Developments in algorithmic trading will eventually lead to a high-touch level of service within a low-touch environment, according to report from TABB Group.
Increasing use of algorithmic optimisation methods, which enable an automated approach to algo selection, will be required to enable traders to more effectively manage their time.
The report suggests that algorithmic trading will increasingly move to a feedback-loop system, where an automated system will analyse the order relative to the market, determine the best strategy for a given order, select an appropriate algorithm and then feed this information back into the system in to reanalyse the order.
Many traders are already using tools to automated part of their flow, especially for smaller orders that do not require a high level of resources by using direct market access (DMA) or scheduling algorithms.
However, there is increased pressure to free up valuable trader time on orders that are too big for DMA but too small to be worth significant human resources.
Miranda Mizen, TABB's principal and director of equities research, claims demand is shifting towards having better "auto-pilot" functions and monitoring tools that can change course in the event of market turbulence.
"In the low-touch environment, the arms race is shifting to the intelligence built into algorithms and algorithmic strategies to give buy-side traders an optimal choice of tools and strategies and clear visibility of liquidity across the marketplace", she said.
This is driving development of more strategic algorithms, which can trade in and out of lit markets and switch tactics based on parameters set by the trader. These kinds of algos can understand momentum, manage correlation and minimise slippage.
Additionally, the notion of algorithmic optimisation is developing. Systems using an engine, which can use predictive analytics to switch automatically between algorithms are set to become significant. The trader can set the algorithmic strategy, and the optimisation engine will use all algorithms available within a broker's algo suite for a given order.
This essentially mimics the trader manually switching between a set of algos. Technology that uses predictive analytics to automate this switching is only just beginning to emerge in the market, according to TABB.
As the quant tools used by the buy-side become more complex, sell-side firms are coming under increased pressure to be similarly well equipped in order to offer a competitive trading edge.
"There's a need for smarter tools that can better predict the outcome of different strategies for high-touch traders covering clients more thoroughly and for execution consultants providing algorithmic expertise", Mizen adds.