- For clients who are seeking more consistent excess returns over time, we sometimes explore different combinations of hard-currency EM government debt and corporates, together with EM local currency debt.
- Excess returns from different portfolio managers can be weakly correlated, so combining funds and strategies can result in more consistent alpha, generated across different economic regimes.
Emerging markets debt is not a homogeneous asset class, and this is something that asset allocators can use to their advantage. For clients who are seeking more consistent alpha over time, we sometimes explore different combinations of hard-currency EM government debt (EMH), hard-currency EM corporates (EMC) and EM local currency debt (EML). Here we’ll give a simple overview of some of the considerations.
Because EMH, EMC and EML are driven by different risk factors, and are therefore imperfectly correlated, it makes sense to blend them in structural asset allocation. In terms of tactical allocation, because of their different return patterns, they may offer opportunities for adding value via dynamic rotation.
How much of each EMD sector to include?
Over the last 15 years, EMH has outperformed EMC and EML. So, based solely on past returns, it’s difficult to justify adding corporates and local debt to EMH. But returns are cyclical, and when designing a blended strategy one needs to look at future return expectations rather than historical performance. For example, EM local currency returns have been muted by a persistently strong dollar in recent years but, by the same token, a change in the dollar’s fortunes would be positive for the sector. (The J.P. Morgan GBI-EM Global Diversified index has shown an average correlation of about -0.7 with the US dollar since 2003.)
From a diversification perspective, as shown in the table, at times EMC and EML have outperformed EMH, and the three sectors have historically been imperfectly correlated. For example, since 2005 the rolling 36-month correlation between EMC and EML has fluctuated between roughly 0.39 and 0.85. The correlation between EMH and EML has ranged between about 0.52 and 0.85.
Figure 1: Leadership Among EM Debt Sectors Rotates
Calendar Year Performance of EM Hard Currency, Corporate and Local Currency Debt (%)
Period January 2003 to July 2018
Past performance is not a reliable indicator of future performance.
Sources: T. Rowe Price and Bloomberg Index Services, Inc. January 2003 through May 2018. Returns measured in US dollar.
EMH: JP Morgan EMBI Global TR, EMC: JPM CEMBI Broad Diversified, EML: JPM GBI-EM Global Diversified.
For example, since 2005 the rolling 36-month correlation between EMC and EML has fluctuated between roughly 0.39 and 0.85. The correlation between EMH and EML has ranged between about 0.52 and 0.85.
As a simple exercise, we looked at three hypothetical strategic allocations blending EM debt sectors:
- Lower risk: 60:30:10 EMH:EMC:EML
- Medium risk: 33:33:33 EMH:EMC:EML
- Higher risk: 15:15:70 EMH:EMC:EML
Based on index-level data (in other words with no alpha from active management) over 12-month rolling time periods from January 2003 to May 2018, we found that:
- The lower-risk portfolio would have been the top performer 50% of the time
- Medium risk would have been the top performer 5% of the time
- Higher risk would have been the top performer 45% of the time
Blending EMD can also achieve diversification of alpha sources.
While outperformance by EM debt sectors tends to follow a cyclical pattern, actively managed funds also go through cycles, and these cycles of beta and alpha outperformance are not necessarily synchronized. For example, a manager that emphasizes risk management may add the most alpha when the market is falling and underperform when the market is rising.
Alphas from different portfolio managers can be weakly correlated (they don’t all deliver alpha at the same time) so combining funds and strategies can result in more consistent alpha, generated across different economic regimes.
How does this work in practice?
One way to approach the problem is to start with a long-term strategic allocation, defining desired neutral allocations to EMH, EMC and EML. Having an anchor allocation to each asset class can help minimise the impact of market timing. If desired, this can form the composite benchmark for the EMD blend portfolio.
The next source of value added is to express tactical asset allocation views using dynamic rotation across EMH/EMC/EML. The third, and in some cases most important, source of value added is at the security selection level, in the form of individual portfolio managers’ idiosyncratic bottom-up research.
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