May 03, 2023
In uncertain times, taking on credit risk might seem to be flirting with danger. Even the late great David Swensen thought it unwise to go beyond the safety of U.S. Treasuries in the bond portion of a portfolio.1 But Vanguard’s research indicates that overweighting credit bonds—a broad category that includes U.S. corporate bonds and non-collateralized U.S.-dollar-denominated bonds from foreign agencies and authorities—can enhance long-term portfolio returns.
“Our research validates the credit risk premium, and long-term investors have historically been compensated for taking on that extra risk when implemented thoughtfully within a broader portfolio,” said Kevin J. DiCiurcio, senior investment strategist and head of Vanguard Capital Markets Model® development, and one of the authors of the recent paper Credit risk premia: Considerations for multiasset portfolios.
While some of the paper’s findings aligned with expectations, some did not.
“The findings do not mean investors should haphazardly add credit risk to their portfolio,” DiCiurcio said. “They have to be discerning and selective. Our research showed that there were considerable differences between credit sectors.”
For example, long-term credit should not be overweighted; historically, it has had higher volatility while delivering lower median premia than other sectors. Short-term credit delivered the best risk–return profile.
Emerging markets sovereign debt has historically provided higher returns with less volatility than high-yield U.S. corporate bonds. In Vanguard models for expected returns, that may partially reverse, with emerging markets having greater volatility over high yield but still delivering a modestly higher median return.
The paper looks at various theoretical portfolios for different risk profiles and how overweighting certain credit sectors would change the risk–return projections. The figure below is for a 60% stocks/40% bonds portfolio.
Notes: For legibility, the scales of the x- and y-axes are not the same. The dispersion of the dots would be larger horizontally than vertically if done to scale. Returns of U.S. investment-grade bonds, international bonds (currency hedged), short-term credit bonds, intermediate-term credit bonds, high-yield corporate bonds, and emerging markets sovereign bonds in USD are represented by, respectively, the Bloomberg U.S. Aggregate Bond Index, the Bloomberg Global Aggregate ex USD Index – USD Hedged, the Bloomberg U.S. 1–5 Year Credit Index, the Bloomberg U.S. 5–10 Year Credit Index, the Bloomberg U.S. Corporate High Yield Index, and the Bloomberg Emerging Markets USD Sovereign – 10% Country Capped Index. “4 totals” is a global diversified portfolio constructed using U.S. stocks, international stocks (unhedged), U.S. investment-grade bonds, and international bonds (hedged). For example, for a 60/40 “4 totals” portfolio, we used these proxies: for U.S. stocks, a 36% weighting in the MSCI US Broad Market Index; for non-U.S. stocks, a 24% weighting in the MSCI All Country World ex USA Index; for U.S. bonds, a 28% weighting in the Bloomberg U.S. Aggregate Bond Index; and for non-U.S. bonds, a 12% weighting in the Bloomberg Global Aggregate ex-USD Index – USD Hedged.
Source: Vanguard Asset Allocation Model forecasts as of December 31, 2022.
The “4 totals” portfolio is the base 60/40 portfolio with market-capitalization weightings of stock and bond exposures similar to broad market benchmarks. The three “asset mixes” have an overweight in various credit sectors, all of which raised expected returns but also with higher expected risk. The “VAAM-optimized 4 totals” portfolio sticks with traditional market-cap weightings within the major asset classes but changes the overall stock/bond allocation to roughly match the risk profile of the credit-tilted portfolios.
“What’s interesting is that the optimized portfolio had to increase the stock allocation by almost 5 percentage points to deliver an expected return similar to asset mix number 2 with slightly higher risk,” DiCiurcio said. “For investors seeking to raise expected portfolio returns, a credit tilt is worth considering.”
See the paper for more information, including credit allocations for other portfolios beyond the traditional 60/40 allocation.
1 David Swensen was chief investment officer at Yale University and widely regarded as the father of the Endowment Model that popularized alternative investments among institutional investors. Swensen, however, felt that most investors should avoid alternatives and just stick with stock index funds, real estate, and—within the bond portion of a portfolio—U.S. Treasuries and Treasury Inflation-Protected Securities (TIPS).
All investing is subject to risk, including the possible loss of the money you invest.
Diversification does not ensure a profit or protect against a loss. There is no guarantee that any particular asset allocation or mix of funds will meet your investment objectives or provide you with a given level of income.
Bond funds are subject to interest rate risk, which is the chance bond prices overall will decline because of rising interest rates, and credit risk, which is the chance a bond issuer will fail to pay interest and principal in a timely manner or that negative perceptions of the issuer’s ability to make such payments will cause the price of that bond to decline.
U.S. government backing of Treasury or agency securities applies only to the underlying securities and does not prevent share-price fluctuations. Unlike stocks and bonds, U.S. Treasury bills are guaranteed as to the timely payment of principal and interest.
High-yield bonds generally have medium- and lower-range credit-quality ratings and are therefore subject to a higher level of credit risk than bonds with higher credit-quality ratings.
Bonds of companies based in international markets are subject to national and regional political and economic risks and to the risk of currency fluctuations. These risks are especially high in emerging markets.
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The VCMM projections are based on a statistical analysis of historical data. Future returns may behave differently from the historical patterns captured in the VCMM. More important, the VCMM may be underestimating extreme negative scenarios unobserved in the historical period on which the model estimation is based.
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