Thomas Haugaard - Hard Currency Emerging Markets Debt at JHI (EP.356)

0:04Hello, I'm Ted Seides and this is Capital Allocators. This show is an open exploration of the people and process behind capital allocation. Through conversations with leaders in the money game, we learn how these holders of the keys to the kingdom allocate their time and their capital. You can join our mailing list and access premium content at CapitalAllocators.com. All opinions expressed by TED and podcast guests are solely their own opinions and do not reflect the opinion of capital allocators or their firms. This podcast is for informational purposes only and should not be relied upon as a basis for investment decisions.

0:44Clients of capital allocators or podcast guests may maintain positions in securities discussed on this podcast. Hi, guest on today's Sponsored Insight is Thomas Haugel, a portfolio manager on the Emerging Markets Debt Hard Currency Team at Janus Henderson Investors, where he helps manage$1.3 billion just one year into the team's tenure at JHI. Thomas spent the last decade in the strategy with the same team, a prior decade in emerging markets research, and a decade before that in academia studying emerging markets. Our conversation covers Thomas's path to investing, the opportunity set, and misconceptions of hard currency debt, and his team's approach to the sector.

1:27This is our third sponsored insight from Janice Henderson, following conversations with Daniel Grania on emerging market equities and Andy Acker on biotech. Those insights are replayed in the feed. Before we get going, we're hosting our fifth cohort of Capital Allocators University in New York City on February 22nd. CAU is designed for allocators with 5 to 15 years of experience to connect with each other and learn critical frameworks to help advance their careers. Rahul Moodgal and I will be joined by a few past guests on the show for a day filled with presentations about skills, Q &A, and small group discussions.

2:10For those who have attended one of the first four cohorts, we're now ready for you to return for a second semester too. Spots are limited, so hop on the website and register today. Thanks so much for spreading the word about Capital Allocators University. Please enjoy a conversation with Thomas Haugoff. Thomas, thanks so much for joining me. Very pleased to join you. Why don't we start with your first interest in emerging markets? Well, it's been a long journey. I think my first interest in EM was really an academic interest. this was during university back in the late 90s that's where you saw the financial crisis you saw the Asian financial crisis you had the backdrop of the Mexican crisis in the 80s and you had other crisis in Latin America in the 90s so for me the academic interest in understanding how a financial crisis plays out and the implications and how you can avoid it I think that was the first interest in EM because back then, financial crisis was really an EM concept.

3:22What did you learn from that early academic research? Well, I learned that if you make the wrong policy decisions, it can have huge implications. These countries had fixed exchange rates and they opened up and attracted a lot of capital. They had a very long period of high growth. So in the short term, those policies had huge potential. You saw a lot of catching up in many of the Asian economies, including Thailand, Indonesia, Korea. And then you saw the implications of financial markets speculating in these economies. You saw huge short-term capital flows being channeled into property sectors and other investments that didn't really generate hard currency in the long term.

4:08And eventually, if you don't accumulate FX reserves and you have a lot of risk taking and you assume that you have fixed exchange rates, then there is a risk that you overshoot. And that's what happened. Then immediately when you started speculating about the sustainability of those fixed FX regimes, that's when it cracked. And then you saw the downside of it. So I think I learned from that, that financial markets are very powerful. Expectations can be self-fulfilling. And if you make the good policy choices, you can have a slow and steady catching up. And if you don't, it will be a bumpy ride and you can have capital flows coming in and out in a very brief moment.

4:49How'd you get your start as an investor? So I started off on sell side. So I covered mainly China, Latin America, or a Swedish commercial bank. But in terms of getting closer to the investment side of things, I did a short internship at Goldman. That was between my bachelor and master's degree. And that was the initial teaching of my interest in financial markets and emerging markets because I worked for Jakob Novy and I was back then head of the CE department, Economic Research of Eastern Europe. And I saw the power of convergence of developing countries. They were basically looking at the Romania's of this world and trying to figure out how being a part of the EU and potentially the euro area, how that would lead to convergence that we've seen in Southern Europe as well.

5:38And you saw some of the implications investment-wise in terms of interest rate convergence and the amount of wealth being generated in those processes, of course, piqued my interest quite a lot. I spent 10 years in the Central Bank, looking at EM, the Danish Central Bank. And then finally, in 2013, I moved to the buy side and decided that putting my hand on the plate instead of just writing research was the next step that I really would like to take. So when you saw the first 20 years, academia, Central Bank, and then the sell side, when it came time to move to the buy side, how did you decide what area of emerging markets you wanted to focus on?

6:22Well, the easy answer was that the opportunity that arose in 2013 was very unique. And you could say it could have been any EM asset class. And I would probably have jumped to it because it was about analyzing EMs. My now fellow colleagues, Bent and Jakob and Sreen, they were put together to set up a team from scratch to run an EMD hard currency strategy. So that position, I think in hindsight, was perfect in the sense that hard currency for me is one of the more analyzable asset classes of EM at the country level. And that is really what interests me is what happens at the country level. I'm not that motivated by the nitty gritty of understanding what a central bank does next week, how inflation moves.

7:12I like the bigger drivers of risk premium of countries. Especially, I like to look at policies and what are the consequences of economic policies. And those are some of the key drivers in hard currency. And it's a very fundamentally oriented asset class. I'd love to walk through the investment opportunity set in EM hard currency debt. And as a starting point, why don't you just walk through the basics of the differentiation between hard currency and local currency markets? Hard currency, the investment universe there is defined by EM countries issuing either in US dollars or euros, predominantly in hard currencies, which basically means that it's a credit risk asset class.

7:57There's no local currency risk, contrary to the local currency side, which is where the local FX risk is dominating historically those returns. So that is Brazil issuing in Brazilian RIAI. And of course, Brazil also issues in dollars. But we focus entirely on hot currency space. What does that investment universe look like? Hot currency as an asset class constitutes around 1.3 trillion USD. It's very comparable in size to the US high yield market. And you could say the hot currency space is dominated by large sovereigns. So you have quite a lot of issuances that are above 1 billion. So it's a relatively large sovereign and relatively liquid market.

8:40You find more than 80 countries issuing hard currency. And that number of countries has more than doubled in the last 20 years. The local currency, you could say benchmark universe is more narrow. It is around 20 countries. So the benchmark that we typically use, which I think is a good description of the asset class, is the JP Morgan's MB Global Diversified. And that benchmark has close to 70 countries. It is only US dollar bonds from the sovereign and 100 % state-owned companies. So what we call qualsides. In that benchmark, no country weighs more than 5%. So you can imagine if you have 70 countries, they all weigh less than 5%.

9:22It's a very diverse group of countries that you have there. In the local currency space, The benchmark is a GBIEM, and that is where you can have countries weighing up to 10%. I think if you take the top 10 countries in the MB, the hard currency index, they constitute around 42 % of the total index. If you take top 10 names in the local currency index, it's around 86 % of the index. So it is a very wide, diverse asset class. And I think globally, it's probably, at the country level, the most diverse asset class that you can find. And remember, it constitutes around 50 % to 60 % of global GDP and 80 % of the entire global population.

10:07So it's an asset class that is very difficult to avoid having some exposure to, if not directly, then indirectly. What is the regional diversification like, the 70 countries in terms of concentration? It is widely split all over the globe. So one thing that is peculiar about hard currency is compared to other EM asset classes is that China is a relatively small part of it. You typically see China being a very big part of other asset classes. So EM equities, it's huge. It's very difficult to avoid China in many ways. In the hard currency, in the SBI universe, and in the MB, it's probably around 4.5%.

10:47So China is a much smaller part than it is in most asset classes, but you have a relatively equal distribution across regions in EM hard currency. At that asset class level, what are the drivers of return as you look at how you're going to generate returns in this space? So total return comes from a combination of carry and potential capital gains. So in the hard currency, the underlying interest rate is the US treasury yield. And it's a relatively long duration asset class, so duration a little less than seven years. That means that you can imagine what kind of volatility you've seen in total return in that asset class, just from the basic fact that you've seen massive volatility in US treasury yields this So you have a developed market component of your total return, which is movements in U.S.

11:42Treasury yields and the carry that you get from that if nothing changes. We are not focused on that. We focus entirely on the EM side of the asset class. So we focus entirely on the risk premium, the spread that you get on top of U.S. Treasury yields. And we focus entirely on figuring out where that is going at the country level. So if Kenya trades at a spread of 600 to US treasuries, my job is to figure out if that is fair or not. And if it's not, then to take a position on it. So you have these two components, a DM component and an EM component. How do you think about credit risk and default risk in these countries?

12:21That is an immensely complicated question because it goes to the very core of our investment process is how to understand sovereign credit risk. So it requires somewhat lengthy explanation, I would say. Ultimately, credit risk is about the ability and willingness to pay. The risk premium for a country is an expression of the default probability and loss given default. And that's a combination of these two factors of ability and willingness to pay. That defines the risk premium for a country. And you could say, my job is to figure out if those two in combination is expressed in the price. or not.

13:01I'd love to dive into that investment process. Before we do that, just at the asset class level, I'd love to hear some of your thoughts on misconceptions that people have about the asset class. You've seen many crises and some defaults and restructurings in EM at the country level. That is something that you haven't seen in developed markets for a very long time. So I think there's an inherent bias just from history. On top of that, I think there There is some inherent bias in the sense that most people understand developed markets, have faith in the institutions. There's a longer track record of prudent economic policies, independent central banks, and that track record is shorter for EM.

13:45So that gives rise to a bit of uncertainty about how stable they are in some countries. To answer your question, it's very difficult to talk about 1EM because you can dig into EM. It has 80 countries or more in it. So, of course, you can find countries where there's reason to be pessimistic and where reality is probably even worse than perception. And there are definitely a lot of countries where reality is better than perception. We also weigh down a little bit by some of the bad names in the investment universe. It is far more likely that you will see headlines that are negative. You won't see a headline in any of the popular media saying Costa Rica approved a fiscal reform back in 2018.

14:28when in fact that was very important for the country and it put it on a path that is far better than what many people feared. And you probably also see more news about Venezuela. Russia is the obvious. Turkey mentioned some of these controversial leaders. Venezuela was sanctioned and out of the asset class and now seems to be coming back. Russia is out of the asset class as well, given sanctions and the war in Ukraine. But some of these bad names are inherently connected to emerging markets, and that creates a sense of risk. And we're forgetting many of the very normally functioning and a middle-income, somewhat boring EM countries.

15:10And there are plenty of those where you've seen a significant transition to policy setups that are very similar to developed markets. And that is not something that reaches a lot of headlines, but it is something that has been happening in the past 20 years, I would argue. When you bring all of this together, the underlying characteristics, some of the misconceptions, at that index level, I'd be curious to hear both the history and maybe expectations of just the return and risk characteristics of the universe itself. If you just look at sharp ratios, simply look at the return relative to volatility, and you rank it, I think it's relatively competitive as a class.

15:54So definitely indicating that there is some kind of premium to be harvested. And I think we've been doing this for 10 years and we have consistently seen how you can generate alpha. I think it's one of the asset classes where there are good alpha opportunities. And I think the history, not just for us, but for hard currency managers in general, it is an asset class with a lot of inefficiencies at the country level or even at the security level. I'd love to turn to how you go about doing it. When you have a universe, you said, of 70, 80 different countries to look at, what team do you have in place to be able to cover the world?

16:34This is probably the question that we've been facing the most when meeting institutional investors because they look at our team. And we are a team of four that back in 2013 was put together to design a hard currency strategy from scratch. And the way we chose to set it up was somewhat, I would say, unusual, where we have Jacob and Bent on the portfolio management side, risk management side, liquidity management, and responsible for picking bonds within countries. And then we have myself and my colleagues on the country research side. So now you're already half the number of people looking at countries, and you still have 80 countries to look at.

17:15we realized back then that we need to build some tools that can help us. It is not feasible to cover 80 countries ad hoc. It's not feasible to know what's going on in all these 80 countries all the time. That thinking where you think that you understand what's being priced in a country, and then you have to form an opinion about what's going to happen in the next one, two, three months, that is not a feasible approach with our setup. So we decided back then that we will try to build some tools that can guide us in systematically assessing sovereign credit risk. And that sounds very fluffy, I would say.

17:52But what it basically means is that can you find some data out there that can help you identify what is important for sovereign credit risk? And can you use that data to guide you in forming views of sovereign credit risk? The second question is, can you form a view of sovereign credit risk that is investment relevant? Something that seems to drive markets somehow. Those were some of the basic questions we asked back in 2013. And we studied many different measures of sovereign credit risk. Because you could say, ultimately, you have three kinds of expressions of sovereign credit risk. You have the actual defaults.

18:33That is a binary variable. either a country is defaulting or not. And you can try to gather all the macroeconomic financial data and even some governance data, if you can find that, and you can model that and see if it explains those incidences of defaults, because that is what you would like to say something about, the probability of default, and then you would have to make some assumptions about the recovery value. But in 2013 and 2014, when we worked on these tools, we didn't have that many defaults. And you had several serial defaulters. It means that when you stress test the model like that, you put in some extra defaults, they have massive implications for what matters and how it matters.

19:13And it was a very unstable exercise we did back then. Then we looked at the risk premium in the market spreads. So as I mentioned, Kenya, let's say trading 600, Mongolia trading 500. And the variation in all these spreads, that's the market interpretation of what sovereign credit risk is. And ultimately, you could argue what we would like to say something about is what's the fair spread? And modeling those with economic, financial and governance variables, we realized that this very high frequency market data with a lot of noise from the markets, beta movements, supply, technical things that influence risk premium, again, the relationship to these more slow moving macroeconomic and governance variables was not very clear.

19:59So we ended up looking at ratings. So the question is, is there enough information in ratings between countries and over time that will allow you to understand sovereign credit risk and allow you to understand it in an investment relevant way? Because we can easily agree that ratings are public information. There's no market relevant price information in those ratings. You need to uncover what's the dynamic nature between how markets are pricing sovereign risk and ratings. And we did a big study of that. And we realized that, first of all, ratings move very slowly. They tend to move with a lot of trend and persistence.

20:37They don't move up and down in a short period of time unless you understand there's a very clear shock. So for us, intuitively, that was important because it suggested that there is measure of sovereign credit risk that moves slowly with trend. And you can imagine, and that goes to your question, how do you cover all these countries with two people? If you can identify something that is more slow moving with trend, you can reduce the analytical frequency needed to understand it. But of course, it needs to be relevant for the market. So we looked at how the market trades different types of ratings processes.

21:15And the way we did that was we calculated an implied market rating. This is basically just a statistical way of translating a spread for Kenya of 600 into a rating, which means how is the market pricing Kenya relative to all the other EMD hard currency countries? Is it a B plus? And we tracked that for all these countries in our investment universe. And we realized that there is a systematic relationship between ratings and that market pricing. The dynamics of that relationship is market is forward-looking one and a half, two years. And this is a stylized fact. There are plenty of deviations from that depending on specific economic development phases.

21:57But in general, the market is forward-looking by one and a half, two years. So you need to form an opinion about where ratings are going. An additional piece of information from that study was that there seems to be some inefficiencies in the way that the market behaves when you have turning points, when you move from a positive rating story to a neutral rating story, or when you move from a downgrade story to a stable story. At the end of a positive rating story, we almost always found that the market is pricing one to two notches too much of a good story. So when credit risk is actually not going down anymore, there's a tendency for investors to stick with a good story for a little bit too long before you realize that it's no longer an improving story.

22:42And I would say even worse so on the downside, that investors tend to punish the bad stories too much. So it takes time to understand that it's no longer a deteriorating story. So those two observations convinced us that we try to predict where the rating is going one and a half, two years out, and build a model that helps us to do that in a systematic way. And then we need to take into account what's the journey from today till two years out. How is that ratings process going to play out? And how will that influence this behavioral inefficiency that we've seen in the market where you over and undershoot depending on if the ratings process is changing direction?

23:22We believe firmly that the way to understand sovereign risk needs to have a good foundation, an empirical foundation. We believe that variation in ratings in the past 20 years over time and between countries allows us to extract that information in an objective way. So we built a statistical model that identifies what explains ratings. It identifies around 85 % of the entire variation. It gives us all of the risk factors, which could be something like GDP growth, debt, current accounts, all the traditional ones that you would expect to be in there and some other ones that you probably would not have expected.

24:00And it also identifies their relative importance in terms of these betas. How much does debt metrics matter? How much does growth matter? Ultimately, the question of aggregating all these risk factors is the challenge for us. And this way, we collect forecasts from different sources to try to figure out where the rating is going. We are, of course, not ignorant in the sense that we know that everything cannot be modeled and quantified. So you have to have a combination of the quantitative empirical foundation. The better, the cleaner, the more objective it is, the better starting point it is to understand sovereign risk.

24:35And then you need to qualitatively take into account the things that you know are not accounted for in the quantitative model. So a combination of quantitative and qualitative analytical frameworks is needed to understand sovereign risk. in a forward-looking, market-relevant way. I'd love to break down some of the key components that go into your model and try to understand a little more about what you've seen quantitatively and then where you have qualitative judgments. So if you take a closer look at some of the key factors that drive sovereign risk that you need to understand and try to predict, most important is the fiscal indicators.

25:15Because after all, it is about the ability to service your debt or the willingness. So different measures of public finances in terms of the sheer size of debt to GDP, but also in terms of interest costs, debt servicing costs and the debt profile and different things. Those are key to understand what's the ability to pay. And debt dynamics generally is at the very top of the list of empirically relevant factors. But what might surprise a lot of people is that we also included the World Bank governance indicators in the statistical model. And the second most important variable to understand where ratings are going is regulatory quality.

25:56That captures the perceptions of the ability of the government to formulate and implement policies and regulations. It's basically like a great book of how market-friendly is a government? How does it allow the private sector to grow? And I think that has very important implications because it says that not only do we need to understand fiscal policy, because that is already captured in the fiscal policy variables, outside of fiscal policy, general issues of governance that influences how the overall perception of the quality of policies and institutions, that matters a lot. But you cannot predict for 80 countries governance measures.

26:38So we have spent a lot of time to try to figure out what pushes these governance variables in a certain direction. It can be fiscal policy focused in Brazil. It can be structural reforms in other countries where they have perhaps good setup in terms of economic policy. It is really more of a country-by-country assessment. When you look at the perspective of, say, democratic to autocratic governments, have you found in your work that a certain type of political regime is better or worse for the credit risk of the sovereign over time? Systematically, I'm not able to give you a clear answer on that.

27:19It is very clear that in most cases where you have less democratic countries, you will also find that across the board, governance measures, institutions, regulatory quality, rule of law. In most cases, they are a lot lower, which means that sovereign risk is higher. What is complicated is that political stability is sometimes very high when you don't have elections. Now we're talking about a small subset of countries in the investment universe. But what that means is that you actually have a very high degree of political stability. And we all know that political change comes with uncertainty.

27:57And this is not just an EM thing. It's a US thing, it's a European thing that the political cycle creates uncertainty. So I would say there are pluses and minuses in terms of political systems from a credit risk perspective. In theoretical terms, if you have the benevolent dictator, the ultimate dictator allocating resources efficiently, making all the right decisions with a high degree of willingness to pay, that would be a very low risk setup. but at the same time, it would not be a democracy. Unfortunately, autocratic regimes are not the benevolent dictator in any way. There is a lot of risk with it, and I think we've seen many cases in the past, and luckily some of these countries like Zimbabwe, et cetera, are not in our investment universe.