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.

State Bank of India reported 9.92 in PE Price to Earnings for its fiscal quarter ending in December of 2024. Data for State Bank of India | SBIN - PE Price to Earnings including historical, tables and charts were last updated by Trading Economics this last July in 2025.

Infosys stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

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.

JPMorgan (JII) Stock: Is the Indian Investment Trust a Winner?

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

This statistic illustrates the share of income of Bombay Stock Exchange (BSE) from data dissemination fees in India from 2012 to the first half of 2017. The income of BSE from data dissemination fees constituted ***** percent of the total income of the Indian stock exchange in the fiscal year 2016.

India's main stock market index, the SENSEX, fell to 82259 points on July 17, 2025, losing 0.45% from the previous session. Over the past month, the index has climbed 1.00% and is up 1.13% 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.

Predicting stock market prices following corporate earnings calls remains a significant challenge for investors and researchers alike, requiring innovative approaches that can process diverse information sources. This study investigates the impact of corporate earnings calls on stock prices by introducing a multi-modal predictive model. We leverage textual data from earnings call transcripts, along with images and tables from accompanying presentations, to forecast stock price movements on the trading day immediately following these calls. To facilitate this research, we developed the MiMIC (Multi-Modal Indian Earnings Calls) dataset, encompassing companies representing the Nifty 50, Nifty MidCap 50, and Nifty Small 50 indices. The dataset includes earnings call transcripts, presentations, fundamentals, technical indicators, and subsequent stock prices. We present a multimodal analytical framework that integrates quantitative variables with predictive signals derived from textual and visual modalities, thereby enabling a holistic approach to feature representation and analysis.

The Earnings Per Share for GSK Pharmaceuticals in India during fiscal year 2024 was valued at around 41 Indian rupees. This was a sharp increase from the previous year. In financial year 2024, GSK ranked as the leading brand in the private vaccine market and dermatology segment.

In 2025, stock markets in the United States accounted for roughly ** percent of world stocks. The next largest country by stock market share was China, followed by the European Union as a whole. The New York Stock Exchange (NYSE) and the NASDAQ are the largest stock exchange operators worldwide. What is a stock exchange? The first modern publicly traded company was the Dutch East Industry Company, which sold shares to the general public to fund expeditions to Asia. Since then, groups of companies have formed exchanges in which brokers and dealers can come together and make transactions in one space. Stock market indices group companies trading on a given exchange, giving an idea of how they evolve in real time. Appeal of stock ownership Over half of adults in the United States are investing money in the stock market. Stocks are an attractive investment because the possible return is higher than offered by other financial instruments.

The earnings per share of Maruti Suzuki Limited in India amounted to around *** Indian rupees at the end of financial year 2024. That year, the company sold over **** million vehicles across India.

In 2022, the subscription video-on-demand (SVOD) segment dominated India's video streaming market, contributing to almost 67 percent of the total revenue, while advertising video-on-demand (AVOD) accounted for roughly 25 percent. Looking ahead, although SVOD was projected to maintain its lead, AVOD's revenue contribution was expected to continue expanding.

State Bank of India stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

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

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.

Sensex to Surge, Experts Predict Strong Growth for the Indian Index

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

In 2022, a significant ** percent of the total revenue in India's video games market was attributed to social and casual gaming, with the remaining revenue coming from eSports. Forecasts for 2027 indicated that the social and casual games segment is expected to further strengthen its position, making up a substantial ** percent of the market revenue.

From 2007 to 2023, Burnpur Cement Limited was the standout performer, with a 286 percent increase on its listing day. Whereas, Tata Technologies saw a 168 percent surge in value on its listing day. Numerous companies in India saw substantial increases in their stock value on the day they were listed on the stock market, a phenomenon known as listing day gains.

India NGNBF&I: Share Trading and Investment Holding: Profit Allocation Ratio: Profits Retained to Earning Before Tax data was reported at 61.900 % in 2019. This records an increase from the previous number of 56.500 % for 2018. India NGNBF&I: Share Trading and Investment Holding: Profit Allocation Ratio: Profits Retained to Earning Before Tax data is updated yearly, averaging 57.250 % from Mar 2012 (Median) to 2019, with 8 observations. The data reached an all-time high of 68.900 % in 2015 and a record low of 37.700 % in 2012. India NGNBF&I: Share Trading and Investment Holding: Profit Allocation Ratio: Profits Retained to Earning Before Tax data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Banking Sector – Table IN.KBU025: Non Government Non Banking Financial and Investment Companies (NGNBF&I): Financial Ratio: Share Trading and Investment Holding.

In 2020, B2B events accounted to over ** percent of the total revenue of events and exhibition market in India. It was followed by B2C events making up to about ** percent of revenue. The total revenue of events and exhibition market is forecasted to reach over *********** U.S. dollars in 2026.

India NGNBF&I: Share Trading and Investment Holding: Appropriations: Earnings Before Tax (EBT) data was reported at 222,550.000 INR mn in 2019. This records an increase from the previous number of 165,120.000 INR mn for 2018. India NGNBF&I: Share Trading and Investment Holding: Appropriations: Earnings Before Tax (EBT) data is updated yearly, averaging 102,180.000 INR mn from Mar 2012 (Median) to 2019, with 8 observations. The data reached an all-time high of 222,550.000 INR mn in 2019 and a record low of 57,680.000 INR mn in 2014. India NGNBF&I: Share Trading and Investment Holding: Appropriations: Earnings Before Tax (EBT) data remains active status in CEIC and is reported by Reserve Bank of India. The data is categorized under India Premium Database’s Banking Sector – Table IN.KBU019: Non Government Non Banking Financial and Investment Companies (NGNBF&I): Financial Performance: Share Trading and Investment Holding.

In financial year 2023, the revenue of India's information technology services sector was estimated to reach 125 billion U.S. dollars. It was an 8.3 percent increase in comparison with the previous year. Most of the value was generated by export.