Despite being an active manager, PIMCO understands the appeal of passive ETFs: They aim to provide efficient index-oriented exposure to a market, or beta, attempting to match the index’s return, before fees. However, most benchmarks are not investable; they provide a hypothetical stream of returns that ignores real and unavoidable investment realities, and that’s especially true of emerging market debt. For a variety of reasons, including illiquidity, high transaction costs, and nonstandard tax regimes, generic passive EM debt exposure provides returns that are often meaningfully less than index returns (see Figure 1). And these index-related issues are particularly painful for emerging market local debt. As a result, most EM index tracking funds tend to lag their indices by 70 to 90 basis points on average. It is thus no coincidence that it is here that we see some of the greatest investment opportunities.
Figure 1: Less than zero: The inherent drag of EM benchmarks
Despite periodic drawdowns driven by currency adjustments, EM local bond markets remain one of the favorite destinations for investors looking to diversify portfolio risk and capture attractive yield levels relative to developed markets. But there are real questions about how best to capture the benefits of the category.
Bad benchmarks, better beta?
EM indices in particular are very costly to replicate. This is the result of transactions costs as part of the rebalancing process, withholding taxes (for local instruments), fees and ill-timed portfolio flows.
As an example, the JP Morgan GBI-EM benchmark (the most common benchmark for EM local accounts) assumes zero taxes and transaction costs when calculating performance. Yet the government of Indonesia (representing close to 10% of the benchmark) actually levies up to 20% withholding taxes on investors. When all these various headwinds are added up, we estimate that generic passive replication of EM benchmarks creates an inherent drag of about 25 to 45 basis points —and that’s before management fees, which remain material given the resource intensity of the asset class.
With “smart” index construction, optimization and execution, we seek to eliminate these drags, bringing performance back in line with the benchmark before fees (see Figure 2).
Figure 2: PIMCO EM Advantage Local Bond ETF uses a three-pronged approach to overcome the deficiencies of traditional indexing.
The advantage of the Advantage (smarter passive exposures)
PIMCO EM Advantage Local Bond ETF tracks an index that is constructed in a different way: Instead of using the market value of outstanding debt as a weighting factor, the EM Advantage index uses countries’ GDP size as the factor driving the weight in the index. This construction logic results in less exposure to the most indebted countries and more exposure to larger economies including China and India, which are usually not well represented in traditional benchmarks. The EM Advantage index thus captures a larger share of EM GDP compared to traditional market-weighted indices like the JP Morgan GBI-EM GD, offering a fairer representation of emerging markets in an investor’s portfolio (subject to a maximum exposure of 15% per country).
Further, by setting a minimum eligible country rating at BB- and several liquidity and tradability tests, the index overcomes a hurdle for countries with illiquid or inaccessible local markets. In such situations, we look to build the exposure using currency forwards instead of bonds.
However, notwithstanding better representation of EM economies and higher quality, even the EM Advantage index suffers from the same performance drags. Given this reality, we believe EM investors should seek out “better beta” by exploring the following strategies, which seek to mitigate these benchmark-induced drags.
Smart optimization: Exploit inefficiencies while controlling for tracking error
As we have outlined, attempting to fully replicate the index or use some stratification approach can be costly and ignore market inefficiencies in EM local markets. Instead, we apply an optimization model to overweight and underweight securities in the index based on the mean reversion of carry and value factors in the underlying bonds, optimized against their estimated transaction costs. We manage risk by constraining total portfolio duration, country duration and curve exposure. And we take no benchmark-relative currency risk. The resulting portfolio very closely replicates the risk factors of the index while maximizing carry and exploiting the inefficiencies present in individual country curves.
Smart rebalancing and turnover management
Because any index must be traded monthly on a set schedule to adjust for additions and exclusions, and to maintain weight caps, investors may take advantage of trading inefficiencies by trading less frequently and sometimes in advance of regular index rebalancing. Optimal trading frequency, to reduce trading costs while maintaining reasonable tracking error, is between 3 and 3 ½ months. We can also anticipate large rebalance events in the index and trade ahead of those dates to save on transaction costs and avoid chasing illiquid markets. We also anticipate new issues, and with our scale we can seek to gain allocations to them ahead of their inclusion in the benchmark.
Finally, investing internationally can produce a drag on performance from taxes, based on the country and tax jurisdiction involved. In countries such as Colombia, Brazil, and Indonesia taxes are levied locally on income or on capital gains earned by an investor. We utilize various strategies, including offshore issuance, to minimize or eliminate the tax impact of investing in emerging markets with minimal tracking error.
Headwinds to performance in emerging market bonds are formidable. The median passive manager in emerging market local bonds have underperformed their benchmark by 70 to 90 basis points per year over the last decade. The strategies reviewed here may help to deliver “better beta” to investors interested in accessing emerging market local debt.