The Key Statistic When Evaluating ETFs

September 08, 2014

Real-world tracking difference is incredibly important. So why does nobody look at it?

[This article was co-written by Dave Nadig.]

Our goal here at ETF.com is to help ETF investors make better choices.

Core to that mission is helping investors identify which ETFs do the best job of tracking their indexes. Historically, academics have used “tracking error” to measure this.

Tracking error is a measure ripped from academic studies that, used in isolation, can mislead investors and cause poor decision-making. Unfortunately, it’s also the statistic you’re most likely to find on your Bloomberg terminal or fund fact sheet.

At ETF.com, we present an alternative set of statistics we developed years ago to actually measure how well ETFs that track indexes do their jobs: “tracking difference.” It’s more accurate, more intuitive and, ultimately, more useful than traditional measures of tracking error.

What Is Tracking Error?

Most people assume that tracking error measures how well a fund performs compared with its index. If I hold the fund for a period of time, how close will I be to that index’s return when I sell?

But that’s not actually what tracking error measures. Instead, tracking error measures—and here’s the textbook definition—the standard deviation of the daily differences in return between the net asset value (NAV) of a fund and its index. In English, that means that what drives tracking error is the consistency of a fund’s return, not the quality of that return.

Here’s what we mean. Imagine two funds: One trails its index by 5 basis points every day, while the other bounces back and forth, trailing by 5 basis points one day and beating it by 5 basis points the next. Using the standard measure of tracking error, the former fund is perfect: Because it misses the index return by a fixed amount each day, it has precisely zero tracking error.

Back in the world of reality, that “perfect tracking” means that, by the end of the year, the fund is trailing its index by roughly 12 percentage points. Ouch.

By comparison, our 5-basis-points-up, 5-basis-points-down fund has enormous tracking error … but it ends the year with exactly the same return as the index.

There are other perverse results of the way tracking error is calculated:

  • Outperformance is treated with the same disdain as underperformance
  • Small, one-day data errors—or even data-rounding—create massive impacts
  • Accounting discrepancies between the fund and the index can produce shocking “false” results

What’s bad about all this is that these statistics—available widely on Bloomberg and other financial sites—lead investors to make wrong decisions time and time again.

 

Find your next ETF

Reset All