I recently noticed the GreenHaven Continuous Commodity Index Fund (GCC) won the “Best Commodity Broad Basket ETF” award for 2012 from Morningstar.
I also noticed that the same fund scores abysmally low in what in our ETF Analytics product calls “Fit” (18 out of 100, to be exact).
The most straightforward way to explain Fit is from our Analytics Methodology document , which says:“Simply put, the higher the Fit score, the better the fund resembles the broad market.”
It’s ironic that, among 15 ETFs, the recipient of the “Best Commodity Broad Basket ETF” is the one ETF that is the furthest from resembling the broad market, again based on our analysis .
Morningstar’s choice for the award is completely legitimate. I haven’t run the calculations myself, but from a quick glance, and based on the posted criteria, it appears to be the right choice.
What I hope to do is explain how the “Best Commodity Broad Basket ETF” is actually the worst at representing its market.
To do that, we need to ask, What is a broad, representative commodities basket? Without an answer, we can’t assess the specific bets a particular fund is making regarding, say, overweighting a sector, the size of bucket or the geographical focus of the fund.
In equities, market capitalization is used to determine a representative basket of the market but, due to offsetting long and short interest in futures contracts, market cap is the wrong criterion for commodities.
GreenHaven’s GCC won the “Best Commodity Broad Basket ETF” award because exposure was not a factor. Instead, Morningstar used cost of ownership and three-year returns as criteria. That’s fair—after all, selecting a benchmark can be difficult.
At IndexUniverse, we compare broad commodities ETFs against a global production-weighted index. In commodities, a fund’s Fit score is a measure of how well it matches a production-weighted benchmark for its segment.
So, why does GCC earn such a low Fit score?
GCC earns a low Fit score because it has massive biases compared with the broad production-weighted commodities market.
For example, on a global production-weighted basis, agriculture comprises only about 15 percent of the market, yet GCC allocates nearly half of its portfolio—47 percent—to agriculture.
Again, the fund’s heavy allocation to agriculture is not a bad thing. After all, on a production-weighted basis, energy comprises nearly 70 percent of the broad commodities market. So, GCC is actually improving upon that concentrated market and produces a more diversified basket.
In the end, it all comes down to GCC’s methodology.
GCC tracks the Thomson Reuters Equal Weight Continuous Commodity Total Return Index, which, as its name suggests, is an equal-weighted index. So, the fund equal-weights each commodity in its index—a whopping 47 percent of which fall under the umbrella of agriculture.
As long as you’re OK with agriculture as half of your commodities exposure, GCC is a great fund.
What I’m trying to illustrate is the importance of understanding your true investment exposure. Setting a neutral benchmark gives us a compass with which we can understand the ways that a fund tilts away from the market.
This is even more important when we step outside of equities. For example, in equities, most people know right away that Apple Inc. (AAPL) is bigger than Lululemon (LULU), or that financials are a bigger piece of the U.S. market than utilities.
The same isn’t always true outside of equities.
Can you tell me whose municipal debt is a larger slice of the muni bond market:Texas or Florida? Or, on a production-weighted basis, which industry is larger:industrial metals or livestock?
GCC is a great example of a fund that is award-worthy, in its own right, but far from representative of a broad production-weighted take on the market.
Ultimately, it’s important to use benchmarks to discern how our exposure compares with the broad market.
After all, we live in a world of relativity.
At the time this article was written, the author held no positions in the securities mentioned. Contact Spencer Bogart at email@example.com .
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