United States New York Stock Exchange: Index: Utilities Select Sector Index data was reported at 799.500 NA in Apr 2025. This records an increase from the previous number of 799.140 NA for Mar 2025. United States New York Stock Exchange: Index: Utilities Select Sector Index data is updated monthly, averaging 585.900 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 834.850 NA in Nov 2024 and a record low of 375.130 NA in Aug 2013. United States New York Stock Exchange: Index: Utilities Select Sector 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: S&P: Monthly.

New York Stock Exchange: Index: S&P Consumer Staples Select Sector Index data was reported at 826.910 NA in Apr 2025. This records an increase from the previous number of 825.980 NA for Mar 2025. New York Stock Exchange: Index: S&P Consumer Staples Select Sector Index data is updated monthly, averaging 581.670 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 840.110 NA in Sep 2024 and a record low of 395.070 NA in Aug 2013. New York Stock Exchange: Index: S&P Consumer Staples Select Sector 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: S&P: Monthly.

Daily sample data for E-mini Energy Select Sector Index XAE timestamped in Chicago time

United States New York Stock Exchange: Index: S&P Communication Services Select Sector Index data was reported at 499.250 NA in Apr 2025. This records a decrease from the previous number of 504.840 NA for Mar 2025. United States New York Stock Exchange: Index: S&P Communication Services Select Sector Index data is updated monthly, averaging 256.660 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 535.040 NA in Jan 2025 and a record low of 128.980 NA in Aug 2013. United States New York Stock Exchange: Index: S&P Communication Services Select Sector 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: S&P: Monthly.

United States New York Stock Exchange: Index: S&P Energy Select Sector data was reported at 847.570 NA in Apr 2025. This records a decrease from the previous number of 984.570 NA for Mar 2025. United States New York Stock Exchange: Index: S&P Energy Select Sector data is updated monthly, averaging 735.960 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 1,005.670 NA in Jun 2014 and a record low of 300.330 NA in Oct 2020. United States New York Stock Exchange: Index: S&P Energy Select Sector 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: S&P: Monthly.

As of the first half of 2023, the price performance of FTSE 350 index was stagnant. The sector showing the best performance throughout the first half of 2023 was the construction and materials one, with a price increase of 30 percent.

United States New York Stock Exchange: Index: S&P Industrial Select Sector data was reported at 1,324.440 NA in Apr 2025. This records an increase from the previous number of 1,322.420 NA for Mar 2025. United States New York Stock Exchange: Index: S&P Industrial Select Sector data is updated monthly, averaging 763.060 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 1,446.730 NA in Nov 2024 and a record low of 439.570 NA in Aug 2013. United States New York Stock Exchange: Index: S&P Industrial Select Sector 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: S&P: Monthly.

United States New York Stock Exchange: Index: S&P Health Care Select Sector data was reported at 1,419.450 NA in Apr 2025. This records a decrease from the previous number of 1,476.000 NA for Mar 2025. United States New York Stock Exchange: Index: S&P Health Care Select Sector data is updated monthly, averaging 921.250 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 1,586.510 NA in Aug 2024 and a record low of 493.270 NA in Aug 2013. United States New York Stock Exchange: Index: S&P Health Care Select Sector 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: S&P: Monthly.

New York Stock Exchange: Index: Dow Jones US Select Sector: Health Care Providers Index data was reported at 27,844.910 NA in Apr 2025. This records a decrease from the previous number of 29,279.610 NA for Mar 2025. New York Stock Exchange: Index: Dow Jones US Select Sector: Health Care Providers Index data is updated monthly, averaging 19,608.350 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 32,324.470 NA in Aug 2024 and a record low of 9,141.580 NA in Aug 2013. New York Stock Exchange: Index: Dow Jones US Select Sector: Health Care Providers 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.

Graph and download economic data for Producer Price Index by Industry: Other Selected Services Less Trade, Transportation, and Warehousing Industries (PCUASTDSVASTDSV) from Dec 2006 to Jun 2025 about warehousing, trade, transportation, services, PPI, industry, inflation, price index, indexes, price, and USA.

Dow Jones U.S. Select Telecommunications index is expected to continue its upward trend in the near term. The index is currently trading near its all-time high, and there are several factors that could continue to support its rise. One factor is the strong performance of the technology sector, which is a major component of the index. Another factor is the increasing demand for telecommunications services as more and more people rely on the internet for work, entertainment, and communication. However, there are also some risks to consider. One risk is the possibility of a recession, which could lead to a decline in demand for telecommunications services. Another risk is the increasing competition from new entrants into the market.

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.

New York Stock Exchange: Index: Dow Jones US Select Sector: Investment Services Index data was reported at 24,611.120 NA in Apr 2025. This records an increase from the previous number of 24,491.610 NA for Mar 2025. New York Stock Exchange: Index: Dow Jones US Select Sector: Investment Services Index data is updated monthly, averaging 11,160.510 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 27,290.120 NA in Jan 2025 and a record low of 5,452.540 NA in Aug 2013. New York Stock Exchange: Index: Dow Jones US Select Sector: Investment Services 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 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.

Pharmaceuticals Sector Expected to See Moderate Growth, Dow Jones U.S. Select Pharmaceuticals Index Forecasts

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

Context

In this dataset you can find the Top 100 companies in the technology sector. You can also find 5 of the most important and used indices in the financial market as well as a list of all the companies in the S&P 500 index and in the technology sector.

The Global Industry Classification Standard also known as GICS is the primary financial industry standard for defining sector classifications. The Global Industry Classification Standard was developed by index providers MSCI and Standard and Poor’s. Its hierarchy begins with 11 sectors which can be further delineated to 24 industry groups, 69 industries, and 158 sub-industries.

You can read the definition of each sector here.

The 11 broad GICS sectors commonly used for sector breakdown reporting include the following: Energy, Materials, Industrials, Consumer Discretionary, Consumer Staples, Health Care, Financials, Information Technology, Telecommunication Services, Utilities and Real Estate.

In this case we will focuse in the Technology Sector. You can see all the sectors and industry groups here.

To determine which companies, correspond to the technology sector, we use Yahoo Finance, where we rank the companies according to their “Market Cap”. After having the list of the Top 100 best valued companies in the sector, we proceeded to download the historical data of each of the companies using the NASDAQ website.

Regarding to the indices, we searched various sources to find out which were the most used and determined that the 5 most frequently used indices are: Dow Jones Industrial Average (DJI), S&P 500 (SPX), NASDAQ Composite (IXIC), Wilshire 5000 Total Market Inde (W5000) and to specifically view the technology sector SPDR Select Sector Fund - Technology (XLK). Historical data for these indices was also obtained from the NASDQ website.

Content

In total there are 107 files in csv format. They are composed as follows:

• 100 files contain the historical data of tech companies.
• 5 files contain the historical data of the most used indices.
• 1 file contain the list of all the companies in the S&P 500 index.
• 1 file contain the list of all the companies in the technology sector.

Column Description

Every company and index file has the same structure with the same columns:

Date: It is the date on which the prices were recorded. High: Is the highest price at which a stock traded during the course of the trading day. Low: Is the lowest price at which a stock traded during the course of the trading day. Open: Is the price at which a stock started trading when the opening bell rang. Close: Is the last price at which a stock trades during a regular trading session. Volume: Is the number of shares that changed hands during a given day. Adj Close: The adjusted closing price factors in corporate actions, such as stock splits, dividends, and rights offerings.

The two other files have different columns names:

List of S&P 500 companies

Symbol: Ticker symbol of the company. Name: Name of the company. Sector: The sector to which the company belongs.

Technology Sector Companies List

Symbol: Ticker symbol of the company. Name: Name of the company. Price: Current price at which a stock can be purchased or sold. (11/24/20) Change: Net change is the difference between closing prices from one day to the next. % Change: Is the difference between closing prices from one day to the next in percentage. Volume: Is the number of shares that changed hands during a given day. Avg Vol: Is the daily average of the cumulative trading volume during the last three months. Market Cap (Billions): Is the total value of a company’s shares outstanding at a given moment in time. It is calculated by multiplying the number of shares outstanding by the price of a single share. PE Ratio: Is the ratio of a company's share (stock) price to the company's earnings per share. The ratio is used for valuing companies and to find out whether they are overvalued or undervalued.

Acknowledgements

SEC EDGAR | Company Filings NASDAQ | Historical Quotes Yahoo Finance | Technology Sector Wikipedia | List of S&P 500 companies S&P Dow Jones Indices | S&P 500 [S&P Dow Jones Indices | DJI](https://www.spglobal.com/spdji/en/i...

Browse Select Sector SPDR Trust (XLV) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

Supported market data schemas: MBP-1, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, TBBO, Trades, Statistics, Definition Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

Browse Select Sector SPDR Trust (XLE) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

Supported market data schemas: MBP-1, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, TBBO, Trades, Statistics, Definition Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

United States New York Stock Exchange: Index: Dow Jones US Select Sector: Aerospace & Defense Index data was reported at 39,709.750 NA in Apr 2025. This records an increase from the previous number of 38,749.690 NA for Mar 2025. United States New York Stock Exchange: Index: Dow Jones US Select Sector: Aerospace & Defense Index data is updated monthly, averaging 24,081.430 NA from Aug 2013 (Median) to Apr 2025, with 141 observations. The data reached an all-time high of 39,709.750 NA in Apr 2025 and a record low of 10,720.910 NA in Aug 2013. United States New York Stock Exchange: Index: Dow Jones US Select Sector: Aerospace & Defense 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.

United States - Producer Price Index by Industry: Selected Health Care Industries was 148.16600 Index Dec 2006=100 in May of 2025, according to the United States Federal Reserve. Historically, United States - Producer Price Index by Industry: Selected Health Care Industries reached a record high of 148.16600 in May of 2025 and a record low of 100.00000 in December of 2006. Trading Economics provides the current actual value, an historical data chart and related indicators for United States - Producer Price Index by Industry: Selected Health Care Industries - last updated from the United States Federal Reserve on July of 2025.

In general, the stock prices of the same industry have a similar trend, but those of different industries do not. When investing in stocks of different industries, one should select the optimal model from lots of trading models for each industry because any model may not be suitable for capturing the stock trends of all industries. However, the study has not been carried out at present. In this paper, firstly we select 424 S&P 500 index component stocks (SPICS) and 185 CSI 300 index component stocks (CSICS) as the research objects from 2010 to 2017, divide them into 9 industries such as finance and energy respectively. Secondly, we apply 12 widely used machine learning algorithms to generate stock trading signals in different industries and execute the back-testing based on the trading signals. Thirdly, we use a non-parametric statistical test to evaluate whether there are significant differences among the trading performance evaluation indicators (PEI) of different models in the same industry. Finally, we propose a series of rules to select the optimal models for stock investment of every industry. The analytical results on SPICS and CSICS show that we can find the optimal trading models for each industry based on the statistical tests and the rules. Most importantly, the PEI of the best algorithms can be significantly better than that of the benchmark index and “Buy and Hold” strategy. Therefore, the algorithms can be used for making profits from industry stock trading.