As seen in the exchange traded fund (ETF) market, the U.S. stock market seems to be defying traditional elements of savvy investing.
Gary Gordon for ETF Expert points out that risk or risky investments are often associated with NASDAQ, tech, or small stocks. However, these types of stocks have been the leaders through the close of last week in this bear market.
This is exemplified by the iShares Russell 2000 Index (IWM), which is showing a technical uptrend. IWM is down 3.5% year-to-date, but is up 5.8% over the past month. This is not bad at all compared to alternative indexes. The S&P 500, for instance, has lost more than 12% this year and the S&P 500 SPDR Trust (SPY) is down 12.3% year-to-date and still more than 5% below its 200-day moving average.
These tech and small companies seem to be early leaders in the race toward economic recovery. However, these types of stocks are not the solution for the tough economic times. This being said, it is important to note what can be taken away from this bear market as an investor.
As an investor, one can limit the impact of costs, taxes and other potential adverse outcomes. ETFs, for example, are a great way to reduce both costs and taxes.
Even more important, an investor can make certain that they do not suffer big losses on investments by accepting smaller losses. Of course this is easier said than done, but it shows the importance of not falling in love with a stock, a company, or a particular investing theme.
A good example of this would have been to expect oil to soar to more than $200 per barrel, as many top investment professionals did. Feeling that oil would climb this high, one may have purchased United States Oil (USO), perhaps at a price well above $100 per share. However, as oil prices fell and USO selling at $91 per share on Monday, the tendency to fall in love with this investing theme would leave an investor with a quick and substantial loss.
It’s a good reminder to stick with your plan – sell when it drops 8% of the high or falls below its 200-day moving average.