Pakistan's main stock market index, the KSE 100, rose to 141103 points on August 1, 2025, gaining 1.23% from the previous session. Over the past month, the index has climbed 8.25% and is up 80.38% 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 August of 2025.

Key information about Pakistan KSE 100

• Pakistan KSE 100 closed at 41,452.7 points in Jun 2023, compared with 41,330.6 points at the previous month end
• Pakistan Equity Market Index: Month End: Pakistan: KSE 100 data is updated monthly, available from Sep 1996 to Jun 2023, with an average number of 11,785.8 points
• The data reached an all-time high of 50,591.6 points in May 2017 and a record low of 841.7 points in Oct 1998

Stock market return (%, year-on-year) in Pakistan was reported at 16.44 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on August of 2025.

Pakistan Karachi Stock Exchange: Index: KSE 100 Index data was reported at 81,114.200 NA in Sep 2024. This records an increase from the previous number of 78,488.220 NA for Aug 2024. Pakistan Karachi Stock Exchange: Index: KSE 100 Index data is updated monthly, averaging 40,556.645 NA from Jun 2013 (Median) to Sep 2024, with 134 observations. The data reached an all-time high of 81,114.200 NA in Sep 2024 and a record low of 21,005.690 NA in Jun 2013. Pakistan Karachi Stock Exchange: Index: KSE 100 Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s Pakistan – Table PK.EDI.SE: Karachi Stock Exchange: Monthly.

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 July 28 of 2025.

This is a preprocessed dataset of 2 companies from Pakistan Stock Exchange.

Graph and download economic data for Stock Market Turnover Ratio (Value Traded/Capitalization) for Pakistan from 1996 to 2011 about Pakistan, ratio, and stock market.

Key information about Pakistan Market Capitalization: % of GDP

• Pakistan Market Capitalization accounted for 9.8 % of its Nominal GDP in Jun 2024, compared with a percentage of 7.6 % in the previous year
• Pakistan Market Capitalization: % Nominal GDP is updated yearly, available from Jun 2000 to Jun 2024
• The data reached an all-time high of 36.0 % in Jun 2007 and a record low of 6.0 % in Jun 2001

Pakistan Market Cap: PSX: All Shares data was reported at 13,520,596.056 PKR mn in Apr 2025. This records a decrease from the previous number of 14,374,200.085 PKR mn for Mar 2025. Pakistan Market Cap: PSX: All Shares data is updated monthly, averaging 4,126,558.206 PKR mn from Mar 1999 (Median) to Apr 2025, with 314 observations. The data reached an all-time high of 14,495,888.757 PKR mn in Dec 2024 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.Z003: Karachi Stock Exchange: Market Capitalization (New Classification).

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Stock price volatility in Pakistan was reported at 17.28 in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Pakistan - Stock price volatility - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

The COVID-19 pandemic has emerged as a significant event of the current century, introducing substantial transformations in economic and social activities worldwide. The primary objective of this study is to investigate the relationship between daily COVID-19 cases and Pakistan stock market (PSX) return volatility. To assess the relationship between daily COVID-19 cases and the PSX return volatility, we collected secondary data from the World Health Organization (WHO) and the PSX website, specifically focusing on the PSX 100 index, spanning from March 15, 2020, to March 31, 2021. We used the GARCH family models for measuring the volatility and the COVID-19 impact on the stock market performance. Our E-GARCH findings show that there is long-term persistence in the return volatility of the stock market of Pakistan in the period of the COVID-19 timeline because ARCH alpha (ω1) and GARCH beta (ω2) are significant. Moreover, is asymmetrical effect is found in the stock market of Pakistan during the COVID-19 period due to Gamma (ѱ) being significant for PSX. Our DCC-GARCH results show that the COVID-19 active cases have a long-term spillover impact on the Pakistan stock market. Therefore, the need of strong planning and alternative platform should be needed in the distress period to promote the stock market and investor should advised to make diversified international portfolio by investing in high and low volatility stock market to save their income. This study advocated the implications for investors to invest in low volatility stock especially during the period of pandemics to protect their return on investment. Moreover, policy makers and the regulators can make effective policies to maintain financial stability during pandemics that is very important for the country’s economic development.

Key information about Pakistan Market Capitalization

• Pakistan Market Capitalization accounted for 49.986 USD bn in Feb 2025, compared with a percentage of 50.382 USD bn in the previous month
• Pakistan Market Capitalization is updated monthly, available from Mar 1999 to Feb 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

A significant correlation between financial news with stock market trends has been explored extensively. However, very little research has been conducted for stock prediction models that utilize news categories, weighted according to their relevance with the target stock. In this paper, we show that prediction accuracy can be enhanced by incorporating weighted news categories simultaneously into the prediction model. We suggest utilizing news categories associated with the structural hierarchy of the stock market: that is, news categories for the market, sector, and stock-related news. In this context, Long Short-Term Memory (LSTM) based Weighted and Categorized News Stock prediction model (WCN-LSTM) is proposed. The model incorporates news categories with their learned weights simultaneously. To enhance the effectiveness, sophisticated features are integrated into WCN-LSTM. These include, hybrid input, lexicon-based sentiment analysis, and deep learning to impose sequential learning. Experiments have been performed for the case of the Pakistan Stock Exchange (PSX) using different sentiment dictionaries and time steps. Accuracy and F1-score are used to evaluate the prediction model. We have analyzed the WCN-LSTM results thoroughly and identified that WCN-LSTM performs better than the baseline model. Moreover, the sentiment lexicon HIV4 along with time steps 3 and 7, optimized the prediction accuracy. We have conducted statistical analysis to quantitatively assess our findings. A qualitative comparison of WCN-LSTM with existing prediction models is also presented to highlight its superiority and novelty over its counterparts.

Pakistan PK: Stocks Traded: Total Value: % of GDP data was reported at 9.882 % in 2016. This records a decrease from the previous number of 10.019 % for 2015. Pakistan PK: Stocks Traded: Total Value: % of GDP data is updated yearly, averaging 16.919 % from Dec 1996 (Median) to 2016, with 21 observations. The data reached an all-time high of 143.188 % in 2004 and a record low of 0.221 % in 2014. Pakistan PK: Stocks Traded: Total Value: % of GDP data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.WDI: Financial Sector. The value of shares traded is the total number of shares traded, both domestic and foreign, multiplied by their respective matching prices. Figures are single counted (only one side of the transaction is considered). Companies admitted to listing and admitted to trading are included in the data. Data are end of year values.; ; World Federation of Exchanges database.; Weighted average; Stock market data were previously sourced from Standard & Poor's until they discontinued their 'Global Stock Markets Factbook' and database in April 2013. Time series have been replaced in December 2015 with data from the World Federation of Exchanges and may differ from the previous S&P definitions and methodology.

National Bank of Pakistan, Stock Exchange 2001-2022

The Pakistani market for toilet paper, napkins, towels and tissue stock amounted to $9.2B in 2024, remaining relatively unchanged against the previous year. Over the period under review, the total consumption indicated buoyant growth from 2012 to 2024: its value increased at an average annual rate of +5.5% over the last twelve years. The trend pattern, however, indicated some noticeable fluctuations being recorded throughout the analyzed period.

JS Bank Limited, Pakistan Stock Exchange 2007-2022

Equity Market Index: USD data was reported at 105.180 2010=100 in Apr 2025. This records a decrease from the previous number of 105.387 2010=100 for Mar 2025. Equity Market Index: USD data is updated monthly, averaging 109.134 2010=100 from Sep 2006 (Median) to Apr 2025, with 223 observations. The data reached an all-time high of 242.962 2010=100 in Apr 2008 and a record low of 42.065 2010=100 in Jun 2023. Equity Market Index: USD data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Pakistan – Table PK.World Bank.GEM: Equity Market Index. Local equity market index valued in US$ terms

A significant correlation between financial news with stock market trends has been explored extensively. However, very little research has been conducted for stock prediction models that utilize news categories, weighted according to their relevance with the target stock. In this paper, we show that prediction accuracy can be enhanced by incorporating weighted news categories simultaneously into the prediction model. We suggest utilizing news categories associated with the structural hierarchy of the stock market: that is, news categories for the market, sector, and stock-related news. In this context, Long Short-Term Memory (LSTM) based Weighted and Categorized News Stock prediction model (WCN-LSTM) is proposed. The model incorporates news categories with their learned weights simultaneously. To enhance the effectiveness, sophisticated features are integrated into WCN-LSTM. These include, hybrid input, lexicon-based sentiment analysis, and deep learning to impose sequential learning. Experiments have been performed for the case of the Pakistan Stock Exchange (PSX) using different sentiment dictionaries and time steps. Accuracy and F1-score are used to evaluate the prediction model. We have analyzed the WCN-LSTM results thoroughly and identified that WCN-LSTM performs better than the baseline model. Moreover, the sentiment lexicon HIV4 along with time steps 3 and 7, optimized the prediction accuracy. We have conducted statistical analysis to quantitatively assess our findings. A qualitative comparison of WCN-LSTM with existing prediction models is also presented to highlight its superiority and novelty over its counterparts.