The top chart displays what I call the Momentum Curve (data obtained from the excellent Index Indicators site). This enables us to see the percentages of stocks in the SPX average that are trading above moving averages of varying lengths across the past five trading sessions. What we can see most recently is that the percentages of stocks trading above their 3, 5, and 10-day moving averages bottomed out ahead of the recent market low and now have moved smartly higher, even as we remain oversold vis a vis the longer-term averages. We typically see the reverse pattern at cyclical market peaks, where the percentages of stocks above their shorter-term moving averages head downward in advance of an ultimate price high.
The middle chart, also drawn from data available from Index Indicators, is a multiperiod measure of breadth specific to the stocks in the SPX average. Specifically, we're looking at the sum of new highs minus new lows over a 5, 20, and 100-day basis. The composite new lows bottomed most recently on October 13th, a few days prior to the recent price lows. The composite new highs topped well before the most recent price peak in September.
The bottom chart, drawn from data available on the very useful Barchart site, is a running total of the number of stocks crossing above their 20-day moving averages minus the number crossing below those averages. This covers all common shares across the major exchanges, which makes it a broader breadth-related measure. Most recently, the cumulative number of crossovers bottomed on October 1 and based for a while, as other breadth measures continued lower. The cumulative number of crossovers very commonly peaks well ahead of price during cyclical topping periods, as occurred prior to the September high.
New traders often look to indicators such as these for specific buy and sell signals. My experience is that analyzing any single indicator for such guidance is less helpful than synthesizing the information across multiple measures. Across a series of well-constructed measures that examine different portions of the market across differing time frames, common themes will emerge that tell a story. It's that story that ultimately provides the basis for useful trade ideas. The story is less about what markets *should* be doing based upon share earnings, economic fundamentals, or esoteric numerological schemes and more about concretely assessing whether the individual components of indexes, on balance, are trading stronger or weaker over time. The best way to use these indicators, I find, is to take the time to create a narrative that makes sense of all the observations--and then generate an alternative narrative suggested by data that don't fit into the original story. Having that "Plan B" narrative is very useful in staying flexible and avoiding confirmation biases regarding your primary view.
As with the other measures, I will be updating these periodically to keep up with evolving market conditions.
Further Reading: More Posts on Indicators and Patterns
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