The best choice for those looking for license-free US market data for commercial use is US Equities Basic, which includes data display, redistribution, professional trading, and more.

US Equities Basic is based upon a derived IEX feed. The volume coverage is 3-5% of the total trading volume in North America, which helps entities mitigate license expenses and start with real-time data.

US Equities Basic provides raw quotes, trades, aggregated time series (OHLCV), and snapshots. Both REST API and WebSocket API are available.

End-of-day price information disseminated after 12:00 AM EST does not require licensing in the United States by law. This applies to all exchanges, even those not included in the US Equities Basic. Finazon combines all price information after every trading day, meaning that while markets are open, real-time prices are available from a subset of exchanges, and when markets close, data is synced and contains 100% of US volume. All historical prices are adjusted for corporate actions and splits.

Tip: Individuals with non-professional usage are not required to get exchange licenses for real-time data and, hence, are better off with the US Equities Max dataset.

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.

API Crude Oil Stock Change in the United States increased to 3.52 BBL/1Million in October 10 from 2.78 BBL/1Million in the previous week. This dataset provides - United States API Crude Oil Stock Change- actual values, historical data, forecast, chart, statistics, economic calendar and news.

Context

This data set consists of >1 year of historical data about the number of users that hold each stock available on the Robinhood stock brokerage. It is the dataset that powers https://robintrack.net/

Content

Data was collected from the Robinhood API once per hour over the entire period.

The popularity metric represents the number of unique accounts that hold at least one share of the asset. This only includes normal, long shares (not options).

Acknowledgements

Robinhood provides their popularity data publicly, which I feel is a great step in the right direction for an industry (finance) where data has traditionally been expensive, low-quality, and hard to find. I feel it's only right that I share this historical popularity data freely as well.

Caveats + Possible Issues

Robinhood gives free shares of a certain set of stocks as rewards to users for referring others to their platform. Some of the most popular stocks are at the top because of this.

The popularity metrics change over weekends and when the market is closed due to the fact that Robinhood accounts can be created/closed/transferred over those periods. The metric reported at each timestamp is the exact value that the Robinhood API reported at that instant.

Inspiration

This data can be used as a measure of retail sentiment. By seeing what traders do in response to changes in price and different news events, it can be determined if retail traders are "buying the dip" or panicking and leaving the market.

I didn't include price data due to possible legal limitations. However, it should be relatively easy to obtain this data yourself from a different source and combine it with this data set.

Access LSEG's London Stock Exchange (LSE) Market Data, and find benchmarks, indices, and real-time and historic market information.

The Real-time Candlestick OHLC API provides current candlestick data that covers all major stock exchanges including NYSE, NASDAQ, LSE, Euronext to NSE of India, TSE, and a few more. Users can choose from candlestick data with 1 min, 2 min, 5 min, 15 min, 30 min, 1 hour, 4 hour, 1 day, 1 week, 1 month and 1 year interval. By using the real-time candlestick OHLC data, they can visualize data on candlestick charts and build financial products.

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team use quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, United Kingdom, Europe

When there is a vast variety of metrics and tools available to gain market insight, Insider trading offers valuable clues to investors related to future share performance. We at Smart Insider provide global insider trading data and analysis on share transactions made by directors & senior staff in the shares of their own companies.

Monitoring all the insider trading activity is a huge task, we identify 'Smart Insiders' through specialist desktop and quantitative feeds that enable our clients to generate alpha.

Our experienced analyst team uses quantitative and qualitative methods to identify the stocks most likely to outperform based on deep analysis of insider trades, and the insiders themselves. Using our easy-to-read derived data we help our clients better understand insider transactions activity to make informed investment decisions.

We provide full customization of reports delivered by desktop, through feeds, or alerts. Our quant clients can receive data in a variety of formats such as XML, XLSX or API via SFTP or Snowflake.

Sample dataset for Desktop Service has been provided with some proprietary fields concealed. Upon request, we can provide a detailed Quant sample.

Tags: Stock Market Data, Equity Market Data, Insider Transactions Data, Insider Trading Intelligence, Trading Data, Investment Management, Alternative Investment, Asset Management, Equity Research, Market Analysis, Africa

Real-time commodities pricing data allows you to grasp where the market is, was and will be – from exchange data and OTC prices to specialist fundamentals.

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.

API Group Soaring: (APG) Stock Forecast

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 CBOE Volatility Index: VIX (VIXCLS) from 1990-01-02 to 2025-10-16 about VIX, volatility, stock market, and USA.

EDI now provides seven daily feeds, timed to international trading cycles at 03:30, 07:00, 09:00, 11:00, 13:00, 15:00, and 17:15 GMT/UTC, giving clients consistent, market-aligned data throughout the day.

The Worldwide Fixed Income (WFI) Service enables you to keep track of new bond issues or changes in terms and conditions for both corporate and government issuances. Data is sourced globally from stock exchanges, central banks, ministries of finance, lead managers, paying, calculation and transfer agents.

The fixed income data service cover 40 event types including redemption, conversion, defaults and contains static data outlining key terms and conditions and call schedules. EDI can provide you with pricing supplements, offering circulars, term sheets and prospectuses for as many securities as possible subject to availability. It covers approximately 30% of the Fixed Income database. Use cases: Bond Issuance Tracking | Portfolio Risk Management | Portfolio Valuation | Investment Management | Market Analysis

With the service you will have access to: -International debt securities in more than 150 countries A broad range of asset types including: -Convertibles -FRNs -Permanent interest bearing shares -Preferred securities -Treasury bills In addition, where possible we can extend both instruments and geographic coverage to fully cover your portfolio.

Originally in the equity space, Exchange Data International (EDI) moved to the Fixed Income arena following an increased demand from clients to add debt instruments to its coverage. As the firm was approached by a major credit rating agency to build a customised fixed income service, it developed its own Fixed Income service providing global coverage of the debt market. New countries and sources are continually researched and added to enhance geographic coverage and increase the volume of securities in the database. The service provides historical data back from 2007.

Asset Classes Fully covered: • Canadian strip packages without underlying • Cash management bills • Certificate of deposit (tenure more than 28 days) • Commercial papers (tenure more than 28 days) • Convertibles • Corporate bonds • Government bonds • Municipal securities • Short-term corporate Bonds • Short-term government Bonds • Strips (parent needed) • Treasury bills

Covered if in portfolio: • Asset-backed securities (ABS) (securities entered with critical fields and just covered for live • client’s portfolio and Canada; offering documents processed for live clients; corporate actions not maintained) • Certificates (just covered for live client’s portfolio) • Mortgage-backed securities (MBS) (securities entered with critical fields and just covered for live client’s portfolio and Canada, offering documents processed for live clients; corporate actions not maintained) • Musharaka Sukuks (securities entered with critical fields and just covered for live client’s Portfolio; offering documents processed for live clients; corporate actions not maintained) • Structured Products • Genussschein (AT, CH and DE) • Mortgage-pass through certificates • Pass-through certificates In addition, EDI provides a comprehensive global Fixed Income Corporate Action/Event service, to compliment the reference data, including security and issuer level events and distributions.

Explore LSEG's Equities Pricing Data, and gain global coverage of over 7 million securities, assets in over 200 exchanges and 20 years of price history.

Context

With the sole mission to democratize financial data, Finnhub is excited to release the new Financials as Reported dataset for bulk download. The data is cleaned and sourced directly from SEC filings from 2010-2020.

If you don't need bulk download, you can query this data for free on our website: https://finnhub.io/docs/api#financials-reported. We also provide various type of financial data such as global fundamentals, deep historical tick data, estimates and alternative data.

Finnhub Stock API https://finnhub.io/terms-of-service

Inspiration

Originally, I was planning to use the Python Quandl api to get the data from here because it is already conveniently in time-series format. However, the data is split by reporting agency which makes it difficult to get an accurate image of the true short ratio because of missing data/difficulty in aggregation. So, I clicked on the source link which turned out to be a gold mine because of their consolidated data. Only downside was that it was all in .txt format so I had to use regex to parse through and data scraping to get the information from the website but that was a good refresher 😄.

For better understanding of what the values in the text file mean, you can read this pdf from FINRA: https://www.finra.org/sites/default/files/2020-12/short-sale-volume-user-guide.pdf

Functionality

I condensed all the individual text files into a single .txt file such that it's much faster and less complex to write code compared to having to iterate through each individual .txt file. I created several functions for this dataset so please check out my workbook "FINRA Short Ratio functions" where I have described step by step on how I gathered the data and formatted it so that you can understand and modify them to fit your needs. Note that the data is only for the range of 1st April 2020 onwards (20200401 to 20210312 as of gathering the data) and the contents are separated by | delimiters so I used \D (non-digit) in regex to avoid confusion with the (a|b) pattern syntax.

If you need historical data before April 2020, you can use the quandl database but it has non-consolidated information and you have to make a reference call for each individual stock for each agency so you would need to manually input tickers or get a list of all tickers through regex of the txt files or something like that 😅.

Thoughts

An excellent task to combine regular expressions (regex), web scraping, plotting, and data wrangling... see my notebook for an example with annotated workflow. Please comment and feel free to fork and modify my workbook to change the functionality. Possibly the short volumes can be combined with p/b ratios or price data to see the correlation --> can use seaborn pairgrid to visualise this for multiple stocks?

View LSEG's extensive Economic Data, including content that allows the analysis and monitoring of national economies with historical and real-time series.

A table that shows the historical breakdown of the Debt Held by the Public, Intragovernmental Holdings and the Total Public Debt Outstanding.

National Stock Number extract includes the current listing of National Stock Numbers (NSNs) , NSN item name and descriptions, and current selling price of each product listed in GSA Advantage and managed by GSA. Each NSN is listed with the vendors description of the item. Some descriptions exceed the standard length and are truncated.

View LSEG's Lipper Fund Research Database, providing independent fund content to benchmark fund performance, manage risk, and more.

Access LSEG's London Metal Exchange (LME) Data, and find global reference prices and real-time and delayed data for industrial metals trading.