, a provider of data and analytics as a service, has launched analytics for trading performance on its analytics platform.
The service acts similar to transaction cost analysis (TCA) providing traders with the ability to assess historical trading data with comparisons of liquidity providers and data visualization technology.
The new product could also be seen as a response to increasing transparency requirements which define the conduct of all market participants, including the need for buy-siders to prove best execution. It allows big xyt’s customers to achieve and demonstrate best execution through post-trade (TCA) when trading electronically.
big xyt has clients across exchanges, market makers, sell and buy-side firms using its analytics products. The addition of TCA functionality helps the company accelerate business growth as the appreciation of its value has risen in the post-MiFID II liquidity landscape.
Additional value-added functionality
Amongst its many functions, , such as Liquidity Cockpit, track all changes in trade conditions or execution venues, while also applies custom measures such as Large. This includes an automated ad-hoc reporting facility that could be integrated into clients’ internal applications for analysis such as broker review, sales, workflow optimisation as well as compliance and best execution.
Commenting on the news, big xyt CEO Robin Mess said, “Working with our clients has enabled us to evolve our offering to include TCA. The normalised data we provide enables them to analyse the data allowing them to see the full picture and make fully informed comparisons.” he added, “We are delighted to see them quickly benefitting from our unique analytics approach and the flexibility of the output.”
Mark Montgomery, head of strategy and business development, added “We are effectively delivering data analytics as a service applied to TCA, enabling firms to ask themselves whether they are applying the right benchmarks and right trading strategies. He continued “By giving clients the ability to interrogate their own data and assess a consolidated view they can validate trends that are fit for their purpose”