Every so often, it is a good idea to look at the broader market and attempt to see if the evidence is shifting in favor of (or against) certain sectors. This can be a particularly useful exercise if your investing style includes concentrations in certain sectors. Sector ETFs make this element of investing easy and low-cost, but it is important to have methods for getting a handle on various sectors’ prospects.
There are many ways to analyze sectors and sector index funds, and I am going to look at just one here. There are two major truisms in sector investing. First, investors chase performance and overwhelmingly prefer asset classes that have been out-performing in recent years. Second, the sectors that out-perform have historically always reverted back to a reasonable level of performance.
This does not mean that asset classes that have delivered high returns for several years will deliver low returns in the future. Some asset classes have higher volatility (i.e. risk) and thus are rationally expected to deliver higher average returns. The big risk is that you invest in an asset class that has been generating returns out of all balance with risk levels, so that the odds are that this asset class will correct substantially to come back in line with the risk-return balance that capital markets maintain (think real estate).
Quantext Portfolio Planner [QPP] projects the future expected return of assets and asset classes based on the assumption of a long-term balance in risk and return. Numerous tests have demonstrated that creating an outlook for future performance based on this assumption is far superior to looking at trailing performance. On average, we find that using trailing performance to predict future performance has about twice the error of using QPP’s approach.
The stock market is remarkably efficient in the long-term at balancing risk and return. The success of this type of approach provides us with a basis for evaluating which sectors are likely to do well going forward and which are likely to correct.
To accomplish this, we compare the QPP-projected average annual return to the trailing average annual return over recent years. If the projected average return is considerably less than the trailing average return, this is a warning signal. If the projected average return is greater than the trailing return, this suggests that a sector needs to generate some higher future earnings to achieve the return level that is associated with its risk level.
It can take a long time for asset classes to revert to the mean, of course. As John Maynard Keynes famously quipped, ‘the markets can remain irrational longer than you can remain solvent.’
In March of 2007, I published an analysis that looked at leading and lagging ETFs in this way. I specifically looked at the sectors for which QPP showed the highest disparity between trailing three-year average return and QPP-projected future average return. The REIT ETF, ICF, had a trailing three-year average annual return of 26% and a projected future average annual return of 11.7%. This was the sector ETF with the worst projected future return relative to trailing performance. Since that article was published, ICF is down about 15% and we are in the midst of a massive downturn in real estate.
The sector with the highest positive spread between trailing performance and projected performance was software (via IGV). The trailing three-year average return for IGV was 7% and the projected future performance was 14.9% per year. Since that article, IGV has gone up by about 15%. On the other hand, EEM was also projected to have generated un-sustainable returns, and it continues to out-perform.
At the time that I wrote this article, I was looking for a place to invest some funds. I chose to invest in energy because although that sector (represented by IGE) had generated very high return over the trailing three years, the projected average return was consistent with these levels. (Note: I invested in COP rather than IGE because I prefer to own individual stocks and I liked COP for some other reasons. I do not own IGE)
I have revisited this theme of comparing trailing performance to projected future returns for a number of major sector ETFs and the results are shown below. I have rank-sorted these ETFs based on the size of the spread between trailing average return and projected average return.
What looks promising based on this standpoint? Commodities (NYSEARCA:DJP), TIPS (NYSEARCA:TIP), and high-yield bonds (NYSE:COY) look attractive. I have added a question mark next to the return for commodities because there is an open question as to whether commodities will deliver the same risk-adjusted returns as an asset class as securities. QPP actually projects higher average annual returns for the commodities index than 10%, but history suggests that commodities generate less return relative to risk in the long-term than securities. In other words, I am less confident about using QPP to project average return for commodities.
It is interesting that commodities and TIPS ETFs appear relatively under-valued on this basis. This suggests that investors have been heavily discounting the probability of inflation. Software (NYSEARCA:IGV), Internet firms (NYSE:IIH), and small-cap and NASDAQ (IWM, QQQQ) also look pretty attractive. In the case of the NASDAQ and small-cap index, this does not mean that these sectors/ETFs have been substantially under-performing, but at least they are generating returns that are consistent with projections.
Among the sectors that have been out-performing the level that QPP projects as the expected return, energy remains interesting. IGE and IYE have generated very high returns over the past three years, but the projected average return is also very high—albeit lower than the trailing returns. If IGE has generated 27.5% per year for the past three years, what would it generate over the next three years to bring the annual returns in line with the 19.8% projected? If IGE returns 12% per year over the next three years, the average return for the total six year period will be the 19.8% that QPP projects as the long-term average return for this ETF.
I am happy with this outcome, should it occur. Calculating an estimate of future return by assuming that the future return averaged to the trailing return will average out to the projected long-term return (as I did for IGE above) is a very approximate way to gauge the attractiveness of a sector. Even if the statistics are all correct (i.e. QPP’s expected return calculation is perfect), the time period required for the statistics to average out is unknown and there is no reason to assume that the returns will average out over six years (or any other short period, for that matter). That said, this approach is a useful quick way to look at which sectors are out of balance and what would have to happen to bring them back into balance:
Before looking at the table before, remember that this is just an indicator---not a projection of what is likely to occur.
One thing that looks odd here is commodities (due to the caveats mentioned earlier). Is it plausible that emerging markets will generate negative returns over the next several years? This is a very hard call and not one that can be answered here. The chart above implies that we will have to see substantially lower returns in the future to bring this asset class back into line---but we really don’t know how long this will take. The key point is that it is unlikely that things will all revert to the mean in just six years, so again I caution that this is simply an indicator—not a projection.
Also, in case it was not clear, QPP does not incorporate this kind of assumption into its projections. That said, emerging markets have been generating returns that are too high to be sustainable, given their risk levels.
To put these results into context, I will discuss how I think about these sorts of results in personal terms. (Nothing in this discussion should be construed as advice to buy or sell anything. I am not an investment advisor.) In the table above, we are taking a qualitative idea of reversion-to-the-mean and using QPP’s projections via the equation shown above the table. I am personally over-weight in energy and utilities because I like the return potential of energy and I like the portfolio effects of utilities, even though I do not expect them to generate the high returns that we have seen over the past three years. I have some internet exposure that has not been spectacular, but results such as those shown above support my feeling that we will see a sector shift with software, small-cap, and technology becoming popular again.
The results above suggest that large-cap has had its run of out-performance, and I generally agree with this. I am by nature a value investor, so I won’t be selling my value-oriented assets, but I will probably add some weight to software, small cap, etc. My more NASDAQ-oriented investments have outperformed this year, and the QPP results support other evidence that small-cap is not massively out of balance, so I will continue to look for new prospects here.
Also, while I do not maintain any meaningful exposure to bonds, TIPS look interesting just because a reasonable forward view suggests that they are under-valued (i.e. QPP projects returns considerably higher than trailing returns). Healthcare has been a boring low-return sector, and QPP expects it to remain this way. I own a chunk of JNJ, but I don’t expect great things---it is there for diversification purposes.
Going forward, QPP expects REIT’s to under-perform their recent years, but I have known that for a while (as discussed in the March article linked earlier). The relative under-performance of commodities (other than energy and metals), as well as the underperformance in TIPS, suggest that the market is discounting inflationary risk and I am going to give this theme considerable thought. It is often the risk that we ignore or discount that really hurts us, and inflation has some potential in this regard.
Another point that deserves consideration, of course, is risk. Assets with high expected returns will also be riskier assets, and I have not discussed risk preferences here. The list of ETFs / asset classes analyzed here covers a wide spectrum of risk levels, from very low (i.e. TIPS) to very high (energy, emerging markets, etc.). Any investor thinking about an allocation to an asset class needs to consider the risk levels that he/she can take on, in the broader context of his/her overall portfolio.
In closing, I will note that this entire discussion has been based on the idea that all asset classes will ultimately abide by some rational balance between risk and return. This type of balance is historically the most consistent evidence of broadly efficient capital markets. My approach is purely about using statistical models to project risk and return. There is no consideration of fundamental factors in this analysis.
Disclosure: author is long COP.