Understand the true impact of large and hidden trades on the order book and how they affects venue participant behaviour.
Leverage this insight to test, implement & validate policy decisions as well as scrutinise trading actions.
Sample use cases:
— Provide end clients and competitive venues with more detailed trading insight based on number of orders, true liquidity positioning and cost to liquidate a given size
— Change market participant behaviour by optimising compensation structures by analysing granular order dynamics
— Leverage the trading insight data bundles to better understand market conditions surrounding trades across venues
— Have more context to understand decisions brokers make when routing trades
Typical metrics: Order imbalance, Trade prices, Volatility, Order Fill behaviour, BMLL Platometrics liquidity, Liquidation cost, Trade quality, Spread metrics.
The data sets are available both as data feeds via API/SFTP or via dashboards, below some visual outputs on trading volumes & auction percentages from our Data API.