Stock market return (%, year-on-year) in Denmark was reported at 31.18 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Denmark - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

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.

Stock market return (%, year-on-year) in Kazakhstan was reported at 30.94 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Kazakhstan - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

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.

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.

The average for 2021 based on 87 countries was 32.21 percent. The highest value was in Venezuela: 991.39 percent and the lowest value was in Botswana: -6.38 percent. The indicator is available from 1984 to 2021. Below is a chart for all countries where data are available.

Stock market return (%, year-on-year) in Jamaica was reported at 1.4322 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Jamaica - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

The Dow Jones Industrial Average (DJIA) index dropped around ***** points in the four weeks from February 12 to March 11, 2020, but has since recovered and peaked at ********* points as of November 24, 2024. In February 2020 - just prior to the global coronavirus (COVID-19) pandemic, the DJIA index stood at a little over ****** points. U.S. markets suffer as virus spreads The COVID-19 pandemic triggered a turbulent period for stock markets – the S&P 500 and Nasdaq Composite also recorded dramatic drops. At the start of February, some analysts remained optimistic that the outbreak would ease. However, the increased spread of the virus started to hit investor confidence, prompting a record plunge in the stock markets. The Dow dropped by more than ***** points in the week from February 21 to February 28, which was a fall of **** percent – its worst percentage loss in a week since October 2008. Stock markets offer valuable economic insights The Dow Jones Industrial Average is a stock market index that monitors the share prices of the 30 largest companies in the United States. By studying the performance of the listed companies, analysts can gauge the strength of the domestic economy. If investors are confident in a company’s future, they will buy its stocks. The uncertainty of the coronavirus sparked fears of an economic crisis, and many traders decided that investment during the pandemic was too risky.

Stock market return (%, year-on-year) in United States was reported at 32.65 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. United States - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on June of 2025.

ABSTRACT The purpose of this article was to develop a new indicator to estimate the aggregate long-term expected return on stocks. There is not a widely used method to model directly the aggregated expected return of the stock market. Most current methods use indirect approaches. We developed a new indicator that does not need an econometric model to generate expected returns and provides an estimate of the long-term expected returns. The proposed methodology can be used to develop an indicator of future returns of the stock market similar to the yield-to-maturity used for bonds. We used a restricted one-stage constant-growth model - a variant of the residual income model (RIM) - whose main input is the duration of companies’ competitive advantage and cyclical adjusted real return on invested capital (ROIC) with a 10-year average. We used a new methodology to develop an indicator of the long-term expected return on the equity market at the aggregate level, considering the duration of the competitive advantage of companies. Our results showed a strong correlation between the estimated implied return on equity (IRE) of current stock prices and realized returns of the 10-year real total return of the index.

Aruba: Stock market return, percent: The latest value from is percent, unavailable from percent in . In comparison, the world average is 0.00 percent, based on data from countries. Historically, the average for Aruba from to is percent. The minimum value, percent, was reached in while the maximum of percent was recorded in .

Paraguay: Stock market return, percent: The latest value from is percent, unavailable from percent in . In comparison, the world average is 0.00 percent, based on data from countries. Historically, the average for Paraguay from to is percent. The minimum value, percent, was reached in while the maximum of percent was recorded in .

Stock market return (%, year-on-year) in Vietnam was reported at 46.82 % in 2021, according to the World Bank collection of development indicators, compiled from officially recognized sources. Vietnam - Stock market return (%, year-on-year) - actual values, historical data, forecasts and projections were sourced from the World Bank on July of 2025.

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

An In-depth Analysis of the S&P 500 Index: Performance, Composition, and Implications

Financial data:

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

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

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

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

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

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

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

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

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

• Data cleaning and preprocessing are essential before model training

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

In the illustrated period, Norges Bank Investment Management (NBIM) market returns exhibited fluctuations, hitting a peak value in 2008 at -23.3 percent, and reaching its lowest value in the subsequent year, 2009, at 25.6 percent. By 2023, the rate was reported at 7.4 percent.

Between March 4 and March 11, 2020, the S&P 500 index declined by ** percent, descending into a bear market. On March 12, 2020, the S&P 500 plunged *** percent, its steepest one-day fall since 1987. The index began to recover at the start of April and reached a peak in December 2021. As of December 29, 2024, the value of the S&P 500 stood at ******** points. Coronavirus sparks stock market chaos Stock markets plunged in the wake of the COVID-19 pandemic, with investors fearing its spread would destroy economic growth. Buoyed by figures that suggested cases were leveling off in China, investors were initially optimistic about the virus being contained. However, confidence in the market started to subside as the number of cases increased worldwide. Investors were deterred from buying stocks, and this was reflected in the markets – the values of the Dow Jones Industrial Average and the Nasdaq Composite also dived during the height of the crisis. What is a bear market? A bear market occurs when the value of a stock market suffers a prolonged decline of more than 20 percent over a period of at least 2 months. The COVID-19 pandemic caused severe concern and sent stock markets on a steep downward spiral. The S&P 500 achieved a record closing high of ***** on February 19, 2020. However, just over 3 weeks later, the market closed on *****, which represented a decline of around ** percent in only 16 sessions.

Belize: Stock market return, percent: The latest value from is percent, unavailable from percent in . In comparison, the world average is 0.00 percent, based on data from countries. Historically, the average for Belize from to is percent. The minimum value, percent, was reached in while the maximum of percent was recorded in .

High-Tech Companies on NASDAQ

Market Capitalization and Performance Metrics

By [source]

About this dataset

This dataset offers an insightful look into the performance of high-tech companies listed on the NASDAQ exchange in the United States. With information pertaining to over 8,000 companies in the electronics, computers, telecommunications, and biotechnology sectors, this is an incredibly useful source of insight for researchers, traders, investors and data scientists interested in acquiring information about these firms.

The dataset includes detailed variables such as stock symbols and names to provide quick identification of individual companies along with pricing changes and percentages from the previous day’s value as well as sector and industry breakdowns for comprehensive analysis. Other metrics like market capitalization values help to assess a firm’s relative size compared to competitors while share volume data can give a glimpse into how actively traded each company is. Additionally provided numbers include earnings per share breakdowns to gauge profits along with dividend pay date symbols for yield calculation purposes as well as beta values that further inform risk levels associated with investing in particular firms within this high-tech sector. Finally this dataset also collects any potential errors found amongst such extensive scrapes of company performance data giving users valuable reassurance no sensitive areas are missed when assessing various firms on an individual basis or all together as part of an overarching system

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How to use the dataset

This dataset is invaluable for researchers, traders, investors and data scientists who want to obtain the latest information about high-tech companies listed on the NASDAQ exchange in the United States. It contains data on more than 8,000 companies from a wide range of sectors such as electronics, computers, telecommunications, biotechnology and many more. In this guide we will learn how to use this dataset effectively.

Basics: The basics of working with this dataset include understanding various columns like symbol, name, price,pricing_changes, pricing_percentage_changes,sector,industry,market_cap,share_volume,earnings_per_share. Each column is further described below: - Symbol: This column gives you the stock symbol of the company. (String) - Name: This column gives you the name of the company. (String)
- Price: The current price of each stock given by symbol is mentioned here.(Float) - Pricing Changes: This represents change in stock price from previous day.(Float) - Pricing Percentage Changes :This provides percentage change in stock prices from previous day.(Float) - Sector : It give information about sector in which company belongs .(String). - Industry : Describe industry in which company lies.(string). - Market Capitalization : Give market capitalization .(String). - Share Volume : It refers to number share traded last 24 hrs.(Integer). - Earnings Per Share : It refer to earnings per share per Stock yearly divided by Dividend Yield ,Symbol Yield and Beta .It also involves Errors related with Data Set so errors specified here proviedes details regarding same if any errors occured while collecting data set or manipulation on it.. (float/string )

Advanced Use Cases: Now that we understand what each individual feature stands for it's time to delve deeper into optimizing returns using this data set as basis for our decision making processes such as selecting right portfolio formation techniques or selecting stocks wisely contrarian investment style etc. We can do a comparison using multiple factors like Current Price followed by Price Change percentage or Earnings feedback loop which would help us identify Potentially Undervalued investments both Short Term & Long Term ones at same time and We could dive into analysis showing Relationship between Price & Volumne across Sectors and

Research Ideas

• Analyzing stock trends - The dataset enables users to make informed decisions by tracking and analyzing changes in indicators such as price, sector, industry or market capitalization trends over time.
• Exploring correlations between different factors - By exploring the correlation between different factors such as pricing changes, earning per share or beta etc., it enables us to get a better understanding of how these elements influence each other and what implications it may have on our investments

Acknowledgements

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Learn more about Market Research Intellect's Return Filters Market Report, valued at USD 1.5 billion in 2024, and set to grow to USD 2.8 billion by 2033 with a CAGR of 8.5% (2026-2033).

Fiji South Pacific Stock Exchange: Index: SPX Total Return Index data was reported at 9,148.130 NA in Apr 2025. This records a decrease from the previous number of 9,158.830 NA for Mar 2025. Fiji South Pacific Stock Exchange: Index: SPX Total Return Index data is updated monthly, averaging 6,476.855 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 9,607.670 NA in Dec 2019 and a record low of 1,577.920 NA in Jan 2012. Fiji South Pacific Stock Exchange: Index: SPX Total Return Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s Fiji – Table FJ.EDI.SE: South Pacific Stock Exchange: Monthly.