26 datasets found
  1. T

    Pakistan Stock Market (KSE100) Data

    • tradingeconomics.com
    • ar.tradingeconomics.com
    • +13more
    csv, excel, json, xml
    Updated Feb 4, 2020
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    TRADING ECONOMICS (2020). Pakistan Stock Market (KSE100) Data [Dataset]. https://tradingeconomics.com/pakistan/stock-market
    Explore at:
    json, excel, csv, xmlAvailable download formats
    Dataset updated
    Feb 4, 2020
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    May 25, 1994 - Aug 8, 2025
    Area covered
    Pakistan
    Description

    Pakistan's main stock market index, the KSE 100, fell to 145383 points on August 8, 2025, losing 0.18% from the previous session. Over the past month, the index has climbed 9.66% and is up 85.04% 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.

  2. Pakistan Karachi Stock Exchange: Index: KSE 100 Index

    • ceicdata.com
    Updated Jan 15, 2025
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    CEICdata.com (2025). Pakistan Karachi Stock Exchange: Index: KSE 100 Index [Dataset]. https://www.ceicdata.com/en/pakistan/karachi-stock-exchange-monthly/karachi-stock-exchange-index-kse-100-index
    Explore at:
    Dataset updated
    Jan 15, 2025
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jul 1, 2023 - Aug 1, 2024
    Area covered
    Pakistan
    Description

    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.

  3. T

    Pakistan - Stock Market Return (%, Year-on-year)

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 29, 2017
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    TRADING ECONOMICS (2017). Pakistan - Stock Market Return (%, Year-on-year) [Dataset]. https://tradingeconomics.com/pakistan/stock-market-return-percent-year-on-year-wb-data.html
    Explore at:
    excel, json, xml, csvAvailable download formats
    Dataset updated
    May 29, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 1976 - Dec 31, 2025
    Area covered
    Pakistan
    Description

    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.

  4. F

    Stock Market Turnover Ratio (Value Traded/Capitalization) for Pakistan

    • fred.stlouisfed.org
    json
    Updated May 7, 2024
    + more versions
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    (2024). Stock Market Turnover Ratio (Value Traded/Capitalization) for Pakistan [Dataset]. https://fred.stlouisfed.org/graph/?id=DDEM01PKA156NWDB
    Explore at:
    jsonAvailable download formats
    Dataset updated
    May 7, 2024
    License

    https://fred.stlouisfed.org/legal/#copyright-public-domainhttps://fred.stlouisfed.org/legal/#copyright-public-domain

    Area covered
    Pakistan
    Description

    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.

  5. T

    Karachi Stock Exchange KSE100 Index - Index Price | Live Quote | Historical...

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 29, 2017
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    TRADING ECONOMICS (2017). Karachi Stock Exchange KSE100 Index - Index Price | Live Quote | Historical Chart [Dataset]. https://tradingeconomics.com/kse100:ind
    Explore at:
    excel, xml, csv, jsonAvailable download formats
    Dataset updated
    May 29, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2000 - Jul 28, 2025
    Area covered
    Pakistan
    Description

    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.

  6. Pakistan Equity Market Index

    • ceicdata.com
    Updated Jun 15, 2023
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    CEICdata.com (2023). Pakistan Equity Market Index [Dataset]. https://www.ceicdata.com/en/indicator/pakistan/equity-market-index
    Explore at:
    Dataset updated
    Jun 15, 2023
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jul 1, 2022 - Jun 1, 2023
    Area covered
    Pakistan
    Description

    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

    CEIC calculates monthly Equity Market Index from daily Equity Market Index based on the last business day of the month. Pakistan Stock Exchange Limited provides Equity Market Index

  7. P

    Pakistan Market Cap: PSX: All Shares

    • ceicdata.com
    Updated Aug 9, 2020
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    CEICdata.com (2020). Pakistan Market Cap: PSX: All Shares [Dataset]. https://www.ceicdata.com/en/pakistan/karachi-stock-exchange-market-capitalization-new-classification/market-cap-psx-all-shares
    Explore at:
    Dataset updated
    Aug 9, 2020
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Mar 1, 2024 - Feb 1, 2025
    Area covered
    Pakistan
    Variables measured
    Market Capitalisation
    Description

    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).

  8. f

    E-GARCH findings.

    • plos.figshare.com
    xls
    Updated Apr 16, 2024
    + more versions
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    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti (2024). E-GARCH findings. [Dataset]. http://doi.org/10.1371/journal.pone.0295853.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 16, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

  9. i

    Dataset for Stock Market Prediction

    • ieee-dataport.org
    Updated Jul 8, 2024
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    Umara Umar (2024). Dataset for Stock Market Prediction [Dataset]. https://ieee-dataport.org/documents/dataset-stock-market-prediction
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    Dataset updated
    Jul 8, 2024
    Authors
    Umara Umar
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Hascol

  10. P

    Pakistan PK: Stocks Traded: Total Value: % of GDP

    • ceicdata.com
    Updated Apr 15, 2018
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    CEICdata.com (2018). Pakistan PK: Stocks Traded: Total Value: % of GDP [Dataset]. https://www.ceicdata.com/en/pakistan/financial-sector/pk-stocks-traded-total-value--of-gdp
    Explore at:
    Dataset updated
    Apr 15, 2018
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Pakistan
    Variables measured
    Turnover
    Description

    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.

  11. f

    Descriptive statistics.

    • figshare.com
    xls
    Updated Apr 16, 2024
    + more versions
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    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti (2024). Descriptive statistics. [Dataset]. http://doi.org/10.1371/journal.pone.0295853.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 16, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

  12. i

    Pakistan's Toilet Paper, Napkins, Towels and Tissue Stock Market Report 2025...

    • indexbox.io
    doc, docx, pdf, xls +1
    Updated Aug 1, 2025
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    IndexBox Inc. (2025). Pakistan's Toilet Paper, Napkins, Towels and Tissue Stock Market Report 2025 - Prices, Size, Forecast, and Companies [Dataset]. https://www.indexbox.io/store/pakistan-toilet-paper-napkins-towels-and-tissue-stock-market-analysis-forecast-size-trends-and-insights/
    Explore at:
    docx, xlsx, pdf, doc, xlsAvailable download formats
    Dataset updated
    Aug 1, 2025
    Dataset authored and provided by
    IndexBox Inc.
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jan 1, 2012 - Aug 9, 2025
    Area covered
    Pakistan
    Variables measured
    Demand, Supply, Price CIF, Price FOB, Market size, Export price, Export value, Import price, Import value, Export volume, and 8 more
    Description

    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.

  13. KSE-Dataset

    • kaggle.com
    Updated Mar 24, 2020
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    Ghazanfar Ali (2020). KSE-Dataset [Dataset]. https://www.kaggle.com/ghazanfarali/ksedataset/code
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 24, 2020
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Ghazanfar Ali
    Description

    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.

  14. P

    Pakistan PK: Stocks Traded: Total Value

    • ceicdata.com
    Updated May 15, 2023
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    CEICdata.com (2023). Pakistan PK: Stocks Traded: Total Value [Dataset]. https://www.ceicdata.com/en/pakistan/financial-sector/pk-stocks-traded-total-value
    Explore at:
    Dataset updated
    May 15, 2023
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Pakistan
    Variables measured
    Turnover
    Description

    Pakistan PK: Stocks Traded: Total Value data was reported at 27.536 USD bn in 2016. This records an increase from the previous number of 27.108 USD bn for 2015. Pakistan PK: Stocks Traded: Total Value data is updated yearly, averaging 20.824 USD bn from Dec 1996 (Median) to 2016, with 21 observations. The data reached an all-time high of 140.293 USD bn in 2004 and a record low of 539.700 USD mn in 2014. Pakistan PK: Stocks Traded: Total Value 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 converted to U.S. dollars using corresponding year-end foreign exchange rates.; ; World Federation of Exchanges database.; Sum; 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.

  15. f

    VAR lag selection criteria.

    • plos.figshare.com
    xls
    Updated Apr 16, 2024
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    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti (2024). VAR lag selection criteria. [Dataset]. http://doi.org/10.1371/journal.pone.0295853.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 16, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

  16. Pakistan PK: Market Capitalization: Listed Domestic Companies: % of GDP

    • ceicdata.com
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    CEICdata.com, Pakistan PK: Market Capitalization: Listed Domestic Companies: % of GDP [Dataset]. https://www.ceicdata.com/en/pakistan/financial-sector/pk-market-capitalization-listed-domestic-companies--of-gdp
    Explore at:
    Dataset provided by
    CEIC Data
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 1, 2005 - Dec 1, 2016
    Area covered
    Pakistan
    Variables measured
    Turnover
    Description

    Pakistan PK: Market Capitalization: Listed Domestic Companies: % of GDP data was reported at 32.967 % in 2016. This records an increase from the previous number of 24.420 % for 2015. Pakistan PK: Market Capitalization: Listed Domestic Companies: % of GDP data is updated yearly, averaging 19.720 % from Dec 1993 (Median) to 2016, with 24 observations. The data reached an all-time high of 46.537 % in 2004 and a record low of 6.781 % in 2001. Pakistan PK: Market Capitalization: Listed Domestic Companies: % 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. Market capitalization (also known as market value) is the share price times the number of shares outstanding (including their several classes) for listed domestic companies. Investment funds, unit trusts, and companies whose only business goal is to hold shares of other listed companies are excluded. 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.

  17. f

    Spillover effect of COVID-19 cases on stock market return volatility.

    • plos.figshare.com
    xls
    Updated Apr 16, 2024
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    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti (2024). Spillover effect of COVID-19 cases on stock market return volatility. [Dataset]. http://doi.org/10.1371/journal.pone.0295853.t007
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 16, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Baixiang Wang; Muhammad Waris; Katarzyna Adamiak; Mohammad Adnan; Hawkar Anwer Hamad; Saad Mahmood Bhatti
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Spillover effect of COVID-19 cases on stock market return volatility.

  18. f

    p-values for the second hypothesis test.

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
    + more versions
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    Shazia Usmani; Jawwad A. Shamsi (2023). p-values for the second hypothesis test. [Dataset]. http://doi.org/10.1371/journal.pone.0282234.t007
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Shazia Usmani; Jawwad A. Shamsi
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    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.

  19. f

    Data from: S1 Dataset -

    • plos.figshare.com
    xlsx
    Updated Apr 16, 2024
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    Rekurd S. Maghdid; Saeed Mohammed Kareem; Yaseen Salih Hama; Muhammad Waris; Rana Tahir Naveed (2024). S1 Dataset - [Dataset]. http://doi.org/10.1371/journal.pone.0301698.s001
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    xlsxAvailable download formats
    Dataset updated
    Apr 16, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Rekurd S. Maghdid; Saeed Mohammed Kareem; Yaseen Salih Hama; Muhammad Waris; Rana Tahir Naveed
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The objective of the study is to explore the relationship between country governance practices along with political stability and Economic policy uncertainty, and stock market performance of two different economies, Pakistan and Kurdistan region of Iraq. To meet our objectives, we used the 25 years past data from 1996 to 2021. Data is collected from the DataStream database. The regression analysis is used as the method of estimation for linear and moderation effect. Our results show that regulatory quality, rules of law and political stability has significant positive relationship with stock market performance of Pakistan, but all the governance indicators have significant positive relationship with stock market performance of the Kurdistan Region of Iraq. Moreover, political stability has significant moderating impact between the governance practices and the performance of the stock markets of both economies indicating that the governance practices perform well with the political stability that leads to rise in the stock market indices of selected countries. Economic policy uncertainty has significant negative moderation impact due to creating the risk in both economies that decrease the performance of the stock markets of the selected economies. Finally, our study advocated some implications for the investors to increase their confidence on the stock of high political stability and low economic policy uncertainty economies. Government can take significant measures to control the uncertainty of the policy and portfolio managers can adjust their risk on the ground of the political stability and efficient governance practices countries.

  20. f

    S2 Data -

    • plos.figshare.com
    xlsx
    Updated Oct 19, 2023
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    Zhiying Mai; Hassan Mujtaba Nawaz Saleem; Muhammad Kamran (2023). S2 Data - [Dataset]. http://doi.org/10.1371/journal.pone.0292284.s002
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    xlsxAvailable download formats
    Dataset updated
    Oct 19, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Zhiying Mai; Hassan Mujtaba Nawaz Saleem; Muhammad Kamran
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The stock market is the barometer of the economy that reflects the overall health and direction of the economic development and is affected by different factors including social, environmental and political. It is important to investigate the effect of the political instability on the stock market performance, especially on emerging economies. Therefore, we aim to study the relationship between political instability and stock market performance in Pakistan. To meet our objectives, we used past data from 1996 to 2021. Data are collected from the DataStream data base. MSCI indices are used as the proxy for the Stock market performance of the selected country. World governance six indicators are used in the study as the explanatory variable concentrating the political instability index as the main explanatory variable. Regression analysis is used but two-way robustness analysis was done for the accuracy of the findings through GMM methods and taking GDP as another endogenous variable. Our findings shows that the political stability has significant positive impact on the stock market performance while, political instability has negative impact on stock market performance. Moreover, other governance indicators has a significant positive impact on performance. However, political instability disrupts the operations and economical activities that leads to decrease the investor confidence and also decrease the foreign investment with the increment of the risk in the country. Moreover, our study has some implications for investors to develop the diversified portfolio to minimize the risk and policy makers can increase their foreign direct investment within the economy by controlling the political instability.

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TRADING ECONOMICS (2020). Pakistan Stock Market (KSE100) Data [Dataset]. https://tradingeconomics.com/pakistan/stock-market

Pakistan Stock Market (KSE100) Data

Pakistan Stock Market (KSE100) - Historical Dataset (1994-05-25/2025-08-08)

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6 scholarly articles cite this dataset (View in Google Scholar)
json, excel, csv, xmlAvailable download formats
Dataset updated
Feb 4, 2020
Dataset authored and provided by
TRADING ECONOMICS
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
May 25, 1994 - Aug 8, 2025
Area covered
Pakistan
Description

Pakistan's main stock market index, the KSE 100, fell to 145383 points on August 8, 2025, losing 0.18% from the previous session. Over the past month, the index has climbed 9.66% and is up 85.04% 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.

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