Algorithmic Trading Usage: Variations by Strategy ( by ITG)
According to recent research by Greenwich Associates, large institutions are increasingly turning to algorithmic trading and smart order routing solutions to solve their liquidity problems. Greenwich found that the largest respondents to its flagship US survey increased their use of algos and SOR by 10% between 2015 and 2016.
While algo usage is increasing across the board, ITG found that institutional traders are using different algo strategies in different ways. In analyzing data from ITG’s Peer Universe database of transaction costs, which captures nearly 20% of institutional trading activity, we found the following insights about algorithmic trading of US large cap stocks:
- Opportunistic algos attract the largest orders, at almost 1% of median daily volume (4,800 share average trade size)
- Dark algo order sizes are smaller, at 0.22% median daily volume (2,000 share average trade size)
- Some 91% of dark algo orders are placed with limits versus just 8% for scheduled algos (ie TWAP, VWAP, Volume Participation)
- Implementation Shortfall algo orders are placed most frequently in the morning while scheduled algo orders are more common leading into the close.
- Placement of dark and opportunistic orders spike in both the morning and around the close, mirroring overall volume profiles throughout the day.
Algorithms have become more prevalent in the spot FX market.
QB’s Algo Suite for futures market trade execution is also being co-located to HKEX.
Breaking data silos is key to deploying automation beyond 'nuisance' orders.
They can be used on quantum hardware expected to be available in 5 to 10 years.
Streaming blocks change the basis of matching and price discovery so institutions can find new liquidity.