July 6, 2021  |  Emerging Markets Debt
5 Differentiators in Emerging Markets Debt

Head of Emerging Markets Debt Team, Portfolio Manager

Marcelo Assalin, CFA, is the head of William Blair’s emerging markets debt (EMD) team, on which he also serves as a portfolio manager. He is also a member of William Blair Investment Management’s leadership team. Before joining William Blair, Marcelo was head of EMD at NN Investment Partners, a role he began in 2015, and lead portfolio manager for blended debt portfolios. Previously, he was the lead portfolio manager for NNIP’s local currency strategies. Before joining NNIP in 2013, Marcelo was a senior EMD portfolio manager and head of emerging market sovereign debt and local currency at ING IM USA (now Voya Financial). Before that, he worked in various capacities, including CIO from 2005 to 2008, at SulAmerica Investimentos. Marcelo began his career as a credit analyst at Bank Boston in Sao Paulo, covering Brazilian companies. Marcelo received a B.A. in business administration & accounting from the University of São Paulo.

Portfolio Manager

Marco Ruijer, CFA, is a hard currency portfolio manager on William Blair’s emerging markets debt (EMD) team. Before joining William Blair, Marco was the lead portfolio manager on NN Investment Partners’ EMD team, where he was responsible for managing EMD hard currency portfolios. Before joining NNIP in 2013, Marco was a senior fund manager for EMD at Mn Services in the Netherlands, where he managed various EMD portfolios. Before that, he worked with Mn Services’ investment strategy and risk management team. Marco began his career in 1998 as an investment trainee at Mn. Marco received an M.A. in international financial economics from the University of Amsterdam.

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While we believe overall market conditions should remain favorable for emerging markets (EM) debt, the pandemic created idiosyncratic risks and diverging prospects across EMs. This makes it critical to have a clear understanding of the opportunities and risks these markets represent—and our hard currency strategy’s combination of top-down macro views with rigorous bottom-up credit analysis helps us navigate these opportunities and risks. Here are five key differentiators to our approach.

  1. Obsession With Diversification Limits Drawdown Potential

Some investors associate EM debt with high risk, but the annualized default rate in sovereign EM debt over the past 20 years is 1%, much lower than other credit asset classes. Still, because EM debt is a high-yield asset class, defaults are a consideration, and to minimize our exposure to them, we use several risk-management strategies.

Risk management is a critical, continuous element of our investment process. We take concentration risk seriously and believe a diversified portfolio will limit drawdown risk and provide for better long-term risk adjusted returns. We typically hold a large number of relatively small positions (typically 1% active cash exposure to a single country), rather than concentrating too much risk in a small number of countries. We also analyze risks in the portfolio from different perspectives: active cash allocations, active spread duration, duration, liquidity, and sensitivity to relevant global risk factors.

Our research process is integrated into William Blair’s proprietary research tool, Summit, which allows us to analyze sovereign fundamentals and identify country and security selection opportunities with greater efficiency. Summit systematically categorizes fundamental and market data in an easy-to-use platform, allowing us to share information and collaborate with other William Blair investment teams. Having input from many perspectives, as well as insight into the interaction of market and economic dynamics between EMs and developed markets, reinforces and complements what we do. 

  1. Alpha Strategically Optimized Across the EM Debt Market

Our process is structured to strategically combine several sovereign and corporate debt options to optimize our risk-adjusted return potential.

The EM debt universe consists of three main types of debt: 1) sovereign debt, which is issued directly by EM countries; 2) quasi-sovereign debt, which is issued by companies that are owned by governments or have explicit government guarantees; and 3) corporate credit, which is issued by companies based in EM countries.

The core of our portfolio consists of hard currency sovereign and quasi-sovereign bonds, which is the biggest component of EM debt. The J.P. Morgan Emerging Markets Bond Index Global Diversified (EMBI-GD), which represents the sub-asset-class, has 74 issuing countries. Historical default rates are low at approximately 1% annualized with restructuring rates typically higher than corporate bonds.

We have a strategic overweight to frontier markets because we believe the risk premium there is mispriced.

We tend to overweight frontier markets (up to 25% of assets) because we believe the risk premium there is structurally mispriced. Of the 74 countries in the J.P. Morgan EMBI-GD, 36 are also in the frontier-focused J.P. Morgan Next Generation Markets Index. This index has a slightly higher historical default rate of approximately 1.5% annualized but compensates investors with a higher carry.

We also typically hold up to 15% in hard currency corporate debt because we believe a combination of hard currency options will optimize our risk-adjusted returns. This sub-asset-class is usually represented by the J.P. Morgan Corporate EMBI Diversified Composite Index, which represents 42 countries and has a low historical default rate of 1.5% annualized.

  1. Beta-Bucket Approach Optimizes Allocation of Risk Budget

We assess global market dynamics monthly using our top-down analytical framework. The framework consists of two pillars: 1) global macro conditions and 2) the fundamental backdrop, technical conditions, and valuations for EM debt.

The output of the process is a top-down score that reflects our views of the asset class and informs the allocation of the risk budget throughout the portfolios.

To achieve a more efficient deployment of the risk budget, we divide the investable universe into three risk buckets—high-beta countries, medium-beta countries, and low-beta countries—and allocate the risk budget to risk buckets according to our top-down score.

Segmenting the investable universe into different risk buckets also provides for more efficient relative value assessment among countries. For example, Argentina neighbors Chile, but these countries offer totally different credit risks. Argentina is better compared to Ukraine than Chile, and Chile is better compared to Poland than Argentina.

Segmentation also provides for more accurate risk management. When investing in high-beta countries, we look at how much active cash we have allocated, because ultimately the biggest risk is that investors are not repaid in full. When investing in low-beta countries, on the other hand, the risk of default is very low. The debt of these countries tends to be highly correlated with U.S. Treasury yields, and the most relevant risk metric there is spread duration, so we look more closely at active spread duration contributions in that space.

  1. Sovereign Risk Model Identifies Mispriced Opportunities

The next step in the process is country selection within each risk bucket. The starting point for our country selection process is our proprietary Sovereign Risk Model (SRM), a framework that we have developed over more than 25 years of quantitative research in EM debt.

The model uses a combination of factors to score each country in our investable universe along two dimensions: fundamentals and environmental, social, and governance (ESG) factors.

The fundamentals score is constructed by looking at 14 macroeconomic variables, which can be grouped into three major categories that we believe are critical components of credit analysis: economic growth and resilience, public finance health, external balances and buffers.

The output of the model provides a common starting point—an unbiased data set encompassing the entire EM debt universe. Portfolio managers use SRM scores as the basis for country selection, complementing the scores with qualitative analysis of additional factors—such as technical conditions, sustainability trends, and vulnerability to climate risks (using our ESG dashboard), and geopolitical and political dynamics—to add nuance to the sizing of positions.

We then use the risk scores that come from our model to help assess fair value for sovereign spread levels, as the chart below shows.

Once we define the countries we want to overweight or underweight, the next step is to define the most efficient instrument selection: sovereign debt, quasi-sovereign debt, or corporate credit debt—all of which we look at in conjunction with the attractiveness of the different points of the yield and spread curve.

  1. Spread Over Sovereign Model Captures Corporate Opportunities

To select corporate credit issuers, we use a proprietary framework called Spread Over Sovereign (SOS) model.

This bottom-up approach combines a valuation screen, fundamental analysis, and a risk-management framework to help capture the excess spread corporates offer over their countries of risk, while avoiding exposure to excess idiosyncratic corporate credit risk.

Corporate credit analysis is carried out by the team’s dedicated analysts using a multi-risk-factor framework that includes financial risk, business profile risk, management and strategy risk, debt structure, ESG factors, and sovereign risk. By adding spread while avoiding issuers on a deteriorating credit trend, the team believes it can improve the risk/return profile of portfolios. 

Potential Benefits

Despite an improvement in bond liquidity, EM debt remains under-researched and not properly understood. As a result, it is under-owned, with global fixed-income indices and institutional investors under-allocated. But this creates inefficiencies, which translate into opportunities to unlock alpha through rigorous research and risk management. We believe the differentiators of our process—described above—help us capture and exploit opportunities on behalf of our investors.

Marcelo Assalin, CFA, is a portfolio manager on and head of William Blair’s Emerging Markets Debt team.

Marco Ruijer, CFA, is a portfolio manager on William Blair’s Emerging Markets Debt team.

Head of Emerging Markets Debt Team, Portfolio Manager

Marcelo Assalin, CFA, is the head of William Blair’s emerging markets debt (EMD) team, on which he also serves as a portfolio manager. He is also a member of William Blair Investment Management’s leadership team. Before joining William Blair, Marcelo was head of EMD at NN Investment Partners, a role he began in 2015, and lead portfolio manager for blended debt portfolios. Previously, he was the lead portfolio manager for NNIP’s local currency strategies. Before joining NNIP in 2013, Marcelo was a senior EMD portfolio manager and head of emerging market sovereign debt and local currency at ING IM USA (now Voya Financial). Before that, he worked in various capacities, including CIO from 2005 to 2008, at SulAmerica Investimentos. Marcelo began his career as a credit analyst at Bank Boston in Sao Paulo, covering Brazilian companies. Marcelo received a B.A. in business administration & accounting from the University of São Paulo.

Portfolio Manager

Marco Ruijer, CFA, is a hard currency portfolio manager on William Blair’s emerging markets debt (EMD) team. Before joining William Blair, Marco was the lead portfolio manager on NN Investment Partners’ EMD team, where he was responsible for managing EMD hard currency portfolios. Before joining NNIP in 2013, Marco was a senior fund manager for EMD at Mn Services in the Netherlands, where he managed various EMD portfolios. Before that, he worked with Mn Services’ investment strategy and risk management team. Marco began his career in 1998 as an investment trainee at Mn. Marco received an M.A. in international financial economics from the University of Amsterdam.

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Glossary

INDICES
The Bloomberg Barclays U.S. Aggregate Bond Index is a broad-based benchmark that measures the investment grade, U.S. dollar-denominated, fixed-rate taxable bond market, including Treasuries, government-related and corporate securities, mortgage-backed securities (agency fixed-rate and hybrid ARM pass-throughs), asset-backed securities, and commercial mortgage backed securities.

The MSCI ACWI IMI Index is a free float-adjusted, market capitalization-weighted index that captures large, mid, and small cap representation across developed and emerging markets.

The MSCI ACWI ex-US IMI Index is a free float-adjusted, market capitalization-weighted index that captures large, mid, and small cap representation across developed and emerging markets, excluding the U.S. The Value and Growth Indices are a subset of the Index that adopt a framework for style segmentation in which value and growth securities are characterized using different attributes. Multiple factors are used to identify value and growth characteristics.

The MSCI ACWI Small Cap Index is a free float-adjusted, market capitalization-weighted index that captures small cap representation across developed and emerging markets.

The MSCI Emerging Markets Index is a free float-adjusted, market capitalization-weighted index that is designed to measure the equity market performance of emerging markets.

The MSCI World Index is a free float-adjusted, market capitalization-weighted index that is designed to measure the equity market performance of developed markets.

The Russell 2000 Index is a market capitalization-weighted index designed to represent the small cap segment of the U.S. equity universe.

Index performance is for illustrative purposes only. The indices are unmanaged, do not incur fees or expenses, and cannot be invested in directly.

TERMS
Alpha is a measure of an investment's return in excess of the market's return, after both have been adjusted for risk.

Beta is a measure of the volatility of an investment relative to the overall market, represented by a comparable benchmark.

Half-life is a statistical measure of the time required for the discrepancy between price and value to contract by half of its starting value. Fundamental value estimates are based on the Dynamic Allocation Strategies team's proprietary research.

P/E Ratio is a measure of valuation which compares share price to earnings per share, calculated using estimates for the next twelve months.

Standard deviation is a statistical measurement of variations from the average.

QUANTITATIVE MODELS – FACTOR DEFINITIONS
The William Blair Earnings Trend Model captures information about short- and medium-term changes in analyst estimates in an attempt to anticipate future estimate changes and stock performance. The score combines measurements of earnings revisions, momentum, and earnings surprise.

The William Blair Valuation Model combines varying metrics used to characterize the relationship between the stock’s trading price and its intrinsic value. By going beyond using only one or two measures, the model attempts to build a more holistic version of a stock’s worth vis-a-vis the market. The score combines measurements of earnings/cash flow based, asset-based, and model-based factors.