Liquidity Data
Various dataset that could help with the assesment of security liquidity to inform trading decisions.
Data is updated weekly as data arrives after market close US-EST time.
Tutorials
are the best documentation — Liquidity Data Tutorial
Input Datasets
Public Data from Financial Intermediaries
Models Used
Aggregate Calculations
Model Outputs
Price Improvement, Market Opportunity
Description
This dataset provides comprehensive liquidity metrics for various stocks, including price improvement data and market making opportunities.
It offers investors valuable insights into execution quality, liquidity risk, and market microstructure, enabling more informed trading decisions and strategy development across different market conditions and participant types.
Data Access
Price Improvement Dataset
The latest Price Improvement dataset provides information on price improvements for various stocks, offering insights into trading execution quality.
Market Opportunity Dataset
The latest Market Opportunity dataset offers information on market making opportunities and liquidity provision for different stocks.
All data
The full history can be obtained using the full_history=True
command:
Accessing Specific Tickers
You can also retrieve data for specific tickers across these datasets. For example:
Data Dictionary
Price Improvement Dataset
ticker
Stock symbol
date
Date of the data point
total_price_improvement
Total price improvement amount
shares
Number of shares traded
price_improvement_per_share
Average price improvement per share
average_price_improvement
Average price improvement
Market Opportunity Dataset
ticker
Stock symbol
date
Date of the data point
missed_liquidity
Volume of missed liquidity opportunities
exhausted_liquidity
Volume of exhausted liquidity
routed_liquidity
Volume of routed liquidity
volume_opportunity
Total volume opportunity
average_daily_vol
Average daily trading volume
rolling_daily_vol
Rolling average of daily trading volume
buy_pressure_log
Logarithmic measure of buying pressure
buy_pressure_pct
Percentage measure of buying pressure
missed_liquid_pct
Percentage of missed liquidity
exhausted_liquid_pct
Percentage of exhausted liquidity
vol_uncaptured
Percentage of uncaptured volume
retail_pressure
Measure of retail trading pressure
institutional_pressure
Measure of institutional trading pressure
algorithmic_pressure
Measure of algorithmic trading pressure
retail_institute_ratio
Ratio of retail to institutional pressure
algo_institute_ratio
Ratio of algorithmic to institutional pressure
retail_algo_ratio
Ratio of retail to algorithmic pressure
Use Cases
Execution Quality Analysis: Evaluate the execution quality of trades using price improvement data.
Market Making Strategies: Develop market making strategies based on liquidity provision opportunities.
Liquidity Analysis: Assess the liquidity of a stock by analyzing various liquidity metrics.
Trading Strategy Development: Incorporate liquidity data into quantitative trading strategies.
Market Microstructure Analysis: Study market microstructure using detailed liquidity and price improvement data.
Performance Benchmarking: Compare execution quality across different brokers or trading venues.
Risk Management: Assess liquidity risk and potential transaction costs for large orders.
Regulatory Compliance: Monitor best execution practices and demonstrate compliance with regulatory requirements.
These datasets form a comprehensive toolkit for liquidity analysis, enabling detailed examination of price improvements, liquidity provision, and related metrics across different market participants.
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