Cycles abound in the market. From intraday
to decennial frequencies, cycles have been
identified and written about. See Larry
William’s “The Right Stock and the Right
Time,” for example, and Jeffrey Hirsch’s
“Stock Trader’s Almanac.” One in
particular, though, makes theoretical sense
and, at the same time, can be supported
statistically: the pre-election year S&P
500 return in the Presidential cycle has
averaged +16.5% with16-of-16 positive years
between 1940 and 2006, while election,
post-election and midterm years returned on
average 7.0, 3.7 and 5.3%, respectively.
Clearly, the dynamic of a pre-election
year—like 2007—is different as those holding
power support economic policies favorable to
the economy and commercial profits.

Another cycle Hirsch has written about
extensively is the six-month cycle. It’s
embodied in the statement: “go away in
May.” Investing two $10,000 lots in the Dow
30 and segregating each into six-month
periods was eye opening. Between 1950 and
2006, investing in the Dow 30 stocks between
May 1 to October 31 and cash otherwise
reduced its $10,000 to $9,728, while
investing solely in the November 1 to April
30 period increased that $10,000 to
$515,480. Impressive, but the Dow index
suffers two inadequacies: it’s a price, not
market cap, weighted index, and it’s limited
to just 30 stocks. Ken Fisher in his best
seller, “The Only Three Questions That
Count,” explains why a price-weighted index,
like the Dow or NIKKEI, paints a totally
inaccurate picture of the market. Let’s
look at how the S&P 500, a market-cap
weighted index has performed over the same
time period.

The accompanying chart shows how the S&P
500—and the market generally--varied over the 1950-2006
period. Pre-election years are segregated for the 14
Presidential cycles, and each month’s close relative to
index’s annual average is charted as a percentage
change. Two points are obvious: (1) pre-election
years, like 2007, behave differently than the other
three in the election cycle, and (2)
June-through-December offered above average returns for
the year.

Putting these data in a little more
perspective, the probability of getting above average
performance in 13 of 14 pre-election years if there were
no positive bias, i.e., if there were a 50-50 chance
(like flipping a fair coin and getting 13 of 14 heads)
would be 0.000854 or one chance in 1170. Other
probabilities are as follows: 12 of 14 (0.005554), 11
of 14 (0.022217) and 10 of 14 (0.061096). Summarizing,
there is a high probability
in pre-election years
that the market reflects a positive bias for
the latter half of the year. As Ken Fisher suggests in
his most recent quarterly report, the rest of 2007
should indeed be bullish.