Recommended futures roll dates

Global Coverage

Tick Data provides historical intraday data for several asset types:


Trade and Quote data with Ticker Mapping® and corporate actions for all listed equities from:

  • U.S. Exchanges (all Consolidated Tape Association participants) from Jan-1-1993.
  • U.S. National Best Bid & Offer (NBBO) data from Jan-1-2004.
  • Toronto Stock Exchange from Jan-1-2001.
  • Brazil (BM&F BOVESPA) from May-7-2008.
  • Mexico (Bolsa Mexicana de Valores – BMV) from May-7-2008.
  • London Stock Exchange from Jan-1-2000.
  • Deutsche Boerse (Xetra) from Jan-1-2003.
  • Euronext (Amsterdam, Brussels, Lisbon & Paris) from Apr-1-2002.
  • Borsa Italiana from Jan-1-2004.
  • Bolsa de Madrid from Dec-1-2004.
  • SIX Swiss Exchange from Oct-17-2011.
  • NASDAQ OMX Nordic Exchange from Oct-21-2008.
  • Oslo Børs from Nov-9-2012.
  • Pan-Europe MTF venues (BATS, Chi-X, and Turquoise) from Oct-26-2009.
  • Korea Exchange (KRX) from May-7-2008.
  • Hong Kong (HKEx) from May-13-2008.
  • Australia Securities Exchange (ASX) from May-7-2008.
  • Japan (JPX (TSE & Osaka), Fukuoka Stock Exchange, Sapporo Stock Exchange and Hercules Market) from Oct-1-2008.

See our Equity Products page for more information.


Trade and quote data for 150+ futures symbols from exchanges in North America, South America, Europe, and Australia as far back as 1974.
See our Futures Data Products page for more information.


Trade and quote data for all listed U.S. equity and index options reported to the Options Price Reporting Authority (OPRA) from Jul-2-2004.
See our Options Data Products page for more information.


Level I Quote data for 2,000+ spot currency pairs from May-7-2008.
See our Forex Data Products page.

Cash Indices

Data for over 60 cash indices as far back as 1983.
See our Cash Index Data Products page.

Market Internal Indicators

Data for 16 market indicators from Jul-1-2003.
See our Market Indicator Data Products page.

Research-Quality Data

The industry’s most demanding consumers of historical market data choose Tick Data, LLC, because we provide the highest-quality historical data available in a fraction of the time, at a fraction of the cost it would take to build and maintain a comparable data set on their own. Data quality is absolutely critical for our clients. As you might imagine, the quality of our data is the result of a meticulous process:

Data Sources

We strongly believe that a research-quality historical dataset cannot be collected from a single real-time feed. Dropped data packets, feed outages, full buffers, network traffic, etc. are too common. Therefore, whenever possible we enter into agreements with exchanges and obtain our data directly from official exchange archives after the close (i.e. data is downloaded after the market close, and not collected off of a live feed).

If we are unable to source data directly from an exchange, or if the data is for an over-the-counter market like spot Forex, we source the data from highly-reputable data vendors that have redundant direct exchange connections to multiple, geographically-diverse ticker plants. Our suppliers have fail-over and comparison processes in place to ensure that the data they sent is complete and accurate. Finally, our suppliers have the ability to provide the data post-close via FTP download.

Filtering Suspect Ticks

Even though we obtain most of our data either directly from the exchanges, or from a very robust archival process, this raw data is not research-ready. Errors can persist even in exchange-sourced data.

Therefore, we have introduced two filtering processes that add significant value to our equity, futures, and cash index trade data. Using a proprietary price filtering algorithm and codes included in the data by the exchanges, we remove or modify suspect ticks to improve the utility of the data without taking out the reality of volatile, free markets. Our process includes:

  • Data Validation – We first programmatically look for any gaps where a trade has not occurred for a period of time unusual at that time of day for that specific symbol, or where the price difference between two consecutive trades is uncharacteristic for that particular symbol. We also ensure we have data for all available symbols in the dataset.
  • Price Filtering – Our algorithmic filters flag trades that appear to be non-representative of market conditions (i.e. “bad ticks”) and suggest corrected values. We do not overwrite suspect ticks in the source files, but flag them for removal by TickWrite®. Our TickWrite data management software can use the unfiltered or filtered prices in its output. Having both prices in the data allows clients to review the results of our filtering and choose the time series they prefer.
  • Condition Code Filtering – We also filter our tick-by-tick trade data for various condition codes that denote out-of-sequence trades, cancelled trades, block trades, off-exchange transactions, and other conditions that require data points to be removed prior to use by a quant. As with the price filter, the tick-by-tick trade source data files contain the ticks flagged for removal, and the user can decide whether or not TickWrite should include them in output time series files.

Delivery to Clients

The final step is to make the finished data available for delivery to clients. We offer several flexible ways to access our data. By using one of the available versions of TickWrite to generate custom-formatted time series files, a client has data that is truly research-quality and research-ready.

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