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US Equities Trade and Quote Minute Bar

GET 
/api/v1/data/us-equity/eq-taq-1min/:ticker

The U.S. Equities Trade and Quote Minute Bar dataset provides a minute-by-minute analytical view of U.S. equity market activity, derived from consolidated trade and quote (TAQ) data. Each one-minute bar contains approximately 60 calculated metrics, summarizing intraday price behavior, quote dynamics, and trading activity. In addition to standard Open, High, Low, Close, and Volume (OHLCV) measures, the dataset includes market microstructure indicators such as trade classification at bid/mid/ask, uptick and downtick statistics, bid-ask spread measures, and time-weighted bid and ask metrics. These features support intraday liquidity analysis, signal development, and short-horizon market studies without the complexity of tick-level data. The dataset uses a continuous minute-bar timeline. When no qualifying trade or quote updates occur during a given minute, the most recent bid and ask values are carried forward, ensuring a complete, gap-free time series that simplifies downstream joins and modeling. Data is derived from Equity Securities Information Processor (SIP) feeds and includes all eligible trades and top-of-book quotes, including off-exchange trades reported to FINRA Trade Reporting Facilities (TRF). Coverage spans all U.S. public-traded equity issue types, including common and preferred stocks, ETFs, ETNs, ADRs, warrants, and units.

For more details, please refer to the dataset documentation: US Equities Trade and Quote Minute Bar Guide (algoseek and Excluding FINRA TRF aggregation logic).

Aggregation Logic Options​

This dataset is available with different aggregation logic variants, which may affect how certain data fields are calculated.

algoseek​

algoseek core team comes from a high-frequency background and uses accepted de facto standards for calculating OHLC bars. See documentation for details on included/excluded fields.

Excluding FINRA TRF​

Excludes all trades that are done off the public ("lit") exchanges.  These trades from dark pools, internal crossing, OTC deals, etc.  These are trades that are not normally possible to participate in, so they can skew the backtesting if Client is only executing on public exchanges. Removing these trades provides a more realistic view of actual trades taking place, but does lose insight into the whole market.

Advanced Filtering

You can provide one or multiple filter expressions based on the dataset's columns to narrow down the results. For example, StartDate.gt=2023-01-01&StartDate.lt=2023-12-31, Ticker=AAPL.

Please refer to the Advanced Filtering Guide for the extensive reference.

Request​

Responses​

JSON, CSV file, or gzip-compressed CSV file, depending on the value of response_format query parameter