Investors and analysts often use the relative performance of sector ETFs to gauge investor appetite for risk, or discover which industries or sectors are falling in and out of favor. They also look for clues which may help signal a recession or economic boom.
While there is a measure of validity to such analysis, different ETFs have different betas. Beta, you will recall, measures the sensitivity of a stock or portfolio to the actions of a broad market index such as the Standard and Poors 500. Simplifying somewhat, if company XYZ goes up twice as fast as the market, it has a beta of 2.0. We would expect XYZ to fall twice as fast as the market on the downside as well, and in fact financial research does tend to show that betas are pretty symmetric across market conditions. In contrast, we would expect a company with a beta of .5 to go up, and down, half as fast as the market.
Nonetheless, research also shows that betas of portfolios, especially portfolios of stocks in a similar industry or sector, are far more stable over time and over various market conditions than individual stocks are. This is a logical consequence of diversification: the role of each individual company is minimized, and balanced by other holdings. What is good news for company ABC in a portfolio, making the shares volatile to the upside, may be bad news for competitor DEF, making their shares volatile to the downside. The net effect on the volatility of the portfolio (or an ETF which is designed to track it) would be small.
This is another great advantage for investors in ETFs. When you buy one stock, a change in management, or levels of indebtedness, or entering a new market with a new product, in short all kinds of factors, can lead to big shifts in the overall riskiness of those shares. With a sector ETF, this is far less likely to occur.
This is borne out if you look at "Beta data" for sector ETFs. Consider the Select Sector SPDR-Health Care (XLV). According to Yahoo Finance, over the last 3, 5, and 10 years respectively, its beta has been .56, .60, and .57.
On the other hand, the Select Sector SPDR-Basic Materials (XLB) has been much more volatile: a beta of 1.24, 1.18, and 1.18 over these same time spans.
Notice that health care has stayed low risk, and basic materials high risk, even if individual companies in these ETFs might have changed their stripes over the interim.
In advancing markets, the high beta ETFs will be the superior performers---"beating the market," in street jargon. In a declining market low beta ETFs will beat the market by falling less. To see if they are really out-or-under performing, you must adjust your expectations given these different levels of risk.
A good recent example is the Health Care ETF, XLV. In the rally earlier this summer, it appears at first glance that health care stocks tracked the market fairly closely, maybe even underperformed some:
But this is incorrect. Given that the beta of the health care ETF is .57, you would expect that health care shares would gain only a little more than half what the market gained over this period. Measured by the SPDR S&P 500 ETF Trust (SPY) stocks gained about 12%. XLV gained far more than half that! So a closer look reveals that the health care sector outperformed the market during this period.
By the way this trend continued during the market selloff in the weeks before and shortly after the election.
The market fell 6%, but health care shares fell far less than half that. For the mathematically inclined: you would have expected them to fall (.57)(6.0%) or 3.42%. They fell only 2%.
This is the advantage of knowing that ETF betas are far more stable than those of individual shares. While not particularly meaningful for extremely short periods used by day traders, over time the risk profile of each ETF is stable enough to allow analysis like this to be helpful for investors seeking clues about relative performance.
For the record, there has been one sector ETF for which the beta has changed. For years the Select Sector SPDR-Energy (XLE) had a beta very close to 1.0, but in the last few years this beta has increased to 1.21. I'll leave oil analysts to suggest why this may have occurred, since XLE is dominated by companies in that industry.
In future articles I will continue with examples of how this analysis can be used to flag superior performance; whether this performance endures long enough to be profitable, and whether such information can give us clues about where the US and world economy may be headed.