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  • US Stock & Options Historical Data, in Plain CSV

    One-time purchase, delivered as CSV/ZIP files, yours to keep. No API, no subscription, no lock-in.

    Files for research, not a live feed

    These datasets are built for offline research and repeatable backtests: local CSV/ZIP archives you can version, reload into Python, R, Excel, DuckDB, or your backtesting framework, and rerun without API quotas or subscription rules. HistoricalData.net is not a real-time market-data feed, not tick-level trade or quote data, and not a fundamentals database.

    How purchase and delivery work

    1. Open the stock or options product page and review the coverage, fields, samples, limitations, and checkout options.
    2. Download a free sample and, for stocks, check ticker coverage before checkout.
    3. Pay by card through Stripe.
    4. Receive a secure download link on the confirmation page and by email.

    Frequently asked questions

    What data can I download?

    Daily and 1-minute OHLCV stock bars for U.S. listed and delisted tickers, plus end-of-day U.S. options data with bid/ask, volume, open interest, Greeks, implied volatility, and underlying prices where available.

    Is this a subscription or an API?

    For stock and long-range options archives, it is a downloadable file product purchased through Stripe. HistoricalData.net also provides public metadata endpoints for coverage lookup, but it does not sell a real-time feed or tick-level trading API.

    Does the stock archive include delisted stocks?

    Yes. Delisted ticker records are included so researchers can build backtests that are less exposed to survivorship bias.

    Can I try before buying?

    Yes. Free stock and options sample files are available so you can verify the CSV structure and data fields first.

    How fresh is the data?

    The stock bundle is rebuilt every Saturday (U.S. Eastern). The options data is updated every U.S. trading day, typically available by about 5:30 pm ET. Check the product pages and public status endpoint for current dataset freshness.

    Read the full FAQ

    Machine-readable resources

    Coverage and freshness metadata: /api/status · /api/catalog · /api/symbol/{ticker}. Docs for AI agents and developers: API/MCP reference · OpenAPI spec · llms.txt.

    Start with the dataset that matches your research

    Use samples and coverage lookup first, then choose the archive you need for local analysis.

    Stock data page Options data page

    Methodology · Data quality