Sector Detector: Financials and InfoTech look strong
Sabrient’s fundamentals-based SectorCast-ETF model appears to have softened its conservative posture in the wake of last week's market weakness. Sectors like Financials, InfoTech, and Energy that are more dependent on economic stability and growth are scoring higher this week (based on Friday's closing data), pushing traditionally defensive sectors lower. Notably, after correcting the hardest, stocks in the Materials sector have been receiving upward revisions from the analyst community, which is lifting it from the bottom of the rankings for the first time in a long time.
Although Sabrient remains cautious on the market given the tenuous state of the U.S. and global economies and the higher stock valuations, the re-emergence of sectors like Financials, InfoTech, and Energy in the SectorCast-ETF rankings would appear to be near-term bullish. Nevertheless, an absolute return approach, like Sector Detector’s model portfolio, remains highly desirable.
Latest rankings: Again this week, and somewhat surprisingly, Financials (XLF) remains the top-ranked sector with a score of 84 (out of 100). You might recall that it jumped 30 points last week to take the top spot for the first time. XLF is powered by its top score in projected year-over-year change in earnings across the sector and aggregate projected price to earnings (P/E) ratio. (Keep in mind, however, that it ranks dead last in trailing return on equity.) 
After Financials retaining its hold on the top, there has been quite a bit of shuffling among the other nine sectors, based on SectorCast-ETF’s one-month forward look.
Information Technology (IYW) jumped from fourth place last week to second place this week to make its way into the model portfolio, sporting a score of 76. It was propelled primarily by a host of new analyst upward revisions among its constituent stocks during the week.
Top-ranked stocks within XLF and IYW include Assurant (NYSE: AIZ), Goldman Sachs (NYSE: GS), Western Digital (NYSE: WDC), and Corning (NYSE: GLW).
In the middle of the pack, traditionally defensive sectors Consumer Staples and Utilities dropped significantly in the rankings, while Energy (XLE) continued to strengthen. XLE jumped from a score of 51 to 61 primarily due to an improvement in its aggregate projected P/E. And Materials, which is another commodity-oriented sector tied to both global demand and the dollar, has emerged from its perennial position in tenth place (last) all the way up to sixth, as its score jumped by almost 50%, from 35 to 51. The recent price correction predicted by the SectorCast-ETF model has led to a much more appealing projected P/E.
At the bottom of the rankings, long-time cellar-dwellers Industrials & Materials have been replaced as the fundamentally most overvalued sectors by Telecommunications (IYZ) with a score of 28 and Consumer Discretionary (XLY) at 38. Although the model indicates that international telecom stocks and ADRs have excellent forward valuations, IYZ contains only U.S. telecoms, and they are showing more analyst downgrades than upgrades and a poor projected year-over-year change in earnings across the sector. XLY is saddled with the worst (highest) aggregate projected P/E.
Low-ranked stocks within IYZ and XLY include PAETEC Holding (Nasdaq: PAET), Virgin Media (Nasdaq: VMED), Marriott International (NYSE: MAR), and Harley-Davidson (NYSE: HOG).
These scores represent the view that Financials and InfoTech stocks may be undervalued overall, while Telecom and Consumer Discretionary stocks may be overvalued.
Performance: The table below shows the performance of each of the prior four weekly portfolios as of the market close on Tuesday, 2/2/10.
The recent crash in the Materials sector has been the main driver behind the strong performance of Sector Detector’s long/short model portfolio over the past four weeks. Also, the addition of Financials last week into the long portfolio was quite timely. This table demonstrates the benefits of an absolute return approach in beating the market...while allowing the investor to sleep better at night.
Disclosure: Author has no positions in stocks or ETFs mentioned.
About SectorCast: The rankings are based on Sabrient’s SectorCast model, which builds a virtual profile of each of the 10 ETFs in the table below based on bottom-up scoring of their constituent stocks. The model employs a fundamentals-based multi-factor approach including forward valuation, earnings growth prospects, analyst revisions, and various return ratios.
SectorCast has tested to be highly predictive for identifying the best (most undervalued) and worst (most overvalued) sectors, with a 1-month forward look. Of course, each ETF has a unique set of constituent stocks, so the sectors represented will score differently depending upon which set of ETFs is used. For Sector Detector, I use 8 Select Sector SPDRs, but because the SPDRs combine InfoTech and Telecom into one ETF, I use the two iShares for those sectors rather than the SPDR Select Technology ETF.
About Trading Strategies: Sector Detector has shown how you can use this information in three ways to identify ETFs that have the potential to enhance your upside, downside, or market-neutral trading ideas. First, if you are bullish on the broad market, you can go long the SPDR Trust exchange-traded fund (SPY), which tracks the S&P 500 Index, and enhance it with long positions in SectorCast’s top-ranked sector ETFs. Conversely, if you are bearish and short (or buy puts on) the SPY, you could also consider shorting the two lowest-ranked sector ETFs to enhance your short bias.
However, if you really don't want to bet on which way the market is going, you could try a market-neutral, long/short trade—that is, go long the top-ranked ETFs and short the lowest-ranked ETFs. And here’s a more aggressive strategy to consider: You might trade some of the highest and lowest ranked stocks from within those top and bottom-ranked ETFs, such as the ones I identify above.
About Performance Tracking: I track each week’s set of ETFs as a mini-portfolio over the course of four weeks. Because SectorCast does not include any technical triggers, this will give the fundamentals-based model a chance to achieve its predicted move.