Beware: Outperformance Can Be Bad

Beware: Outperformance Can Be Bad

Take a deeper dive into index-fund outperformance: It can teach you a lot.

ETF specialist
Reviewed by: Howard Lee
Edited by: Howard Lee

Outperformance should never be bad. However, when it comes to passive index investing, significant outperformance by a fund over its underlying index may underscore hidden market crosscurrents and issues in portfolio management.


In this vein, recent outperformance by the SPDR Nuveen S&P High Yield Municipal Bond ETF (HYMB | C-63) over its underlying index looks great from the surface, but a deeper look under the hood reveals a much more nuanced situation.


Sources Of Outperformance

Generally, securities lending and portfolio optimization are the most likely sources of outperformance for most index-tracking ETFs.


Except for unit investment trusts, most open-ended funds registered under the Investment Company Act of 1940 are permitted to engage in securities lending, though issuers can opt out of the program.


My colleague Dennis Hudachek has blogged about the impact of securities lending on funds’ tracking performance, so I’ll spare you the details. But here’s the main takeaway: Strong securities-lending revenues may indicate an abundance of bearish sentiment in the underlying securities, but not always.


Securities-lending revenues increase when there’s robust demand for the securities. In other words, people who are looking to borrow the shares for shorting purposes are often willing to pay up for it. This may mean many people are betting on the downside, but not always. Specifically, a small amount of shorting of an illiquid security with a small amount of shares outstanding can generate a false signal of strong demand.


Regardless, ETF investors should take a look at the annual and semiannual reports to see if a fund is getting revenues from securities lending. Or you can simply click on the “Efficiency” tab of our free fund reports to see if a fund is actively lending securities and, if so, take full measure of its revenue-sharing policy.


In the case of HYMB, the muni bond ETF I mentioned above, the latest annual report doesn’t indicate any revenues from securities lending. So it leaves portfolio optimization as the likely source of outperformance.


Portfolio Optimization And Hard-To-Access Markets

Another nuance that not all ETF investors are aware of is the ability of a ’40-Act open-ended ETF to “optimize” its portfolio relative to its underlying index. Optimization means the ETF neither must hold all of the securities nor in the exact proportion as its underlying index. Portfolio managers can sample index constituents and optimize portfolio holdings according to liquidity constraints and prevailing market condition to best track the performance of the underlying index.


Portfolio optimization is absolutely critical for investing in markets with access and liquidity constraints, including the high-yield municipal bond market that HYMB canvasses. The muni bond space is notoriously illiquid. Most municipal bonds don’t even trade on a daily basis.


The high-yield pocket of the municipal bond market poses a particular challenge in liquidity and portfolio management. It’s simply logistically impossible to source all the securities to fully replicate a market-value-weighted high-yield municipal bond index.


Due to liquidity constraints in the high-yield municipal bond market, it comes as no surprise that HYMB has a highly concentrated and optimized portfolio relative to its index. HYMB’s sector and maturity exposure align well with its index, but the fund takes on a drastically different credit profile. The table below summarizes some of the key differences between the fund and its underlying index:


(Fund – Index)
Number of Holdings46930,990-30,521
Average Maturity (Yrs)20.6719.371.3
Yield to Maturity (%)4.95.71-0.81
Average Price ($)104.6297.177.45
Aa (%)00.2-0.2
A (%)20.3610.0710.29
Baa (%)23.1420.332.81
Below Baa (%)35.8543.01-7.16
Not Rated (%)20.6626.39-5.73
As of 1/28/2015



Sampling with less than 2 percent of index constituents, it’s not a matter if HYMB can track its index tightly and consistently, it’s a matter of how far and how often HYMB’s performance drifts from its index over time after fees.


It turns out that HYMB’s rolling one-year tracking difference statistic is rather volatile, as shown by the chart below. The fund has seen its fair shares of underperformance since inception. That said, HYMB’s highly optimized portfolio has worked in its favor recently, but there’s no guarantee it will do so consistently going forward.



The Market Vector High-Yield Municipal ETF (HYD | C-59) encounters similar liquidity constraints. The fund also employs a highly optimized portfolio to track its index, which also leads to major tracking differences, though they have been consistently on the downside. One can certainly argue that periodic upside tracking differences are better than consistent downside differences. However, the key takeaway is that investors of either fund are unlikely to get index level return consistently.


It’s worth mentioning that portfolio optimization doesn’t necessarily lead to large and/or volatile tracking difference. The SPDR Barclays Aggregate Bond ETF (LAG | A-99) proves that an optimized fixed-income portfolio can track its index with relative precision and consistency.


Final Thoughts

Enjoy outperformance while it lasts. If one truly wants outperformance, go with actively managed funds. But when there are significant performance deviations of an index fund from its underlying index, one should really dig under the hood to understand where these deviations are coming from.

At the time this article was written, the author held no positions in the securities mentioned. Contact Howard Lee at [email protected].


Howard Lee is the fixed-income ETF analyst in the ETF Analytics group at FactSet, a team that maintains and develops an industry-leading suite of ETF-related data and analytics products. Prior to joining FactSet in April 2015, he was the fixed-income ETF analyst at, where he generated all analytical data on U.S. listed fixed-income ETFs. Howard graduated from Columbia University, magna cum laude, with a double major in economics and political science. He speaks Cantonese and understands Mandarin.