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Ignoring trading volume in ETFs can prove costly for investors. Ratings examined selected data from ETFs with high average daily turnover vs. those with low trading volume. The study revealed that funds with heavier trading activity tend to save their investors in annual expenses as well as in some crucial trading-related costs.

As can been seen in the accompanying table, the 50 ETFs with the lowest average trading volume over the period from December 2007 through January 2008 saddled their holders with a median annual expense ratio that was more than double that of the 50 ETFs with the highest average daily turnover for the period.

This seems logical, as heavier trading volumes would normally seem to be associated with larger funds that can spread expenses over wider ownership bases.

While an ETF's expense ratio represents a constant cost paid over an investor's entire holding period for the security, trading expenses can also eat into the overall return on the investment.

Measurements of differentials between bids and asked quotes over a two-day period showed that buyers and sellers of the low-volume ETFs were virtually certain to be confronted with significantly higher transaction "spreads" than those experienced by traders in the high-volume ETFs.

Average bid/asked spreads in the low-volume ETFs ranged from two cents to a painful $2.41, with the median value being six cents per share.

For the high-volume funds, the spreads ranged from one cent to five cents. Since the spreads were a penny for 33 of the 50 highest volume ETFs, the median for that group was one cent.

In fact, all but one of the 50 highest-volume ETFs averaged a spread of three cents or less for the period of the study.

Because traders are confronted with the bid/asked spread on both sides of their trades -- when they buy an ETF and again when they sell the shares -- the unusually wide spreads can be decidedly negative factors in investment returns, especially when shares are held for relatively short periods.

Similarly, a person loses on both sides of a round-trip trade when he buys an ETF when its market price is at a premium to its net asset value per share, then sells it when its market quote is at a discount to its NAV.

Ideally, investors would prefer that the uncertainties created by premiums and discounts of market price vs. NAV be minimized in ETF transactions. A basic premise of ETFs is that, unlike traditional closed-end funds, their respective market prices should closely adhere to their corresponding NAVS throughout every trading day.

The market prices of high-volume ETFs tracked, on average, their corresponding NAVs relatively closely during the month of January. Using daily average premiums and discounts of market price versus NAVs, the price of the median high-turnover fund departed from its NAV by only 0.15% -- less than half the deviation of 0.34% for the median ETF from the low-volume group.

Absolute values (disregarding plus and minus signs) were used to determine deviations of prices from NAVs. This identified the relative distances that prices differed from NAVs without regard as to whether the deviation was positive or negative.

As with bid/asked spreads, investors stand to have their overall returns negatively zapped by premiums and discounts at each end of the ownership period of an ETF. While optimists might hope to buy at a discount and sell the ETF at a premium, experienced closed-end fund investors can relate how those vehicles can stagnate for years at painfully wide and unyielding discounts.

However, bid/asked spreads, as well as premiums and discounts, are only endured by investors at the times of purchases and sales. Long-term investors, therefore, can spread these fixed costs over lengthy holdings periods, thereby minimizing their impact on total investment returns.

Still, it is logical to pay attention to an ETF's trading volume, as it can be a factor in the cost of a fund as well as its ultimate investment return.

Richard Widows is a senior financial analyst for Ratings. Prior to joining, Widows was senior product manager for quantitative analytics at Thomson Financial. After receiving an M.B.A. from Santa Clara University in California, his career included development of investment information systems at data firms, including the Lipper division of Reuters. His international experience includes assignments in the U.K. and East Asia.