FinFeedAPI provides equity market data covering over 11,000 symbols, featuring historical T+1 data with an unlimited loopback period. We deliver everything from detailed trade records and multiple levels of order book depth (Level 1-3) to crucial regulatory and system messages.

Our data is engineered for performance, featuring nano-second precision timestamps. This ensures a competitive edge for high-frequency trading by enabling fair, accurate, and auditable transaction sequencing, critical for regulatory compliance. Access comprehensive equity market intelligence directly through our robust API offerings.

Why FinFeedAPI?

Market Coverage & Data Depth: - Historical Data: T+1 data on 11K+ symbols with unlimited historical lookback. - Trade Feeds: Detailed trade records including timestamps, sizes, prices, and conditions (e.g., odd lot, intermarket sweep, extended hours). - Level 1 Quotes: Best bid/ask prices, sizes, and timestamps. - Level 2 Price Book: Market depth with multiple bid/ask prices and aggregate order sizes. - Level 3 Order Book: The complete order book detailing individual orders.

Essential Messages: - Admin Messages: Trading status, official open/close prices, auction states, short sale restrictions, retail liquidity indicators, security directory. - System Events: Exchange-level notifications for key trading session phases.

Precision & Reliability: - Nano-second Timestamps: Ensuring fair, accurate, and auditable transaction sequencing for HFT and compliance. - Institutional Trust: Relied upon by financial institutions for dependable equity market information.

Financial institutions and trading firms rely on FinFeedAPI for mission-critical equity market intelligence. We are committed to delivering clean, precise, and comprehensive data when it matters most. If you require dependable and granular stock market data, FinFeedAPI provides the actionable insights you need.

Databento provides the industry’s fastest cloud-based solutions for intraday and real-time tick data. First to deliver full L3 (MBO) over internet.

Access L2 market data with Databento's market by price (MBP-10) schema, which aggregates book depth by price and includes every order across the top ten price levels.

Access L3 market data with Databento's market-by-order (MBO) schema, which provides full order book depth, including every order at every price level, tick-by-tick with accurate queue position.

NYSE Integrated is a proprietary data feed that disseminates full order book updates from the New York Stock Exchange (XNYS). It delivers every quote and order at each price level, along with any event that updates the order book after an order is placed, such as trade executions, modifications, or cancellations.

NYSE is the leading venue for listing blue-chip companies and large-cap stocks. Powered by NYSE's Pillar platform, its hybrid market model of floor-based auction and electronic trading allows it to capture a significant portion of trading activity during the US equity market open and close. As of January 2025, the NYSE represented approximately 6.31% of the average daily volume (ADV) across all exchange-listed US securities, including those listed on Nasdaq, other NYSE venues, and Cboe exchanges.

NYSE is also the only exchange to offer Designated Market Maker (DMM) privileges, allowing the floor to send D-Quote Orders, short for Discretionary Orders, throughout the day. Most D-Quote Orders execute in the closing auction, where they're known as Closing D Orders and allow traders to access the NYSE closing auction after 3:50 PM. This creates significant price discovery during the NYSE Closing Auction, where interest represented via the floor contributes more than 40% of total volume.

NYSE is also unique for being the only exchange with a Parity/Priority Allocation model for matching. This resembles a mixed FIFO and pro-rata matching algorithm, where the participant who sets the best price is matched first, and then the remaining shares are allocated to other orders entered by floor brokers at that price (parity allocation). Floor brokers may utilize e-Quotes to to receive such parity allocation of incoming executions.

With L3 granularity, NYSE Integrated captures information beyond the L1, top-of-book data available through SIP feeds, enabling accurate modeling of the book imbalances, queue dynamics, and the auction process. This data includes explicit trade aggressor side, odd lots, and imbalances. Auction imbalances offer valuable insights into NYSE’s opening and closing auctions by providing details like imbalance quantity, paired quantity, imbalance reference price, and book clearing price.

Historical data is available for usage-based rates or with any Databento US Equities subscription. Visit our pricing page for more details or to upgrade your plan.

Asset class: 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: MBO, MBP-1, MBP-10, TBBO, Trades, BBO-1s, BBO-1m, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Imbalance, Statistics, Status (Learn more)

Resolution: Immediate publication, nanosecond-resolution timestamps

United Kingdom's main stock market index, the GB100, fell to 8941 points on July 11, 2025, losing 0.38% from the previous session. Over the past month, the index has climbed 0.63% and is up 8.34% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from United Kingdom. United Kingdom Stock Market Index (GB100) - values, historical data, forecasts and news - updated 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.

It is forecast that in 2025, some ** percent of all vehicles sold globally will have Level 2 autonomy or higher. Almost every second vehicle sold worldwide will be a Level 2 entry autonomous vehicle (AV). Level 2 advanced and Level 3 highway pilot AV sales will account for around ** and * percent of total vehicle sales, respectively.In 2030, roughly the same share of new vehicles sold worldwide will have Level 2 autonomy or higher as in 2025. It is projected, however, that in 2030 vehicles with more advanced autonomous-driving features will start penetrating the market.

Get Nasdaq real-time and historical data with support for fast market replay at over 19 million book updates per second. Test our data for free with only 4 lines of code.

Nasdaq TotalView-ITCH is a proprietary data feed that disseminates full order book depth and last sale data from the Nasdaq stock market (XNAS). It delivers every quote and order at each price level, along with any event that updates the order book after an order is placed, such as trade executions, modifications, or cancellations. Nasdaq is the most active US equity exchange by volume and represented 13.03% of the average daily volume (ADV) as of January 2025.

With its L3 granularity, Nasdaq TotalView-ITCH captures information beyond the L1, top-of-book data available through SIP feeds and enables more accurate modeling of book imbalances, trade directionality, quote lifetimes, and more. This includes explicit trade aggressor side, odd lots, auction imbalance data, and the Net Order Imbalance Indicator (NOII) for the Nasdaq Opening and Closing Crosses and Nasdaq IPO/Halt Cross—the best predictor of Nasdaq opening and closing prices available. Other key advantages of Nasdaq TotalView-ITCH over SIP data include faster real-time dissemination and precise exchange-side timestamping directly from Nasdaq.

Real-time Nasdaq TotalView-ITCH 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 or to upgrade your plan.

Breadth of coverage: 20,329 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: MBO, MBP-1, MBP-10, BBO-1s, BBO-1m, TBBO, Trades, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, Definition, Statistics, Status, Imbalance Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

The value of the DJIA index amounted to ********* at the end of March 2025, up from ********* at the end of March 2020. Global panic about the coronavirus epidemic caused the drop in March 2020, which was the worst drop since the collapse of Lehman Brothers in 2008. Dow Jones Industrial Average index – additional information The Dow Jones Industrial Average index is a price-weighted average of 30 of the largest American publicly traded companies on New York Stock Exchange and NASDAQ, and includes companies like Goldman Sachs, IBM and Walt Disney. This index is considered to be a barometer of the state of the American economy. DJIA index was created in 1986 by Charles Dow. Along with the NASDAQ 100 and S&P 500 indices, it is amongst the most well-known and used stock indexes in the world. The year that the 2018 financial crisis unfolded was one of the worst years of the Dow. It was also in 2008 that some of the largest ever recorded losses of the Dow Jones Index based on single-day points were registered. On September 29, 2008, for instance, the Dow had a loss of ****** points, one of the largest single-day losses of all times. The best years in the history of the index still are 1915, when the index value increased by ***** percent in one year, and 1933, year when the index registered a growth of ***** percent.

Canada's main stock market index, the TSX, fell to 27023 points on July 11, 2025, losing 0.22% from the previous session. Over the past month, the index has climbed 1.53% and is up 19.18% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from Canada. Canada Stock Market Index (TSX) - values, historical data, forecasts and news - updated on July of 2025.

India's main stock market index, the SENSEX, fell to 82500 points on July 11, 2025, losing 0.83% from the previous session. Over the past month, the index has climbed 0.99% and is up 2.46% compared to the same time last year, according to trading on a contract for difference (CFD) that tracks this benchmark index from India. BSE SENSEX Stock Market Index - values, historical data, forecasts and news - updated on July of 2025.

The Australian Securities Exchange (ASX) was established in July 2006 after the Australian Stock Exchange merged with the Sydney Futures Exchange, making it one of the top 20 global exchange groups by market capitalization. ASX facilitates trading in leading stocks, ETFs, derivatives, fixed income, commodities, and energy, commanding over 80% of the market share in the Australian Cash Market, with the S&P/ASX 200 as its main index. We offer comprehensive real-time market information services for all instruments in the ASX Level 1 and Level 2 (full market depth) products, and also provide Level 1 data as a delayed service. You can access this data through various means tailored to your specific needs and workflows, whether for trading via electronic low latency datafeeds, using our desktop services equipped with advanced analytical tools, or through our end-of-day valuation and risk management products.

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.

Analysis of ‘Monthly Stock Evolution of the Strategic Reserve of DM and PPE ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/5f4dc7a9454ae3205a47944b on 13 January 2022.

--- Dataset description provided by original source is as follows ---

Monitoring the monthly evolution of the centrally existing Strategic Reserve stock of medical devices (DM) and personal protective equipment (PPE). The quantities referred to in the data set shall relate to the difference between the total entries and the total number of departures occurring up to the last day of each month.

Article 263-A of Law 27-A/2020 determines the establishment of a strategic reserve of medicines and devices, as well as the public availability of this information.

Order No 8057/2020 of 13 August 2020 details, in particular in paragraph 6, the public disclosure with monthly updates and reference to the distribution on the national territory of the data from the strategic reserve.

This data set is part of that monitoring, concerning the stock of medical devices and personal protective equipment of the Strategic Reserve.

Remarks:

• Stocks include acquisitions at central level and also donations;
• Data may be subject to change.

--- Original source retains full ownership of the source dataset ---

Tweet Sentiment's Impact on Stock Returns

862,231 Labeled Instances

By [source]

About this dataset

This dataset contains 862,231 labeled tweets and associated stock returns, providing a comprehensive look into the impact of social media on company-level stock market performance. For each tweet, researchers have extracted data such as the date of the tweet and its associated stock symbol, along with metrics such as last price and various returns (1-day return, 2-day return, 3-day return, 7-day return). Also recorded are volatility scores for both 10 day intervals and 30 day intervals. Finally, sentiment scores from both Long Short - Term Memory (LSTM) and TextBlob models have been included to quantify the overall tone in which these messages were delivered. With this dataset you will be able to explore how tweets can affect a company's share prices both short term and long term by leveraging all of these data points for analysis!

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How to use the dataset

In order to use this dataset, users can utilize descriptive statistics such as histograms or regression techniques to establish relationships between tweet content & sentiment with corresponding stock return data points such as 1-day & 7-day returns measurements.

The primary fields used for analysis include Tweet Text (TWEET), Stock symbol (STOCK), Date (DATE), Closing Price at the time of Tweet (LAST_PRICE) a range of Volatility measures 10 day Volatility(VOLATILITY_10D)and 30 day Volatility(VOLATILITY_30D ) for each Stock which capture changes in market fluctuation during different periods around when Twitter reactions occur. Additionally Sentiment Polarity analysis undertaken via two Machine learning algorithms LSTM Polarity(LSTM_POLARITY)and Textblob polarity provide insight into whether people are expressing positive or negative sentiments about each company at given times which again could influence thereby potentially influence Stock Prices over shorter term periods like 1-Day Returns(1_DAY_RETURN),2-Day Returns(2_DAY_RETURN)or longer term horizon like 7 Day Returns*7DAY RETURNS*.Finally MENTION field indicates if names/acronyms associated with Companies were specifically mentioned in each Tweet or not which gives extra insight into whether company specific contexts were present within individual Tweets aka “Company Relevancy”

Research Ideas

• Analyzing the degree to which tweets can influence stock prices. By analyzing relationships between variables such as tweet sentiment and stock returns, correlations can be identified that could be used to inform investment decisions.
• Exploring natural language processing (NLP) models for predicting future market trends based on textual data such as tweets. Through testing and evaluating different text-based models using this dataset, better predictive models may emerge that can give investors advance warning of upcoming market shifts due to news or other events.
• Investigating the impact of different types of tweets (positive/negative, factual/opinionated) on stock prices over specific time frames. By studying correlations between the sentiment or nature of a tweet and its effect on stocks, insights may be gained into what sort of news or events have a greater impact on markets in general

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: reduced_dataset-release.csv | Column name | Description | |:----------------------|:-------------------------------------------------------------------------------------------------------| | TWEET | Text of the tweet. (String) | | STOCK | Company's stock mentioned in the tweet. (String) | | DATE | Date the tweet was posted. (Date) | | LAST_PRICE | Company's last price at the time of tweeting. (Float) ...

Analysis of ‘TESLA Stock Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/varpit94/tesla-stock-data-updated-till-28jun2021 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

What is TESLA?

Tesla, Inc. is an American electric vehicle and clean energy company based in Palo Alto, California. Tesla's current products include electric cars, battery energy storage from home to grid-scale, solar panels and solar roof tiles, as well as other related products and services.

Information about this dataset

This dataset provides historical data of TESLA INC. stock (TSLA). The data is available at a daily level. Currency is USD.

--- Original source retains full ownership of the source dataset ---

Extensive and dependable pricing information spanning the entire range of financial markets. Encompassing worldwide coverage from stock exchanges, trading platforms, indicative contributed prices, assessed valuations, expert third-party sources, and our enhanced data offerings. User-friendly request-response, bulk access, and tailored desktop interfaces to meet nearly any organizational or application data need. Worldwide, real-time, delayed streaming, intraday updates, and meticulously curated end-of-day pricing information.

Analysis of ‘CIP05 - Stock Levels in Industrial Production (1979-1990)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/80f446d5-ed68-42da-967a-ac6a83d327d0 on 11 January 2022.

--- Dataset description provided by original source is as follows ---

Stock Levels in Industrial Production (1979-1990)

--- Original source retains full ownership of the source dataset ---

Japan's main stock market index, the JP225, fell to 39432 points on July 14, 2025, losing 0.35% from the previous session. Over the past month, the index has climbed 2.93%, though it remains 4.47% lower than a year ago, according to trading on a contract for difference (CFD) that tracks this benchmark index from Japan. Japan Stock Market Index (JP225) - values, historical data, forecasts and news - updated on July of 2025.

Analysis of ‘CIP12 - Stock Levels in Industrial Production (1979-1990)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/7b9cfdf1-b90a-43d9-84d8-143ed2c7a044 on 16 January 2022.

--- Dataset description provided by original source is as follows ---

Stock Levels in Industrial Production (1979-1990)

--- Original source retains full ownership of the source dataset ---