AxeTrading and ICE integrate analytics into QEMS

Published on 22 October 2021

ICE’s pricing, analytics and market data has been incorporated into the AxeTrader Quoting and Execution Management System (QEMS) to allow users access ICE’s pricing and analytics tools, including end-of-day evaluated pricing, continuous fixed income evaluated pricing, best execution services and ICE Liquidity Indicators.

ICE Liquidity Indicators can help in quantifying security and portfolio liquidity across fixed income and equity asset classes, while ICE’s Best Execution Service can help customers manage and measure bond trade execution quality and support them with their assessment of regulatory compliance.

Mark Watters, CCO and co-founder of AxeTrading and Stephen Baker, global head of Sales of Fixed Income and Data Services at ICE discuss the demand from traders and other investment professionals for more informed and efficient decision making, and the capability that AxeTrader QEMS provides with dealer-grade pricing through a user configurable quoting engine and the addition of ICE’s pricing and analytics tools deepens the resources available to AxeTrading customers.

Dan Barnes: Welcome to Trader TV – your insight into trading for professional investors minds. I am Dan Barnes and I’m here at the Fixed Income Leaders Summit in Europe, the first Fixed Income Leaders Summit in-person since 2019. Joining me today are Stephen Baker, Global Head of Sales of Fixed Income and Data Services at ICE, and Mark Watters, CCO and Co-founder of AxeTrading.

Guys, welcome to the show.

Stephen Baker: Thanks, Dan.

Mark Watters: Thank you, Dan.

Dan Barnes: Stephen, starting with you, what sort of analytics do you think needs to be integrated or used within an EMS that moment?

Stephen Baker: So the key thing if we boil it down is to provide the trader with the right type of information for them to be able to make pre-trade and post-trade decisions, and then go to their investors and be able to give them a really good idea and confidence that the trades that were executed and the strategy of the fund were under best execution. So you’re finding a score that was done at the right liquidity levels and that there was enough pricing in the market to be able to do that. That’s the fundamental crux. It’s not about, ‘Oh, you should be using this type of product.’ It’s more about what analytics can the traders be using to be able to do a more effective and more efficient job?

Stephen Baker: I’d agree with Stephen. I think giving the trader the essential information to make the right decisions is key. For us, being able to put it into a place where the trader can actually use it in their workflow is also a vital part of the picture. So within our actuator QEMS, we’ve made sure that the data that’s available from quality data providers, such as ICE, is available to the trader in a way that it can be visually present when they’re trading, but also integrated into the actual trading workflow, guiding their trading process. Even to the extent that they want to automate, they can use the data to do that, as well.

Dan Barnes: That’s really interesting and presumably because trading is part of the investment process, you’ll always be able to have data which can be provided to the portfolio manager as well as the trading desk, so they’re seeing the same picture?

Mark Watters: Indeed. Very often, the picture of the market that the traders are seeing is quite different from what the investor, the portfolio manager thinks the market is. And to be able to share an accurate picture between the two constituents of the trade or the investment process is key. So there are workflow tools that you can use, including taking the data into our QEMS and sharing it then with the portfolio managers, harmonizing the workflow between the portfolio manager and the trader through a process that’s consistent and seamless that can solve those problems. But it does involve integrating the right data and then making it consistently available to the different constituents of the investment process.

Dan Barnes: Stephen, do you see consumption by both trading desks and PMs? Or does it tend to come from one side or the other?

Stephen Baker: I think you are seeing analysts, the portfolio managers, the traders, the risk managers all being part of a workflow, as Mark said. And having that consistent data, consistent analytics enables them to have a more efficient dialog.

So before the trade, where is that continuous pricing that then everybody can look at? Then when they’re looking at liquidity, where is that liquidity and how long will it take the trader to be able to execute that trade without leakage to the market? And that is key when you’re talking to the portfolio manager and the trader, and to have that dialog and analytics in front of them is really, really powerful.

And then after the trade, it’s, ‘OK. Did we do best execution?’ And then being able to have risk and compliance and the trader sitting there with the same consistent data, same consistent analytics from best execution and then transactional cost analysis is paramount.

Dan Barnes: Absolutely. And that brings me to my next question, how do you see these analytics effectively turning into trading efficiency?

Stephen Baker: Buy-side traders are looking to wider sets of data, richer sets of data to augment their trading process to improve their understanding of the market before they trade, as Stephen was saying. To drive their trading strategies, whether that be through just guiding them through the actual trading process, helping them fx to decide when is the right time to trade, what’s the right size?

And then also driving automation strategies. We’re hearing more and more about algorithmic trading. To go and integrate themselves to multiple different sets of data and to find a way to incorporate the analytics, involves investment of their own time and resources into that part of the process. They can outsource that to a technology provider like us who integrates good quality sources of data to then readily feed the algorithmic trading process. There are more and more buy-side firms building infrastructures to automate and improve or augment their trading process through algorithmic trading and data is key to that.

Dan Barnes: That’s fantastic. So can you tell me how the two firms are working together to actually deliver this then to traders?

Stephen Baker: We are looking to provide efficiency to the traders because they’ve got a complex day and a complex role, especially if they’re still in their hybrid environment. They’re not in their office where they can just go and chat to somebody. They’re having to do things remotely. So being able to have our data and our analytics streamed through into the axe trading application is, I think, invaluable because it gives the information in one consolidated container on what is a very crowded desk workspace for a trader. And so we’re not creating complexity. I think what we’re doing is we’re creating efficiency and effectiveness for that trader.

Mark Watters: It’s also worth remembering that ICE is a broad coverage of the fixed income markets, it runs several trading venues, it has a clearing business. All of that helps to inform the data and being able to make that data available through an API that is constantly evolving with new analytics being brought into it, just makes it convenient for a client who wants to integrate to that data source with an axe trader EMS. To be able to have knowledge that their investment in that API is going to continue to yield more and more quality data in fixed income and underpin their investment in electronification and potentially algorithmic trading.

Dan Barnes: Guys, that’s been fantastic. Thank you very much.

Mark Watters: It’s been a pleasure. Thanks very much, Dan.

Mark Watters: Yes. Thanks, Dan.