View data of the S&P 500, an index of the stocks of 500 leading companies in the US economy, which provides a gauge of the U.S. equity market.

China's main stock market index, the SHANGHAI, rose to 3520 points on July 14, 2025, gaining 0.27% from the previous session. Over the past month, the index has climbed 3.86% and is up 18.35% 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.

Israel's main stock market index, the TA-125, fell to 3051 points on July 13, 2025, losing 2.22% from the previous session. Over the past month, the index has climbed 12.37% and is up 48.25% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Israel. Israel Stock Market (TA-125) - values, historical data, forecasts and news - updated on July of 2025.

While the global coronavirus (COVID-19) pandemic caused all major stock market indices to fall sharply in March 2020, both the extent of the decline at this time, and the shape of the subsequent recovery, have varied greatly. For example, on March 15, 2020, major European markets and traditional stocks in the United States had shed around 40 percent of their value compared to January 5, 2020. However, Asian markets and the NASDAQ Composite Index only shed around 20 to 25 percent of their value. A similar story can be seen with the post-coronavirus recovery. As of November 14, 2021 the NASDAQ composite index value was around 65 percent higher than in January 2020, while most other markets were only between 20 and 40 percent higher.

Why did the NASDAQ recover the quickest?

Based in New York City, the NASDAQ is famously considered a proxy for the technology industry as many of the world’s largest technology industries choose to list there. And it just so happens that technology was the sector to perform the best during the coronavirus pandemic. Accordingly, many of the largest companies who benefitted the most from the pandemic such as Amazon, PayPal and Netflix, are listed on the NADSAQ, helping it to recover the fastest of the major stock exchanges worldwide.

Which markets suffered the most?

The energy sector was the worst hit by the global COVID-19 pandemic. In particular, oil companies share prices suffered large declines over 2020 as demand for oil plummeted while workers found themselves no longer needing to commute, and the tourism industry ground to a halt. In addition, overall share prices in two major stock exchanges – the London Stock Exchange (as represented by the FTSE 100 index) and Hong Kong (as represented by the Hang Seng index) – have notably recovered slower than other major exchanges. However, in both these, the underlying issue behind the slower recovery likely has more to do with political events unrelated to the coronavirus than it does with the pandemic – namely Brexit and general political unrest, respectively.

Graph and download economic data for Index of Common Stock Prices, New York Stock Exchange for United States (M11007USM322NNBR) from Jan 1902 to May 1923 about New York, stock market, indexes, and USA.

The Long Depression was, by a large margin, the longest-lasting recession in U.S. history. It began in the U.S. with the Panic of 1873, and lasted for over five years. This depression was the largest in a series of recessions at the turn of the 20th century, which proved to be a period of overall stagnation as the U.S. financial markets failed to keep pace with industrialization and changes in monetary policy. Great Depression The Great Depression, however, is widely considered to have been the most severe recession in U.S. history. Following the Wall Street Crash in 1929, the country's economy collapsed, wages fell and a quarter of the workforce was unemployed. It would take almost four years for recovery to begin. Additionally, U.S. expansion and integration in international markets allowed the depression to become a global event, which became a major catalyst in the build up to the Second World War. Decreasing severity When comparing recessions before and after the Great Depression, they have generally become shorter and less frequent over time. Only three recessions in the latter period have lasted more than one year. Additionally, while there were 12 recessions between 1880 and 1920, there were only six recessions between 1980 and 2020. The most severe recession in recent years was the financial crisis of 2007 (known as the Great Recession), where irresponsible lending policies and lack of government regulation allowed for a property bubble to develop and become detached from the economy over time, this eventually became untenable and the bubble burst. Although the causes of both the Great Depression and Great Recession were similar in many aspects, economists have been able to use historical evidence to try and predict, prevent, or limit the impact of future recessions.

Vietnam VN: Stocks Traded: Total Value: % of GDP data was reported at 17.001 % in 2017. This records an increase from the previous number of 10.850 % for 2016. Vietnam VN: Stocks Traded: Total Value: % of GDP data is updated yearly, averaging 10.850 % from Dec 2008 (Median) to 2017, with 9 observations. The data reached an all-time high of 21.384 % in 2009 and a record low of 5.527 % in 2011. Vietnam VN: 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 Vietnam – Table VN.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.

Data Analytics in Financial Market Outlook

The global data analytics in financial market size was valued at approximately USD 10.5 billion in 2023 and is projected to reach around USD 34.8 billion by 2032, growing at a robust CAGR of 14.4% during the forecast period. This remarkable growth is driven by the increasing adoption of advanced analytics technologies, the need for real-time data-driven decision-making, and the rising incidence of financial fraud.

One of the primary growth factors for the data analytics in the financial market is the burgeoning volume of data generated from diverse sources such as transactions, social media, and online banking. Financial institutions are increasingly leveraging data analytics to process and analyze this vast amount of data to gain actionable insights. Additionally, technological advancements in artificial intelligence (AI) and machine learning (ML) are significantly enhancing the capabilities of data analytics tools, enabling more accurate predictions and efficient risk management.

Another driving factor is the heightened focus on regulatory compliance and security management. In the wake of stringent regulations imposed by financial authorities globally, organizations are compelled to adopt robust analytics solutions to ensure compliance and mitigate risks. Moreover, with the growing threat of cyber-attacks and financial fraud, there is a heightened demand for sophisticated analytics tools capable of detecting and preventing fraudulent activities in real-time.

Furthermore, the increasing emphasis on customer-centric strategies in the financial sector is fueling the adoption of data analytics. Financial institutions are utilizing analytics to understand customer behavior, preferences, and needs more accurately. This enables them to offer personalized services, improve customer satisfaction, and drive revenue growth. The integration of advanced analytics in customer management processes helps in enhancing customer engagement and loyalty, which is crucial in the competitive financial landscape.

Regionally, North America has been the dominant player in the data analytics in financial market, owing to the presence of major market players, technological advancements, and a high adoption rate of analytics solutions. However, the Asia Pacific region is anticipated to witness the highest growth during the forecast period, driven by the rapid digitalization of financial services, increasing investments in analytics technologies, and the growing focus on enhancing customer experience in emerging economies like China and India.

Component Analysis

In the data analytics in financial market, the components segment is divided into software and services. The software segment encompasses various analytics tools and platforms designed to process and analyze financial data. This segment holds a significant share in the market owing to the continuous advancements in software capabilities and the growing need for real-time analytics. Financial institutions are increasingly investing in sophisticated software solutions to enhance their data processing and analytical capabilities. The software segment is also being propelled by the integration of AI and ML technologies, which offer enhanced predictive analytics and automation features.

On the other hand, the services segment includes consulting, implementation, and maintenance services provided by vendors to help financial institutions effectively deploy and manage analytics solutions. With the rising complexity of financial data and analytics tools, the demand for professional services is on the rise. Organizations are seeking expert guidance to seamlessly integrate analytics solutions into their existing systems and optimize their use. The services segment is expected to grow significantly as more institutions recognize the value of professional support in maximizing the benefits of their analytics investments.

The software segment is further categorized into various types of analytics tools such as descriptive analytics, predictive analytics, and prescriptive analytics. Descriptive analytics tools are used to summarize historical data to identify patterns and trends. Predictive analytics tools leverage historical data to forecast future outcomes, which is crucial for risk management and fraud detection. Prescriptive analytics tools provide actionable recommendations based on predictive analysis, aiding in decision-making processes. The growing need for advanced predictive and prescriptive analytics is driving the demand for specialized software solut

France's main stock market index, the FR40, fell to 7829 points on July 11, 2025, losing 0.92% from the previous session. Over the past month, the index has climbed 0.83% and is up 1.36% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from France. France Stock Market Index (FR40) - values, historical data, forecasts and news - updated on July of 2025.

TagX is your trusted partner for stock market and financial data solutions. We specialize in delivering real-time and end-of-day data feeds that power software, trading algorithms, and risk management systems globally. Whether you're a financial institution, hedge fund, or individual investor, our reliable datasets provide essential insights into market trends, historical pricing, and key financial metrics.

TagX is committed to precision and reliability in stock market data. Our comprehensive datasets include critical information such as date, open/close/high/low prices, trading volume, EPS, P/E ratio, dividend yield, and more. Tailor your dataset to match your specific requirements, choosing from a wide range of parameters and coverage options across primary listings on NASDAQ, AMEX, NYSE, and ARCA exchanges.

Key Features of TagX Stock Market Data:

Custom Dataset Requests: Customize your data feed to focus on specific metrics and parameters crucial to your trading strategy.

Extensive Coverage: Access data from reputable exchanges and market participants, ensuring accuracy and completeness in your analyses.

Flexible Pricing Models: Choose pricing structures based on your selected parameters, offering cost-effective solutions tailored to your needs.

Why Choose TagX? Partner with TagX for precise, dependable, and customizable stock market data solutions. Whether you require real-time updates or end-of-day valuations, our datasets are designed to support informed decision-making and enhance your competitive edge in the financial markets. Trust TagX to deliver the data integrity and accuracy essential for maximizing your trading potential.

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Securities Exchanges Market Size 2025-2029

The securities exchanges market size is forecast to increase by USD 56.67 billion at a CAGR of 12.5% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing demand for investment opportunities. This trend is fueled by a global economic recovery and a rising interest in various asset classes, particularly in emerging markets. Another key driver is the increasing focus on sustainable and environmental, social, and governance (ESG) investing. This shift reflects a growing awareness of the importance of long-term value creation and the role of exchanges in facilitating socially responsible investments. This trend is driven by the expanding securities business units, including stocks, bonds, mutual funds, and other securities, which cater to the needs of investment firms and individual investors. However, the market is not without challenges. Increasing market volatility poses a significant risk for exchanges and their clients.
Furthermore, the rapid digitization of trading and the emergence of alternative trading platforms are disrupting traditional exchange business models. To navigate these challenges, exchanges must adapt by investing in technology, expanding their product offerings, and building strong regulatory frameworks. Data analytics and big data are also crucial tools for e-brokerage firms to gain insights and make informed decisions. By doing so, they can capitalize on the market's growth potential and maintain their competitive edge. Geopolitical tensions, economic instability, and regulatory changes can all contribute to market fluctuations and uncertainty.

What will be the Size of the Securities Exchanges 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, financial instrument classification plays a crucial role in facilitating efficient trade matching through advanced execution quality metrics and order book liquidity. Quantitative trading models leverage options clearing corporation data to optimize portfolio holdings, while trade matching engines utilize high-speed data storage solutions and portfolio optimization algorithms to minimize latency and enhance market depth indicators. Data center infrastructure and network bandwidth capacity are essential components for supporting complex algorithmic trading strategies, including latency reduction and price volatility forecasting. Market impact measurement and risk assessment methodologies are integral to managing market impact and mitigating fraud, ensuring regulatory compliance through transaction reporting standards and regulatory compliance software.

Exchange traded funds (ETFs) have gained popularity, necessitating robust quote dissemination systems and trade surveillance analytics. Server virtualization and cybersecurity threat mitigation strategies further strengthen the market's resilience, enabling seamless integration of data-driven quantitative models and sophisticated fraud detection algorithms. Additionally, users of online trading platforms can easily monitor the performance of their assets thanks to real-time stock data.

How is this Securities Exchanges Industry segmented?

The securities exchanges 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.

Service

  Market platforms
  Capital access platforms
  Others


Trade Finance Instruments

  Equities
  Derivatives
  Bonds
  Exchange-traded funds
  Others


Type

  Large-cap exchanges
  Mid-cap exchanges
  Small-cap exchanges


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Switzerland
    UK


  APAC

    China
    Hong Kong
    India
    Japan


  Rest of World (ROW)

By Service Insights

The Market platforms segment is estimated to witness significant growth during the forecast period. The market is characterized by advanced technologies and systems that enable efficient price discovery, manage settlement risk, and ensure regulatory compliance. Market platforms, which include trading platforms, order-matching systems, and market data dissemination, hold the largest share of the market. These platforms facilitate the buying and selling of securities, providing market liquidity and transparency. Real-time market surveillance and high-frequency trading infrastructure are crucial components, ensuring fair and orderly markets and enabling efficient trade execution. Financial modeling techniques and algorithmic trading platforms optimize trading strategies, while electronic communication networks and central counterparty cleari

Austria: Stock market return, percent: The latest value from 2021 is 42.3 percent, an increase from -20.47 percent in 2020. In comparison, the world average is 32.21 percent, based on data from 87 countries. Historically, the average for Austria from 1987 to 2021 is 7.83 percent. The minimum value, -36.45 percent, was reached in 2009 while the maximum of 71.89 percent was recorded in 1990.

The Nasdaq stock exchange has seen significant fluctuations in its listed companies over recent years. As of December 2024, the exchange boasted a total of ***** listed companies, with ***** domestic and *** international firms. This diverse mix of listings reflects the Nasdaq's global appeal and its role as a major player in the world of stock exchanges.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 214 companies listed on the Panama Stock Exchange (XPTY) in Panama. 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 Panama:

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 Panama:

Panamanian Stock Exchange Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Panamanian Stock Exchange (Bolsa de Valores de Panamá). This index provides an overview of the overall market performance in Panama.

Panamanian Stock Exchange Foreign Company Index: The index that tracks the performance of foreign companies listed on the Panamanian Stock Exchange. This index reflects the performance of international companies operating in Panama.

Company A: A prominent Panamanian company with diversified operations across various sectors, such as shipping, logistics, or finance. This company's stock is widely traded on the Panamanian Stock Exchange.

Company B: A leading financial institution in Panama, offering banking, insurance, or investment services. This company's stock is actively traded on the Panamanian Stock Exchange.

Company C: A major player in the Panamanian energy or real estate sector, involved in the production and distribution of related products. This company's stock is listed and actively traded on the Panamanian Stock Exchange.

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If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Panama, 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 Panama ?

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 Panama?

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 Panama 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 this dataset?

Techsalerator accepts various payment methods, including credit cards, direc...

Estonia: Stock market return, percent: The latest value from 2021 is 43.16 percent, an increase from -3.07 percent in 2020. In comparison, the world average is 32.21 percent, based on data from 87 countries. Historically, the average for Estonia from 1997 to 2021 is 18.77 percent. The minimum value, -41.38 percent, was reached in 1998 while the maximum of 173.71 percent was recorded in 1997.

Canada CA: Market Capitalization: Listed Domestic Companies data was reported at 2,744.720 USD bn in 2022. This records a decrease from the previous number of 3,264.137 USD bn for 2021. Canada CA: Market Capitalization: Listed Domestic Companies data is updated yearly, averaging 910.231 USD bn from Dec 1977 (Median) to 2022, with 45 observations. The data reached an all-time high of 3,264.137 USD bn in 2021 and a record low of 173.942 USD bn in 1977. Canada CA: Market Capitalization: Listed Domestic Companies data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Canada – Table CA.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 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.

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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

Tunisia TN: Stocks Traded: Total Value: % of GDP data was reported at 1.864 % in 2014. This records an increase from the previous number of 0.999 % for 2013. Tunisia TN: Stocks Traded: Total Value: % of GDP data is updated yearly, averaging 1.814 % from Dec 1994 (Median) to 2014, with 10 observations. The data reached an all-time high of 4.167 % in 2010 and a record low of 0.742 % in 1998. Tunisia TN: 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 Tunisia – Table TN.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.

Techsalerator offers an extensive dataset of End-of-Day Pricing Data for all 48 companies listed on the Stock Exchange of Mauritius (XMAU) in Mauritius. 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 Mauritius:

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.

‍

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

Mauritius Stock Exchange (SEM) Domestic Company Index: The main index that tracks the performance of domestic companies listed on the Stock Exchange of Mauritius. This index provides an overview of the overall market performance in Mauritius.

Mauritius Stock Exchange (SEM) Foreign Company Index: The index that tracks the performance of foreign companies listed on the Stock Exchange of Mauritius. This index reflects the performance of international companies operating in Mauritius.

Company A: A prominent Mauritian company with diversified operations across various sectors, such as tourism, financial services, or technology. This company's stock is widely traded on the Stock Exchange of Mauritius.

Company B: A leading financial institution in Mauritius, offering banking, insurance, or investment services. This company's stock is actively traded on the Stock Exchange of Mauritius.

Company C: A major player in the Mauritian agricultural sector, involved in the production and export of agricultural products. This company's stock is listed and actively traded on the Stock Exchange of Mauritius.

‍

If you're interested in accessing Techsalerator's End-of-Day Pricing Data for Mauritius, 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:

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

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 Mauritius?

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 Mauritius 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 this dataset?

Techsalerator accepts various payment methods, includi...

Stock market forecasting is one of the most challenging problems in today’s financial markets. According to the efficient market hypothesis, it is almost impossible to predict the stock market with 100% accuracy. However, Machine Learning (ML) methods can improve stock market predictions to some extent. In this paper, a novel strategy is proposed to improve the prediction efficiency of ML models for financial markets. Nine ML models are used to predict the direction of the stock market. First, these models are trained and validated using the traditional methodology on a historic data captured over a 1-day time frame. Then, the models are trained using the proposed methodology. Following the traditional methodology, Logistic Regression achieved the highest accuracy of 85.51% followed by XG Boost and Random Forest. With the proposed strategy, the Random Forest model achieved the highest accuracy of 91.27% followed by XG Boost, ADA Boost and ANN. In the later part of the paper, it is shown that only classification report is not sufficient to validate the performance of ML model for stock market prediction. A simulation model of the financial market is used in order to evaluate the risk, maximum draw down and returns associate with each ML model. The overall results demonstrated that the proposed strategy not only improves the stock market returns but also reduces the risks associated with each ML model.