Fixed-Income ETFs: A Complete Guide

Author: Marco Santanche

We have discussed the opportunities that can be captured with different strategies, including factor investing, trend following, and more. But there is an asset class that is often overlooked by retail investors: fixed income.

In recent times, the proverbial negative correlation between bonds and equities seems to have disappeared. If that is the case, it makes no sense to invest in fixed-income securities, since the returns are much more attractive on the equity side, and the protection benefits do not exist.

In this episode, we are trying to assess whether this is actually the case, and if fixed-income ETFs hide some unexpected benefit for our portfolio.

What is fixed income exactly?

The two main, traditional asset classes are equities and fixed income, if we exclude cash. As the name states, the difference between stocks and fixed-income securities is that they provide regular payments, often paired with a final payment.

A clear distinction here: fixed income is not an equivalent for bonds. While the latter are a subset of the former, we can still see other securities returning regular, fixed payments: even mortgages might fall into this category. Bonds are generally the most common instrument, and probably one of the most accessible to retail traders. Moreover, their assets under management are much higher than other asset classes, excluding equities (see ETF database).

The reason such fixed (and, as many might mistakenly think, “safe”) investments actually exhibit volatility and changes in price is due to the different risk sources they are exposed to. We can just think about the market issuing “better” bonds: there might be opportunities where for the same face value of the bond we might have a higher coupon rate. In any case, many conditions impact bond prices, including liquidity, credit crises, inflation, and so on.

In practice, a fixed-income security does indeed provide fixed payments (net of defaults and counterparty risk), but it is not as safe as it might look.

In terms of ETFs, we can slice the universe from many different angles:

1. Issuer type: bonds can be issued by sovereign entities, corporates, or municipalities. In terms of ETFs, we can also observe broad market ETFs, covering both sovereigns and corporates.
2. Geography: we can also split the different bond categories by geography, including continents, countries, or regions (e.g. Central Europe, Asia Pacific, etc.).
3. Time to maturity: it is also common to subset according to the remaining life of the bond, usually in buckets like 1-5 year, 1-10 year, etc.
4. Credit quality: bonds can be classified according to their credit risk. Usually, this means high-yield and investment-grade bonds.
5. Security type: even if we remain in the bond subdomain, we have many possibilities, including inflation-linked securities, mortgage-backed securities, floating vs fixed-rate bonds, etc.

Best year-to-date returns

What type of fixed-income ETFs has outperformed in 2023 so far? We can have a look at one of the most complete ETF databases, and try to make sense of the performance for these funds so far. I have not included two of the best-performing funds, one because it uses leverage and another one which seems a little redundant to TTT below.

Source: Bond ETF list

Some of the above categories might sound exotic to inexperienced retail investors. Collateralized loan obligations (CLOs) are a particular type of fixed-income security that is backed by a pool of debt (securitization). The risk is thus usually higher when compared to liquid sovereign or even corporate bonds, since the underlying pool might contain anything, and in exchange for the added risk, the interest rate is also higher.

Senior loans consist instead of securities issued by companies to finance business operations and refinance existing debt. The term “senior” stands for the priority of repayments of the debt, which means that they are the earliest to get repaid (and for this reason, they are safer than junior loans, providing the creditor with lower interest rates).

Finally, interest-rate-hedged securities aim at neutralizing the impact of changes in interest rate. This might include the use of derivatives like interest-rate swaps (IRS).

The different nature of these ETFs contributes to a variety of diversification and risk factors that might affect the funds" performance and their correlations with equities.

Fixed-income ETFs and equity ETFs

While the single ETFs might be difficult to select, especially when we dive into the technical differences of the underlying traded instruments, it is still worth investigating their individual impact and the broader equity indices. Moreover, we will take into account some of the most important fixed-incone buckets in the space, by including some of the most established ETFs in our analysis, like those in the table that follows.

Correlations

Provided that we can only analyze the past year (approximately) due to XCCC data availability, we can observe in the matrix the correlation of the selected funds.

TTT is the most negatively correlated fund of all. The main reason is its strategy, which aims at short selling fixed-income securities, focusing on long-term ones. And the most (negative) correlation is with BND, which consists of US investment-grade (sovereign) securities. Beware of names here: BND is marketed as a total bond market fund, but it consists only of a small subset of all the possible market segments we can think of in the fixed-income space. And this explains the almost opposite correlation with TTT, which - as the name states - is short US Treasuries.

Another interesting finding is about BNDX: this is again a misleading name for the same reason as above, but it focuses on non-US securities, hedging the FX risk. As we can notice, there is a significant, yet insufficient difference in correlations between the two (from the BND-BNDX crossing, we can see on the matrix a 0.84 correlation).

Now the good news: RISR is also very negatively correlated with the rest of the curve, and it is not a short-selling fund. They mostly invest in mortgage-backed securities interest-only (MBS IOs), which are negative-duration instruments (an increase in rates benefits their prices), and while rising interest rates negatively affect the prices of common bonds, they provide a boost to this type of securities. In practice, the interest-rate change has an opposite impact on MBS IOs when compared with bonds, and this explains the negative correlation. Although its correlation with TTT is 0.5, the diversification is still significant.

For the rest, only a few securities can help us in lower correlations. JBBB, the best performer this year, is one of those: it is extremely uncorrelated with the rest of the universe, apart from FLRT, but still with a limited 0.41 level of correlation.

Now a look at the correlation with equities: let us focus on the SPY line (either row or column). BND and BNDX can already help us diversify, but the three aforementioned funds - TTT, RISR, JBBB - do a better job. Amongst the three, it is RISR that has the lowest absolute level of correlation. Similar conclusions can be drawn for IWM (small caps US).

SPDW and PDN (which are almost completely correlated) struggle a bit more to find diversification, outside of TTT and RISR. VWO and EWX (emerging markets) are some of the least correlated with BNDX in the equity space.

Finally, compared with the broader BND and BNDX indices, we can also conclude that HYHG (high-yield interest-rate hedged) is a good diversification source.

Building the fixed-income portion of a portfolio

Let us now observe the impact of a fixed-income portfolio in three sample portfolios:

1. A US-focused investor (SPY, IWM)
2. A DM ex-US-focused investor (SPDW, PDN)
3. An EM-focused investor (VWO, EWX)

The three will split their equity portfolio into large cap (83%) and small cap (17%). Now, how much should they add to their portfolio in terms of fixed income, and which securities, in order to ensure they have good diversification?

First, let us take a look at the performance of each investor before diversifying. We assume that each investor starts investing from the end of September 15, 2022:

The performance shows already how uncorrelated the assets are at some point in time, although not extremely. EM equities, the least correlated across the matrix, has a 0.65 correlation with US and 0.80 correlation with DM.

Now, what happens if we add fixed income? We will start by sticking to the current geography. To show whether this asset class protects us during downturns, we are going to include a 50-50 portfolio of investment-grade and high-yield bonds for the specific region for each investor, and the equity/fixed-income split will be the famous 60-40. This means that:

1. The US portfolio will have the following weights: 50% SPY, 10% IWM, 20% BND, 20% USHY.
2. The Developed Markets ex-US portfolio will have the following weights: 50% SPDW, 10% PDN, 20% BNDX, 20% PGHY.
3. Finally, the Emerging Markets portfolio will have the following weights: 50% VWO, 10% EWX, 20% IGEM, 20% EMHY.
   

Let us first compare each multi-asset portfolio with the original equity-only version.

While returns are graphically very different, especially with the gap in DM and partially US, we see that the benefits on drawdowns are also interesting. We can interpret that as the price of hedging your portfolio with a significant fixed-income portion.

But what happens in EM? For this specific case, diversification benefits are even smaller than one would expect, in particular because of the credit risk that (on average) is much higher for EM than for DM.

It seems like including fixed income makes sense for some sort of drawdown control, but it reduces returns significantly in most of the cases. In practice, suffering during market downturns might be worth it for those patient enough to wait until there is a rebound. In EM, there is little difference, and thus we can conclude that a simpler equity portfolio would be good enough, avoiding additional fees and transactions.

Alternative fixed-income portfolios

But if we consider alternative ETFs, what would happen? In particular, we might want to look at the least correlated to our portfolio. We will try with RISR, the interest-rate-hedged Sovereign Bond ETF, and JBBB, which is a bit more aggressive in style. What if we substitute the local fixed-income portfolios with these two? Here is the performance for the three regions:

Surprise! Our portfolios outperform in all three cases. The two ETFs are contributing positively in both risk-on and risk-off events, and eventually surpass their “standard” geographic alternatives.

An important point to notice here is that these subsets of fixed-income portfolios outperform mostly when interest rates move upwards (that means, in unfavorable environments for bonds). While valid, the findings are limited to this environment, since we are observing the past year’s performance.

But what remains worthy of consideration is their zero-to-negative correlation with the most widely adopted bond indices. If the key point in adding fixed income is the negative correlations, we should then just invest in ETFs with truly negative correlations to our equity portfolio, and not base our decisions on common knowledge or assumptions. Simple as that - we do not need to presume negative correlations when they are not present, but rather can take a look at the data and invest according to it.

Conclusions

Fixed income can help us in negative trends, but it does not really add value to the portfolio, if we do not take real data correlations into account. If we instead dive deeper and look for optimal solutions, there are ETFs that allow us to outperform against a purely equity-based portfolio, by reducing drawdowns and increasing returns over the long term.

Update on strategies

We will now add our optimal 60-40 multi-asset strategies to the shortlist. The appeal of low and negative correlations makes them good candidates as alternatives to the 60-40 portfolio, and we will compare them over time to see if our call is right.

Generally speaking, performance improved when compared with six months ago and one year ago, as per last time. Volatility fell from the previous month and year levels, inflation has been slowing down and markets continued their rally, although there are some risk factors to consider ahead of the next few months.

Updates as of September 15:

Trading strategy is based on the author's views and analysis as of the date of first publication. From time to time the author's views may change due to new information or evolving market conditions. Any major updates to the author's views will be published separately in the author's weekly commentary or a new deep dive.

This content is for educational purposes only and is NOT financial advice. Before acting on any information you must consult with your financial advisor.