The correlation between quant skills and execution quality

Published on 29 November 2021

The profile of bond traders is changing, as quantitative skills and data management become as important as relationships and counterparty engagement. This has a material effect on the way trading occurs, but does that improve execution quality?

Gareth Coltman, Global Head of Trading Automation at MarketAxess explains that there is a direct correlation as traders can reduce high-volume, low-value trading activity using electronic execution, and improve analysis of trade execution quality, allowing more time to focus on the higher value tickets and a better understanding of which counterparties to work with.

Dan Barnes: Welcome to Trader TV – your insight into trading for professional investors. I’m Dan Barnes. In fixed income markets, we’re seeing buy-side traders evolve from a very voice-based trading model to a much more electronic execution model. This creates a range of skills that could potentially be employed.

Joining me today is Gareth Coltman, Global Head of Trading Automation at MarketAxess, and we’re going to be discussing how the traders profile, in terms of skill sets, is evolving over time.

Gareth, welcome back to the show.

Gareth Coltman: Hi, Dan. Great to be here.

Dan Barnes: Tell me, what factors do you think will shape trader profile of the future?

Gareth Coltman: I think the trader of the future is somebody who is going to be capable of dealing with an enormous amount of complexity. We’re seeing increasingly fragmented market structure, emergence of new protocols, a vast amount of data as we see increasing transparency. Some of that data is aggregated. Some of it is raw. So that trader will need to become increasingly reliant on technology as a way to bring all of those pieces together, and carefully choose partners that they’re going to work with to help provide those sources of data and technology.

I think the idea that the trader of the future is going to be an all-singing, all-dancing trader, risk taker and risk manager, quant programmer is unlikely, right? So in reality, there’s going to be a team of people probably supporting that trader. Some of those inside the firm and some partners outside.

Dan Barnes: How do you see the traders profile developing in the future?

Gareth Coltman: We’re going to need to see a trader who is very comfortable with technology, diving into the data and have a capacity to accrue that data using quant tools and programing. We’re still going to need traders who clearly understand the markets. They’re going to be the subject matter experts who understand how to manage risks. And a lot of cases we’re going to see traders who are also portfolio managers.

In other asset classes is pretty easy, right? We have a situation where the portfolio manager chooses the security, gives the security to the trading team and they execute the security. But in fixed income, we have a situation where the outcomes for executing any given security can be wildly different.

What we need and what many firms already have is a workflow where the execution trader is able to have a continuous feedback process with the portfolio manager, and thereby empower that portfolio manager to make investment decisions or even having investment ideas based on information and data about what’s available in the market. That segregation of those two functions solves challenges like conflict of interest, but even if they’re segregated, firms need to find a way that they can create that very, very fluid, information sharing process. And again, I think technology is the solution there.

Dan Barnes: And then how would you characterize that difference with other asset classes?

Gareth Coltman: In fixed income markets the buy-side have this advantage that they have this direct access to the market. It gives them unfiltered access to liquidity, unfiltered access to data, and it means that they have a role in the governance of that market. They’re not always subject to another intermediary in terms of how they get access to it.

But it does create extra challenges. If I’m going to go direct to market, I now have to deal with the complexity of that market. So that buy-side firm has a choice; they’re either going to need to invest in the data and execution and automation solutions themselves and build out proprietary solutions that perhaps they purchase the solution from a vendor. Or they’re going to have to rely on platforms, which is the case largely at the moment, to help them with that access into the market.

Typically, that’s in the form of data. So MarketAxess as a platform provides our Composite Plus Pricing Model as an example of how clients know, ‘where am I likely to trade?’ And in the form of emerging automation tools, so MarketAxess provides buy-side firms with Auto-X, which is a tool which allows them to automate the submission and execution of their RFQ. And we’ve seen a very rapid adoption of that tool.

Where we look at more liquid markets like our high grade market, it’s probably seeing something like a quarter to a third of all asset managers doing their trading using this kind of automated protocol.

Dan Barnes: How would you characterize the sets of support products that a trader needs if he doesn’t have a smart order router, as it does in equities or broker supply trading algorithms?

Gareth Coltman: What we’re hearing from clients is they need solutions in a few main areas. And the first one of those is really pre-trade. Getting access to data, but perhaps more importantly, being able to create insight from that data. Things like predictive models, which allow them to have insight into what’s the likely outcome of this execution? How likely am I to get this done, given my constraints, whether that’s a limit price or having to have a certain number of levels back?

Dan Barnes: How do you see traders themselves evolving to meet the new pressures that they’re facing as the market becomes more electronic and more quantifiable?

Gareth Coltman: When I speak to heads of trading at buy-side firms and speak to the traders themselves, they’re looking to try and acquire skills on the desk to support these types of trading protocol, these types of trading workflow. And obviously, that’s a much more technology-driven approach and a much more data-driven approach. So it’s not uncommon for firms to be looking for people with a data or technology skill set as the kind of starting point for their trading education. There’s obviously a lot more to trading than just being able to code or having a kind of quantitative, mathematical background. But I think these days that’s viewed as a great base skill set to build the rest of the trader experience on top off.

Dan Barnes: That’s great. Gareth that’s been fantastic. Thank you so much.

Gareth Coltman: Thanks, Dan. It’s been a real pleasure.

Dan Barnes: I’d like to thank Gareth for his insights today on the evolving trader profile, and I’d like to thank you for watching. To catch up on our other shows or to subscribe to our newsletter, go to TRADERTV.NET.