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 5 of 2025.

This statistic shows the stock price development of selected companies in the technology industry from January 6, 2020 to February 3, 2025. During this period, stock prices of most of the tech companies have increased. Out of all companies shown here, stock values of **** saw the most substantial increase between January and October 2020. In February 3, 2025, ***** stock prices increased more than others with over an increase of *** index points.

Technology One stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

The latest closing stock price for U-BX Technology as of June 27, 2025 is 2.81. An investor who bought $1,000 worth of U-BX Technology stock at the IPO in 2024 would have $-957 today, roughly -1 times their original investment - a -95.72% compound annual growth rate over 1 years. The all-time high U-BX Technology stock closing price was 548.80 on August 21, 2024. The U-BX Technology 52-week high stock price is 567.04, which is 20079.4% above the current share price. The U-BX Technology 52-week low stock price is 2.36, which is 16% below the current share price. The average U-BX Technology stock price for the last 52 weeks is 32.71. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

The latest closing stock price for Tactile Systems Technology as of June 20, 2025 is 9.97. An investor who bought $1,000 worth of Tactile Systems Technology stock at the IPO in 2016 would have $-100 today, roughly 0 times their original investment - a -1.17% compound annual growth rate over 9 years. The all-time high Tactile Systems Technology stock closing price was 76.29 on February 25, 2019. The Tactile Systems Technology 52-week high stock price is 21.10, which is 111.6% above the current share price. The Tactile Systems Technology 52-week low stock price is 8.61, which is 13.6% below the current share price. The average Tactile Systems Technology stock price for the last 52 weeks is 14.07. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

This dataset contains the historical stock prices of Google (GOOGL) from January 2020 to March 2025. The data was fetched from Yahoo Finance using Python’s yfinance library.

📈 Key Features:

Timeframe: January 2020 - March 2025 Stock Exchange: NASDAQ Data Source: Yahoo Finance File Format: CSV 👨‍💻 Potential Uses:

Stock price prediction using Machine Learning Time-series analysis Stock market trend visualization Algorithmic trading research 📢 Note: This dataset is for educational and research purposes only. It should not be used for actual trading.

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 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

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 October 2020, 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.

The latest closing stock price for TransAct Technologies as of June 30, 2025 is 3.66. An investor who bought $1,000 worth of TransAct Technologies stock at the IPO in 1996 would have $-182 today, roughly 0 times their original investment - a -0.69% compound annual growth rate over 29 years. The all-time high TransAct Technologies stock closing price was 25.26 on May 27, 2004. The TransAct Technologies 52-week high stock price is 5.11, which is 39.6% above the current share price. The TransAct Technologies 52-week low stock price is 3.12, which is 14.8% below the current share price. The average TransAct Technologies stock price for the last 52 weeks is 4.03. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

Cx Technology stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

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

This dataset provides a comprehensive view of daily stock prices and key financial metrics for some of the most prominent technology companies: Apple (AAPL), Microsoft (MSFT), Amazon (AMZN), Google (GOOGL), Tesla (TSLA), Meta (META), NVIDIA (NVDA), IBM (IBM), Oracle (ORCL), and Intel (INTC). Covering the period from January 1, 2020, to the present(08/08/2024), this dataset is ideal for financial analysis, stock market modeling, and trend analysis.

The data includes daily stock prices (Open, High, Low, Close, Adjusted Close, Volume) as well as additional financial metrics such as the Price-to-Earnings (P/E) ratio, Market Capitalization, Price/Sales Ratio, Price/Book Ratio, Dividend Yield, and more. These metrics provide a deeper insight into each company's financial health and market performance.

The dataset was collected using the yfinance library in Python, which pulls historical data from Yahoo Finance. This dataset is particularly useful for those interested in stock price prediction, portfolio analysis, and financial data visualization.

📈 Daily Historical Stock Price Data for GigaCloud Technology Inc. (2022–2025)

A clean, ready-to-use dataset containing daily stock prices for GigaCloud Technology Inc. from 2022-08-18 to 2025-05-28. This dataset is ideal for use in financial analysis, algorithmic trading, machine learning, and academic research.

  🗂️ Dataset Overview

Company: GigaCloud Technology Inc. Ticker Symbol: GCT Date Range: 2022-08-18 to 2025-05-28 Frequency: Daily Total Records: 696 rows (one… See the full description on the dataset page: https://huggingface.co/datasets/khaledxbenali/daily-historical-stock-price-data-for-gigacloud-technology-inc-20222025.

The latest closing stock price for Graphjet Technology as of June 02, 2025 is 0.10. An investor who bought $1,000 worth of Graphjet Technology stock at the IPO in 2022 would have $-990 today, roughly -1 times their original investment - a -78.17% compound annual growth rate over 3 years. The all-time high Graphjet Technology stock closing price was 12.49 on February 26, 2024. The Graphjet Technology 52-week high stock price is 6.60, which is 6500% above the current share price. The Graphjet Technology 52-week low stock price is 0.07, which is 30% below the current share price. The average Graphjet Technology stock price for the last 52 weeks is 1.81. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

Seagate Technology stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

Marvell Technology stock price, live market quote, shares value, historical data, intraday chart, earnings per share and news.

The latest closing stock price for ZW Data Action Technologies as of June 13, 2025 is 1.21. An investor who bought $1,000 worth of ZW Data Action Technologies stock at the IPO in 2007 would have $-976 today, roughly -1 times their original investment - a -18.68% compound annual growth rate over 18 years. The all-time high ZW Data Action Technologies stock closing price was 350.00 on January 04, 2010. The ZW Data Action Technologies 52-week high stock price is 4.53, which is 274.4% above the current share price. The ZW Data Action Technologies 52-week low stock price is 1.11, which is 8.3% below the current share price. The average ZW Data Action Technologies stock price for the last 52 weeks is 2.01. For more information on how our historical price data is adjusted see the Stock Price Adjustment Guide.

Context:- Amazon.com, Inc. is an American multinational technology company specializing in e-commerce, cloud computing, digital streaming, and artificial intelligence. Founded by Jeff Bezos in 1994, Amazon has grown into one of the world’s most valuable companies, revolutionizing online retail and cloud services through its Amazon Web Services (AWS) division.

As of March 2025 Amazon has a market cap of $2.249 Trillion USD. This makes Amazon the world's 4th most valuable company by market cap according to our data. The market capitalization, commonly called market cap, is the total market value of a publicly traded company's outstanding shares and is commonly used to measure how much a company is worth.

Content:- This dataset covers Amazon’s daily stock price data from 2000 to 2025. It includes information on: https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F14466026%2F5453b54c1a5488a995b51a5f3b23fd84%2FStock%20dataset%20variables.jpg?generation=1740822549719886&alt=media" alt="">

Time-period: 2000–2025

Acknowlegements This dataset belongs to me.I'm sharing it here for free.You may do with it as you wish.

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