Matching What You Trade With How You Trade

In several recent posts, I have mentioned that the growing number of ETFs across the "style cube" are providing active market participants with an increasing number of vehicles for trading. A look at recent returns, for example, shows us that value stocks have been outperforming growth and that smaller cap stocks have been outperforming larger cap ones. Just as important, we see patterns of volatility in smaller cap ETFs that may well make them better trading vehicles than their larger, more popular counterparts.

I decided to use a very simple benchmark trading system to evaluate the trading performance of some of the most popular ETFs. On Tuesday, for example, I found 10 ETFs that traded over 3 million shares on the day: QQQQ, SPY, IWM, XLE, OIH, EWJ, XLF, DIA, SMH, and EFA. Notice the growing popularity of small cap trading (IWM) and international trading (EWJ, EFA). Let's see how some of these popular ETFs perform if we simply buy the ETF when it crosses its 20-day moving average to the upside and we sell it when it crosses it to the downside. Such a very simple system should give us a fair number of whipsaw trades, but should also capture nice trending moves.

In the U.S. large caps, of course, we have seen more evidence of mean reversion than trending during the last several years. For example, going back to 2004 (N = 732 trading days), we find that, when the S&P 500 Index (SPY) is above its 5-day moving average *and* above its 20-day moving average (N = 336), the next 10 days in SPY average a loss of -.04% (188 up, 148 down). That is quite an underperformance: The remainder of the occasions in SPY average a 10-day gain of .63% (256 up, 140 down).

Conversely, when SPY has been below its 5-day moving average *and* below its 20-day moving average (N = 194), the next 10 days in SPY average a gain of .77% (124 up, 70 down). A trend following approach in SPY, which would have a trader buying when the index is above its short-term moving averages and selling when the index is below, would have lost considerable money during this bull market.

But with the help of the "performance" feature from the excellent Barchart site, let's actually see how some of the ETFs would have performed since 2005 if we had implemented the simple system described above:

For SPY, we would have had 16 winning trades and 47 losing trades. This would have lost us about 12 SPY points or the equivalent of 120 S&P futures points--during a bull market! The system did catch two large winning trades--it bought in October, 2005 and in July, 2006--but this wasn't enough to make up for a system that had three times as many losing trades as winners.

If we move over to the iShares Emerging Markets ETF (EEM), we find that we had 13 winners since 2005 and 33 losers. Interestingly, however, the system actually made about 25 points over that period. (It started 2005 trading in the 60s). Why? Because the system was able to catch winners that were much larger than the losers. EEM displayed more runs following breaks above and below its moving average than did SPY.

Now let's look at EFA, the iShares MSCI EAFE international ETF. We had 16 winners with our system and 44 losers. That's not at all a favorable ratio, but still the system eked out a little over 5 points of profit. Once again, we saw good sized runs in EFA that simply were not present in SPY--but not ones as pronounced as EEM.

The point of this, of course, is not to trade such a simple system. Indeed, the approach never made more than simple buy-and-hold during the period studied. Rather, we can see that different ETFs display different trending properties that can make the difference between profitability and significant losing. The takeaway message is that *what* you trade should be compatible with *how* you trade.

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