In 2023, the returns on Nifty 50 reported a rise of 19.42 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 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 ********.

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.

Nifty 50: Climb or Crash?

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

Prices for NSE Nifty 50 Index including live quotes, historical charts and news. NSE Nifty 50 Index was last updated by Trading Economics this July 23 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.

Billion Dollar Question: Is Nifty 50 Ready for the Next Bull Run?

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

National Stock Exchange: Index: Nifty 50: Average data was reported at 10,621.792 03Nov1995=1000 in Nov 2018. This records an increase from the previous number of 10,383.810 03Nov1995=1000 for Oct 2018. National Stock Exchange: Index: Nifty 50: Average data is updated monthly, averaging 1,861.302 03Nov1995=1000 from Aug 1990 (Median) to Nov 2018, with 340 observations. The data reached an all-time high of 11,498.440 03Nov1995=1000 in Aug 2018 and a record low of 317.200 03Nov1995=1000 in Jan 1991. National Stock Exchange: Index: Nifty 50: Average data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Financial Market – Table IN.ZA017: National Stock Exchange: Indices (Monthly).

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.

Nifty 50: A Hold for Now, But Long-Term Gains Are Possible

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 dataset shows monthly and annual averages of NSE Nifty 50

Note: 1. The averages are based on daily closing index. 2. S&P CNX Nifty has been re-branded as Nifty 50 w.e.f. November 09, 2015.

Key information about India Sensitive 30 (Sensex)

• India Sensitive 30 (Sensex) closed at 73,198.1 points in Feb 2025, compared with 77,500.6 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 Feb 2025, with an average number of 4,285.0 points
• The data reached an all-time high of 84,299.8 points in Sep 2024 and a record low of 115.6 points in Nov 1979

• In the latest reports, SENSEX recorded a daily P/E ratio of 20.6 in Mar 2025

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 ---

Nifty 50's upward trend is likely to continue, with volatility remaining low. However, global uncertainties like geopolitical tensions and the ongoing pandemic pose risks to this outlook. Additionally, profit-taking and technical corrections may lead to temporary setbacks. Investors should maintain caution and monitor market conditions closely.

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).

India's main stock market index, the SENSEX, rose to 82727 points on July 23, 2025, gaining 0.66% from the previous session. Over the past month, the index has climbed 0.82% and is up 3.22% 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 July of 2025.

This statistic depicts the monthly volatility of the Nifty 50 Index in India from January to December 2017. In December of 2017, the volatility of the Nifty 50 Index was reported as *** percent.

National Stock Exchange of India Limited: Index: NIFTY Total Market data was reported at 12,364.250 NA in Apr 2025. This records an increase from the previous number of 11,984.900 NA for Mar 2025. National Stock Exchange of India Limited: Index: NIFTY Total Market data is updated monthly, averaging 5,025.605 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 13,661.300 NA in Sep 2024 and a record low of 2,155.770 NA in May 2012. National Stock Exchange of India Limited: Index: NIFTY Total Market data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s India – Table IN.EDI.SE: National Stock Exchange of India Limited: Monthly.

3 years data for NIFTY and Dow Jones Index

National Stock Exchange of India Limited: Index: NIFTY Next 50 data was reported at 66,226.550 NA in 15 May 2025. This records an increase from the previous number of 65,540.750 NA for 14 May 2025. National Stock Exchange of India Limited: Index: NIFTY Next 50 data is updated daily, averaging 28,032.450 NA from Jun 2013 (Median) to 15 May 2025, with 2950 observations. The data reached an all-time high of 77,813.250 NA in 27 Sep 2024 and a record low of 10,203.000 NA in 28 Aug 2013. National Stock Exchange of India Limited: Index: NIFTY Next 50 data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under High Frequency Database’s Financial and Futures Market – Table IN.EDI.SE: National Stock Exchange of India Limited.

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.

Nifty 50: A Journey to 20,000 and Beyond?

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

National Stock Exchange of India Limited: Index: NIFTY 50 data was reported at 25,062.100 NA in 15 May 2025. This records an increase from the previous number of 24,666.900 NA for 14 May 2025. National Stock Exchange of India Limited: Index: NIFTY 50 data is updated daily, averaging 11,013.550 NA from Jun 2013 (Median) to 15 May 2025, with 2950 observations. The data reached an all-time high of 26,216.050 NA in 26 Sep 2024 and a record low of 5,285.000 NA in 28 Aug 2013. National Stock Exchange of India Limited: Index: NIFTY 50 data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under High Frequency Database’s Financial and Futures Market – Table IN.EDI.SE: National Stock Exchange of India Limited.

In April 2024, among all the indices listed on the National Stock Exchange (NSE) of India, Nifty 50 had the highest dividend yield of *** percent. This was closely followed by Nifty 100 and Nifty Next **, both with a dividend yield of **** percent, respectively.

What are broad market indices? 

Broad market indices, also called market indices, are utilized to monitor the performance of a collection of stocks that closely mirror the overall stock market. They generally consist of large, liquid stocks listed on the stock exchange. They serve as a benchmark for measuring the performance of the stock market or portfolios such as mutual fund investments. In many broad-based indexes, companies are weighted based on their market value. This means that larger companies carry more weight in determining the index price compared to smaller ones. For instance, in the Nifty-50 index, Cipla, a major pharmaceutical company, has a significant impact, while smaller companies like Natco Pharma have less influence due to their lower market capitalization.

What is Nifty 50? 

Nifty-50 is the flagship index of NSE. It tracks the movement of the portfolio of the ** largest blue-chip companies and most liquid securities in the Indian market. It is extensively used by domestic and foreign investors as the barometer of the Indian capital market. Annual returns of Nifty-50 were around ** percent in fiscal year 2023, indicating strong market performance.