1/20/2026 - Do we find hidden edges among small cap stocks as well as the large cap issues in the SPX? For this analysis, we go back to 2015 and examine the percentage of stocks in the S&P 600 universe ($SML) that are trading above their 3, 5, 10, 20, 50, 100, and 200-day moving averages. These data are readily available on the excellent MarketCharts site. I specifically examined the variability of the breadth readings: the standard deviation of each day's data. The variability captures two market scenarios: when short term breadth turns much higher following a longer-term period of weakness and when it turns much lower following a longer-term period of strength. Note that this is a different way of identifying breadth thrusts.
When variability has been in its highest quartile (thrust conditions), the next 20 day return in $SML has been +1.70%. That compares to a 20-day return of -.05% when breadth readings have been least variable.
There are many other patterns that can be found in the small cap data.
Once again, the idea is not that you should trade small caps or trade them based on these particular historical patterns. Rather, the idea is that a large number of traders focus on the information that is most readily available and that takes the least analysis (chart patterns, news reports), leaving significant opportunities to those willing and able to collect and analyze data. Meaningful edges are to be found over time frames longer than most traders look, and that's why they're hiding in plain sight.
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1/19/2026 - Many traders view technical indicators as something to chart; then they look for chart patterns. In fact, many technical indicators produce data that, when backtested, yield important hidden edges. The stockcharts.com site gives daily readings on a number of technical measures that can be downloaded and tested. For example, when a large number of stocks in the NYSE display an improving Chaikin Money Flow (top quartile of distribution since 2021), the next 30 days in SPY average a gain of only +.55% compared with almost three times that much for the rest of the sample. When a large number of stocks display a weakening Money Flow (weakest half of the distribution), returns average twice as much over the next 30 days than the rest of the sample.
Consider Bollinger Bands. When very few stocks in the NYSE close above their upper Bollinger Bands since 2021 (lowest quartile of distribution), the next 30 days in SPY have shown a dramatic upside edge: three times the average returns of the remainder of the sample.
Most powerful is when relatively uncorrelated indicators display historical edges that line up with one another. Conviction is not just a state of mind. It follows from rigorous analysis and understanding of market behavior.
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1/18/2026 - Now let's take a look at a different hidden edge in the market: not strength, but the absence of weakness. For this analysis, we'll go back to August, 2010 when I began collecting these data (available via Barchart.com) and take a look at the number of stocks in the NYSE universe that are making fresh monthly highs and fresh monthly lows. What we find is that next 20-day returns in SPY average +1.44% when monthly lows are in their lowest quartile. That is about double the return of the next two quartiles. When few stocks are weak, overall market declines are rarer. It takes weakness in some areas of the market to lead the broad averages lower.
Interestingly, next 20-day returns are also superior (+1.27%) when new monthly lows are in their highest quartile. In other words, when we have lots of stocks making new lows and the market is flushing out, that has often been a good time to find value. A similar pattern shows quite superior returns 50 days out when three-month new lows are either very low or very high.
So why are these edges hidden to most traders? They haven't taken the time to download and analyze the data, and they are looking for things to trade in the next few minutes and days--not what has dramatic edge over a period of weeks to months. The need to trade actively hides the edges that play out over time.
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1/16/2026 - Some of the best hidden edges in the market occur, not when institutions are piling into stocks or fleeing them, but when they are rotating existing assets from one sector of the market/economy to others. This sector rotation can easily be tracked by following the breadth within each sector. In this post, we'll use the percentage of stocks trading above their 20-day moving averages as a breadth proxy for each sector. (Data available from Barchart.com).
So let's take the breadth within the energy sector (XLE) minus the breadth of the overall market (SPY). When energy breadth is in the top half of its distribution since 2020, returns in SPY over the next 10, 20, and 30 days are distinctly subnormal. Indeed, when energy sector breadth is highest relative to overall market breadth, the returns over the next 3-5 days have been negative--quite a feat in a bull market period!
Energy stocks do well when energy prices are rising. But that is not an environment that is necessarily good for the overall economy. Seeing where money is flowing alerts us to potential headwinds and tailwinds in the broad market.
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1/15/2026 - Some of the most promising edges in the stock market are found in places traders generally don't look. Actually, this dynamic occurs across markets. For example, the majority of traders in the fixed income (interest rates) markets look for events (central bank policy changes; shifts in patterns of growth) to buy or sell rates. A more subtle approach looks at how rates vary from one another within and across bond markets and trades those relative relationships. So, for instance, if nothing has changed in central bank policies and in macroeconomic news, one part of the rate curve may be priced cheaply relative to another point, or rates in one region of the world will be expensive relative to another region. This offers the opportunity to buy what's cheap, sell what's expensive, and profit from the "mean reversion" when rates return to a more normal relationship. This is a great example of how we can improve our trading psychology by expanding our understanding and perception of opportunity.
So let's start looking at relative relationships within the stock market. I went back to 2020 and calculated the difference between the percentage of stocks above their 5-day moving averages within the consumer staples sector minus the percentage of stocks above their 5-day moving averages within the consumer discretionary sector. These data are readily available on the Barchart.com site. When investors are expecting growth and a strong economy, they are drawn to the consumer discretionary shares which benefit from consumer spending on things like travel, entertainment, etc. When investors are expecting economic weakness, they expect that spending on essential staples will continue, while discretionary spending will decline. By tracking the percentage of stocks in the consumer staples sector above given moving averages minus the percentage of stocks in the consumer discretionary sector, we have a handy economic sentiment measure.
Interestingly, in the quartile of occasions in which the difference between the percentage of stocks above their 5-day moving averages for XLP (staples) minus those for XLY (discretionary) is greatest, the next 20 days of performance in SPY averages only +.42%. All other occasions average +1.36%. When investors flee growth relative to stability, that theme tends to continue in the short run. When we look at the difference between the percentage of stocks above their 20-day moving averages for XLP minus those for XLY, we find a similar pattern 20-50 days ahead. Forward returns in SPY are subnormal when investors are fleeing to the safety of staples.
The point isn't that you should run to trade this pattern. The point is that patterns exist where most traders aren't looking. While the noobs are looking at directional charts, a world of opportunity is being found by the pros in relative space. When you have more ways to identify opportunity, you build an opportunity mindset. Better trading leads to better psychology.