In financial market microstructure research, high-frequency trading data serves as an "electronic microscope" for revealing price formation mechanisms, order book dynamics, and instantaneous investor behaviors. CnOpenData has systematically collected and processed underlying transaction records released by the Shanghai and Shenzhen Stock Exchanges to construct a high-frequency trading database for A-share listed companies. This database comprehensively includes two core tables: tick-by-tick trades and tick-by-tick orders, recording every market trading intention and execution result from 2017 to the present with millisecond-level timestamps. The data field design strictly adheres to the original exchange logic, preserving key attributes such as order direction, price, volume, and association relationships. This provides pristine, precise, and standardized foundational data infrastructure for in-depth research on market microstructure quality, trader behavior patterns, and high-frequency quantitative strategies.

Data Features:

• Complete Event Records with Millisecond-Level Timestamps: The database simultaneously provides "tick-by-tick orders" and "tick-by-tick trades" tables, which can be accurately correlated through key fields such as "order code" to fully reconstruct the entire lifecycle from order submission, queuing, matching, to final execution.
• Native Exchange Fields and Precise Identifiers: The data rigorously retains original exchange fields such as "BS Indicator" (buy/sell direction), "order type", "trade number", "ask/bid queue number". These identifiers serve as the sole precise basis for interpreting order flow direction, distinguishing aggressive versus passive trades, and reconstructing real-time order books, ensuring research rigor and reproducibility.

Potential Applications:

• Academic Research on Market Microstructure: Supports cutting-edge finance research for accurately calculating liquidity metrics (e.g., bid-ask spread, market depth, price impact coefficient); validating information asymmetry theories and order flow toxicity models; analyzing micro-level impacts of circuit breakers and price limit mechanisms on order submission strategies.
• Quantitative Trading and Algorithm Strategy Development: Provides institutional investors with underlying data required for backtesting and optimizing algorithmic trading strategies (e.g., VWAP, TWAP). Millisecond-level data serves as core fuel for developing high-frequency statistical arbitrage, market-making strategies, and smart order routing systems.

  CnOpenData's A-share high-frequency trading data, with its millisecond-level event sequence precision, dual-table ("orders-trades") correlation integrity, and multi-year continuous coverage, constitutes a foundational data engineering project for discerning the subtlest pulsations and most complex interactions in China's A-share market. It represents an essential high-frequency data infrastructure for rigorous market microstructure research and frontier quantitative investment exploration.

Time Range

2017-2025 (updatable as needed)

Field Display

Sample Data

A股上市公司股票逐笔成交表

A股上市公司股票逐笔委托表

Data Update Frequency

Contact separately for special requirements