Do limits improve algo performance?
In algorithmic execution, the price limit serves as the stopping criterion. The algorithm halts execution once the price exceeds this limit, enabling users to control FX algorithm execution risks. However, users have no standard guidelines to set up the optimum price limit.
Two potential scenarios arise:
If the price limit is set too far away, it will never be triggered, offering no price protection.
If the price limit is set too close, it will be activated frequently, leading to a higher risk of incomplete execution.
To tackle this challenge, our recent study transforms the optimum price limit problem into an optimal control model. Instead of relying on numerical solutions, the BestX team employs a statistical method based on a unique dataset from BestX. We hope our paper's insight will guide clients in setting the optimum price limit for each algo style.
Please email contact@bestx.co.uk if you are a BestX client and would like to receive a copy of the paper, which is also hosted within our FAQ section of the UI.