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An Update On The Consensus Index Of Bullish Market Opinion
5/10/2000 11:30:51 AM
In a Market Observation that appeared yesterday, we discussed the Index of Bullish
Market Opinion that is published on a weekly basis by Consensus Inc. of Kansas City.
The survey, which polls futures traders, has served as a strong contrarian indicator in the
past. A large percentage of bulls will tend to occur when the public is already fully
invested in the market. As a result, the sideline cash needed to push the market higher
may be somewhat depleted. Conversely, when the percentage of bulls is at historically
low levels, it will often correspond with a market in which the public is under-invested. In
these instances, a greater amount of sideline cash is available to ultimately push the
market higher.
This morning, the most recent percentage of bullish opinion survey was released. The
percent of bulls has now fallen to 21 percent. Last week, the figure stood at 31 percent.
Today's reading of 21 percent is the lowest result since the 20-percent reading on
October 15 (see the first chart below). That reading corresponded with a short-term
market bottom and a successful test of the 10-month moving average for the S&P 100
Index (OEX - 747.48) (see the second chart below). The only move below the 20 level in
the last six years came in August 1998 in the middle of the international financial panic.
This signal also effectively marked a stock-market bottom at that time, as the OEX was
able to find support at its 20-month moving average.
Chart courtesy of Schaeffer?s Daily Sentiment
Chart courtesy of ILX Systems
As mentioned yesterday, the best "buy" signals from this indicator come after the percent
of bulls has moved back above the 30 level after a reading below this mark. This is
because pessimistic sentiment (a low percentage of bulls in this instance) can always
become more pessimistic. Since the public will likely be most pessimistic at the ultimate
bottom, it proves beneficial to wait until a bottom in negative sentiment can be clearly
identified.
- Jeremy Rehm (jrehm@sir-inc.com)
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