SOR is an automated process used in online trading to quickly execute a trade, based on price and liquidity, across a range of electronic trading venues and counterparties. By analyzing different offers and placing optimized orders, SOR is a response to the challenge of fragmented data and liquidity in the fixed-income marketplace.
It works by applying machine learning to the trading process, so each router path is configured and ‘trained’ on the data record of the previously executed transactions, as well as the trading style and bias of the traders it serves.
SOR has been a key component of equity trading workflow for 20 years. But with AI, it can start to make decisions on which venue trades should be routed to and which dealers should be approached, based on past performance and real-time market conditions. Combined with AI algorithms that aggregate data and automate pricing, SOR allows for complete end-to-end automation of fixed income trading workflows.
SOR works by accessing a range of electronic trading venues simultaneously, quickly finding the best prices, creating a structure to customize algorithms and then helping track, validate and review data for additional controls and analytics.
The SOR engine determines which venue will be directed to activate the trade, factoring in venue liquidity characteristics and the trader’s specific price momentum and execution cost requirements. The routing logic dynamically adapts based on machine learning \of the historical execution records from each specific trading venue and the quality of the available real-time market data at any given moment.
Algorithms determine the size of the trade, execution time and price, aiming for the best volume-weighted or size-adjusted price and trading route. An order route is dynamic, meaning it continues to update existing opportunities and scan for new, better ones as the market conditions change.