How has a shift toward electronic and algorithmic trading impacted analytics in fixed income markets over the past few years?
We’ve seen a significant rise in use of electronic execution channels over the last few years – especially on the rates side at Aviva Investors. We use a handful of algos to execute some smaller size orders in bond futures and e-trading for a portion of our credit flow.
This has opened the door to many more date points to analyse and comes closer to the equity market in terms of analytics. We can analyse dealer performance in more detail due to greater accuracy in timestamps.
How are TCA frameworks evolving in the fixed income space?
TCA vendors are releasing more detailed evaluated pricing models, powered by a number of different market data sources. This provides increased confidence around references prices and cost estimates that the vendors are calculating in their models.
Similar to equities, we can now observe pre- and post-trade bond price moves, as well as improved analytics such as the number of times dealers have won quotes but also how many times they didn’t win and how far they were from the winning quote. Did not quote (DNQ) stats are also very useful for determining which areas dealers’ strengths lie.
What is the best way to validate bond pricing data from multiple sources?
The validation on bond pricing is vital to ensure that the comparison versus executed price and subsequent performance metrics, are valid. Our TCA vendors source data from a variety of market data providers, to ensure they can provide a reference price and cost estimate which are as accurate as possible.
We also have access to liquidity scores which demonstrate the how liquid the bond is and therefore the number of trusted market data sources behind the output. This allows us to segregate the performance numbers into different categories to ensure we can analyse illiquid bonds in an appropriate manner.
What innovation do you expect to have the greatest impact on fixed income data and analytics going forward into 2026?
AI is something which we can’t shy away from and will become a huge part of the industry in the next few years, as the models become even more sophisticated. At Aviva, we’re looking into how AI can be used to aggregate our internal trading data with the TCA output we currently receive for all asset classes.
I’ve heard AI mentioned in almost all of the panels at FILS so far and it’s interesting to see how different firms are using the advanced technology that we now have at our disposable. Whether its chat bots, advanced data models or using AI to design new analytics frameworks, I believe it’s an area that will accelerate over the next year.