Execution Quality Versus Transaction Cost
The balancing act between quality of execution and trading cost is being addressed through new portfolio optimization techniques
Recuing risk and minimizing cost have opposing effects on execution.
“Simply put, trading aggressively incurs higher cost but lower risk, while trading passively yields lower cost but higher risk,” said Jeff Bacidore, head of algorithmic trading at ITG, in a report.
Traders often have secondary consecrations such as maintaining cash- or beta-neutrality, which makes this tradeoff even more challenging.
Fortunately, this cost-risk tradeoff can be achieved via an optimization approach, even when additional constraints are applied.
The core of the approach consists of “portfolio trading algorithms,” which balance cost against risk by executing a basket in a coordinated manner, such as speeding up certain orders while slowing down others to keep the basket risk-balanced.
“Equipped with these advanced quantitative trading techniques, portfolio algorithms help traders improve execution performance and consequently benefit overall investment returns,” Bacidore said.
ITG, an execution and research broker, has launched ITG Algorithms Prism, a web-based tool offering clients comprehensive transparency into the behavior of ITG Algorithms.
Algo Prism provides visibility into the activity of each algorithm, such as the predicted and realized schedules, fill details, and the location, type and price of every open child order.
“ITG has made a considerable investment in building innovative algorithms focused on enhancing client performance,” said Bacidore. “ITG Algorithms Prism is an exciting, modern way for traders to see how ITG adds value in real time.”
Startup EquaMetrics has launched RIZM, a visual programming tool which it says can enable traders who have no prior knowledge of programming, coding or high-level mathematics, to build, to test and deploy complex algo trading strategies.
“We are putting powerful institutional tools into mainstream traders’ hands with the launch of RIZM,” said Amr Mohamed, EquaMetrics’ chief information officer. “Algorithmic trading has long been the domain of only large companies that have the resources for software engineers to build and execute on every trading strategy.”
EquaMetrics has spent the past two years developing RIZM and has raised $3.25 million from private angel investors to date.
“We created RIZM to provide an intuitive, easy-to-use interface that will provide anyone – active professional as well as non-professional traders – access to a cloud-based platform for building, back testing, simulating and executing algorithmic trading strategies,” Mohamed said.
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