How is automation shaping emerging markets?

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Meridy Cleary: Hello, and welcome to J.P. Morgan's Making Sense. I'm Meridy Cleary from the FICC Market Structure and Liquidity Strategy team. And in today's episode, we're going to explore how automation is shaping emerging market rates trading. As more participants look for efficient ways to access EM duration and relative value, the conversation is increasingly about how trades get done, which protocols get used, how liquidity is accessed, and what's driving automated execution. So to discuss these themes, I'm pleased to be joined from New York by Carlos Gomez-Gascón, head of EM rates e-trading at J.P. Morgan. Hi, Carlos. Thanks for joining me.

Carlos Gomez-Gascón: Hey, Meridy. Thanks for having me.

Meridy Cleary: Yeah, it's great to have you. So let's start with the big picture here. You know, when people hear about automation and EM rates, they might picture a similar trend of what has or is happening in developed markets. But of course, as we know, EM market structure is different, right? We're talking about a trading environment that can be heavily shaped by local regulation, which of course can change quite quickly. Hedging needs, liquidity can be episodic. So Carlos, in your seat, how have you seen automation seep into EM rates trading?

Carlos Gomez-Gascón: Thank you, Meridy. That's a very good question. EM rates is actually a very diverse market. You mentioned local regulation. That definitely plays a big role on every country and makes every country a little different. There's also different tools for price discovery, such as broker markets, future markets, etc., which reshape their relationship between dealers and clients, the nature of liquidity. And there's also different levels of electronification in markets. And this is maybe an important distinction between electronification and automation. All electronification means is that a client is able to send a request for pricing to a dealer via an electronic channel. But then, you know, both the client side and the dealer side could be fully manual. It's just the communication being electronic. It's like accessing through a computer rather than, you know, making a phone call or going via chat. And then the second step is automation. Automation is that the response on pricing happens from a machine, effectively.

Meridy Cleary: That's a really important distinction. And I guess if we home in on, you know, your second point around automation, what efficiencies does that bring to EM rates specifically?

Carlos Gomez-Gascón: So in terms of efficiencies, it definitely makes the workflow faster, price discovery more transparent and scalable. That in turn makes the liquidity more consistent. And it also changes a bit like the relationship between dealers and clients, because electronic and automated systems make the nature of the relationship and the discussions more data driven. And, you know, in terms of like the automation itself, what we mean about automation is, you know, automated price responses or there are simpler things like straight through processing. And in the cases where there's places available to do so, also automated hedging.

Meridy Cleary: And Carlos, you run EM rates, which of course covers several different asset classes. Are there nuances in how you approach improving workflows across those and how they interact?

Carlos Gomez-Gascón: Yes, of course. First of all, the three asset classes that I mainly cover are bonds, interest rate swaps and FX swaps. And there's a relationship between all of them and a bit of an echo environment. Maybe the best way to explain it and the starting point is thinking about an FX swap. So an FX swap has, if you break it down into like the different components of its pricing, it's priced out of a SOFR curve, a local curve and the cross currency basis. The SOFR curve is a very well known part of the problem, is very transparent. The local curve effectively is the interest rate swap market. So there we're already like putting together interest rate swaps with FX swaps.

And then finally, there's the bond market, which has very stable, normally very stable bond basis between bonds and swaps as well. So in reality, the three asset classes are a bit of an echo environment. And as you improve one of the pieces of the puzzle, you effectively are able to improve the others. Also in the long run, what you would expect is to take views that encompass the three asset classes together, and to take risk effectively across all of them in a consistent manner.

Meridy Cleary: Okay. And if we focus in on the swap market that you mentioned, when it comes to EM automation, we've seen a steady push and importantly, electronic trading is extending to larger risk sizes and more workflows in EM IRS, right? So if we think about this journey towards electronification in this market, what have you seen driving that change? And why now?

Carlos Gomez-Gascón: First of all, there is a growth in electronic channels and electronification across the board. I think there's a lot of new technologies, new startups, AI and all that, you know, increases the appetite to look at electronic execution in the EM rate space. The growth really is everywhere in LATAM, Asia, Senia, and across all asset classes. IRS though, has the advantage of having a lower capital cost and is therefore the preferred channel for hedge funds. Also IRS has the feature that is much better standardized that maybe other set classes to tenors, which makes backtesting and thinking about strategies of investment a lot simpler of a process.

Meridy Cleary: If we think about now EM local debt, we know that there's been a rise in demand driven by higher yields, attractive currency valuations in EM and structural shifts like de-dollarization, growing domestic institutional buyers in these local markets. So from your seat, how do you see automation or automated workflows and algo pricing shape local currency bonds?

Carlos Gomez-Gascón: Local bond markets are definitely an important area of focus. There is a large proportion of electronification in them, and that's only increasing as we discussed previously. Also it's a very prevalent market for asset managers, and as a result, it can become a very competitive market. And, you know, asset managers tend to trade in baskets that have like a lot of components of bonds at the same time, which makes it increasingly harder for traders to manually get back in those prices in quick succession. And therefore automation helps with increasing the ability to respond to these asset managers.

Meridy Cleary: And regionally, are we seeing a split, for example, you know, faster growth in certain regions when it comes to these trends more broadly, not just focusing on local bonds, but across EM rates?

Carlos Gomez-Gascón: That's a very interesting question. There's obviously a lot of subtleties and differences across every country, but if we focus on regions, I think the most interesting feature of the local bond markets is the repo market. For those that are trying to understand how I connect the repo market to the bond market, this is the way it works. If you're a dealer and a client wants to buy a bond, you need to deliver to the client the bond. But if you do not have the bond, then you need to access the repo market to effectively loan that bond and give it to the client. In EMEA and in LATAM, those repo markets are very functional, and therefore the prices to buy and sell are effectively similar.

Now in APAC, it's a little bit different, and some or a lot of the repo markets, interestingly, are challenging to access. And that means that if the dealer doesn't previously have the bond, then it can be hard for the dealer to access the repo market to loan it, to be able to deliver it to the client. And as a result, that creates some distortion in pricing between when the client's trying to buy and a client's trying to sell. I think that's the main difference.

The other point that I wanted to make, it's also the access to a well-formed and liquid interest rate future market. So examples of that are Brazil and Korea. The reason why I mentioned that is because they provide a much better price discovery and a better means for hedging of the bond risk. And as a result, it makes those markets more liquid and easier to trade, generally speaking.

Meridy Cleary: Okay, interesting. So it kind of sounds like a funding dynamic across regions, I guess you could say, in terms of how you access that. And I guess shifting to who is driving this push and these trends across EM rates automation, we're seeing obviously the rise of systematic funds across markets. From what you see, what are some interesting trends in terms of the client base or who's trading these markets?

Carlos Gomez-Gascón: For sure. Systematic funds, as you mentioned, they're becoming a bigger share of trading overall and EM rates markets are no different. So for sure, systematic funds operate better in an environment with fast price discovery, which is better suited for not only electronic, but also automated workflows. These types of funds tend to be very data driven. Again, we discussed previously how automation, electronification improves the data gathering, which is essential for systematic funds. And yeah, I mean, I think that's one of the main drivers of it.

Meridy Cleary: Yeah, I guess another dynamic is around periods of volatility and how stressed markets can change liquidity conditions and the way that the participants that we just discussed behave in those periods. And of course, emerging markets often see liquidity impact first, right? So in recent periods of volatility, what have been your observations in terms of how market participants potentially increasingly leverage automated solutions? Is that something that you've seen?

Carlos Gomez-Gascón: So in my experience, and this is more of human nature, we tend to stick to what we know works during periods of stress and market participants are basically doing the same thing. Now, the real stretch really comes from the traders on the dealer side, which increased volatility doesn't just mean that the market is changing faster, but also that there's more requests for price discovery and more people that want to buy or sell assets. So as a result, they become really stretched and automated solutions really help them express their views without the need to type every single deal with a price. So they can express things in terms of skews, spreads, widening, things of that nature that scale better than manually typing every single deal price.

Meridy Cleary: And Carlos, there are a number of emerging market benchmark reforms ongoing. I know we discussed regulation at the beginning of this podcast, South Africa's transition to ZARONIA, for example, and of course, other markets like Korea and Poland. So how does electronic workflow enhance efficiencies during and around those transition windows? And how are you monitoring that dynamic and these reforms that are ongoing?

Carlos Gomez-Gascón: When these reforms happen and some of these benchmarks transition, the beginnings are slow and they tend to be very controlled. So in other words, manual, then, you know, the next step is electronification. So you know, once we know that it works, then we look into the electronic workflows and finally they get automated. I think maybe in other types of markets, it may work a little differently, but in emerging markets, at least, that's the more natural process, you know, manual, electronic, automated.

Meridy Cleary: Well, Carlos, thank you so much. This has been a great walkthrough in terms of top themes in EM, rates trading, how electronification and automation are evolving, enhancing workflows. So thank you so much for your time. I really enjoyed it. Thank you.

Carlos Gomez-Gascón: Absolutely. It was a pleasure spending this time with you.

Meridy Cleary: And to our listeners, please stay tuned for more FICC Market Structure features on this channel. Should you wish to discuss any of these themes mentioned today, please reach out to your J.P. Morgan sales representative. Thank you. Have a great day.

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