ContactGary Stone Chief Strategy Officer Email: email@example.comTel: + 1 212 617 2297
All of Bloomberg Tradebook’s execution algorithms access non-displayed liquidity.
Bloomberg Tradebook measures a number of factors related to liquidity including: amount, consistency, average trade sizes, market impact, toxicity, adverse selection and information leakage. The firm does not avoid toxic dark pools but employs tactics in those pools to get as much liquidity as possible without being gamed.
Bloomberg’s dark algos post and remove primarily based on liquidity but also including other factors such as execution success. The automated model selects the non-displayed venue, shares to send, limit, minimum shares and order type. The algorithm balances time in force posting vs. pinging for seeking optimal liquidity. Clients have the ability to optout of any dark pool. The firm’s SOR combines dark and lit venues, so every DMA order type as well as algorithms will interact with the dark.
Bloomberg Tradebook dynamically measures the amount of gaming, leaking and reversion in each pool and will re-rank or pull out venues after detecting patterns. The firm’s quantitative team keeps up to date with new techniques of gaming and HFT in order to adapt its algorithms. The dark seeking logic employs a variety of anti-gaming techniques.
Traders can view real-time fills by venue and monitor how a dark algorithm is working by observing the allocation and interaction with each pool. They can also rest the residual balance of a benchmark algorithm to rest in dark
Service and reporting
Clients can access the firm’s algos via the Bloomberg Tradebook order entry screen or via third party execution or order management systems. Clients can also opt for the dark-only component of an algorithm to customise how they access dark liquidity.
The firm plans to use its agency broker status to connect to new pools and also plans to expand its reach to more global markets.