(18 October 2026) Stocks declined last week as inflation pressures and the prospect of additional interest rate hikes raised doubts about the economic viability of the AI build-out. The tech-heavy NASDAQ slumped 5% while the S&P 500 fell 2%. Interestingly, the broader indexes actually rose modestly on the week as investors rotated out of the AI trade.
Is this the start of a larger pullback? It’s quite possible since the bullish alignments are on the wane while the bearish alignments continue to intensify We had noted the likelihood of some market weakness around the time of the 135-degree Jupiter-Saturn alignment on Oct 31. This negative influence was more likely to prevail since the bullish impact of other alignments such as the heliocentric progressed Mercury-Venus trine essentially ended in early to mid-October.
The chart below is a snapshot of all of the current alignments we are monitoring. Each line represents the relative market impact of an alignment based on historical backtesting. The lines track cumulative price changes across various intervals using an adjusted mean, i.e. the midpoint between the mean and median. We should note that this calculation of relative influence omits consideration of standard deviation, p-values and statistical significance. It should therefore not be seen as the final word on the probable influence of an alignment, but simply a unweighted estimate.
We can see that many of the bullish alignments that are located above the zero line are concentrated in late September and the first half of October. In contrast, more of the bearish below zero alignments are associated with the second half of October and November. This raises the likelihood of more market weakness going forward.
Another way to evaluate the overall effect of these alignments is to weigh relative influence by including their statistical significance. For example, an alignment that produces a 2% mean gain over a 20-day interval with a high standard deviation (e.g. > 5%) and subsequent high p-value (e.g. >0.5) is a less reliable predictor of future market moves than an alignment that produces a 1% mean gain in the same 20-day interval with a low standard deviation (e.g. <2% and low p-value (e.g. <0.05) that reaches statistical significance. The statistically significant alignment makes that 1% gain a more likely outcome.
The Effect Index therefore combines both average price changes and data distribution (i.e. p-value) in a way that makes it a better indicator of future outcomes. The Effect Index calculation is: (mean + median)/2 * (% positive cases) * (1 – p-value). The lower the p-value of a tested interval — and thus the greater its statistical significance — the higher the Effect Index.
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