It’s well known that Chinese policymakers are working hard to avoid economic overheating and runaway inflation. Recent GDP data shows, however, that such efforts have not yet borne fruit. The ETFs that appear in this week’s run of my weekly ETF Pullback strategy would be consistent with the notion that the Beijing won’t get its way.
Here’s this week’s list:
- PowerShares DB Agriculture (DBA)
- iShares MSCI Malaysia (EWM)
- iShares MSCI Taiwan (EWT)
- Market Vectors Nuclear Energy (NLR)
- IQ Taiwan Small Cap (TWON)
This was last week’s list:
- iShares MSCI Sweden (EWD)
- iShares MSCI Hong Kong (EWH)
- Global X InterBolsa FTSE Colombia (GXG)
- Market Vectors-Coal (KOL)
- PowerShares Global Coal (PKOL)
The link between the agriculture ETF and inflation is readily apparent, given that food right now is a major factor in the uncomfortably high inflation trends being seen in many parts of the world. The link between nuclear energy and inflation is less apparent, but probably still genuine. As oil rises, or is seen as likely to rise significantly going forward, alternative energy sources come to be seen as more attractive. Nuclear may not be number one in this regard (I’d vote for solar), but it is likely to be on the table, at least in the minds of investors.
The other three ETFs are plays on GDP. Trade with China is important to Taiwan and Malaysia so it’s hard to imagine their stock markets staying strong unless China continues to progress economically.
With regard to the latter, we need some perspective. Chinese policymakers are definitely not trying to push growth into negative territory. The goal is to have growth remain on a positive track, albeit one that is less buoyant than the near-10% readings that seem to have become normal.
But how much faith do you have in any sort of “fine tuning,” whether in China or elsewhere? Hitting a GDP growth target is as easy as having a pitcher throw directly to a target established by the catcher, but from center field as opposed to the pitchers mound. If and when the market comes to believe the Chinese government will succeed in its efforts to cool growth, it will probably favor recession-oriented strategies, at least at first until China demonstrates it can really avoid that scenario.
The model, a technical strategy that looks for ETFs that are retreating following significant periods of relative strength, presumes they will bounce back following these corrections (see Appendix below for explanation and performance data). Logically, however, it is possible that these downturns may be marking the commencement of new downtrends. But in reality, the transition from uptrend to downtrend is not usually so neat and can be characterized by a series of zigs and zags. The backtested and real-money performance records indicate that more often than not, these initial corrections turn out to be just that, corrections.
Speaking of real money performance, this is depicted in Figure 1, a screen shot from the FolioInvesting.com account I use to trade the model.
click to enlarge images
Lately, performance hasn’t been good, but the early period is more characteristic of the longer-term backtested record; a tendency to outperform or match the broad market with less volatility. But if I’m going to have to tolerate a period of bad performance, as has to be done at times for any model, I can live with it manifesting as a more-or-less matching of a probably-unsustainably strong S&P 500.
Ultimately, I’ll judge the model’s real-life merits later, when the S&P starts to show a more variety in movement and I get a chance to see if the model can continue to be effective in moving to appropriate sectors and/or asset classes, as it often did during the backtest period.
To create this model, I started with a very broad-based ETF screen I created in StockScreen123.com.
- Eliminate ETFs for which volume averaged less than 10,000 shares over the past five trading days
- Eliminate HOLDRs (I don't want to be bothered with the need to trade in multiples of 100 shares)
- Eliminate leveraged and short ETFs (I think of these as hedging tools rather than standard ETF investments of even trading vehicles)
Then I sorted the results and select the top 5 ETFs based on the StockScreen123 ETF Rotation - Basic ranking system, which is based on the following factors:
- 120-day share price percent change - higher is better (15%)
- 1-Year Sharpe Ratio - higher is better (15%)
- 5-day share price percent change - lower is better (70%)
The idea of using weakness as a bullish indicator is certainly not new. But often, it's an add-on to other factors that, on the whole, emphasize strength. Here, the weakness factor is dominant, with a 70 percent weighting.
This model is designed to be re-run every week with the list being refreshed accordingly. I trade through FolioInvesting.com, where I pay a flat annual fee rather than a per-trade commission, so I don't care about the fact that turnover form week to week is often 80%-100%. If you want to follow an approach like this but do have to worry about commissions, the strategy tests reasonably well with three ETFs, or even with one. (Cutting the number of ETFs is far preferable to extending the holding period.)
Figure 2 shows the result of a StockScreen123 backtest of the strategy from 3/31/01 through 12/30/10.
Figure 3 covers the past five years, a very challenging market environment that witnessed the fizzling of many strategies that had succeeded for a long time.