Prices for NSE Nifty 50 Index including live quotes, historical charts and news. NSE Nifty 50 Index was last updated by Trading Economics this September 1 of 2025.

Nigeria's main stock market index, the NSE-All Share, fell to 138768 points on September 2, 2025, losing 0.68% from the previous session. Over the past month, the index has declined 3.68%, though it remains 43.25% 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 September of 2025.

Japan Index: Nagoya Stock Exchange (NSE): Option 25 Index: Price data was reported at 1,104.130 04Jan1988=1000 in Nov 2018. This records a decrease from the previous number of 1,107.090 04Jan1988=1000 for Oct 2018. Japan Index: Nagoya Stock Exchange (NSE): Option 25 Index: Price data is updated monthly, averaging 876.945 04Jan1988=1000 from Jun 1992 (Median) to Nov 2018, with 318 observations. The data reached an all-time high of 1,519.300 04Jan1988=1000 in Jun 2007 and a record low of 577.620 04Jan1988=1000 in May 2012. Japan Index: Nagoya Stock Exchange (NSE): Option 25 Index: Price data remains active status in CEIC and is reported by Nagoya Stock Exchange. The data is categorized under Global Database’s Japan – Table JP.Z002: All Stock Exchange: Market Indices. Data prior to January 1999 was taken from daily conversion.

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.

The dataset contains All India Daily NSE Index Values – NSE-S&P CNX 500 and Nifty 50

Note: 1. CNX Nifty has been rebranded as Nifty 50 w.e.f November 09, 2015.

This dataset contains historical data of the NSE main Index NIFTY 50 which lists the top 50 companies in India. It contains the opening, closing, high, low, adj close, volume data of the NIFTY 50 index from 2007 to 2024.

Japan Index: NSE: Stock Price Index: 1st Section Nagoya Issues data was reported at 3,368.710 04Jan1968=100 in Oct 2018. This records a decrease from the previous number of 3,749.150 04Jan1968=100 for Sep 2018. Japan Index: NSE: Stock Price Index: 1st Section Nagoya Issues data is updated monthly, averaging 2,038.020 04Jan1968=100 from Feb 1999 (Median) to Oct 2018, with 237 observations. The data reached an all-time high of 3,994.950 04Jan1968=100 in May 2015 and a record low of 1,381.220 04Jan1968=100 in Mar 2003. Japan Index: NSE: Stock Price Index: 1st Section Nagoya Issues data remains active status in CEIC and is reported by Nagoya Stock Exchange. The data is categorized under Global Database’s Japan – Table JP.Z002: All Stock Exchange: Market Indices.

Key information about Nigeria NSE All Share

• Nigeria NSE All Share closed at 107,821.4 points in Feb 2025, compared with 104,496.1 points at the previous month end
• Nigeria Equity Market Index: Month End: NSE All Share data is updated monthly, available from Jan 1985 to Feb 2025, with an average number of 21,486.6 points
• The data reached an all-time high of 107,821.4 points in Feb 2025 and a record low of 111.3 points in Jan 1985

• In the latest reports, Weighted Equities recorded a yearly P/E ratio of 108.0 in Dec 2021

Japan Index: NSE: Stock Price Index: 2nd Section Nagoya Issues data was reported at 4,964.590 04Jan1968=100 in Oct 2018. This records a decrease from the previous number of 5,244.000 04Jan1968=100 for Sep 2018. Japan Index: NSE: Stock Price Index: 2nd Section Nagoya Issues data is updated monthly, averaging 1,898.190 04Jan1968=100 from Feb 1999 (Median) to Oct 2018, with 237 observations. The data reached an all-time high of 5,244.000 04Jan1968=100 in Sep 2018 and a record low of 1,228.080 04Jan1968=100 in Dec 2002. Japan Index: NSE: Stock Price Index: 2nd Section Nagoya Issues data remains active status in CEIC and is reported by Nagoya Stock Exchange. The data is categorized under Global Database’s Japan – Table JP.Z002: All Stock Exchange: Market Indices.

Prices for Nigerian Stock Exchange All Share Index including live quotes, historical charts and news. Nigerian Stock Exchange All Share Index was last updated by Trading Economics this September 1 of 2025.

India's main stock market index, the SENSEX, rose to 80364 points on September 1, 2025, gaining 0.70% from the previous session. Over the past month, the index has declined 0.81% and is down 2.66% 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 September of 2025.

This statistic depicts the average annual performance of the Nifty 50 Index in India from years 2011 to 2024. In 2024, the average annual Nifty 50 Index was reported as ********, an increase from the previous year where the value was ********.

Dataset Overview:

The dataset contains information about 6,717 financial instruments listed on the National Stock Exchange (NSE) of India. The data includes a variety of instruments such as equity indices, stocks, and other financial products. Here’s a breakdown of the columns:

• instrument_token: A unique identifier for each instrument.
• exchange_token: Another identifier specific to the exchange.
• tradingsymbol: The trading symbol of the instrument.
• name: The full name of the instrument (some entries might be missing this information).
• last_price: The last traded price of the instrument.
• expiry: Expiry date for derivative instruments (mostly null for this dataset).
• strike: Strike price for options (mostly zero or not applicable here).
• tick_size: The minimum price movement for the instrument.
• lot_size: The lot size for trading the instrument.
• instrument_type: The type of instrument (e.g., equity, index).
• segment: The market segment to which the instrument belongs (e.g., INDICES, EQUITIES).
• exchange: The exchange where the instrument is listed (in this case, all are from NSE).

Sample Data:

Here’s a quick look at the first few entries:

Dataset Description for Kaggle:

Instruments NSE Dataset

Description:

This dataset contains detailed information on 6,717 financial instruments listed on the National Stock Exchange (NSE) of India. It includes a range of instruments such as equity indices, stocks, and derivatives. This dataset can be used for financial analysis, trading strategy development, and backtesting.

Columns:

• instrument_token: Unique identifier for each instrument.
• exchange_token: NSE-specific identifier.
• tradingsymbol: The trading symbol used to identify the instrument on the NSE.
• name: Full name of the instrument (where available).
• last_price: The most recent traded price of the instrument.
• expiry: Expiry date for derivatives (where applicable).
• strike: Strike price for options (mostly irrelevant for this dataset).
• tick_size: The smallest price movement allowed in trading this instrument.
• lot_size: The lot size, indicating the number of units per trade.
• instrument_type: Indicates the type of instrument, such as equity or index.
• segment: The market segment, such as indices or equities.
• exchange: The exchange where the instrument is listed, which in this dataset is the NSE.

Usage:

This dataset is ideal for: - Market Analysis: Understanding the structure and constituents of the NSE. - Trading Strategies: Developing and backtesting trading strategies using historical data. - Educational Purposes: Learning about financial markets and instruments.

Acknowledgments:

The data has been sourced from the National Stock Exchange of India (NSE).

You can use this description as the text when you upload the dataset to Kaggle. It covers all the essential details, making it easy for users to understand the contents and potential applications of the dataset.

Japan Index: NSE: Stock Price Index: 2nd Section Composite data was reported at 3,638.890 04Jan1968=100 in Oct 2018. This records an increase from the previous number of 3,634.600 04Jan1968=100 for Sep 2018. Japan Index: NSE: Stock Price Index: 2nd Section Composite data is updated monthly, averaging 1,350.530 04Jan1968=100 from Feb 1999 (Median) to Oct 2018, with 237 observations. The data reached an all-time high of 3,655.090 04Jan1968=100 in Jul 2018 and a record low of 871.670 04Jan1968=100 in Nov 2002. Japan Index: NSE: Stock Price Index: 2nd Section Composite data remains active status in CEIC and is reported by Nagoya Stock Exchange. The data is categorized under Global Database’s Japan – Table JP.Z002: All Stock Exchange: Market Indices.

Nigerian Stock Exchange (NSE) Top 30 Index Companies List from 15 Jan 2009 - April 2018

A List of top 30 Listed companies on Nigeria Stock Exchange as at April 2018 with their Capitalization Value and Ranking. We also Include a computation of proportion of the NSE controlled by the NSE 30 Index by dividing the total Market Capitalization for the NSE 30 Index by total market Capitalization for the whole NSE. In addition we compute the the ratio of Non-Financial services companies and Financial services companies as a percentage the whole value of NSE Market Capitalization

Disclaimer!!! Data uploaded here are collected from the internet. 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 monetary or any favor) for this dataset.

For the first time, Nifty 50 stocks data and two indices data, along with 55 technical indicators used by Market experts are calculated and made available. Kindly download the data and make sure to share your code in public and if you like this data, do upvote. Thank you.

About Nifty 50

The NIFTY 50 index is a well-diversified 50 companies index reflecting overall market conditions. NIFTY 50 Index is computed using the free float market capitalization method.

NIFTY 50 can be used for a variety of purposes such as benchmarking fund portfolios, launching of index funds, ETFs and structured products.

Overview

This dataset contains historical daily prices for Nifty 100 stocks and indices currently trading on the Indian Stock Market. - Data samples are of 5-minute intervals and the availability of data is from Jan 2015 to Feb 2022. - Along with OHLCV (Open, High, Low, Close, and Volume) data, we have created 55 technical indicators. - More details about these technical indicators are provided in the Data description file.

Content

The whole dataset is around 33 GB (compressed here to 13 GB), and 100 stocks (Nifty 100 stocks) and 2 indices (Nifty 50 and Nifty Bank indices) are present in this dataset. Details about each file are - - OHLCV (Open, High, Low, Close, and Volume) data - 55 Technical indicator values are also present

Inspiration

• Data is uploaded for Research and Educational purposes.

Possible problem statements

• Univariate and Multi-variate time series forecasting of stock prices and index prices
• Multi-variate data can be used to predict the trend of the stock price (Buy or Sell or Hold)
• Different intraday or positional trading strategies can be built out of this multivariate data. [technical indicators are already added here]
• EDA on time series data

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 | | | |

Kenya's main stock market index, the Nairobi 20, rose to 2914 points on September 2, 2025, gaining 1.37% from the previous session. Over the past month, the index has climbed 15.52% and is up 72.33% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Kenya. Kenya Stock Market (NSE20) - values, historical data, forecasts and news - updated on September of 2025.

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.

Should You Buy NSE ITC Right Now? (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

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.

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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...