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Issue No. 60 – January 9, 2006 Prescott, Arizona Systems@WiserTrader.com
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1.0 Trading
Are the major averages engaged in a premature breakout or something more substantial?
1.1 Breakout
A 2 year chart for the S&P 500 Index in Figure 1 shows the index protruding less than 1% above the upper trend line of a rising wedge formation, closing last week at 1,285. The first 4 trading days of 2006 were substantially better than 2005.
FIGURE 1
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This is a statistically interesting time. It has been observed that when the first 5 trading days of January have been up, the index has gained an average of about 13% for the year. The rule has held up about 85% of the time. However, in midterm election years, such as the current one, the rule has held only 43% of the time.
A more robust rule, developed by Yale Hirsch in 1972, states that as the month of January goes, so goes the year. This rule has better than 90% accuracy. When the S&P January gain was around 3.6% or more, the rule has been accurate 100% of the time over the last 50 years.
However, the price of oil is rising once again and, by short term measures, the market is overbought. The recent tendency for traders to sell into strength should not be overlooked. Should the index fall back into the rising wedge formation, it would be bearish for the near term. For now though, volume is higher than average and market breadth is good.
1.2 Filter Studies
Continuing with filter performance studies, the latest 1 year period is shown at the bottom of Table 1. Details of the filters can be found on the web site. The objective of this portion of the analysis is to find the right parameter that describes how S&P 500 performance affects profits for the previous year. Currently we are tracking filter performance with the previous month’s average index value relative to its mean 200 day simple moving average (SMA) for the previous month. The correlation is promising.
Table 1
1 Year Filter Performance versus the S&P 500 Index
Using No Trailing Stop
|
Year Ending |
Prior Year S&P 500 |
Prior Month Avg. S&P 500 Relative to its Mean 200 Day SMA |
Growth $15-$40 Filter |
Growth >$40 Filter |
Absolute Value Filter |
Relative Value Filter |
|
9/02/05 |
9.4% |
+2.5% |
60.1% |
40.7% |
19.3% |
50% |
|
9/30/05 |
8.6% |
+2.3% |
25.4% |
61.4% |
12.3% |
24.1 |
|
11/04/05 |
8.0% |
-0.6% |
8.2% |
14.8% |
4.4% |
-0.6% |
|
12/02/05 |
6.2% |
+2.9% |
24.6% |
9.6% |
17.0% |
34.7% |
|
01/06/06 |
8.2% |
+4.5% |
39.8% |
50.3% |
27.8% |
28.3% |
As the index pulls away from its 200 day SMA, stocks are affected favorably. As the index moves toward its 200 day SMA, stocks are affected adversely. A more detailed look at this is obviously needed.
It still amazes me how the previous month’s index activity has such a strong impact on a full year’s profits. Clearly this is showing us the importance of an ability to anticipate the behavior of the S&P 500 Index. The study will continue at 1 month intervals.
2.0 Market Analysis
The fact that the anticipated repeat of the January 2005 sell off did not occur was met with relief. The Fed’s December FOMC minutes, indicating a lower certainty of further rate increases, provided a rosier outlook for the economy in general and for stocks in particular. A lower cap on interest rates increases the value of stocks and options in valuation models.
Key industry ETF’s in Table 2A are Biotech and Semiconductors which confirm the NASDAQ. Transportation confirms the Dow Jones Industrial Average according to Dow Theory. Banking and Financials are confirming indicators for the S&P 500. Gold and Real Estate are respective indicators for the inverse health of the currency (inflation) and the capacity for consumer spending.
Table 2A
Indices, Key Industry ETF’s and Sector SPDR’s
|
|
1 month |
1 wk ago |
2 wks ago |
3 wks ago |
4 wks ago |
|
Dow Jones Industrials |
1.7% |
2.3% |
-1.5% |
0.1% |
0.9% |
|
NASDAQ |
2.2% |
4.5% |
-2.0% |
-0.1% |
-0.2% |
|
S & P 500 |
2.1% |
3.0% |
-1.6% |
0.1% |
0.6% |
|
Russell 2000 |
1.5% |
3.9% |
-1.9% |
0.5% |
-0.8% |
|
GLD, GOLD |
2.5% |
4.1% |
2.9% |
0.1% |
-4.4% |
|
RKH, Banking |
1.4% |
2.2% |
-2.3% |
0.0% |
1.5% |
|
IYT, Transportation |
2.2% |
0.2% |
-1.7% |
2.7% |
1.0% |
|
SMH, Semiconductors |
4.5% |
8.2% |
-3.1% |
-0.6% |
0.3% |
|
BBH, Biotechnology |
-0.8% |
0.5% |
-2.0% |
2.3% |
-1.5% |
|
IYR, Real Estate |
2.4% |
4.8% |
-1.8% |
-1.1% |
0.6% |
|
OIH, Oil |
4.9% |
8.7% |
-2.5% |
1.4% |
-2.3% |
|
XLE, Energy |
3.2% |
6.3% |
-1.8% |
0.4% |
-1.4% |
|
XLU, Utilities |
0.6% |
2.5% |
-1.4% |
-1.5% |
1.0% |
|
XLB, Materials |
3.9% |
3.7% |
-0.8% |
2.4% |
-1.4% |
|
XLI, Industrial |
1.0% |
1.1% |
-1.3% |
0.5% |
0.7% |
|
XLK, Technology |
0.8% |
5.3% |
-2.3% |
-0.8% |
-1.1% |
|
XLV, Healthcare |
4.4% |
2.6% |
-1.8% |
1.9% |
1.6% |
|
XLF, Financials |
1.8% |
2.5% |
-1.6% |
0.7% |
0.3% |
|
XLP, Consumer Staples |
0.6% |
0.9% |
-1.6% |
-0.5% |
1.9% |
|
XLY, Consumer Discretionary |
-0.1% |
2.1% |
-1.3% |
-1.0% |
0.1% |
