HINDALCO | HINDPETRO | | HINDUNILVR | ICICIBANK | ICICIGI | ICICIPRULI | IGL | | INDIGO | INDUSINDBK | INDUSTOWER | INFY | IOC | | ITC | JINDALSTEL | JSWSTEEL | JUBLFOOD | KOTAKBANK | | LICI | LT | LTI | LUPIN | M&M | | MARICO | MARUTI | MCDOWELL-N | MUTHOOTFIN | NAUKRI | | NESTLEIND | NIFTY 50 | NIFTY BANK | NMDC | NTPC | | ONGC | PEL | PGHH | PIDILITIND | PIIND | | PNB | POWERGRID | RELIANCE | SAIL | SBICARD | | SBILIFE | SBIN | SHREECEM | SIEMENS | SUNPHARMA | | TATACONSUM | TATAMOTORS | TATASTEEL | TCS | TECHM | | TITAN | TORNTPHARM | ULTRACEMCO | UPL | VEDL | | WIPRO | YESBANK | | | |

Graph and download economic data for Volatility of Stock Price Index for India (DDSM01INA066NWDB) from 1984 to 2021 about volatility, stocks, India, price index, indexes, and price.

Description:

Empowering Indian Investors: NSE's Historical Yearly Financial Ratios for 1800 Stocks with Predictive Modeling and Strategy Backtesting

Financial data is the lifeblood of investment analysis and decision-making, and for Indian investors navigating the dynamic National Stock Exchange (NSE), access to comprehensive and tailored datasets is crucial. The NSE 1800 Stocks Historical Yearly Financial Ratios dataset is a valuable resource designed to empower Indian investors, analysts, and financial professionals with the essential financial information needed for predictive modeling and strategy backtesting within the context of the Indian stock market.

Motivation:

The Indian stock market presents unique opportunities and challenges. The motivation behind this dataset is to provide Indian investors with a robust financial dataset that enables them to perform predictive modeling and strategy backtesting independently. It aims to streamline the analysis process, promote data-driven decision-making, and enhance the understanding of Indian stock market dynamics.

Context:

Understanding the financial performance of Indian companies is fundamental for Indian investors, and this dataset offers a wealth of historical financial metrics and ratios for 1800 stocks listed on the NSE. It is distinguished by the ability to:

1 Perform Predictive Modeling: Users can leverage this dataset to build their predictive models tailored to the Indian market's unique characteristics. These models can assist investors in forecasting financial metrics, stock prices, and market trends specific to the Indian context.

2 Conduct Strategy Backtesting: Indian investors can independently test their investment strategies using historical data from the NSE. This dataset serves as the foundation for users to assess the performance of their strategies while considering factors such as Indian economic cycles, regulatory changes, and market dynamics.

3 Evaluate Financial Health: Users can assess the financial stability, profitability, and operational efficiency of Indian companies by utilizing a comprehensive collection of historical financial ratios and metrics.

4 Support Informed Decision-Making: By providing access to the historical financial data of 1800 stocks listed on the NSE, this dataset equips Indian investors with the information needed to make well-informed investment decisions, navigate the Indian stock market, and manage their portfolios effectively.

In summary, the NSE 1800 Stocks Historical Yearly Financial Ratios for Predictive Modeling and Strategy Backtesting (Tailored for Indian Investors) dataset is a robust resource that empowers Indian investors to independently perform predictive modeling and strategy backtesting. It serves as a foundational dataset to support data-driven investment decisions within the unique context of the Indian stock market. Whether you are an Indian investor, analyst, or financial professional, this dataset equips you with the financial data needed to enhance your investment strategies and decision-making.

Stock market capitalization to GDP (%) in India was reported at 97.29 % in 2020, according to the World Bank collection of development indicators, compiled from officially recognized sources. India - Stock market capitalization to GDP - actual values, historical data, forecasts and projections were sourced from the World Bank on November of 2025.

In 2024, the returns on Nifty 50 reported a rise of 8.75 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).

Graph and download economic data for Financial Market: Share Prices for India (SPASTT01INQ661N) from Q1 1957 to Q3 2025 about India and stock market.

Key information about India Market Capitalization

• India Market Capitalization accounted for 5,298.749 USD bn in Oct 2025, compared with a percentage of 5,084.976 USD bn in the previous month
• India Market Capitalization is updated monthly, available from Jan 1993 to Oct 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.

This statistic depicts the average annual performance of the S&P BSE Sensex Index in India from years 2012 to 2024. In 2024, the year-end value S&P BSE Sensex Index was reported at *********, an increase from the previous year where the value was *********.

Nigeria's main stock market index, the NSE All Share, fell to 143210 points on December 1, 2025, losing 0.22% from the previous session. Over the past month, the index has declined 6.85%, though it remains 46.53% higher than a year ago, 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 December of 2025.