Prices for Karachi Stock Exchange KSE100 Index including live quotes, historical charts and news. Karachi Stock Exchange KSE100 Index was last updated by Trading Economics this November 30 of 2025.

Pakistan's main stock market index, the KSE 100, fell to 167838 points on December 2, 2025, losing 0.13% from the previous session. Over the past month, the index has climbed 3.09% and is up 60.52% 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 December of 2025.

Key information about Pakistan Market Capitalization

• Pakistan Market Capitalization accounted for 67.258 USD bn in Nov 2025, compared with a percentage of 66.080 USD bn in the previous month
• Pakistan Market Capitalization is updated monthly, available from Mar 1999 to Nov 2025
• The data reached an all-time high of 96.158 USD bn in May 2017 and a record low of 4.459 USD bn in Sep 2001

Pakistan Market Cap: PSX: All Shares data was reported at 18,866,440.150 PKR mn in Nov 2025. This records an increase from the previous number of 18,561,637.137 PKR mn for Oct 2025. Pakistan Market Cap: PSX: All Shares data is updated monthly, averaging 3,724,340.614 PKR mn from Mar 1999 (Median) to Nov 2025, with 321 observations. The data reached an all-time high of 19,263,817.775 PKR mn in Sep 2025 and a record low of 285,126.330 PKR mn in Sep 2001. Pakistan Market Cap: PSX: All Shares data remains active status in CEIC and is reported by Pakistan Stock Exchange Limited. The data is categorized under Global Database’s Pakistan – Table PK.Z: Karachi Stock Exchange: Market Capitalization (New Classification).

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 379 companies listed on the Pakistan Stock Exchange (XKAR) in Pakistan. This dataset includes the closing prices of equities (stocks), bonds, and indices at the end of each trading session. End-of-day prices are vital pieces of market data that are widely used by investors, traders, and financial institutions to monitor the performance and value of these assets over time.

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Top 5 used data fields in the End-of-Day Pricing Dataset for Pakistan:

1. Equity Closing Price :The closing price of individual company stocks at the end of the trading day.This field provides insights into the final price at which market participants were willing to buy or sell shares of a specific company.

2. Bond Closing Price: The closing price of various fixed-income securities, including government bonds, corporate bonds, and municipal bonds. Bond investors use this field to assess the current market value of their bond holdings.

3. Index Closing Price: The closing value of market indices, such as the Botswana stock market index, at the end of the trading day. These indices track the overall market performance and direction.

4. Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.

5. Date of Closing Price: The specific trading day for which the closing price is provided. This date is essential for historical analysis and trend monitoring.

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Top 5 financial instruments with End-of-Day Pricing Data in Pakistan:

Karachi Stock Exchange (KSE) 100 Index: The main index that tracks the performance of the top 100 companies listed on the Pakistan Stock Exchange (formerly known as the Karachi Stock Exchange). This index provides a broad view of the overall market performance in Pakistan.

Karachi Stock Exchange (KSE) 30 Index: The index that tracks the performance of the top 30 companies listed on the Pakistan Stock Exchange. This index represents the performance of the most influential and actively traded companies in Pakistan.

Company A: A leading Pakistani company in sectors such as textiles, manufacturing, or technology. This company's stock is among the most actively traded on the Pakistan Stock Exchange and has a significant impact on market trends.

Company B: A major financial institution in Pakistan, offering banking, insurance, or investment services. This company's stock is influential in the financial sector and reflects the health of Pakistan's economy.

Company C: A significant player in Pakistan's energy sector, involved in oil and gas exploration, production, or distribution. This company's stock is actively traded and has an impact on Pakistan's energy landscape.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Pakistan, please contact info@techsalerator.com with your specific requirements. Techsalerator will provide you with a customized quote based on the number of data fields and records you need. The dataset can be delivered within 24 hours, and ongoing access options can be discussed if needed.

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Data fields included:

Equity Ticker Symbol Equity Closing Price Bond Ticker Symbol Bond Closing Price Index Ticker Symbol Index Closing Price Date of Closing Price Equity Name Equity Volume Equity High Price Equity Low Price Equity Open Price Bond Name Bond Coupon Rate Bond Maturity Index Name Index Change Index Percent Change Exchange Currency Total Market Capitalization Dividend Yield Price-to-Earnings Ratio (P/E) ‍

Q&A:

1. How much does the End-of-Day Pricing Data cost in Pakistan ?

The cost of this dataset may vary depending on factors such as the number of data fields, the frequency of updates, and the total records count. For precise pricing details, it is recommended to directly consult with a Techsalerator Data specialist.

1. How complete is the End-of-Day Pricing Data coverage in Pakistan?

Techsalerator provides comprehensive coverage of End-of-Day Pricing Data for various financial instruments, including equities, bonds, and indices. Thedataset encompasses major companies and securities traded on Pakistan exchanges.

1. How does Techsalerator collect this data?

Techsalerator collects End-of-Day Pricing Data from reliable sources, including stock exchanges, financial news outlets, and other market data providers. Data is carefully curated to ensure accuracy and reliability.

1. Can I select specific financial instruments or multiple countries with Techsalerator's End-of-Day Pricing Data?

Techsalerator offers the flexibility to select specific financial instruments, such as equities, bonds, or indices, depending on your needs. While the dataset focuses on Botswana, Techsalerator also provides data for other countries and international markets.

1. How do I pay for t...

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

Should You Buy Karachi 100 Index Right Now? (Stock Forecast)

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Actual value and historical data chart for Pakistan Stock Market Return Percent Year On Year

Pakistan PSX: Market Capitalization data was reported at 8,570,926.330 PKR mn in 2017. This records a decrease from the previous number of 9,628,514.370 PKR mn for 2016. Pakistan PSX: Market Capitalization data is updated yearly, averaging 1,723,454.360 PKR mn from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 9,628,514.370 PKR mn in 2016 and a record low of 189,518.300 PKR mn in 1991. Pakistan PSX: Market Capitalization data remains active status in CEIC and is reported by Pakistan Stock Exchange Limited. The data is categorized under Global Database’s Pakistan – Table PK.Z005: Karachi Stock Exchange: Annual Statistics.

Pakistan PSX: Number of Listed Companies: New Listings data was reported at 7.000 Unit in 2017. This records an increase from the previous number of 4.000 Unit for 2016. Pakistan PSX: Number of Listed Companies: New Listings data is updated yearly, averaging 6.000 Unit from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 86.000 Unit in 1992 and a record low of 0.000 Unit in 1999. Pakistan PSX: Number of Listed Companies: New Listings data remains active status in CEIC and is reported by Pakistan Stock Exchange Limited. The data is categorized under Global Database’s Pakistan – Table PK.Z005: Karachi Stock Exchange: Annual Statistics.

Actually, I prepare this dataset for students on my Deep Learning and Machine Learning course.

But I am also very happy to see kagglers play around with it.

Have fun!

Context

High-quality financial data is expensive to acquire and is therefore rarely shared for free. Here I provide the full historical daily price and volume data for all US-based stocks in Karachi stock. It's one of the best datasets of its kind you can obtain.

This Data Contain 801 companies that are registered in Karachi Stock Market, Pakistan. I want to analysis the analysis the Karachi stock market.

Data Details

This dataset contain data from Jan, 01, 2003 to Aug ,30 2019. In each company contain 7 Columns, that are follows 1. Symbol 2. Date 3. Open 4. High 5. Low 6. Close 7. Volume

Objective

• Predict stock share price single variable value. • Predict stock share price multiple variable value. • To find a correlation or forecast time-series data.

Pakistan PSX: Listed Capital data was reported at 1,276,800.580 PKR mn in 2017. This records a decrease from the previous number of 1,291,040.410 PKR mn for 2016. Pakistan PSX: Listed Capital data is updated yearly, averaging 405,646.320 PKR mn from Dec 1991 (Median) to 2017, with 27 observations. The data reached an all-time high of 1,291,040.410 PKR mn in 2016 and a record low of 37,024.300 PKR mn in 1991. Pakistan PSX: Listed Capital data remains active status in CEIC and is reported by Pakistan Stock Exchange Limited. The data is categorized under Global Database’s Pakistan – Table PK.Z005: Karachi Stock Exchange: Annual Statistics.

The Stability of the economy is always a great challenge across the world, especially in under developed countries. Many researchers have contributed to forecasting the Stock Market and controlling the situation to ensure economic stability over the past several decades. For this purpose, many researchers have built various models and gained benefits. This journey continues to date and will persist for the betterment of the stock market. This study is also a part of this journey, where four learning-based models are tailored for stock price prediction. Daily business data from the Karachi Stock Exchange (100 Index), covering from February 22, 2008 to February 23, 2021, is used for training and testing these models. This paper presenting four deep learning models with different architectures, namely the Artificial Neural Network model, the Recurrent Neural Network with Attention model, the Long Short-Term Memory Network with Attention model, and the Gated Recurrent Unit with Attention model. The Long Short-Term Memory with attention model was found to be the top-performing technique for accurately predicting stock exchange prices. During the Training, Validation and Testing Sessions, we observed the R-Squared values of the proposed model to be 0.9996, 0.9980 and 0.9921, respectively, making it the best-performing model among those mentioned above.

Pakistan State Oil (PSO) Stock Price Data Description (as of May 18, 2024)

This dataset provides historical daily stock price data for Pakistan State Oil (PSO) listed on the Karachi Stock Exchange (KSE) under the code PSO.

The data is specifically sourced from Yahoo Finance and covers the period from 2008-01-02 to 2024-05-18.

Data Fields: - Date: (format: YYYY-MM-DD) The date on which the stock price data applies. - Open: The opening price of the PSO stock for that day. - High: The highest price the PSO stock reached during that day's trading. - Low: The lowest price the PSO stock reached during that day's trading. - Close: The closing price of the PSO stock for that day. - Volume: The total number of PSO shares traded on that day. - Adj Close: The adjusted closing price, which factors in stock splits or dividends to provide a more accurate picture of long-term performance.

Data Uses: This dataset is valuable for various financial analyses, including: - Technical analysis: Identify trends and patterns in PSO's historical stock price data (2008-2024) to make informed trading decisions. - Performance tracking: Track PSO's stock performance over the past 16 years and compare it to market benchmarks or other companies. - Investment research: Analyze PSO's financial health, industry trends, and historical price movements to assess its investment potential.

Source: Yahoo Finance

Pakistan Index: KSE All Share Index: Real Estate Investment Trust data was reported at 20,603.300 1995=1000 in May 2018. This records an increase from the previous number of 20,029.200 1995=1000 for Apr 2018. Pakistan Index: KSE All Share Index: Real Estate Investment Trust data is updated monthly, averaging 17,438.300 1995=1000 from Nov 2016 (Median) to May 2018, with 19 observations. The data reached an all-time high of 20,603.300 1995=1000 in May 2018 and a record low of 16,600.530 1995=1000 in Nov 2016. Pakistan Index: KSE All Share Index: Real Estate Investment Trust data remains active status in CEIC and is reported by State Bank of Pakistan. The data is categorized under Global Database’s Pakistan – Table PK.Z001: Karachi Stock Exchange: Index.

Pakistan Market Cap: PSX: Real Estate Investment Trust data was reported at 29,531.000 PKR mn in May 2018. This records an increase from the previous number of 28,708.000 PKR mn for Apr 2018. Pakistan Market Cap: PSX: Real Estate Investment Trust data is updated monthly, averaging 24,994.000 PKR mn from Nov 2016 (Median) to May 2018, with 19 observations. The data reached an all-time high of 29,531.000 PKR mn in May 2018 and a record low of 23,794.000 PKR mn in Nov 2016. Pakistan Market Cap: PSX: Real Estate Investment Trust data remains active status in CEIC and is reported by State Bank of Pakistan. The data is categorized under Global Database’s Pakistan – Table PK.Z003: Karachi Stock Exchange: Market Capitalization (New Classification).

The Pakistani antimony market surged to $14M in 2024, picking up by 84% against the previous year. Over the period under review, consumption continues to indicate notable growth. As a result, consumption attained the peak level and is likely to continue growth in the immediate term.

PSX：市值在12-01-2017达8,570,926.330百万巴基斯坦卢比，相较于12-01-2016的9,628,514.370百万巴基斯坦卢比有所下降。PSX：市值数据按年更新，12-01-1991至12-01-2017期间平均值为1,723,454.360百万巴基斯坦卢比，共27份观测结果。该数据的历史最高值出现于12-01-2016，达9,628,514.370百万巴基斯坦卢比，而历史最低值则出现于12-01-1991，为189,518.300百万巴基斯坦卢比。CEIC提供的PSX：市值数据处于定期更新的状态，数据来源于Pakistan Stock Exchange Limited，数据归类于Global Database的巴基斯坦 – 表 PK.Z005：卡拉奇证券交易所：年度统计。

PSX：上市资本在12-01-2017达1,276,800.580百万巴基斯坦卢比，相较于12-01-2016的1,291,040.410百万巴基斯坦卢比有所下降。PSX：上市资本数据按年更新，12-01-1991至12-01-2017期间平均值为405,646.320百万巴基斯坦卢比，共27份观测结果。该数据的历史最高值出现于12-01-2016，达1,291,040.410百万巴基斯坦卢比，而历史最低值则出现于12-01-1991，为37,024.300百万巴基斯坦卢比。CEIC提供的PSX：上市资本数据处于定期更新的状态，数据来源于Pakistan Stock Exchange Limited，数据归类于Global Database的巴基斯坦 – 表 PK.Z005：卡拉奇证券交易所：年度统计。

In 2024, the Pakistani crude palm oil market decreased by -78.9% to $12M, falling for the fifth consecutive year after three years of growth. Overall, consumption faced a dramatic descent. Crude palm oil consumption peaked at $430M in 2012; however, from 2013 to 2024, consumption remained at a lower figure.