Why is data transparency so important for trading fixed income in APAC?
Riad Chowdhury, Paulo Costa
Costa: The emergence of algo automation trading that we’ve seen over the last few years in Europe, in the US, and now increasingly seen in Asia is a key driver to this. There’s now a lot more process-focused pieces and what drives all of those processes and automation is data. And not just any data – it must be reliable, good quality, and dependable.
At the moment, what we’re seeing is a big swing from voice to electronic training, but with that we’re also seeing a huge, even bigger dependence on the data points to drive it, such as: quality, pricing, liquidity measurement, and the understanding of the context behind those. It’s becoming more a story of migrating towards an almost no touch, low touch piece in larger sizes. There will still remain some higher touch dependency, but for the most part, if you counted by number of tickets, the swing would dictate that most is done automatically through a trading platform.
Thinking about when it comes to where automation’s limit is, that boundary is being tested right now. A few years back, maybe people would draw the line at anything larger than a million size for certain asset classes and that’s now being pushed, particularly in credit markets. You’re now seeing the emergence of larger block trading activity going through the platform and a larger number of portfolio trades – both things are hugely dependent on the quality of the data behind them.
Chowdhury: Notably, similarly to many other industries, what we are increasingly seeing from clients across both the buy- and sell-side is that they are having to process more trades with less or the same number of people. When you can’t scale your business with people, you need technology. On the buy-side, you’ll hear the terms low touch and high touch consistently, and small trades and very liquid bonds are now not needing the attention, it’s all about spending time on the higher touch business of more complex trades.
Recently, especially in the last 12 months, there’s been a dramatic change in sentiment from the buy-side in particular. It’s a bit of a chicken and egg situation, where they need efficiency but don’t know how to get it, so we’ve seen an uptick in conversations now around automation.
There’s also been a shift in the desk set-up at these firms. An area like fixed income trading has been historically fairly specialist, but is now being covered along with other asset classes such as commodities, FX and equities, as buy-side firms are not able to increase headcounts. In that same vein, if you as a small team are handling various different assets, you need to automate as much as you can. Because of these reasons I would say the conversations have really accelerated in the last year.
What are the challenges when it comes to data transparency in the APAC region specifically?
Costa: The truth is Asia is just too vast and so disparate that it’s impossible to put an idea like TRACE, or the equivalent in Europe, in place in Asia. What we’ve found is that our clients have an absolute craving for transparency but potentially not their own. We’ve always handled that in a controlled and measured approach – looking to protect the contributor and also give use to the market and the users.
So, whilst you can’t depend on regulation to drive an Asia transparency model, you can achieve that through implementation of an industry-led solution such as a “give-to-get” model. What that means is to receive certain services, but they would also need to contribute their own data. Our “give back” is to make sure that the data is treated carefully Everything would be published in aggregate and anonymously, but incredibly be more colourful and transparent than what we’ve seen over the last few years in the Asia market.
Chowdhury: I always say there’s no Asia. Just thinking about the contrast between Northeast and Southeast Asia, the types of fixed income products and the types of investors that operate there are very different. Each of these markets have their own nuances and so it’s important to really look at it at a market level. However, what we’ve seen over the course of the last few decades is that transparency generally leads to better outcomes for the fixed income market.
On the buy-side, data is central to help with the transaction cost analysis they are doing to understand if they got good execution on trades. Equally on the sell-side, they’re in the business of recycling risk so they need to know where the market is trading.
They’re thinking to themselves ‘if a buy side client just sold me some bonds, I need to sell these things back. What is a reasonable price, where I should sell it, and am I losing money?’ Data has simply become critical in terms of how the market operates on a daily basis.
Can you tell us more about data use cases in fixed income specifically?
Chowdhury: When it comes to data, many algorithmic traders on the dealer side would want to just consume the raw data and use it however their algos need it. But the other factor which is coming into play more and more is generating insights from data.
Data adds a rich layer of context for players interpreting market signals—but unless you step back and view it from a broader perspective, it’s easy to miss the bigger picture. These insights, which can inform trading and investment decisions, are becoming a key focus of discussion.
While the data conversation still largely centres on raw inputs—think of an algorithm as a data-hungry monster, always wanting more—there’s a growing appreciation for the narrative side of data: the stories and insights it reveals.
Costa: Traditional buy-side firms are becoming more sophisticated and they’re leveraging data more and more. You’ve seen the emergence of a lot more EMS’s coming to the market to support that process and to help their infrastructure. In the same vein, systematics and ETFs have a role to play. At MarketAxess we’re seeing the emergence of more these types of firms looking to launch credit strategies into the APAC region and that has further enhanced the adoption of electronic trading across the region.
These guys are so data hungry, data-focused and data-driven, that it’s almost forced the more traditional parts of firms to keep pace with it. All of that plays into why the hot word at the moment everyone is about: transparency, transparency, transparency.