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

Context : NIFTY 50 is the flagship stock market index of the National Stock Exchange (NSE) in India which is one of the leading stock exchanges in India. NIFTY 50 represents the performance of 50 large-cap companies across various sectors of the Indian economy.
Similarly NIFTY 100 represents the performance of the top 100 companies listed on the NSE based on market capitalization. NIFTY 100 is also part of several other indices, such as NIFTY 200, NIFTY 500, and NIFTY 100 Equal Weight Index.

In the National Stock Exchange (NSE) of India, there are three market segments based on the market capitalization of the listed companies. They are: - Large-cap: This segment includes the top 100 companies listed on the NSE based on market capitalization. - Mid-cap: This segment includes companies that rank between 101 and 250 based on market capitalization. - Small-cap: This segment includes companies that rank below the top 250 companies based on market capitalization. Market capitalization is calculated by multiplying a company's total outstanding shares by its current market price per share. The NSE's NIFTY Mid-cap 100 and NIFTY Small-cap 250 indices track the performance of companies in the mid-cap and small-cap segments of the market, respectively.

The NIFTY500 Multicap 50:25:25 index is a variant of the NIFTY 500 index, which represents the top 500 companies listed on India's National Stock Exchange (NSE). The Multicap 50:25:25 variant is a modified version of the NIFTY500 index that divides stocks into three categories based on market capitalization. The top 50 companies by market capitalization are classified as large-cap companies under this variant, while the next 150 companies are classified as mid-cap companies. The remaining 300 businesses are classified as small-cap.

Content : This Dataset contains records for all NIFTY-50 , NIFTY 200, NIFTY Midcap 100, NIFTY Smallcap 250, NIFTY500 Multicap 50:25:25 stocks, as on 1st March, 2023 - 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 - CHNG - Change in the price - %CHNG - Percentage change - Volume - volume of transaction - Value - Turn over in lakhs - 52W H - 52 Week High price - 52W L - 52 Week Lowest price - 365 D % CHNG - Past 365 Days Change Percentage - 30 D % CHNG - Past 30 Days Change Percentage

Note : - %CHNG: % change is calculated with respect to adjusted price on ex-date for Corporate Actions like: Dividend, Bonus, Rights & Face Value Split and also adjusted for Past 365 days & 30 days. - 52 W H/L: 52 week High & Low prices are adjusted for Bonus, Split & Rights Corporate actions.

Acknowledgements : The data is obtained from NSE website This is just daily level data provided here, you will get vast and detailed real-time & historical data from the official website.

Image Credit : https://gettyimages.com

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 | | | |

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

[COVID-19-IMPACT]


Further information about India Sensitive 30 (Sensex)

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

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 December 2 of 2025.

The S&P BSE Sensex index, one of India's two main stock indices, lost almost *********** of its value between the end of February and the end of March 2020, owing to the economic impact of the global coronavirus (COVID-19) pandemic. It has since recovered, surpassing its pre-corona level in *************.The S&P BSE Sensex index includes 30 companies listed on the Bombay Stock Exchange which are representative of various industrial sectors of the Indian economy. It is considered one of the main Indicators of the Indian stock market, along with the CNX Nifty Index (which includes shares from India's other main stock exchange, the National Stock Exchange).

UPDATED EVERY WEEK Last Update - 26th July 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

Context

• The NIFTY 50 is a well-diversified 50 stock index and it represents 13 important sectors of the economy.
• It is used for a variety of purposes such as benchmarking fund portfolios, index-based derivatives, and index funds.
• NIFTY 50 is owned and managed by NSE Indices Limited.
• The NIFTY 50 index has shaped up to be the largest single financial product in India.

This data contains all the indices of NSE. NIFTY 50, NIFTY BANK, NIFTY 100, NIFTY COMMODITIES, NIFTY CONSUMPTION, NIFTY FIN SERVICE, NIFTY IT, NIFTY INFRA, NIFTY ENERGY, NIFTY FMCG, NIFTY AUTO, NIFTY 200, NIFTY ALPHA 50, NIFTY 500, NIFTY CPSE, NIFTY GS COMPSITE, NIFTY HEALTHCARE, NIFTY CONSR DURBL, NIFTY LARGEMID250, NIFTY INDIA MFG, NIFTY IND DIGITAL, INDIA VIX

File Information and Column Descriptions.

Nifty 50 index data with 1 minute data. The dataset contains OHLC (Open, High, Low, and Close) prices from Jan 2015 to Aug 2024. - This dataset can be used for time series analysis, regression problems, and time series forecasting both for one step and multi-step ahead in the future. - Options data can be integrated with this minute data, to get more insight about this data. - Different backtesting strategies can be built on this data.

File Information

• This dataset contains 6 files, each file contains nifty 50 data with different intervals.
• Different intervals are - 1 min, 3 min, 5 min, 15 min, and 1 hour, Daily data from intervals of 2015 Jan to 2024 August.

Column Descriptors

• Each file contains OHLC (Open, High, Low, and Close) prices and Data time information. Since these are Nifty 50 index data, so volume is not present.

Inspiration

Time series forecasting - Predict stock price

• Predict future stock price one step ahead and multi-step ahead in time.
• Use different time series forecasting techniques for forecasting the future stock price. ### Machine learning and Deep learning techniques
• Possible ML and DL models include Neural networks, RNNs, LSTMs, Transformers, Attention networks, etc.
• Different error functions can be considered like RMSE, MAE, RMSEP etc. ### Feature engineering
• Different augmented features can be created and that can be used for forecasting.
• Correlation analysis, Feature importance to justify the important features.

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.

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

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Stonks by unknown memer.

Prices for Nairobi Securities Exchange Ltd All Share Index including live quotes, historical charts and news. Nairobi Securities Exchange Ltd All Share Index was last updated by Trading Economics this December 2 of 2025.

Latest broker research reports with buy, sell, hold recommendations along with forecast share price targets and upside. Browse thousands of reports and search by company or the broker.

This dataset contains the data of quarterly results of NIFTY 500 companies. Nifty 500 is an index maintained by the National Stock Exchange of India (NSE). The Nifty 500 is designed to represent the performance of the 500 largest publicly traded companies listed on the NSE, spanning various sectors of the Indian economy. Nifty 500 includes stocks from large, mid, and small-cap segments, providing a comprehensive view of the overall market.

The dataset contains 17 columns covering aspects of the companies and their quarterly results. These columns are described below: Name: The name of the company.

NSE Code: The National Stock Exchange code assigned to the company for trading on the NSE.

BSE Code: The Bombay Stock Exchange code assigned to the company for trading on the BSE.

Sector: The sector to which the company belongs. Sectors classify companies based on the nature of their business activities.

Industry: The industry in which the company operates, providing more detailed information about its specific line of business.

Revenue: The total income generated by the company during a specific quarter, reflecting its sales or service revenue.

Operating Expenses: The total expenses incurred by the company in its day-to-day operations, excluding financial and tax-related expenses.

Operating Profit: The profit obtained after deducting operating expenses from revenue, indicating the profitability of the core business operations.

Operating Profit Margin: The percentage representing the proportion of revenue that translates into operating profit, indicating operational efficiency.

Depreciation: The decrease in the value of the company's assets over time, representing the allocated cost of tangible assets.

Interest: The cost of borrowing for the company, reflecting interest payments on loans and other financial obligations.

Profit Before Tax: The company's profit before deducting income tax, including operating profit and other non-operating income or expenses.

Tax: The income tax expense incurred by the company during the quarter.

Net Profit: The profit remaining after deducting all expenses, including operating expenses, depreciation, interest, and taxes.

Earnings Per Share (EPS): The portion of a company's profit allocated to each outstanding share of common stock, providing a measure of profitability on a per-share basis.

Net Profit TTM (Trailing 12 Months): The sum of net profits over the most recent 12-month period, giving a broader perspective on the company's performance.

EPS TTM (Trailing 12 Months): The earnings per share calculated over the trailing 12-month period, providing a longer-term view of earnings on a per-share basis.

Key information about Nigeria NSE All Share

• Nigeria NSE All Share closed at 143,520.5 points in Nov 2025, compared with 154,126.5 points at the previous month end
• Nigeria Equity Market Index: Month End: NSE All Share data is updated monthly, available from Jan 1985 to Nov 2025, with an average number of 21,564.8 points
• The data reached an all-time high of 154,126.5 points in Oct 2025 and a record low of 111.3 points in Jan 1985

Further information about Nigeria NSE All Share

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

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 ...

China's main stock market index, the SHANGHAI, fell to 3898 points on December 2, 2025, losing 0.42% from the previous session. Over the past month, the index has declined 1.98%, though it remains 15.36% higher than a year ago, 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 December of 2025.

Hong Kong's main stock market index, the HK50, rose to 26095 points on December 2, 2025, gaining 0.24% from the previous session. Over the past month, the index has declined 0.24%, though it remains 32.15% higher than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Hong Kong. Hong Kong Stock Market Index (HK50) - values, historical data, forecasts and news - updated on December of 2025.

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.

The NSE Futures and Options (F&O) dataset is a collection of data related to derivatives traded on the National Stock Exchange of India. Derivatives, such as futures and options, are financial instruments whose value is derived from an underlying asset, such as stocks, indices, commodities, or currencies. The F&O segment allows traders and investors to speculate on or hedge against future price movements of these assets.

Key Components of the NSE Futures and Options Dataset: 1. Futures Data: Futures Contracts: Agreements to buy or sell an underlying asset at a predetermined price at a future date. Underlying Asset: The asset on which the contract is based (e.g., individual stocks, stock indices like NIFTY, commodities). Contract Specifications: Expiry Date: The date on which the contract will expire. Contract Price: The agreed-upon price for the asset. Lot Size: The quantity of the underlying asset that each contract represents. Open Interest: The total number of outstanding (unsettled) contracts. Volume: The number of contracts traded during a specific period. Settlement Price: The final price of the contract upon expiry.

1. Options Data: Options Contracts: These give the buyer the right (but not the obligation) to buy (Call Option) or sell (Put Option) an underlying asset at a predetermined price before or at a certain expiration date. Option Types: Call Option: Gives the holder the right to buy the asset. Put Option: Gives the holder the right to sell the asset. Strike Price: The price at which the holder of the option can buy/sell the underlying asset. Expiry Date: The date by which the option must be exercised. Premium: The price paid by the option buyer to acquire the option contract. Implied Volatility: A measure of the market’s expectation of the underlying asset's volatility. Greeks: Quantities representing the sensitivity of the option’s price to various factors: Delta: Sensitivity to price changes in the underlying asset. Theta: Sensitivity to time decay (as the option approaches expiry). Vega: Sensitivity to changes in the asset's volatility. Gamma: The rate of change in Delta. Open Interest: Total number of outstanding options contracts. Volume: The number of option contracts traded during a specific period.

2. Option Chain: An option chain is a table showing all available option contracts for a particular stock or index. It includes strike prices, premiums (call and put), open interest, and volume for different expiry dates.

3. Index Derivatives: Futures and options on stock indices like NIFTY 50, Bank NIFTY, etc. These contracts track the performance of the index as the underlying asset.

Key Metrics in F&O Data: Open Interest (OI): The total number of open contracts (both bought and sold) that have not been settled. This helps gauge market participation and liquidity. Price (Premium): In options, the premium is the cost of buying the contract. In futures, the price reflects the contract value. Strike Price: Particularly important for options, it is the price at which the option can be exercised. Expiry Date: Futures and options contracts have specific expiration dates, typically the last Thursday of the month for monthly contracts. Trading Volume: The number of contracts traded within a given period, which can indicate the level of activity in a particular contract.

Use of NSE F&O Data: Speculation: Traders use F&O to speculate on future price movements of stocks, indices, or commodities. Hedging: Investors use F&O to hedge against adverse price movements in their portfolio (for example, buying put options to protect against a market downturn). Arbitrage: Taking advantage of price differences between the underlying asset and its derivative (futures or options).

Data Types: Historical Data: Contains past data on prices, volumes, open interest, etc. for futures and options contracts. Traders use this to analyze trends, patterns, and volatility. Real-time Data: Provides live updates on the price, open interest, and trading volume of contracts. This data is crucial for day traders and high-frequency traders.

How Traders and Analysts Use This Data: Price Action Analysis: Studying how the price of the futures or options contracts changes over time. Open Interest Analysis: A rising OI indicates new money coming into the market, while falling OI can indicate exiting positions. Option Greeks: Traders analyze the Greeks to manage risk and position sizing in options trading. Volatility Analysis: By analyzing implied and historical volatility, traders can gauge market sentiment and potential price swings.

Key information about India P/E ratio

• India SENSEX recorded a daily P/E ratio of 23.360 on 02 Dec 2025, compared with 23.380 from the previous day.
• India SENSEX P/E ratio is updated daily, with historical data available from Dec 1988 to Dec 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 85,706.670 points in Nov 2025.

📊 NIFTY500 Stocks Data

Get comprehensive historical stock data for the NIFTY 500 index! 📈 This dataset includes stock prices at various time intervals for each NIFTY 500 company, organized into Excel files.

📁 File Naming Convention

• Files named by NSE code, e.g., RELIANCE.xlsx

📜 Data Description

Each sheet in an Excel file contains: - 📅 Date: Date and time - 🏦 Open: Opening price - 📈 High: Highest price - 📉 Low: Lowest price - 🔒 Close: Closing price - 🔄 Volume: Shares traded

🎯 Usage

Ideal for: - Financial analysts 📊 - Data scientists 🤖 - Market researchers 🔍 Analyze stock trends, develop trading strategies, or conduct research with varied timeframes for both long-term and short-term analysis.

📝 Licensing

• MIT License: Free to use for any purpose, even commercially 🌐

📥 How to Access

1. Download from Kaggle ⬇️
2. Unzip the file 🗂️
3. Open Excel files to explore 📂

Happy analyzing! 📊🚀

Context

Nifty per minute data is really difficult to find online, you might have to buy an API key from Zerodha or other data vendors to get per minute data. Fortunately, I've extracted a lot of data using the API key but due to the size of the data, it is in month-wise format. I Will be collating the data in yearly format and will upload the same here.

Content

The data have 7 columns: Symbol, Y-M-D, Time, Open, High, Low, Close values for every minute. With the help of the historical data, you can make your own indicators, tweak and check which indicators are giving you better trade profits. Basically, you can make your own trading model, and once done, you can buy Zerodha's API key, get live data and make your own trades.

Note: Some months captured the 8th and 9th column for volume and OI respectively. Make sure to clean and use the data accordingly.

Inspiration

The main inspiration behind me collecting and working on this data is to make a trading model of my own, where I could trigger the trades when my model gives me a signal. I do trade on the Nifty index but after making a perfect model, I'll rather trade with more confidence and informed decisions. I'll be uploading more data as soon as possible.

You can train and validate your model on this data and I'll get you the test data soon. Till then happy modeling :) Leave comments if you need any help.