Emerging Market Bonds: Hard Currency Security Selection for Systematic Investors
Emerging market bonds sound exotic. But they are actually a massive, growing slice of the global fixed income universe. We’re talking about $29.6 trillion in total EM fixed income as of 2020. And yet most investors either ignore them completely or treat them as a single homogenous bucket of “risky stuff.”
Chapter 7 of Systematic Fixed Income shows that a systematic approach to picking these bonds can produce strong, diversified returns. The trick is knowing what signals to use and how to deal with the data challenges that come with sovereign debt from developing countries.
What Are Hard Currency Bonds?
Hard currency bonds are bonds issued by emerging market countries but denominated in US dollars. The “hard” currency part means the issuer owes you in USD, not their local currency.
This matters a lot. A country like Turkey or Brazil can always print more lira or real to pay off local currency debt. But they can’t print US dollars. So when an emerging sovereign issues a hard currency bond, the investor faces real credit risk. If the country’s finances deteriorate, if their currency collapses, if their exports dry up, they might not be able to generate enough dollars to pay you back.
Richardson focuses on the JP Morgan Emerging Market Bond Index Global Diversified (EMBIGD). This index tracks USD-denominated sovereign and quasi-sovereign bonds from about 73 countries. It had a market cap of around $1.15 trillion in 2020. Each country is capped at 10% of the index to prevent any single country from dominating.
As of end of 2020, the index held 861 individual bonds. 546 from sovereign entities and 315 from quasi-sovereign entities (government-owned or government-guaranteed organizations). The median sovereign issuer had about four bonds outstanding.
The Risk You’re Actually Taking
Here’s an important number. Over the 2002 to 2020 period, 82% of the return variation in hard currency EM bonds came from spread risk (the credit component), and only 18% came from the risk-free component (US Treasury yields).
So when you buy these bonds, you’re mostly betting on sovereign credit risk, not interest rates. That’s why security selection in this space is really about figuring out which countries are more or less likely to struggle with their dollar obligations.
The Data Problem
This is where EM bonds get tricky. With corporate bonds (Chapter 6), Richardson used structural models like distance-to-default. Those models need clean measures of leverage and asset volatility. For a corporation, you can get balance sheets, market caps, equity volatility. The math works.
For a sovereign country? Not so much. How do you measure the “leverage” of an entire nation? Countries don’t file GAAP financial statements. They don’t practice accrual-based accounting. Tracking what a government truly owes is hard even in developed markets, let alone emerging ones.
So Richardson takes a different approach. Instead of forcing sovereign data into a structural model, he uses a reduced form approach. He measures the key ingredients directly and puts them into a regression.
The Value Signal
The value signal uses a regression that looks like this:
Spread = a + B(RATING) x RATING + B(VOLATILITY) x VOLATILITY + error
RATING is the average credit rating from the major agencies. VOLATILITY is the trailing 12-month standard deviation of country equity returns.
The regression is estimated using an expanding window panel approach (because the cross-section is small, typically under 25 sovereign entities with liquid CDS contracts each month). Time fixed effects soak up common macro movements in spreads.
The residual from this regression is your value signal. A large positive residual means the country’s credit spread is wider than what its rating and volatility would suggest. That’s a “cheap” bond. A large negative residual means the spread is tight relative to fundamentals. That’s “expensive.”
It’s simple. It captures the two core ingredients of default risk (leverage via ratings, and volatility). And it avoids the data problems that make structural models impractical for sovereigns.
The Momentum Signal
Momentum for EM bonds is measured using an equal-weighted combination of three six-month trailing return metrics:
- CDS returns for that country
- Foreign exchange returns (local currency vs. USD)
- Country equity returns
If all three are trending positively, that’s a strong momentum signal to go long that country’s credit. The idea is that positive trends in a country’s CDS, currency, and stock market all point to improving economic health.
Richardson also mentions that fundamental momentum measures can help. Things like improving GDP growth expectations or declining sovereign debt levels could reinforce the price-based signals. But the chapter sticks with the simpler price-based version.
The Carry Signal
Carry is the return you earn if nothing changes. For EM hard currency bonds, it’s measured simply as the level of the five-year CDS spread at the start of each month. Countries with higher CDS spreads offer more carry. You’re collecting a bigger insurance premium by selling protection on their debt.
Of course, there’s a reason spreads are higher. These countries are riskier. But historically, the carry premium has been more than enough to compensate for the occasional blowup. This pattern holds across many asset classes and time periods.
The Defensive Signal
Defensive investing means preferring safer, lower-risk sovereigns that deliver higher risk-adjusted returns. Richardson builds this signal from two measures:
- Expected inflation from Consensus Economics forecasts. Lower expected inflation means better monetary discipline.
- Asset/Debt ratio combining foreign reserves plus GDP (grossed up by growth expectations) in the numerator, and government external debt plus 50% of private external debt in the denominator. Higher ratios mean lower leverage.
The defensive theme is an equal-weighted combination of both.
How Do They Perform?
Richardson tests all four signals using long/short portfolios built from five-year CDS contracts on 25 emerging sovereigns from 2004 to 2018.
Individual Sharpe ratios range from 0.34 (defensive) to 0.68 (momentum). But the real story is what happens when you combine them. The equally weighted combination of all four signals produced a Sharpe ratio of 1.11. That’s very strong. And it works because the four signals have low correlations with each other.
Even better, the returns don’t just reflect traditional market risk premia. When regressed against the standard equity factors (market, size, value, momentum, quality, betting-against-beta) plus credit and term premia, the systematic EM signals show minimal exposure. These are genuinely orthogonal return sources. The combined portfolio’s alpha remains statistically significant even after controlling for all those factors.
What About Corporate EM Bonds?
The chapter briefly covers emerging market corporate bonds, tracked by the JP Morgan CEMBI index (about $500 billion in market cap). Research by Dekker, Houweling, and Muskens (2021) finds that similar systematic signals (value, momentum, low-risk, and size) work for EM corporates too. Both long/short and long-only approaches show attractive risk-adjusted returns.
But implementation is harder. Liquidity in EM corporate bonds is thinner. You may need relationships with more trading counterparties. The opportunity is real, but the execution challenges are bigger.
The Bottom Line
Emerging market hard currency bonds offer a genuine, large-scale opportunity for systematic investors. The same themes that work in developed market corporates (value, momentum, carry, defensive) also work here, even though you need different tools to measure them.
The data isn’t as clean. The models are simpler by necessity. But the payoff is a set of return sources with low correlation to each other and to traditional risk premia. For an investor building a diversified systematic fixed income portfolio, that’s exactly what you want.
The key insight from this chapter: don’t let the messiness of emerging market data scare you away. Adapt your signals, keep them simple, and let diversification across themes do the heavy lifting.
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Book: Systematic Fixed Income: An Investor’s Guide by Scott Richardson, Ph.D. Published by John Wiley & Sons, 2022. ISBN: 9781119900139.