Nasdaq Basic provides Best Bid and Offer and Last Sale information for all U.S. exchange-listed securities based on liquidity within the Nasdaq market center, as well as trades reported to the FINRA Trade Reporting Facility (TRF) operated in partnership with FINRA/Nasdaq TRF.

Need a cost-effective, real-time U.S. equity quote and trade solution? Nasdaq Basic is the leading exchange-provided alternative for real-time Best Bid and Offer and Last Sale information for all U.S. exchange-listed stocks. With Basic, investors access a proprietary data product that provides accuracy, liquidity, instrument coverage and accessibility with significant cost-savings.

Nasdaq Basic with NLS Plus is our most cost-effective solution for real-time US equities, offering the broadest coverage and added granularity—such as trade aggressor side—for a fraction of the cost of consolidated feed alternatives like SIP data.

This proprietary, consolidated data feed disseminates top-of-book (L1) data from every Nasdaq-operated venue and covers all US stocks and ETFs, including those listed on the NYSE, NYSE Arca, NYSE American, and Cboe exchanges. As the premium tier of Nasdaq's Basic product, it combines Nasdaq Last Sale (NLS) Plus and Nasdaq BBO (QBBO) to provide: - Best bid and offer (BBO) quotes for the Nasdaq stock market (XNAS), which are within 1% of the NBBO 99.22% of the time. - Tick-by-tick price and size for orders executed on Nasdaq (XNAS), Nasdaq BX (XBOS), and Nasdaq PSX (XPSX). - All off-exchange trades reported to FINRA/Nasdaq's Carteret and Chicago Trade Reporting Facilities (TRFs), which aggregate data from most of the 30 ATSs and account for approximately 45% to 49% of the average daily volume (ADV) in all exchange-listed securities.

With the addition of TRF data, Nasdaq Basic with NLS Plus captures the majority of the trading activity and liquidity within US equity markets. As of January 2025, this dataset represented 62.9% ADV, including both on-exchange and off-exchange trades.

This dataset is an ideal choice for market participants who need an accurate BBO but don't directly execute trades or display quotes for FINRA broker-dealer obligations. It also features substantially lower exchange license fees for real-time data compared to Nasdaq TotalView-ITCH, with pricing designed for distribution use cases and per-user rates that are reduced by more than 65%.

Real-time Nasdaq Basic with NLS Plus data is included with a Plus or Unlimited subscription through our Databento US Equities service. Historical data is available for usage-based rates or with any subscription. Visit our pricing page for more details.

Breadth of coverage: 11,595 products

Asset class(es): Equities

Origin: Directly captured at Equinix NY4 (Secaucus, NJ) with an FPGA-based network card and hardware timestamping. Synchronized to UTC with PTP.

Supported data encodings: DBN, CSV, JSON Learn more

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

Resolution: Immediate publication, nanosecond-resolution timestamps

United States NASDAQ: Index: Total Return: NASDAQ US Benchmark Basic Materials Index data was reported at 2,246.010 NA in Apr 2025. This records a decrease from the previous number of 2,299.500 NA for Mar 2025. United States NASDAQ: Index: Total Return: NASDAQ US Benchmark Basic Materials Index data is updated monthly, averaging 1,430.215 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 2,512.079 NA in Sep 2024 and a record low of 831.760 NA in May 2012. United States NASDAQ: Index: Total Return: NASDAQ US Benchmark Basic Materials 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: NASDAQ: Total Return: Monthly.

This statistic presents the total number of companies listed on the NASDAQ Composite Index in 1999 and 2013. It was found that at year end 2013 the index was composed of 2,472 companies. This was a drop from the figure in 1999 which reported a year end total of 4,715 component companies listed on the exchange.

United States NASDAQ: Index: NASDAQ US Benchmark Basic Resources Index data was reported at 1,047.510 NA in Apr 2025. This records a decrease from the previous number of 1,049.540 NA for Mar 2025. United States NASDAQ: Index: NASDAQ US Benchmark Basic Resources Index data is updated monthly, averaging 685.360 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 1,167.530 NA in Nov 2024 and a record low of 347.510 NA in Jan 2016. United States NASDAQ: Index: NASDAQ US Benchmark Basic Resources 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: NASDAQ: Monthly.

United States NASDAQ: Index: Total Return: NASDAQ US Benchmark Basic Resources Index data was reported at 1,378.090 NA in Apr 2025. This records a decrease from the previous number of 1,378.640 NA for Mar 2025. United States NASDAQ: Index: Total Return: NASDAQ US Benchmark Basic Resources Index data is updated monthly, averaging 746.670 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 1,525.660 NA in Nov 2024 and a record low of 386.380 NA in Jan 2016. United States NASDAQ: Index: Total Return: NASDAQ US Benchmark Basic Resources 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: NASDAQ: Total Return: Monthly.

This statistic presents the most common reasons for delisting from the NASDAQ stock exchange between 1999 and 2013. It was found that regulatory non-compliance was responsible for 17.4 percent of delistings from the exchange during the period.

United States NASDAQ: Index: NASDAQ US Benchmark Basic Materials Index data was reported at 1,685.630 NA in Apr 2025. This records a decrease from the previous number of 1,727.690 NA for Mar 2025. United States NASDAQ: Index: NASDAQ US Benchmark Basic Materials Index data is updated monthly, averaging 1,220.650 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 1,924.130 NA in Mar 2022 and a record low of 814.490 NA in May 2012. United States NASDAQ: Index: NASDAQ US Benchmark Basic Materials 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: NASDAQ: Monthly.

United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Basic Resources Index data was reported at 1,273.480 NA in Apr 2025. This records a decrease from the previous number of 1,274.570 NA for Mar 2025. United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Basic Resources Index data is updated monthly, averaging 731.480 NA from Dec 2012 (Median) to Apr 2025, with 149 observations. The data reached an all-time high of 1,412.700 NA in Nov 2024 and a record low of 377.590 NA in Jan 2016. United States NASDAQ: Index: Net Total Return: NASDAQ US Benchmark Basic Resources 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: NASDAQ: Net Total Return: Monthly.

The Dow Jones U.S. Basic Materials index is expected to experience moderate growth in the near term, with potential upside driven by increased demand for raw materials from expanding industries such as construction and manufacturing. However, geopolitical uncertainties and supply chain disruptions pose risks to the index's performance, potentially leading to price volatility and downward pressure.

This statistic presents the year-end closing values of the NASDAQ telecommunications index from 2010 to 2018. The value of NASDAQ telecommunications index amounted to 349 points in 2018.

Comprehensive collection of financial reports and documents for Basic-Fit N.V. (BFIT)

Based on the total number of companies listed, the Japan Exchange Group was the largest stock exchange operator in the world as of Janaury 2025, with 3,968 companies listed. Of these, only six were foreign companies, with the remaining being domestic. The stock exchange with the highest number of international companies at this time was the U.S. Nasdaq, with 871. However, despite only having the seventh-highest number of companies, the New York Stock Exchange has the highest market capitalization of any stock exchange operator.

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.

Dow Jones Basic Materials: Signs of a Rebound or a Relentless Decline?

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

The Dow Jones Industrial Average (DJIA) is a stock market index used to analyze trends in the stock market. While many economists prefer to use other, market-weighted indices (the DJIA is price-weighted) as they are perceived to be more representative of the overall market, the Dow Jones remains one of the most commonly-used indices today, and its longevity allows for historical events and long-term trends to be analyzed over extended periods of time. Average changes in yearly closing prices, for example, shows how markets developed year on year. Figures were more sporadic in early years, but the impact of major events can be observed throughout. For example, the occasions where a decrease of more than 25 percent was observed each coincided with a major recession; these include the Post-WWI Recession in 1920, the Great Depression in 1929, the Recession of 1937-38, the 1973-75 Recession, and the Great Recession in 2008.

Sweden Nasdaq Stockholm: Index: OMX Stockholm Basic Resources data was reported at 2,180.857 NA in Apr 2025. This records a decrease from the previous number of 2,297.043 NA for Mar 2025. Sweden Nasdaq Stockholm: Index: OMX Stockholm Basic Resources data is updated monthly, averaging 1,560.590 NA from Jan 2012 (Median) to Apr 2025, with 160 observations. The data reached an all-time high of 2,720.910 NA in Apr 2022 and a record low of 706.450 NA in Aug 2012. Sweden Nasdaq Stockholm: Index: OMX Stockholm Basic Resources data remains active status in CEIC and is reported by Exchange Data International Limited. The data is categorized under Global Database’s Sweden – Table SE.EDI.SE: Nasdaq Stockholm: 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.

Is IShares U.S. Basic Materials ETF Your Building Block?

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 the coronavirus spreads around the world, the impact on the Polish stock exchange is increasing. As of 4 March, the WIG20 index was at the level of 1,860.95 points. Since then, the index has been systematically decreasing, and it reached the level of 1,305.73 points on 12 March. The reason for the falls on the stock exchange is a coronavirus (COVID-19). Fear of the epidemic has been visible in the markets for three weeks. As of 27 March, WIG20 has lost over 31 percent since the beginning of the year. Most probably, the first quarter of 2020 will be the worst in the history of the index. Even worse than the end of the memorable 2008, when the financial crisis broke out. On June 29, WIG20 index reached the closing value of 1,769.47, which is a decrease of 17.70 percent compared to the beginning of 2020.

As of June 17, 2024, the most shorted stock was for, the American holographic technology services provider, MicroCloud Hologram Inc., with 66.64 percent of their total float having been shorted. This is a change from mid-January 2021, when video game retailed GameStop had an incredible 121.07 percent of their available shares in a short position. In effect this means that investors had 'borrowed' more shares (with a future promise to return them) than the total number of shares available for public trading. Owing to this behavior of professional investors, retail investors enacted a campaign to drive up the stock price of Gamestop, leading to losses of billions when investors had to repurchase the stock they had borrowed. At this time, a similar – but less effective – social media campaign was also carried out for the stock price of cinema operator AMC, and the price of silver. What is short selling? Short selling is essentially where an investor bets on a share price falling by: borrowing a number of shares selling these shares while the price is still high; purchasing the same number again once the price falls; then returning the borrowed shares at a profit. Of course, a profit will only be made if the share price does fall; should the share price rise the investor will then need to purchase the shares back at a higher price, and thus incur a loss. Short selling can lead to some very large profits in a short amount of time, with Tesla stock generating over one billion dollars in short sell profits during the first week of March 2020 alone, owing to the financial crash caused by the coronavirus (COVID-19) pandemic. However, owing to the short-term, opportunistic nature of short selling, these returns look less impressive when considered as net profits from short sell positions over the full year. The risks of short selling Short selling carries greater risks than traditional investments, and for this reason financial advisors often recommend against this strategy for ‘retail’ (i.e. non-professional) investors. The reason for this is that losses from short selling are potentially uncapped, whereas losses from traditional investments are limited to the initial cost. For example, if someone purchases 100 dollars of shares, the maximum they can lose is the 100 dollars the spent on those shares. However, say someone borrows 100 dollars of shares instead, betting on the price falling. If these shares are then sold for 100 dollars but the price subsequently rises, the losses could greatly exceed the initial investment should the price rise to, say, 500 dollars. The risks of short selling can be seen by looking again at Tesla, with the company causing the greatest losses over 2020 from short selling at over 40 billion U.S. dollars.