Trade-data edge grows in relevance

Fixed-income traders and investors are increasingly using insights from trade data to inform decisions – from trade ideas to best-execution principles. Executives from Refinitiv and Yieldbroker explain why the data their firms’ tie-up provides could become even more important to the market in the next cyclical evolution.

Refintiv distributes Yieldbroker’s market data – covering Australian and New Zealand fixed income and interest-rate derivatives as well as related products like banks bills – to its customers globally. This means users have access to information from the largest single trading platform in the Australasian secondary market, which also hosts new-issuance auctions for most of Australia and New Zealand’s government-sector borrowers.

According to its Sydney-based chief executive, Anthony Robson, Yieldbroker estimates its trading venue captures nearly half of all transaction volume in the “bellwether” domestic dealer- to-client market. Activity has migrated to Yieldbroker organically, as Australia and New Zealand have no regulatory or other mandates to trade on platform.

Refinitiv makes tick history from Yieldbroker available across 14 specific data points, including factors like yield to maturity and modified duration. Data stretching back to 2003 is cloud hosted and available via GUI or API to mitigate end-user cost.


The use of tick data to inform trade and investment decisions is already proliferating. Chris Young, Asia regional sales director, enterprise data solutions at Refinitiv in Sydney, explains this used to be the realm of high-frequency traders who used granular tick data to do things like back-testing trade ideas. This naturally started in the most liquid asset classes – equity, followed by FX.

Times are changing, however. “We are starting to see a lot more interest in tick history across the fixed-income market,” Young reveals. “There is a changing dynamic in the type of market users involved but there are other elements at play, too. For instance, in Europe regulation brought the idea that users should have to do transactional cost analysis for non-equity instruments to the fore.”

Even when there is no regulatory mandate, Young says market participants increasingly recognise trade data can be used to measure best practice, reduce execution cost and satisfy compliance requirements.
Perhaps more significant is the global trend for deployment of data-informed trading even outside the most liquid markets.

Robson suggests that perhaps only two global OTC markets – US and Eurozone sovereign bonds – have sufficient transaction volume to support traditional high-frequency trading.

But data-informed trading still has a growing role, especially in markets like Australian sovereign bonds – which Robson says “bats above its weight” in volume and liquidity.
Young adds: “The bond trader sat at a desk manually working off six screens is still a reality and isn’t going to go away. But at the same time we are seeing more use of the acronym ‘TWC’ – traders who code. This means the people making the trading decisions increasingly often have backgrounds in data science, quants and the like. They cannot operate without data, and they want more of it to interrogate and understand.”

Uptake of data-based trading in fixed income is likely to get a boost from what increasingly appears to be an imminent turn in the policy and market cycle. Supernormal liquidity has made funding readily available to most borrowers for the past decade or more, but Robson believes the return of inflation and gradual fiscal consolidation is likely to bring competition for capital back on to the agenda across global markets. Debt-market jurisdictions will need to be match fit as holistic investment and trading destinations.

“Being able to distribute market data actually helps educate the global network, which is going to be increasingly important,” Robson says. “Post-COVID-19, borrowing requirements in many areas are likely to explode – and in this context I believe individual jurisdictions will need to set themselves apart from others in a competition for capital. Having this type of data available helps the Australian and New Zealand markets do that.”

He points to the Australian sovereign borrowing task as the most obvious example. The Australian Office of Financial Management did plenty of groundwork to prepare for a massively increased issuance task, building global relationships ahead of time. Even so, Robson says: “Ultimately, when supply goes through the roof a borrower has to consider what the offset will be on the demand side. This is where the idea of implied competition for capital comes in.”

A changing rates environment will exacerbate this. Low rates are manageable if investors expect them to fall further, but demand for duration could alter significantly if bond buyers anticipate ultra-low yield is locked in for years to come.