What are the current trends you are seeing in the development of new FX algo strategies and related toolsets?
Mauricio Sada-Paz: Recent innovations in the algo space are mainly focused on improved access to liquidity. At BofA, this includes both enhancements to internal liquidity, as well as accessing new external matching/netting venues. Specifically, we are integrating new flows into BofA’s Internal Matching Engine (IME), adding more full amount liquidity and accessing new external peer-to-peer matching/netting services. The aim of these enhancements is to improve execution performance by interacting with more unique liquidity.
Can you share with us any upcoming new additions or enhancements you will be making to your FX algo suite?
Tan Phull: We continue to make significant investment in our algo and principal liquidity offering. In the coming months, BofA will roll out new VWAP and TWAP strategies. On the liquidity side, BofA is adding mid-market liquidity from Curex P2P and Siege FX. In addition, there are enhancements across our own liquidity offering and a new mid-book matching engine. Next year and beyond, we are rolling out an entirely new algo suite and a new liquidity-seeking strategy.
What are the main drivers behind client demand for improved FX algo analytics/TCA?
Mauricio Sada-Paz: Client TCA has gone from being a “check box” service offering to being a central part of the risk management process for many clients. This is an important development in the industry and discussions with our clients are increasingly more in depth around algo logic, Smart Order Router (SOR) capabilities and liquidity venues we access to help them drive their own decision making. We have also evolved our services to provide more information to clients in respect of questions regarding this data.
How are algo providers seeking to address the challenge of the evolving FX liquidity landscape?
Tan Phull: Peer-to-peer matching/netting is an important new market development. It will enable algo providers to help customers access more unique liquidity and may improve their overall algo execution performance.
In what ways are toolsets being further enhanced to enable clients to have better control over their algo execution?
Mauricio Sada-Paz: Leading providers should be able to customize algos for clients depending on TCA data and objectives. Clients are more sophisticated and conversations are more about algo performance and less about “bells and whistles”. The majority of FX clients want their partner banks, who have the data, knowhow and the analytical tools, to optimize each algo’s default settings, so that the algo can do what it was designed to do.
Is there a place for the practical application of emerging technologies in FX algo trading?
Tan Phull: AI and ML are still buzzwords for a lot of electronic trading. The key is do they help solve problems to produce better execution outcomes. With a diverse set of clients and execution strategies, BofA has a rich dataset across many currency pairs. We are using ML techniques to cluster data and to proactively monitor execution quality to improve fill rates and overall execution performance.
How will the changes to the FX Global Code impact FX algo providers and users?
Mauricio Sada-Paz: BofA has issued a statement of commitment to the FX Global Code. The addition of the “Algo Due Diligence” questionnaire this year will help standardise information across algo providers and allow apples to apples comparison. In addition, greater transparency will foster additional algo adoption.
What are clients looking for in the further development of the FX algo and TCA space?
Tan Phull: The buy side is very focused on becoming more efficient in how they execute and want to increase automation. Improvements in TCA data will increase algo use and automation in a virtuous cycle. BofA is dedicated to working closely with clients to assist them in using data to drive their execution decisions and improved access to liquidity through enhancements to BofA’s IME and new external venues with unique liquidity.