Artificial intelligence, machine learning, and a move to the cloud are cited as trends in improving transaction cost analysis as regulators have focused on best execution.
MiFID II regulations went live in the European Union at the start of this year and strengthened the best execution requirements. A report from consultancy Aite Group, MiFID II Best Execution: Multi-Asset-Class TCA Goes Mainstream, said that as a result transaction cost analysis and best execution have become fundamentally interchangeable functions.
Audrey Blater, PhD, author of the report, wrote: The TCA arms race will translate into more and better technology, benchmarks, and functionality, which will be required to stay competitive and satisfy the growing demand.
In addition, MiFID II included fixed income, some foreign exchange transactions (not spot) and commodities in the best execution requirements for the first time as well as introducing pre-trade transparency requirements and post-trade reporting in these asset classes. Therefore expansion into multi-asset-class TCA is an area of growth for many vendors, particularly in the fixed income and derivatives, although they suffer from a paucity of readily available market data.
Additional trends are the use of artificial intelligence, machine learning, and a move to the cloud. Firms with the budget to invest in artificial intelligence will automate the aggregation, cleaning, and analysis of increasing volumes of data.
Artificial intelligence
As the move to more AI gains further traction, Aite Group believes market participants will see the delineation between winners and losers in the TCA provider space as well as the introduction of more bells and whistles as data quality improves-such as real-time TCA-by both internal and third-party providers, added Blater.
Corvil, which provides data analytics for electronic trading, has launched Intelligence Hub, which uses machine learning to provide digital intelligence and sends proactive alerts in real-time on signals which are most important to specific clients.
David Murray, chief business development officer at Corvil, told Markets Media this month that market participants are looking for help in using data in three areas – client intelligence, measuring execution quality, and venue analysis. They find it difficult to analyse huge amounts of data and determine which signals are most important
He said: Clients need to ingest huge volumes of data and we have created several machine learning algos to correlate anomalies. This is a self-service solution for the business, operations and compliance.Christophe Roupie, MarketAxess[/caption]
Christophe Roupie, head of Europe and Asia at MarketAxess told Markets Media this month that the provider of fixed income electronic trading platforms is developing predictive data using machine learning and artificial intelligence to profile market behaviour, liquidity and available bonds
Transaction cost analysis needs a reference to understand the behaviour of the underlying price and the impact of the execution against market liquidity, he added. Our solution will be very meaningful in determining a reference price and measuring execution quality.
Aite added that until price discovery in fixed income reaches critical mass, investors are likely continue to use TCA to gain insight into certain post-trade metrics and reporting but must also rely on models and other information when making trading and investing decisions.
Cloud
Blater continued that some TCA providers are planning a move to the cloud as product upgrades and data localization become more important and even required in certain jurisdictions.
As several TCA providers are US-based, with trade data being sent to US servers, European clients can use reporting modules, which are launched on the cloud, while keeping their data in Europe, she said. As data demands and solutions continue to become more bespoke and complex, its hard to envision a world in which all TCA providers arent using cloud technology.
Other trends are that vendors will offer TCA solutions that become more customized and granular in mature areas, such as equity and even foreign exchange, especially as there are improvements in market data sources that allow the creation of established benchmarks.
For the buy-side, the use of TCA for alpha generation is still in nascent stages at some institutions according to Aite.
Two asset managers that seem similar on paper will have different performance results given their ability and willingness to use cost analysis in their strategies, added Blater. At some point, this difference is expected to become a battle of the haves versus the have-nots.
