Stéphane Marie-François: Exploring transaction cost analysis
How can you leverage TCA innovation to drive better efficiencies across all asset classes and markets?
The TCA on equities has been around globally for a number of years and is therefore much more mature than the TCA on all other asset classes such as FI, FX and listed derivatives.
To date, the lack of accurate data and the need for standards is particularly pronounced for fixed income trading and over-the-counter (OTC) markets generally. Intraday data may not be available for many derivatives or fixed income instruments, making the use of TCA irrelevant. The Request for Quote (RFQ) workflow on FX justifies limited use of TCA as most costs are standardized between brokers. Nevertheless, the fact that different asset classes may have similarities in terms of liquidity profile or regulation justifies the use of the TCA. There remains huge future potential for TCA in general once cleaner data becomes available at a decent cost. Equity TCA is the most advanced and can be taken as a benchmark to improve and strengthen other asset classes, just adapt the metrics for each asset class.
How can the TCA allow traders to better interact and visualize liquidity across all asset classes?
TCA has become one of the most important components for buy-side trading desks in recent years. It gives the trader a quantitative measure and in-depth analysis of exactly what happened on each execution. TCA gives traders insight to better assess the difficulty of their trades pre-trade, during execution with real-time fills, and an in-depth post-trade overview. There’s a big topic going on right now about real-time TCA. I think it’s at too early a stage because there isn’t a solid solution yet. We already have tools with some vendors, but they are limited in scope and options. I believe we can do better and trust brokers and Execution Management System (EMS) providers to deliver in the months to come. Brokers already have tools like machine learning (ML) or artificial intelligence (AI) that power their SOR to improve trading decisions or behaviors of their algorithms. If we could have these kind of tools, it would help the search for liquidity and avoid toxic places, while readjusting the size to avoid adverse selection, etc. We could obtain the information in dedicated dashboards and/or alerts directly integrated into our EMS.
Do you think institutional interest in trading cryptocurrencies and digital assets is growing and how do you think TCA will evolve to reflect that?
Clearly, the appetite is growing. The high returns generated in the past and the endless innovation around blockchain technology and decentralized finance (DeFi) are two sources of expectations. This asset class can provide diversification and generate alpha. The limits today are around the legal framework, but we are making progress. TCA is an area that can be complicated because it relies on clean data. The cryptocurrency world is still unregulated and prices can be different from exchange to exchange. I think it’s still at an early stage. Rebuilding a band will be tricky. At present, gaining exposure to these assets is quite limited for our industry with the use of products like Exchange Traded Funds (ETFs) which are expensive at the moment. I don’t know if TCA would be of much help.
What are the limits of the multi-asset TCA, how to improve them?
Certain asset classes such as fixed income are lagging in terms of ACR, and there is no one-size-fits-all solution. A good TCA relies on good (and public) data. Some tools rely solely on client data and this may mean that the sample is not a good indicator of the market if the data set is too small. Collecting data comes at a cost, and companies will likely need to create a team to analyze it to justify the cost of spending. I think as of today, most trading desks – except the big ones – use the tools sometimes included in the EMS (like we have with Virtu for stocks and FXall for FX). Having clean, cheaper and consolidated data would be a game-changer.
What role does automation play on a multi-asset desktop, is full automation desirable?
As a multi-asset trading desk, automation is the key to success in strengthening order workflows. This helps traders save time so they can focus on more complex commands or code and develop other tools. Full automation depends on your style, flows, and size. We opted for partial automation as we believe full automation may not be appropriate given our order flow. From our perspective and given the complexity of some of the orders we trade, there is little room for a full automation process which could lead to additional operational risk and unsolicited costs. We saw this during Covid where we decided to handle 100% of the orders on our own given the level of volatility in the markets. For large companies, this makes sense, especially when the orders are liquid and small in value.