Equity Tick-by-Tick Data
Buy and sell equity tick-by-tick data data. Every trade, every millisecond — high-frequency trading AI needs tick data from real market microstructure.
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Find Me This Data →Overview
What Is Equity Tick-by-Tick Data?
Equity tick-by-tick data captures every individual trade executed in the market at the millisecond level, revealing the precise sequence of buy and sell orders, prices, and volumes. Unlike aggregated minute or hourly bars, tick data provides granular insight into order flow and price discovery by showing market microstructure in real time. This level of detail is essential for quantitative traders, algorithmic trading systems, and high-frequency traders seeking to understand hidden trading opportunities and execute strategies that bridge the gap between backtesting performance and live market results. Tick data is particularly valuable for intraday traders, scalpers, and those deploying machine learning models on market dynamics. By analyzing the sequence of trades and order book activity, traders can detect impending large moves and optimize execution decisions. The market for tick data is growing rapidly alongside AI-driven trading platforms, which are projected to expand at high double-digit rates as firms increasingly rely on detailed market microstructure data to improve transaction cost analysis, run accurate backtests, and generate alpha.
Market Data
$12.55 billion opportunity
AI Trading Platform Market Size (2025-2029)
Source: Technavio
21.9%
AI Trading Platform CAGR (2024-2029)
Source: Technavio
20.6%
AI Trading Platform YoY Growth (2024-2025)
Source: Technavio
40% growth during forecast period
North America Market Dominance
Source: Technavio
Over 100 trillion rows
Broader Market Context: Historical Tick Data Archive Depth
Source: LSEG
Who Uses This Data
What AI models do with it.do with it.
Algorithmic and Quantitative Traders
Quant developers use tick data to bridge the gap between backtesting strategies on historical data and executing live trading. Tick data reveals market microstructure details that minute-level aggregated data cannot capture, improving strategy accuracy and reducing slippage.
High-Frequency and Scalp Traders
Intraday traders and scalpers rely on tick-by-tick data to understand order flow and detect aggressive versus quiet trading patterns. This insight supports real-time price discovery and helps identify short-term trading opportunities at the millisecond level.
Hedge Funds and Institutional Investors
Professional trading firms use tick data for transaction cost analysis (TCA), deploying AI and ML models on historical tick records to optimize execution strategies and uncover hidden trading opportunities across markets.
Research and Backtesting
Academic institutions, traders, and hedge funds source historical intraday tick data spanning 10-30 years to conduct rigorous backtests, validate trading strategies, and ensure research-ready datasets for publication and live deployment.
What Can You Earn?
What it's worth.worth.
Standard Historical Tick Data
Varies
Pricing depends on data depth (10-30 years), asset classes (equities, futures, options, crypto), and resolution (1-minute to full tick). Bundles typically offer discounts for multi-asset purchases.
Premium Real-Time Tick Feeds
Pricing varies based on volume, exclusivity, and licensing terms
Note: Market research reports about this category typically run Varies, but actual data licensing prices are negotiated case-by-case based on volume, freshness, and exclusivity.
Institutional Tick Archives
Varies
Large-scale historical repositories (e.g., 100+ trillion rows) with cleaned, normalized, and globally sourced tick records are priced based on query volume, geographic coverage, and data freshness.
What Buyers Expect
What makes it valuable.valuable.
Data Accuracy and Completeness
Tick data must be rigorously tested for accuracy, cleanly structured, and normalized. Buyers expect comprehensive records covering all trades, with proper handling of splits, dividends, and delisted securities. Missing or erroneous ticks undermine backtests and live strategy performance.
Low Latency and Real-Time Delivery
For live trading applications, tick data feeds must minimize latency and deliver millisecond-precision timestamps. Co-location at major exchanges and direct sourcing from market infrastructure are critical for high-frequency trading systems.
Cross-Market Consistency and Standardization
Tick data quality and availability vary across asset classes (equities, crypto, forex, commodities). Buyers require standardized, well-documented formats and consistent data integrity rules to avoid strategy breakage when deploying across multiple markets.
Extended Historical Depth
Institutional buyers and researchers demand tick archives spanning 10-30+ years for robust backtesting and alpha research. Data must include delisted tickers and support accurate reconstruction of historical market states.
Scalability and Efficient Storage
Tick data volumes reach millions of records per day in liquid markets. Buyers expect solutions that handle massive data ingestion, fast querying, and efficient storage to overcome challenges in record-keeping, analysis, and ML model training.
Companies Active Here
Who's buying.buying.
Deploy tick data for transaction cost analysis (TCA), AI/ML strategy optimization, and live execution across multiple asset classes.
Use tick-by-tick data to validate strategies during backtesting and ensure live performance accuracy by understanding market microstructure and order flow dynamics.
Access historical intraday tick data spanning 10-30 years for rigorous research, academic publication, and strategy validation.
Leverage real-time tick feeds to detect price discovery opportunities and aggressive order flow patterns for intraday and short-term trading.
FAQ
Common questions.questions.
What is the difference between tick data and minute-level bar data?
Minute-level data aggregates trades into fixed intervals (OHLCV bars), while tick data captures every individual trade in sequence. Tick data reveals order flow, market microstructure, and price discovery that aggregated bars obscure, making it critical for algorithmic traders validating strategies in live markets.
Why do backtested strategies often underperform in live trading?
Strategies backtested on minute-level K-line data lack visibility into the market's microscopic dynamics. Tick data exposes hidden trading opportunities and execution nuances—such as order book activity and slippage—that minute bars completely miss, explaining the gap between backtest results and live performance.
What are the biggest challenges in implementing tick data?
The two major hurdles are tick data quality control (noise, latency, incomplete records) and cross-market sourcing (data availability and integrity vary drastically across equities, forex, crypto, and commodities). Equities markets have standardized, accessible tick data, while forex and crypto markets suffer from fragmentation and poor consistency.
How far back does historical tick data typically go?
Premium providers offer tick history spanning 10-30+ years. For example, LSEG maintains over 30 years of historical tick data with over 100 trillion rows, while FirstRate Data offers tick data going back 10 years and minute-bar data spanning 15+ years across stocks, futures, options, and crypto.
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