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.

Context

The National Stock Exchange of India Ltd. (NSE) is an Indian stock exchange located at Mumbai, Maharashtra, India. National Stock Exchange (NSE) was established in 1992 as a demutualized electronic exchange. It was promoted by leading financial institutions on request of the Government of India. It is India’s largest exchange by turnover. In 1994, it launched electronic screen-based trading. Thereafter, it went on to launch index futures and internet trading in 2000, which were the first of its kind in the country.

With the help of NSE, you can trade in the following segments:

• Equities

• Indices

• Mutual Funds

• Exchange Traded Funds

• Initial Public Offerings

• Security Lending and Borrowing Scheme

https://cdn6.newsnation.in/images/2019/06/24/Sharemarket-164616041_6.jpg" alt="Stock image">

Companies on successful IPOs gets their Stocks traded over different Stock Exchnage platforms. NSE is one important platofrm in India. There are thousands of companies trading their stocks in NSE. But, I have chosen two popular and high rated IT service companies of India; TCS and INFOSYS. and the third one is the benchmark for Indian IT companies , i.e. NIFTY_IT_INDEX .

Content

The dataset contains three csv files. Each resembling to INFOSYS, NIFTY_IT_INDEX, and TCS, respectively. One can easily identify that by the name of CSV files.

Timeline of Data recording : 1-1-2015 to 31-12-2015.

Source of Data : Official NSE website.

Method : We have used the NSEpy api to fetch the data from NSE site. I have also mentioned my approach in this Kernel - "**WebScraper to download data for NSE**". Please go though that to better understand the nature of this dataset.

Shape of Dataset:

INFOSYS - 248 x 15 || NIFTY_IT_INDEX - 248 x 7 || **TCS - 248 x 15

• Colum Descriptors:

• Date: date on which data is recorded

• Symbol: NSE symbol of the stock

• Series: Series of that stock | EQ - Equity

OTHER SERIES' ARE:

EQ: It stands for Equity. In this series intraday trading is possible in addition to delivery.

BE: It 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.

BL: This series is for facilitating block deals. Block deal is a trade, with a minimum quantity of 5 lakh shares or minimum value of Rs. 5 crore, executed through a single transaction, on the special “Block Deal window”. The window is opened for only 35 minutes in the morning from 9:15 to 9:50AM.

BT: This series provides an exit route to small investors having shares in the physical form with a cap of maximum 500 shares.

GC: This series allows Government Securities and Treasury Bills to be traded under this category.

IL: This series allows only FIIs to trade among themselves. Permissible only in those securities where maximum permissible limit for FIIs is not breached.

• Prev Close: Last day close point

• Open: current day open point

• High: current day highest point

• Low: current day lowest point

• Last: the final quoted trading price for a particular stock, or stock-market index, during the most recent day of trading.

• Close: Closing point for the current day

• VWAP: volume-weighted average price is the ratio of the value traded to total volume traded over a particular time horizon

• Volume: the amount of a security that was traded during a given period of time. For every buyer, there is a seller, and each transaction contributes to the count of total volume.

• Turnover: Total Turnover of the stock till that day

• Trades: Number of buy or Sell of the stock.

• Deliverable: Volumethe quantity of shares which actually move from one set of people (who had those shares in their demat account before today and are selling today) to another set of people (who have purchased those shares and will get those shares by T+2 days in their demat account).

• %Deliverble: percentage deliverables of that stock

Acknowledgements

I woul dlike to acknowledge all my sincere thanks to the brains behind NSEpy api, and in particular SWAPNIL JARIWALA , who is also maintaining an amazing open source github repo for this api.

Inspiration

I have also built a starter kernel for this dataset. You can find that right here .

I am so excited to see your magical approaches for the same dataset.

THANKS!

Stock market volatility is a measure of risk in investment and it plays a key role in securities pricing and risk management. The paper empirically analyzes the relationship between India VIX and volatility in Indian stock market. India VIX is a measure of implied volatility which reflects markets’ expectation of future short-term stock market volatility. It is a volatility index based on the index option prices of Nifty. The study is based on time series data comprising of daily closing values of CNX Nifty 50 index comprising of 1656 observations from March 2009 to December 2015. The results of the study reveal that India VIX has predictive power for future short-term stock market volatility. It has higher forecasting ability for upward stock market movements as compared to downward movements. Therefore, it is more a bullish indicator. Moreover, the accuracy of forecasts provided by India VIX is higher for low magnitude future price changes relative to higher stock price movements. The current value of India VIX is found to be affected by past period volatility up to one month and it has forecasting ability for next one-month’s volatility which means the volatility in the Indian stock markets can be forecasted for up to 60 days period.

During the fiscal year 2023, 98 percent of the equity derivatives traded on the National Stock Exchange of India (NSE) were index options. In the same period, both index futures and single stock futures did not contribute to the equity derivative segment.

What are options and futures? 

Options and futures are financial instruments used in the stock market to manage risks or speculate changes in asset prices. Options grant the buyer the choice to buy or sell an asset at a predetermined price by a specified date. They are not obligatory. ‘Call options’ allow buying, while ‘put options’ allow selling. Whereas futures contracts allow individuals to buy or sell an asset at an agreed price on a future date. At expiration, futures contracts require the individual to buy or sell the underlying asset.

Why are options preferred over futures in the Indian stock market? 

Options provide greater flexibility by granting buyers the right to trade without imposing an obligation. This flexibility offers leverage, potentially resulting in significant cost savings. With limited risk, individuals can only lose the cost of the contract, ensuring losses do not surpass the initial investment. Moreover, options enable strategic maneuvers, allowing individuals to hedge positions and merge trades for strategic positioning and potentially high returns. Consequently, the combination of flexibility, cost-efficiency, risk management, and strategic potential establishes options contracts as favored financial instruments in the stock market.

The Indian security brokerage market, valued at approximately ₹3940 million (assuming "Million" refers to Indian Rupees) in 2025, is experiencing robust growth, projected to expand at a Compound Annual Growth Rate (CAGR) of 7.89% from 2025 to 2033. This growth is fueled by several key factors. Increased internet and smartphone penetration, coupled with rising financial literacy and a young, digitally-savvy population, are driving greater participation in online trading platforms. Government initiatives promoting financial inclusion and deregulation are also contributing to market expansion. The market is segmented by security type (bonds, stocks, treasury notes, derivatives, others), brokerage service (stocks, insurance, mortgage, real estate, forex, leasing, others), and service model (full-service, discount, online, robo-advisor). The dominance of online and discount brokerage models reflects the cost-conscious nature of many Indian investors. Leading players such as Zerodha, Angel Broking, Upstox, and Groww are leveraging technology to enhance user experience and expand their market share, while established players like ICICI Direct are adapting to the changing landscape. Competition remains fierce, with firms continually innovating to attract and retain clients. The competitive landscape is characterized by a mix of established full-service brokers and rapidly growing online discount brokers. While established players leverage their brand recognition and comprehensive service offerings, the online discount brokers are attracting a significant share of the market through low-cost trading platforms and user-friendly interfaces. The increasing popularity of robo-advisors, which offer automated investment management, represents a significant emerging trend. However, regulatory challenges and concerns related to cybersecurity and investor protection remain potential restraints. The market’s future growth will depend on sustained economic growth, investor confidence, and the ongoing development of robust regulatory frameworks. Further expansion is expected in less-penetrated segments like insurance and real estate brokerage services, aligning with the broader financial needs of the growing middle class. This comprehensive report provides an in-depth analysis of the burgeoning India security brokerage market, projecting robust growth from 2025 to 2033. The study covers the historical period (2019-2024), with 2025 serving as the base year and estimated year. We delve into market size, segmentation, key players, and future trends, providing valuable insights for investors, businesses, and stakeholders. Search-optimized keywords include: India stock market, India brokerage firms, online trading India, security brokerage India, discount brokers India, financial markets India, Indian investment market, wealth management India, robo-advisors India. Recent developments include: May 2023: Fintech unicorn Groww acquired a 100 percent stake in the mutual fund business of Indiabulls Housing Finance for INR 175.62 crores (21.23 million USD). The acquisition was made to make mutual funds more accessible, simpler, and transparent, besides lowering the cost by Groww., March 2022: Axis Bank consolidated its position amongst the large private lenders by agreeing to acquire Citibank's consumer businesses covering loans, credit cards, wealth management, and retail banking operations in India, in line with its growth ambitions.. Key drivers for this market are: High Retail Participation, Favorable systematic liquidity in domestic and international market. Potential restraints include: High Retail Participation, Favorable systematic liquidity in domestic and international market. Notable trends are: Increasing Demat account and brokerage business affecting Indian Security Brokerage Market.

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.

The New York Stock Exchange (NYSE) is the largest stock exchange in the world, with an equity market capitalization of almost ** trillion U.S. dollars as of June 2025. The following three exchanges were the NASDAQ, PINK Exchange, and the Frankfurt Exchange. What is a stock exchange? A stock exchange is a marketplace where stockbrokers, traders, buyers, and sellers can trade in equities products. The largest exchanges have thousands of listed companies. These companies sell shares of their business, giving the general public the opportunity to invest in them. The oldest stock exchange worldwide is the Frankfurt Stock Exchange, founded in the late sixteenth century. Other functions of a stock exchange Since these are publicly traded companies, every firm listed on a stock exchange has had an initial public offering (IPO). The largest IPOs can raise billions of dollars in equity for the firm involved. Related to stock exchanges are derivatives exchanges, where stock options, futures contracts, and other derivatives can be traded.

The Asia-Pacific capital market exchange ecosystem is experiencing robust growth, driven by increasing financialization in the region's rapidly developing economies. A compound annual growth rate (CAGR) exceeding 7% from 2019 to 2024 suggests a significant market expansion, projected to continue into the forecast period (2025-2033). Key drivers include rising domestic savings, increasing foreign direct investment (FDI), and the proliferation of retail and institutional investors. The expansion of digital financial services and fintech innovations further fuels this growth, facilitating easier access to markets and investment products. While market segments vary significantly across the region, the dominance of equity and debt markets is evident, reflecting the developmental stage of many economies. The presence of major stock exchanges like the Shanghai, Tokyo, and Hong Kong exchanges underscores the region's importance in the global financial landscape. However, regulatory hurdles, geopolitical uncertainties, and potential macroeconomic shifts pose some restraints to sustained growth. The study focuses on key markets within the Asia-Pacific region, including China, Japan, South Korea, India, Australia, and others, providing a detailed picture of market dynamics and future potential within each specific nation. Furthermore, the growing participation of institutional investors, alongside a rising retail investor base, points to a mature and deepening market. This expanding market presents significant opportunities for both domestic and international players. However, navigating the diverse regulatory environments and understanding the unique characteristics of each national market is crucial for success. Future growth will likely be shaped by government policies promoting financial inclusion, technological advancements enhancing market efficiency, and the overall macroeconomic stability of the region. The continued development and deepening of these capital markets will play a critical role in driving economic growth and development across the Asia-Pacific region for the foreseeable future, attracting further foreign investment and fostering greater financial integration within the area. Please note: I cannot create hyperlinks. I also cannot provide financial data (market size, growth rates, etc.) as this requires specialized market research. The following report description provides a framework; you would need to fill in the financial data from your research. Recent developments include: July 2022: The eligible companies listed on Beijing Stock Exchange were allowed to apply for transfer to the Star Market of the Shanghai Stock Exchange. A transfer system is a positive approach for bridge-building efforts between China's multiple layers of the capital market., February 2022: The China Securities Regulatory Commission (CSRC) approved the merger of Shenzhen Stock Exchange's main board with the SME board. The merger will optimize the trading structure of the Shenzhen Stock Exchange.. Notable trends are: Increasing Foreign Direct Investment in Various Developing Economies in Asia-Pacific.

Key information about India Market Capitalization

• India Market Capitalization accounted for 4,388.733 USD bn in Feb 2025, compared with a percentage of 4,899.710 USD bn in the previous month
• India Market Capitalization is updated monthly, available from Jan 1993 to Feb 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

From the survey conducted in early 2020 which assessed the impact of the coronavirus pandemic on investors in India, it was found that ** percent of the respondents planned to buy equity slowly, while ** percent indicated they would purchase more aggressively. The reason for this was optimism among the investors, and the reasoning that they would stand to make bigger gains by buying equity at a lower price.

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.

PhonePe: The Future of Digital Payments in India

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

China's main stock market index, the SHANGHAI, rose to 3606 points on July 24, 2025, gaining 0.65% from the previous session. Over the past month, the index has climbed 4.33% and is up 24.91% compared to the same time last year, 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 July of 2025.

The India Mutual Fund Market is Segmented by Fund Type (Equity, Bond, Hybrid, Money Market, and Others), by Investor Type (Retail and Institutional), by Management Style (Active and Passive), and by Distribution Channel (Online Trading Platform, Banks, Securities Firm, and Others). The Market Forecasts are Provided in Terms of Value (USD).

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 ---

Tweet Sentiment's Impact on Stock Returns

862,231 Labeled Instances

By [source]

About this dataset

This dataset contains 862,231 labeled tweets and associated stock returns, providing a comprehensive look into the impact of social media on company-level stock market performance. For each tweet, researchers have extracted data such as the date of the tweet and its associated stock symbol, along with metrics such as last price and various returns (1-day return, 2-day return, 3-day return, 7-day return). Also recorded are volatility scores for both 10 day intervals and 30 day intervals. Finally, sentiment scores from both Long Short - Term Memory (LSTM) and TextBlob models have been included to quantify the overall tone in which these messages were delivered. With this dataset you will be able to explore how tweets can affect a company's share prices both short term and long term by leveraging all of these data points for analysis!

More Datasets

For more datasets, click here.

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How to use the dataset

In order to use this dataset, users can utilize descriptive statistics such as histograms or regression techniques to establish relationships between tweet content & sentiment with corresponding stock return data points such as 1-day & 7-day returns measurements.

The primary fields used for analysis include Tweet Text (TWEET), Stock symbol (STOCK), Date (DATE), Closing Price at the time of Tweet (LAST_PRICE) a range of Volatility measures 10 day Volatility(VOLATILITY_10D)and 30 day Volatility(VOLATILITY_30D ) for each Stock which capture changes in market fluctuation during different periods around when Twitter reactions occur. Additionally Sentiment Polarity analysis undertaken via two Machine learning algorithms LSTM Polarity(LSTM_POLARITY)and Textblob polarity provide insight into whether people are expressing positive or negative sentiments about each company at given times which again could influence thereby potentially influence Stock Prices over shorter term periods like 1-Day Returns(1_DAY_RETURN),2-Day Returns(2_DAY_RETURN)or longer term horizon like 7 Day Returns*7DAY RETURNS*.Finally MENTION field indicates if names/acronyms associated with Companies were specifically mentioned in each Tweet or not which gives extra insight into whether company specific contexts were present within individual Tweets aka “Company Relevancy”

Research Ideas

• Analyzing the degree to which tweets can influence stock prices. By analyzing relationships between variables such as tweet sentiment and stock returns, correlations can be identified that could be used to inform investment decisions.
• Exploring natural language processing (NLP) models for predicting future market trends based on textual data such as tweets. Through testing and evaluating different text-based models using this dataset, better predictive models may emerge that can give investors advance warning of upcoming market shifts due to news or other events.
• Investigating the impact of different types of tweets (positive/negative, factual/opinionated) on stock prices over specific time frames. By studying correlations between the sentiment or nature of a tweet and its effect on stocks, insights may be gained into what sort of news or events have a greater impact on markets in general

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: reduced_dataset-release.csv | Column name | Description | |:----------------------|:-------------------------------------------------------------------------------------------------------| | TWEET | Text of the tweet. (String) | | STOCK | Company's stock mentioned in the tweet. (String) | | DATE | Date the tweet was posted. (Date) | | LAST_PRICE | Company's last price at the time of tweeting. (Float) ...

Snapshot img

Stockbroking Market Size 2025-2029

The stockbroking market size is forecast to increase by USD 27.45 billion at a CAGR of 10.1% between 2024 and 2029.

The market is characterized by the increasing need for real-time investment monitoring and surveillance, driven by heightened market volatility and investor demand for transparency. This trend is further fueled by advancements in technology, enabling brokerages to offer more sophisticated trading platforms and tools. The integration of artificial intelligence (AI) and algorithms into trading platforms has led to cloud-based solutions, enabling active and passive portfolio management. However, the market faces significant challenges, primarily due to the ongoing trade war and its associated economic uncertainties. The escalating tensions have led to increased market volatility and investor risk aversion, potentially dampening trading volumes and investor confidence.
As a result, stockbrokers must adapt to these market dynamics by offering innovative solutions that mitigate risk and provide value-added services to attract and retain clients. To capitalize on opportunities and navigate challenges effectively, companies should focus on enhancing their technology offerings, expanding their geographical reach, and developing strategic partnerships to stay competitive in this dynamic market. Additionally, users of online trading platforms can easily monitor the performance of their assets thanks to real-time stock data. 

What will be the Size of the Stockbroking Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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In the dynamic market, order routing optimization plays a crucial role in maximizing execution efficiency. Business continuity planning is essential to ensure uninterrupted services during crises. Financial statement analysis and performance attribution models help assess investment strategy implementation and identify areas for improvement. Data visualization tools facilitate effective operational risk management by providing insights into trading algorithms' performance. Backtesting methodologies and execution quality metrics are integral to refining quantitative trading models and derivatives pricing models. Futures trading strategies and disaster recovery planning are essential components of risk appetite modeling, enabling firms to manage volatility and mitigate potential losses. The stockbroking industry is essential for the smooth functioning of financial analytics.

Trade blotter reconciliation and client communication channels are vital for maintaining transparency and trust in client relationships. Portfolio construction strategies, financial reporting standards, and investment strategy implementation require a deep understanding of various regulatory requirements, including anti-money laundering (AML) and regulatory technology solutions. Algorithmic trading performance and account opening procedures are subject to continuous monitoring and optimization. Information security management and tax reporting compliance are essential aspects of maintaining a robust and compliant stockbroking business. Options trading strategies and transaction cost reduction are critical elements of a well-rounded investment offering.

How is this Stockbroking Industry segmented?

The stockbroking industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Mode Of Booking

  Offline
  Online


Type

  Long term trading
  Short term trading


End-user

  Institutional investor
  Retail investor


Geography

  North America

    US
    Canada
    Mexico


  Europe

    France
    Germany
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Mode Of Booking Insights

The Offline segment is estimated to witness significant growth during the forecast period. Offline stockbroking is the traditional method of engaging in stock trading activities without the use of online platforms or electronic systems. Investors work with stockbrokers who act as an intermediary between them and the stock exchange. Offline stockbroking includes: Communication: Investors place their buy or sell orders through direct communication via calls, emails, or in person with their stockbrokers. Offline is still dominating the market due to the ease of use due to factors such as personalized services, extensive research, complex investment strategies, trust, and relationship building by the investors over time, also in the offline segment they can access initial public offerings or other restricted offerings which may not be readily available on an online brokera

The India Asset Management Market is Segmented by Asset Class (Equity, Fixed Income, Alternative Assets, and Other Asset Classes), by Firm Type (Broker-Dealers, Banks, Wealth Advisory Firms, and Other Firm Types), by Mode of Advisory (Human Advisory and Robo-Advisory), by Client Type (Retail and Institutional), and by Management Source (Offshore and Onshore). The Market Forecasts are Provided in Terms of Value (USD).

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.

In 2023, the leading equity index futures and options contract traded worldwide based on volume was Bank Nifty Index Options, traded on the National Stock Exchange of India. Over the year a total of ** billion Bank Nifty Index Options contracts were traded - over ** million more than second-placed CNX Nifty Index Options, also traded on the National Stock Exchange of India.

Pakistan's main stock market index, the KSE 100, rose to 139451 points on July 22, 2025, gaining 0.89% from the previous session. Over the past month, the index has climbed 20.04% and is up 76.55% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Pakistan. Pakistan Stock Market (KSE100) - values, historical data, forecasts and news - updated on July of 2025.