Much of market theory assumes that price movement is difficult to predict because information is reflected in prices quickly. If that were fully accurate, persistent and measurable patterns would be less likely to endure.
They do.
Trends develop and can extend beyond what randomness alone would suggest. Leadership becomes concentrated and can remain in place for periods of time. These outcomes have been observed across different markets and timeframes, indicating that price behavior has structure, even if it is not always linear.
The same frameworks that argue for efficiency acknowledge this sort of fluctuation through what they classify as anomalies. Momentum and value are among the most widely studied of these.
Momentum reflects the tendency for securities that have outperformed to continue outperforming over an intermediate horizon—a phenomenon that has been observed across multiple market cycles.
Value reflects the tendency for lower-priced securities, when properly defined, to generate higher long-term returns, although results can vary significantly across periods.
Both patterns are observable. The challenge is not identifying the pattern, but rather determining how to apply it .
Momentum is often treated as a continuation strategy. That assumes strength alone is sufficient. It does not account for how the underlying conditions supporting that strength may be changing.
Value is often reduced to buying what appears inexpensive. This practice assumes price will revert without addressing whether the underlying business supports that outcome.
In both cases, the pattern is simplified to a single variable, which limits its usefulness.
The current market highlights these limitations.
The S&P 500 is holding above 7,000, with performance driven by a relatively small group of large-cap companies tied to artificial intelligence. A limited number of securities accounts for a disproportionate share of index movement.
At the same time, trading activity has remained relatively subdued compared to the strength of the advance, suggesting participation is not broad.
Expectations have also shifted. Earlier in the cycle, markets responded to projected investment in artificial intelligence. The focus is now moving toward whether that investment produces measurable returns, raising the threshold required to sustain current valuations.
These factors influence how patterns develop.
When price advances without broad participation or disruption, trends can continue without creating consistent entry points. Fewer resets in conditions reduce the number of situations where risk and pricing meaningfully diverge.
Opportunities tend to emerge when expectations are challenged and the market adjusts. These periods are often brief, but they create conditions where patterns become more actionable.
Momentum and value remain relevant, but their effectiveness depends on how they are applied within the current environment. And like I say each week, this is why I rely on my indicator to identify when those shifts in conditions are occurring—regardless of the broader market environment.
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