I have been struggling to understand a problem that I am going to refer to as the ‘yield paradox.’  Yields for individual asset classes look low.  The 10-year Treasury bond is yielding about 1.9%, and 30-year Treasury bonds are yielding a similarly paltry 3%.  The S&P 500 is yielding 2.1%, which is very low by comparison to historical levels.  Investment-grade corporate bond indexes are yielding less than 4% (see LQD, for example, at 3.8%).  Given that the official rate of inflation for 2012 was 1.7%, these yields mean that investors are getting very little yield net of inflation.  The very low yields on bonds and on stock indexes is a direct result of the Fed’s actions in holding interest rates at historical lows via Quantitative Easing.  We have not yet gotten to the paradox.

Even as bond yields and stock index yields have become very low, it remains possible to create portfolios with substantial levels of yield and moderate risk.  I have explored this topic in a range of articles and blog posts.  There are solid yields available from a variety of sectors and asset classes that dwarf what you can get from either broad stock indexes or bond indexes.  The question, of course, is how much risk you are taking on to get these high yields.  By all risk measures that I am aware of, however, it appears that it is possible to create a portfolio with yields much higher than what is available with traditional stock-bond allocations and with no more risk.  This is the ‘yield paradox.’  If investors are looking for higher yield, why are they largely ignoring the types of portfolios that can provide yields substantially higher than traditional asset allocations?

The first possible explanation is that many investors are largely unfamiliar with some of the asset classes that currently provide meaningful yield.  Master Limited Partnerships (MLPs), mortgage REITs (mREITs), and high-yield municipal bonds are considered to be somewhat out of the mainstream.  Nowhere is the familiarity problem as great as for high-yield bonds (aka junk bonds).  Because these asset classes are less familiar, they ‘feel’ more risky on an emotional basis.

Another component of the ‘yield paradox’ is simply that relatively few people are willing to be contrarians.  If a stock’s price has declined but the company has maintained the dividend (so the yield is high), many investors will avoid the stock.  Certainly, sometimes this situation turns into a ‘value trap’ and the company will subsequently cut its dividend and/or see its price continue to fall.  On the other hand, the well-documented ‘value premium’ associated with buying stocks when their prices are depressed relative to fundamentals has historically provided investors buying higher-yielding stocks with substantially higher returns than the broad stock indexes.  Nevertheless, the predominant result is that investors tend to believe that stocks with yields considerably above the average index level are too risky to bet on.

The third explanation for the ‘yield paradox’ has to do with money manager incentives.  Portfolios which exploit the yield anomaly tend to have high tracking error relative to standard benchmarks, particularly in comparison to their more traditional counterparts.  Money managers are often judged based on their recent performance relative to a benchmark.  Increased tracking error means a higher probability of under-performing a benchmark in the near-term, which is a threat to one’s job security.  The tendency of fund managers to avoid assets which increase tracking error relative to the benchmarks by which they are judged is well documented .

At the start of 2013, it remains possible to create a portfolio with high-yield and historical risk that is in the range of levels considered appropriate for individual investors.  Consider, for example, the following portfolio:

Ticker Weight Yield
JNK 20% 6.70%
EDV 16% 3.10%
BWP 10% 7.90%
CTL 10% 7.30%
CLMT 10% 7.90%
FTE 9% 14.50%
EXC 6% 6.90%
EONGY 6% 7.30%
NLY 5% 12.10%
AGNC 5% 16.00%
LQD 3% 3.80%
Sample high-yield portfolio

This portfolio has a yield of 7.8% and a trailing four-year risk level (annualized volatility) of 9.9%.  A portfolio that is 57% allocated to the S&P 500 (SPY) and 43% to an aggregate bond index (AGG) has the same trailing four-year risk level and a yield less than 2%.  Tracking error vs. a benchmark is measured by a statistic called R^2 (R-squared) which measures the percentage of the variance in returns for the portfolio that can be explained by the variability in the benchmark (typically the S&P 500).  Higher R^2 corresponds to a lower probability of meaningfully under-performing your benchmark.  The portfolio in the table above has R^2=55%, while the 57% S&P 500 / 43% bond portfolio has an R^2 of 98%.

This portfolio provides a good example of a ‘yield paradox’ portfolio, although I hasten to note that this is not an endorsement of this portfolio for any specific person.  Further, there are many other examples that I have written about in the last couple of years.  You can construct such a portfolio entirely out of funds or you can include individual stocks.

There are a number of possible objections with regard to the portfolio above and other ‘yield paradox’ portfolios that appear to be able to provide high levels of yield at moderate risk.  The first concern is simply that the trailing historical volatility may not be a relevant guide to the future.  In other words, might this portfolio actually be much riskier than its historical volatility suggests?  As a partial response to this question, I have run the portfolio through a forward-looking Monte Carlo simulation that suggests that this portfolio is expected to be about 2/3 as risky as the S&P 500, which is equal to the projected future risk of a portfolio that is 65% allocated to the S&P 500 and 35% allocated to the aggregate bond index.  If market volatility shoots up, this portfolio will become more volatile, but the analysis suggests that this portfolio’s risk level is within the range that many investors would find acceptable.  Of course, the Monte Carlo simulation is just a model—it’s not a crystal ball.  Might there be risks that the model is not properly accounting for?  Certainly.

There are a number of features of this portfolio that are consistent with my conclusions with regard to why it is possible to create such an apparent yield anomaly.  The two largest holdings are junk bonds (JNK) and long-duration Treasury bonds (EDV), both of which are quite risky.  There is a 20% allocation to MLPs (BWP and CLMT).  MLPs remain relatively unknown to many individual investors and are often ignored in books on investing.  Individual MLPs tend to be volatile, and these are no exception.  Over the past four years, for example, CLMT has been twice as volatile as the S&P 500.  There is a 10% allocation to two mREITs (NLY and AGNC) which can also be volatile.  The portfolio also has exposure to European stocks via France Telecom (FTE) and E.ON (EONGY), a large energy utility based in Germany.  Both FTE and E.ON have suffered in the Euro-zone crisis and their high yields are a result of reduced share prices.  As share price declines, dividend yield increases because yield equals dividend divided by share price.

How is it that we can construct a portfolio which appears to have a fairly modest risk level out of components that, on a standalone basis, are quite volatile?  This question brings me to another possible explanation of the ‘yield paradox.’  The ability to create a portfolio with 7.8% yield and four-year volatility of 9.9% is contingent on risk offsets among these different asset classes.  The risk in one portfolio element offsets some risk in others.  The relatively low risk level of this portfolio is due to low correlations between the returns on the different asset classes in the portfolio.  Is it possible that the market as a whole is not efficiently pricing yield in a way that accounts for the available risk offsets?  This potential is an open question.

It is always possible that the portfolio above contains some risk that neither recent history nor the Monte Carlo simulation is capturing.  If the ‘true’ risk is much higher than my estimates, the anomaly goes away.  The portfolio risk could be higher because either (1) one or more of these asset classes becomes substantially riskier in the future, or (2) the correlations between two or more of these assets increase substantively.

The ‘yield paradox’ is an intriguing problem.  I have presented it here with a few possible explanations but with nothing that could be considered an actual theory.  I am quite certain that most investors and advisors would look at a portfolio like the one above and decide that there is no way they’d ever invest in such a weird mix of assets.  That reaction, of course, may be precisely how such an anomaly could persist.


The views set forth in this blog are the opinions of the author alone and may not represent the views of any firm or entity with whom he is affiliated. The data, information, and content on this blog are for information, education, and non-commercial purposes only. The information on this blog does not involve the rendering of personalized investment advice and is limited to the dissemination of opinions on investing. No reader should construe these opinions as an offer of advisory services.