Nov 03, 2003

Bottom Line: Any positive influence this seasonal pattern may have could last through the end of the year, but not beyond that.

One of the seasonal patterns that has been getting more press lately is that of the Presidential cycle. The theory behind looking at market performance this way is that administrations will do what they can to stay in power, including economic stimulus, and this may have an impact on the stock market. The year prior to an election tends to be the strongest, and the following table breaks it down by month for the S&P 500 from 1951 through 1999.

In the table, "AVG" refers to the average gain or loss from the last day of the prior month to the last day of the month shown, "%POS" shows the percentage of time that month closed higher than the month before, "AVG GAIN" refers to the average return of those months that closed positively, "AVG LOSS" shows the average return of those months that closed negatively, and “B/W” outlines whether the month is better or worse than an average month.

MONTH	AVG	%POS	AVG GAIN	AVG LOSS	B / W
JAN	5.3%	100%	5.3%	0.0%	B
FEB	1.1%	69%	2.7%	-2.5%	B
MAR	2.4%	85%	3.1%	-1.0%	B
APR	3.3%	92%	3.6%	-1.1%	B
MAY	-0.3%	46%	2.6%	-2.9%	W
JUN	1.8%	62%	4.2%	-2.1%	B
JUL	1.4%	62%	4.3%	-3.3%	B
AUG	1.4%	54%	3.5%	-1.0%	B
SEP	-0.6%	31%	2.4%	-2.1%	W
OCT	-1.9%	38%	3.6%	-5.3%	W
NOV	0.7%	62%	3.0%	-2.9%	W
DEC	3.5%	77%	4.8%	-0.7%	B

We can see that 8 out of the 12 pre-election-year months tend to be more positive than a regular, “normal” month. Applicable to our current period, November tends to perform a bit less positive than normal during a pre-election year, but overall it is still a positive month. December, on the other hand, has handily outperformed a random December during this type of cycle. In fact, the largest loss the S&P suffered in December during a pre-election year was just over 1%, while the largest gain was over 11% and there were 4 years where the gain was over 5%.

If we look at the next year (the year of the election), things aren’t quite as positive, as the following table outlines:

MONTH	AVG	%POS	AVG GAIN	AVG LOSS	B / W
JAN	0.6%	54%	4.4%	-3.9%	W
FEB	0.0%	54%	2.0%	-2.4%	-
MAR	1.0%	69%	3.3%	-4.3%	-
APR	0.6%	62%	2.4%	-2.1%	W
MAY	0.0%	69%	1.8%	-4.0%	B
JUN	1.9%	85%	2.6%	-2.0%	B
JUL	0.5%	46%	3.2%	-1.9%	W
AUG	1.0%	54%	3.8%	-2.3%	B
SEP	0.2%	54%	3.1%	-3.1%	B
OCT	0.5%	62%	1.2%	-0.6%	-
NOV	1.9%	54%	5.5%	-2.3%	-
DEC	1.1%	77%	2.4%	-3.2%	-

We can see here that three months tend to perform worse than average, and four better than average. The other five didn’t exhibit a behavior markedly different from an average month.

While this pre-election pattern may hint at a little less positive action than usual in November, December tends to be extremely positive. Of course, we’re only working with 13 samples here, so the statistical significance of this is questionable. We could go back further and test the data from earlier in the century, but I have great reservations about trying to extrapolate those results into the future due to the momentous shifts in market dynamics that have occurred since then (e.g. the rise of institutional funds, the flourishing “alternative” markets such as futures and options, etc.).

Bottom Line: These traders are very close to reaching a fever pitch of speculative excess, and that is never a good thing.

One of the charts that I post to the site each evening is a stochastic of the bull ratio for the Rydex fund assets, appropriately called the Rydex Stochastic. A stochastic measurement simply tells you where the current reading is compared to all other readings over a certain look-back period, in this case three months. A reading of “0” means that the current reading is the lowest seen during that time, while a reading of “1” means that the current reading is the highest. I compute the bull ratio on these funds differently than you will likely find elsewhere, as I weight the fund assets according to their leverage. So $50 million moving into an un-leveraged long fund (such as their OTC fund) will get half the weight that $50 million moving into Velocity would (since their Velocity fund is leveraged 2-to-1). I think this is an appropriate way to look at the data, since investors moving into a leveraged fund are likely significantly more bullish than those moving into an un-leveraged fund, and this should be accounted for.

This means that our Rydex Stochastic measure looks at how aggressive these traders are spreading their money among the total assets in the index fund, and compares it to other readings over the past quarter. When we look at how the S&P 500 has performed after these traders become so aggressive that the stochastic reaches 0.95 or higher, the results are unpleasant. The table below shows these results for the 17 days since August 2000 where the stochastic has reached 0.95 or higher:

	1 Day Later	3 Days Later	5 Days Later	10 Days Later
Avg Ret	(0.4%)	(1.2%)	(2.6%)	(2.9%)
% Pos	24%	29%	12%	0%
Max	2.8%	2.3%	0.5%	(0.6%)
Min	(2.1%)	(3.0%)	(5.7%)	(6.3%)

We can see from the table that the S&P 500 was lower after 10 days every single time, and the bias to the downside was quite large. There was wiggle room in the first few days, but after that, the speculative excesses were worn off via a declining market. The reading we saw last night was 1.0 – the maximum possible - and something that has been matched on only six other days over the past three years. If you pull up the chart on the site, you will not quite see these extremes, as I use a 5-day moving average for that chart.

Below, I have included the “raw” daily readings so you can see how it has acted during the rally beginning this Spring.

Although the indicator didn’t quite reach the 0.95 cutoff in late April, it came as close as possible – 0.94 on April 23^rd. After that, the S&P dropped a quick 22 points over the next two days before resuming its uptrend.

We don’t look at the Rydex data thinking that the market is out to “get” these traders, or that their asset movements can affect the market. The reason these asset flows are effective is because is shows us on a daily basis how a representative sample of traders are adjusting their real-money assets. We know from experience that these traders are almost invariably wrong when they become excessive in their aggression in one direction or the other, and right now it is important to know that these traders are becoming extremely optimistic about the odds for significantly higher prices. While there is some room in the very short-term for these traders to enjoy the ride, history (even during this latest rally) suggests the high-odds play is to sell to this type of mini-mania.

For the past week and a half, I’ve been suggesting that I prefer to concentrate on the long side, or at least not the short side, until we begin to see some failures and/or more evidence of excessive speculation. We’re now beginning to get some of both, as I consider the action on Tuesday and Wednesday to be one sign of a failure. We still haven’t broken any short-term trendlines that I’m watching, or failed to rally from short-term oversold conditions, so on those counts the upside has the edge.

The other side of the coin is excessive speculation. Even in an uptrend, when it gets too heated the market usually takes at least a 2-3 day breather. Plus, we’re now past the first part of the most seasonally strong part of November and will have to wait until around Thanksgiving for the second part. The unknown on seemingly everyone’s lips is the jobs report, due tomorrow before market open. I have no edge in guessing what it contains, so I’m not going to try. It should be noted that historic and implied volatilities are pushing multi-year lows, and I can’t even count how many times I’ve talked about and shown that periods of low volatility are most often followed by periods of high volatility, and these types of catalysts (the jobs report) can be just the thing to snap the rubber band. I certainly have no desire at this point to chase any potential rally we get off tomorrow’s report, but I do have a heightened interest in finding a spot to short it.

Longer-term, I’m still not convinced that any decline we do see will be deep enough or severe enough to warrant establishing short positions other than for a short-term trade. I’ve outlined several times that the momentum we’ve seen during this rally, and its persistency, tend to last longer than we’ve already seen. When we add in the consistent positive bias to the December/January time frame, it makes it difficult to envision a deep, long-term decline during this time.

This disclosure is not intended as trading advice in any form. It is meant as a note to subscribers that the author may have a position directly affected by the market outlook reflected in the commentary. Although the author takes great pains to remain objective in any commentaries, it is only fair that readers should know that the author may have taken positions in accordance with his market outlook. Positions can and do change at any time, without notice to the reader.

I received a few questions about the VIX yesterday. You may have noticed that it actually rose, despite the positive day in the broader market. I’ve shown several times before how it is unusual for the VIX to rise on days the S&P 500 also rises. In fact, it happens about 12% of the time. The unusual part about this is that it happens a little more frequently now than it used to, since the CBOE has switched to its new method of calculating the widely-watched volatility measure. From January 1990 through June 2003, the VIX rose on the same day as the S&P 30 more times with the new calculation than with the old. That isn’t a huge difference, but it is important to point out that there are some nuances with the new calculation that should be addressed so you minimize that chances of making spurious correlations (for example, assuming the rise in the VIX yesterday was a sign of disbelief in the rally).

One of these nuances is how the new calculation treats calendar days versus trading days. I’m not going to go into the details, because the theoreticals aren’t really that important for this discussion. What IS important is knowing that the VIX tends to act differently now on Mondays. With the old calculation, looking over the past 10 years, the VIX rose on Mondays 49% of the time. Its average increase was 0.3%. However, when we look at the “new” VIX, it rose on Mondays more than 70% of the time during that same period, with an average increase of 2.5%. The other days tended to follow each other pretty closely.

I’ve talked before about how the VIX shows some seasonal tendencies. It usually drops below average during the dog days of summer, then picks up above average during the Fall (this is true with the new calculation as well). If we adjust for these consistent seasonal tendencies, some differences tend to emerge. For example, on Friday the VIX closed at 16.10, which is in the bottom 30% of readings over the past decade. But if we adjust that figure to back out the seasonal biases discussed above, it drops down to 14.45, which is in the bottom 22% of readings over that same time period. So, when we look at a more “pure” VIX reading, implied volatility is even lower than it appears on the surface. It can remain this way for months on end, as we’ve already seen, but it must be kept in mind that traders are not seeing any need to protect themselves, which is fine until they need it. A cascading move lower is an increasing possibility in this type of environment.

Bottom Line: Moving one low-dollar stock from one column to another greatly affects today’s reading

Today’s NYSE TRIN reading closed at 1.88, which is quite high. It is especially unusual considering today’s moderate down day in the market. This highlights a quirk with the TRIN that I’ve mentioned before. Whenever you take ratios of ratios, which is what the TRIN does, it can sometimes give very unusual readings if one figure is a little off. As outlined on the site, the TRIN is calculated by taking the number of issues that advanced on the day divided by those that declined. You then divide that by the volume that went into the advancing issues divided by the volume into declining issues.

Even though the number of advancing issues and declining issues were fairly close, declining volume was nearly twice that of advancing volume. That fact is what makes the TRIN elevated – when there is heavy volume in a relatively small number of issues, the TRIN will be greatly skewed. It is typically NOT a good measure of broad-based selling pressure.

The main culprit of today’s skewed reading was Lucent. If that one stock had rallied just $0.13 by the close, then the TRIN reading for the entire NYSE would have gone from 1.88 down to 1.53. If we do the same with AT&T Wireless, then the TRIN drops even further to 1.41. This is more in line with one what would expect given today’s moderate decline in the broader market.

Today’s high TRIN reading was not a sign of broad-based, heavy selling pressure. It was due primarily because two low-priced stocks saw an inordinate amount of downside volume. If those two stocks had rallied enough to close positive on the day, then the NYSE TRIN would have declined by 25%. Be very leery when you see “odd” TRIN readings on moderate days – it is usually just an anomaly, and not a reason for undue concern.

Bottom Line: One of the most effective, readily available indicators we have is heading quickly towards a sell signal

I talk quite a bit about put/call ratios, usually to the chagrin of those who are familiar with options and know what games are played behind the scenes. But as I showed a few days ago, the CBOE equity-only put/call ratio with QQQ options removed tracks the ROBO put/call ratio quite closely, and with that ratio we know exactly what we’re getting. So, I feel comfortable with the CBOE ratio as a contrary indicator, and it has actually done quite a good job at highlighting many of the short-term extremes since March.

The chart below is a 5-day moving average of that CBOE ratio, with some simple trendlines drawn in where the ratio has reached its extremes. We can see that the ratio has been trending lower during the rally, and in fact a 60-day moving average of this data is at its lowest point in its two-year history.

I have drawn in red arrows where the ratio reached a low extreme and began reversing higher (showing traders became overly optimistic by concentrating on call options), and green arrows where the ratio reached a pessimistic extreme when traders were concentrating too much on puts.

Currently, we are coming off the short-term pessimistic extreme seen in late October and are heading quickly to overbought territory. We could reach the 0.45 level or lower in this ratio in another two days should we continue to see the type of option activity we’re seeing now. The ratio is fairly low already, but it has been trending lower during the rally and I would prefer to see something under 0.45 before becoming too anticipatory of a market decline (based on this indicator alone).

This weekend, I noted that I was still not seeing the short side as a high-odds bet and would not until we either saw more speculative model and indicator readings or some type of price failures. I’m still not seeing too many of our indicators push to optimistic extremes where it would have me feeling more comfortable on the short side. We’re close, but not quite there yet – a couple more days of rallying would likely do it. On the other hand, we’re perilously close to having a first failure, as we made it above the mid-October high but have come right back down. A decline (and close) below 1050 would not be a good thing. However, the uptrend still gets the benefit of the doubt in my opinion until we drop below 1020ish and/or cannot rally off short-term oversold readings. Unless or until those things happen, I am viewing dips as short-term buying opportunities. Longer-term, I don’t think either side is particularly attractive, and have every intention of waiting until a more defined and high-probability risk/reward scenario presents itself.