Prices for US 100 Tech Index including live quotes, historical charts and news. US 100 Tech Index was last updated by Trading Economics this July 14 of 2025.

Investors believed the stock price of two large U.S. tech companies in particular would grow by between 2020 and 2025. According to a survey conducted in ************, Tesla especially was believed to witness a stock growth. Nearly half of all respondents selected Tesla, close to double the number of respondents who selected the next-most popular option, Amazon. The source used a large definition of "tech", as the survey included companies that are active in different categories.

Prices for US Tech Composite Index including live quotes, historical charts and news. US Tech Composite Index was last updated by Trading Economics this July 13 of 2025.

Dow Jones U.S. Technology index is predicted to experience a moderate bullish trend with potential for notable gains. The index may face resistance around key technical levels, but overall sentiment remains positive with ample opportunities for investors seeking growth and diversification. However, investors should be aware of potential risks such as market volatility, geopolitical uncertainties, and changes in the technology sector.

This statistic presents a ranking of the market capitalization of selected U.S. tech and internet companies in 2006, and from 2014 to 2020. Apple's market cap soared from 461.41 billion U.S. dollars in 2014 to 1.53 trillion dollars in 2020. Apple's market cap pushed the company ahead of last year's leader Microsoft.

Public offerings of tech and internet companies

A public offering is the offering of securities of a company or a similar corporation to the public. Generally, the securities are to be listed on a stock exchange. The initial public offering (IPO) of a company occurs when a company offers its shares for the first time for public ownership and trading.

Hardware companies such as Apple or IBM have been traded publicly for a while but younger, online-based companies such as Google or most notably Facebook and most recently, Snap Inc. have been generating a lot of buzz surrounding their IPOs and subsequent stock prices. Facebook’s initial public offering was intensely hyped over months with projections of a 100 billion US dollar valuation but it dwindled down to a range of 60 to 75 billion US dollars prior to the listing.

Other tech stock performances have been more stable – both online retailer Amazon and search and digital advertising giant Google’s - now Alphabet's - shares have been on a more upwards trend. The most impressive development however came from Apple which totally changed its stock performance after the 2008 introduction of the iPhone. Since then, the company has been catapulted to the top of the smartphone market, multiplying its market capitalization as well as regularly being ranked as one of the most valuable brands worldwide.

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.

Tech Sector Outlook: Bullish Trend Expected for Dow Jones U.S. Technology Index.

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

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.

Tech Titans' Next Frontier?

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

As of May 23, 2025, Microsoft was the leading tech company by market capitalization globally at 3.38 trillion U.S. dollars. Nvidia ranked second at 3.24 trillion U.S. dollars. Tech company stocks were impacted through 2025 as a result of various global tariff threats by the United States government. Apple among the leaders Since its foundation in a Californian garage in 1976, Apple has expanded massively, becoming one of the most valuable companies in the world. The company started its origins in the PC industry with the Macintosh, but soon entered other segments of the consumer electronics market. Today, the iPhone is the most popular Apple product, although Mac, iPad, wearables, and services also contribute to its high revenues. Aiming at innovation, Apple invests every year in research and development, spanning a wide array of technologies from AI through to extended reality. Nvidia's immense growth With a focus that began with origins in gaming, Nvidia's business strategy has been transformed by demand from data centers that sit at the heart of the AI boom. The company's chips have been favored to support in the training and running of a range of large language models, most notably in the development of OpenAI's ChatGPT.

Graph and download economic data for NASDAQ 100 Index (NASDAQ100) from 1986-01-02 to 2025-07-10 about NASDAQ, stock market, indexes, and USA.

The NYSE U.S. Market Technology Sector Index tracks the performance of the U.S. domiciled equity components listed on the U.S. stock exchanges that offer goods and services in the technology sector. The statistics shows the monthly development of the NYSE U.S. Market Technology Sector Index from December 2015 to June 2023. During that time, the index increased steadily until December 2021. Since then, the NYSE U.S. Market Technology Index fluctuated and stood at ******** as of June 2023.

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.

Will Tech Remain the King? The Dow Jones U.S. Technology Index

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

Graph and download economic data for NASDAQ Composite Index (NASDAQCOM) from 1971-02-05 to 2025-07-10 about NASDAQ, composite, stock market, indexes, and USA.

New York Stock Exchange: Index: Dow Jones US Large Cap Technology Index data was reported at 6,045.360 NA in Apr 2025. This records an increase from the previous number of 6,005.530 NA for Mar 2025. New York Stock Exchange: Index: Dow Jones US Large Cap Technology Index data is updated monthly, averaging 6,432.785 NA from Mar 2024 (Median) to Apr 2025, with 14 observations. The data reached an all-time high of 6,918.630 NA in Dec 2024 and a record low of 5,424.010 NA in Apr 2024. New York Stock Exchange: Index: Dow Jones US Large Cap Technology Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: Dow Jones: Monthly.

As of Janaury 2025, the New York Stock Exchange (NYSE) and the Nasdaq - the two largest stock exchange operators in the United States - held a combined market capitalization for domestic listed companies of over ** trillion U.S. dollars. Both markets were almost evenly sized at this point in time - at approximately ** and ** trillion U.S. dollars, respectively. However, the Nasdaq has grown much quicker than the NYSE since January 2018, when their respective domestic market caps were ** and ** trillion U.S. dollars. Much of this can be attributed to the success of information technology stocks during the global coronavirus (COVID-19) pandemic, as the Nasdaq is the traditional venue for companies operating in the tech sector.

United States New York Stock Exchange: Index: Dow Jones US Technology Index data was reported at 6,729.270 NA in Feb 2025. This records a decrease from the previous number of 6,970.130 NA for Jan 2025. United States New York Stock Exchange: Index: Dow Jones US Technology Index data is updated monthly, averaging 2,038.820 NA from Aug 2013 (Median) to Feb 2025, with 139 observations. The data reached an all-time high of 6,979.640 NA in Dec 2024 and a record low of 788.170 NA in Aug 2013. United States New York Stock Exchange: Index: Dow Jones US Technology Index data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s United States – Table US.EDI.SE: New York Stock Exchange: Dow Jones: Monthly.

This statistic presents the returns of the S&P 500 Information Technology Index in the United States from 2007 to 2023. The IT sector had its worst year in 2008, where it lost **** percent of its value. After three years of value gain, it lost **** percent of its value in 2022. On the contrary, 2023 witnessed the second-highest value gain during this period, reaching **** percent.

The US stock market declined as Nvidia shares dropped, affecting major indices. Investors are cautious ahead of the Federal Reserve's policy meeting.

The annual returns of the Nasdaq 100 Index from 1986 to 2024. fluctuated significantly throughout the period considered. The Nasdaq 100 index saw its lowest performance in 2008, with a return rate of ****** percent, while the largest returns were registered in 1999, at ****** percent. As of June 11, 2024, the rate of return of Nasdaq 100 Index stood at ** percent. The Nasdaq 100 is a stock market index comprised of the 100 largest and most actively traded non-financial companies listed on the Nasdaq stock exchange. How has the Nasdaq 100 evolved over years? The Nasdaq 100, which was previously heavily influenced by tech companies during the dot-com boom, has undergone significant diversification. Today, it represents a broader range of high-growth, non-financial companies across sectors like consumer services and healthcare, reflecting the evolving landscape of the global economy. The annual development of the Nasdaq 100 recently has generally been positive, except for 2022, when the NASDAQ experienced a decline due to worries about escalating inflation, interest rates, and regulatory challenges. What are the leading companies on Nasdaq 100? In August 2023, ***** was the largest company on the Nasdaq 100, with a market capitalization of **** trillion euros. Also, ****************************************** were among the five leading companies included in the index. Market capitalization is one of the most common ways of measuring how big a company is in the financial markets. It is calculated by multiplying the total number of outstanding shares by the current market price.

Context

Stock market data -- and particularly intraday price data -- can be very expensive to buy. To help more people gain access to it, here I provide daily as well as intraday price and volume data for all U.S.-based stocks and ETFs trading on the NYSE, NASDAQ, and NYSE MKT.

Content

The dataset (last updated 12/06/2017) is presented in CSV format as follows:

• Intraday data: Date,Time,Open,High,Low,Close,Volume,OpenInt

• Daily data: Date,Open,High,Low,Close,Volume,OpenInt

Acknowledgements

The dataset belongs to me. I’m sharing it here for free. You may do with it as you wish.

Inspiration

Many have tried, but most have failed, to predict the stock market's ups and downs. Can you do any better?

Graph and download economic data for Quarterly Financial Report: U.S. Corporations: Management and Technical Consulting Services: Capital Stock and Other Capital (Less Treasury Stock) (QFRD326546USNO) from Q4 2009 to Q1 2025 about legal, management, stocks, professional, finance, capital, Treasury, corporate, services, industry, and USA.