Bank of America Merrill Lynch has enhanced its algorithmic trading platform for Canadian equities, adding several algorithms that are well-known in other markets and making changes to improve execution performance.
Two algorithms – Instinct and Quantitative Implementation Shortfall (QIS) – have been introduced to the bank’s Canadian platform.
Instinct is designed to execute small- and mid-cap names effectively and is especially well suited to Canada, according to Bank of America Merrill Lynch. It added that the US implementation of QIS, a benchmark algorithm, increased benchmark performance by approximately 30% in its US implementation.
The bank has also enhanced the Canadian algo platform’s limit order model, introduced micro price logic and added an inter-listed trading engine that analyses real-time foreign exchange rates and consolidated market data to provide efficient cross-border execution and settlement between the US and Canada.
In addition, more than 20 improvements to existing algorithms have been made, including improved spread sensitivity for the Getdone strategy.
“Market structure changes in Canada require ongoing development and investment in our algorithmic suite and create opportunities for strategies like Instinct,” said Daniel Nachtman, algorithms product manager at Bank of America Merrill Lynch, in a statement.