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This dataset provides a comprehensive historical record of stock prices from the Dhaka Stock Exchange (DSE), the primary stock exchange of Bangladesh. Spanning from January 1, 2000, to February 26, 2025, it offers a detailed look into the daily trading activity of 464 unique stocks.
This dataset was meticulously compiled and cleaned to provide a valuable resource for researchers, analysts, and investors interested in the Dhaka Stock Exchange.
While efforts have been made to ensure the accuracy of the data, users are advised to conduct their own due diligence and validation before making any investment decisions based on this dataset.
This description highlights the key aspects of your dataset, its potential uses, and its reliability. Feel free to adjust it further based on any specific details or insights you want to emphasize!
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Prices for Bangladesh DSE General Index including live quotes, historical charts and news. Bangladesh DSE General Index was last updated by Trading Economics this November 28 of 2025.
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TwitterTechsalerator offers an extensive dataset of End-of-Day Pricing Data for all 342 companies listed on the Chittagong Stock Exchange (XCHG) in Bangladesh. 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.
Top 5 used data fields in the End-of-Day Pricing Dataset for Bangladesh:
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.
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.
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.
Equity Ticker Symbol: The unique symbol used to identify individual company stocks. Ticker symbols facilitate efficient trading and data retrieval.
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.
Top 5 financial instruments with End-of-Day Pricing Data in Bangladesh:
Dhaka Stock Exchange (DSE) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Dhaka Stock Exchange. This index provides an overview of the overall market performance in Bangladesh.
Dhaka Stock Exchange (DSE) Foreign Company Index: The index that tracks the performance of foreign companies listed on the Dhaka Stock Exchange. This index reflects the performance of international companies operating in Bangladesh.
Company A: A prominent Bangladeshi company with diversified operations across various sectors, such as textiles, telecommunications, or banking. This company's stock is widely traded on the Dhaka Stock Exchange.
Company B: A leading financial institution in Bangladesh, offering banking, insurance, or investment services. This company's stock is actively traded on the Dhaka Stock Exchange.
Company C: A major player in the Bangladeshi agriculture sector, involved in the production and distribution of agricultural products. This company's stock is listed and actively traded on the Dhaka Stock Exchange.
If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Bangladesh, 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.
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:
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.
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 Bangladesh exchanges.
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.
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.
Techsalerator accepts various payment methods, including credit cards, direct tra...
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Actual value and historical data chart for Bangladesh Stock Market Return Percent Year On Year
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This comprehensive dataset covers historical stock market data from the Dhaka Stock Exchange (DSE) for the period from 1999 to 2023. Collected from the DSE Stocks website, this dataset is organized into separate CSV files for each year, providing a detailed record of stock market trends and movements over this 24-year span.
Data Source: https://dsestocks.com/dse-csv-data/
Contents:
Date: The trading date, formatted as YYYY-MM-DD.
Open: The opening price of the stock on the given date, reflecting the first transaction price of the day.
High: The highest transaction price of the stock on the given date.
Low: The lowest transaction price of the stock on the given date.
Close: The closing price of the stock on the given date, reflecting the final transaction price of the day.
Volume: The total number of shares traded on the given date.
Price Change: The change in stock price from the previous day's closing price.
Usage: This dataset is ideal for analyzing historical trends in the Dhaka Stock Exchange, performing time series analysis, and developing predictive models for stock prices. It offers valuable insights for researchers, analysts, and investors looking to understand the market's behavior over the years. By studying this dataset, users can identify patterns, assess market volatility, and make informed investment decisions.
Key Features:
Comprehensive: Covers 24 years of stock market data, offering a thorough historical perspective.
Detailed: Includes daily trading data, enabling fine-grained analysis of stock market movements.
Pre-Processed: Data has been cleaned and organized for ease of use in modeling and analysis.
Note:
Each CSV file represents the stock data for a specific year from 1999 to 2023. Users must combine these files into a single dataset for a continuous time series analysis.
Acknowledgment: This dataset was obtained from the DSE Stocks website, a reliable source for historical stock market data in Bangladesh.
Example Use Cases:
Trend Analysis: Study the long-term trends in the Dhaka stock market and identify significant periods of growth or decline.
Volatility Assessment: Analyze market volatility over different time frames using the provided data.
Predictive Modeling: Develop machine learning models to forecast future stock prices based on historical data.
Investment Strategy Development: Formulate and backtest investment strategies using historical data.
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A stock index, or stock market index, is an index that measures a stock market, or a subset of the stock market, that helps investors compare current price levels with past prices to calculate market performance. It is computed from the prices of selected stocks (typically a weighted arithmetic mean)
This data is represented Dhaka (The capital of Bangladesh) Stock Exchange Price from January 31, 2013 to September 20, 2020.
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Bangladesh DSE: PE Ratio data was reported at 9.930 Unit in Oct 2025. This records a decrease from the previous number of 10.380 Unit for Sep 2025. Bangladesh DSE: PE Ratio data is updated monthly, averaging 10.790 Unit from Nov 2000 (Median) to Oct 2025, with 298 observations. The data reached an all-time high of 30.580 Unit in Feb 2010 and a record low of 5.900 Unit in Mar 2003. Bangladesh DSE: PE Ratio data remains active status in CEIC and is reported by Dhaka Stock Exchange. The data is categorized under Global Database’s Bangladesh – Table BD.Z: Dhaka Stock Exchange: PE Ratio and Dividend Yield. No available data for April and May 2020 due to temporary closure of Dhaka Stock Exchange from March 29 to May 28, 2020.
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Bangladesh DSE: Turnover: Annual: Value data was reported at 1,498,649.059 BDT mn in 2024. This records a decrease from the previous number of 1,910,874.665 BDT mn for 2023. Bangladesh DSE: Turnover: Annual: Value data is updated yearly, averaging 875,397.045 BDT mn from Jun 1997 (Median) to 2024, with 28 observations. The data reached an all-time high of 3,258,632.868 BDT mn in 2011 and a record low of 12,616.940 BDT mn in 1998. Bangladesh DSE: Turnover: Annual: Value data remains active status in CEIC and is reported by Dhaka Stock Exchange. The data is categorized under Global Database’s Bangladesh – Table BD.Z002: Dhaka Stock Exchange: Turnover.
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TwitterDhaka Stock exchange is one of the major stock markets of Bangladesh. Here the CSV file contains the closing price of the stock market from 2018 to 2020.
Here we have 12 columns in this data set 1. 'INDEX 2. 'DATE' 3. 'TRADINGCODE', 4. 'LTP*', 5. 'HIGH', 6. 'LOW', 7. 'OPENP*', 8. 'CLOSEP*', 9. 'YCP', 10. 'TRADE', 11. 'VALUE(mn)', 12. 'VOLUME'
I scrape this data from the official DSE website.
Working with time series data inspired me to create this dataset.
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Bangladesh DSE: Listed Corporate Bonds data was reported at 16.000 Unit in Jan 2025. This stayed constant from the previous number of 16.000 Unit for Dec 2024. Bangladesh DSE: Listed Corporate Bonds data is updated monthly, averaging 2.000 Unit from Nov 2007 (Median) to Jan 2025, with 205 observations. The data reached an all-time high of 16.000 Unit in Jan 2025 and a record low of 1.000 Unit in Dec 2019. Bangladesh DSE: Listed Corporate Bonds data remains active status in CEIC and is reported by Dhaka Stock Exchange. The data is categorized under Global Database’s Bangladesh – Table BD.Z006: Dhaka Stock Exchange: Number of Listed Companies and Shares. No available data for April and May 2020 due to temporary closure of Dhaka Stock Exchange from March 29 to May 28, 2020.
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TwitterTechsalerator's Corporate Actions Dataset in Bangladesh offers a comprehensive collection of data fields related to corporate actions, providing valuable insights for investors, traders, and financial institutions. This dataset includes crucial information about the various financial instruments of all 342 companies traded on the Chittagong Stock Exchange (XCHG).
Top 5 used data fields in the Corporate Actions Dataset for Bangladesh:
Dividend Declaration Date: The date on which a company's board of directors announces the dividend payout to its shareholders. This information is crucial for investors who rely on dividends as a source of income.
Stock Split Ratio: The ratio by which a company's shares are split to increase liquidity and affordability. This field is essential for understanding changes in share structure.
Merger Announcement Date: The date on which a company officially announces its intention to merge with another entity. This field is crucial for investors assessing the impact of potential mergers on their investments.
Rights Issue Record Date: The date on which shareholders must be on the company's books to be eligible for participating in a rights issue. This data helps investors plan their participation in fundraising events.
Bonus Issue Ex-Date: The date on which a company's shares start trading without the value of the bonus issue. This information is vital for investors to adjust their portfolios accordingly.
Top 5 corporate actions in Bangladesh:
Garment and Textile Industry Investments: Corporate actions related to the garment and textile sector, including investments, expansions, and partnerships, play a vital role in Bangladesh's economy and its status as a major global textiles exporter.
Financial Technology (FinTech) Innovations: Corporate actions involving FinTech startups, digital payment solutions, and mobile banking initiatives contribute to modernizing the financial sector and promoting financial inclusion.
Energy and Infrastructure Projects: Corporate actions related to energy development, including power generation and transportation infrastructure initiatives, support Bangladesh's efforts to improve energy security and connectivity.
Agricultural and Agribusiness Initiatives: Given the significance of agriculture in Bangladesh, corporate actions involving agribusiness projects, technology adoption, and value chain development contribute to food security and rural development.
Consumer Goods and Retail Sector Growth: Corporate actions related to retail and consumer goods, including expansions, branding, and product launches, reflect Bangladesh's growing consumer market and middle-class segment.
Top 5 financial instruments with corporate action Data in Bangladesh
Dhaka Stock Exchange (DSE) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Dhaka Stock Exchange. This index would provide insights into the performance of the Bangladeshi stock market.
Dhaka Stock Exchange (DSE) Foreign Company Index: The index that tracks the performance of foreign companies listed on the Dhaka Stock Exchange, if foreign listings were present. This index would give an overview of foreign business involvement in Bangladesh.
BengalMart: A Bangladesh-based supermarket chain with operations in multiple regions. BengalMart focuses on providing essential products to local communities and contributing to the retail sector's growth.
FinServe Bangladesh: A financial services provider in Bangladesh with a focus on promoting financial inclusion and access to banking services, particularly among underserved communities.
AgriTech Bangladesh: A company dedicated to advancing agricultural technology in Bangladesh, focusing on optimizing crop yields and improving food security to support the country's agricultural sector.
If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Bangladesh, 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.
Data fields included:
Dividend Declaration Date Stock Split Ratio Merger Announcement Date Rights Issue Record Date Bonus Issue Ex-Date Stock Buyback Date Spin-Off Announcement Date Dividend Record Date Merger Effective Date Rights Issue Subscription Price
Q&A:
How much does the Corporate Actions Dataset cost in Bangladesh?
The cost of the Corporate Actions 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.
How complete is the Corporate Action...
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This dataset is originally from Dhaka Stock Exchange Ltd. The objective of the dataset is to assign analytical report writing tasks to Summer 2020 students enrolled in ASDS18: Data Mining course in proceedings of the partial fulfillment of the requirements for the Professional Masters in Applied Statistics and Data Science (PMASDS) degree. This data set was collected using the Dhaka Stock Exchange API.
The datasets consist of several stock company predictor (independent) variables and one target (dependent) variable, Outcome. Independent variables include the last price, net asset value (NAV) of the stock, Earnings Per Share (EPS), price-to-earnings (P/E) ratio of the stock, paid-up capital per share, and so on.
It contains information on 374 listed companies from Dhaka Stock Exchange - DSE, Bangladesh. The outcome tested was Category, 258 tested positive and 500 tested negative. Therefore, there is one target (dependent) variable and 8 attributes.
Dr. Md. Rezaul Karim, Associate Professor, Department of Statistics, Jahangirnagar University, Dhaka, Bangladesh (2021) provided us with this dataset. Using the Dhaka Stock Exchange API this data set was collected to assign analytical report writing tasks to Summer 2020 students in proceedings of the partial fulfillment of the requirements for the Professional Masters in Applied Statistics and Data Science (PMASDS) degree.
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Key information about Bangladesh Market Capitalization
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DSE:成交量:年度:值在06-01-2024达1,498,649.059百万孟加拉塔卡,相较于06-01-2023的1,910,874.665百万孟加拉塔卡有所下降。DSE:成交量:年度:值数据按年更新,06-01-1997至06-01-2024期间平均值为875,397.045百万孟加拉塔卡,共28份观测结果。该数据的历史最高值出现于06-01-2011,达3,258,632.868百万孟加拉塔卡,而历史最低值则出现于06-01-1998,为12,616.940百万孟加拉塔卡。CEIC提供的DSE:成交量:年度:值数据处于定期更新的状态,数据来源于Dhaka Stock Exchange,数据归类于Global Database的孟加拉 – Table BD.Z002: Dhaka Stock Exchange: Turnover。
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This dataset provides a comprehensive historical record of stock prices from the Dhaka Stock Exchange (DSE), the primary stock exchange of Bangladesh. Spanning from January 1, 2000, to February 26, 2025, it offers a detailed look into the daily trading activity of 464 unique stocks.
This dataset was meticulously compiled and cleaned to provide a valuable resource for researchers, analysts, and investors interested in the Dhaka Stock Exchange.
While efforts have been made to ensure the accuracy of the data, users are advised to conduct their own due diligence and validation before making any investment decisions based on this dataset.
This description highlights the key aspects of your dataset, its potential uses, and its reliability. Feel free to adjust it further based on any specific details or insights you want to emphasize!