The Math Behind Stock Alerts

Understanding the statistical significance of our deviation thresholds.

๐Ÿ“Š 200-Day Moving Average

The foundation of our analysis. We calculate the simple moving average over 200 trading days:

MAโ‚‚โ‚€โ‚€ = (Pโ‚ + Pโ‚‚ + ... + Pโ‚‚โ‚€โ‚€) รท 200

This creates our baseline for measuring statistical deviations.

โšก Momentum Deviation

We measure how far the current price deviates from its 200-day average:

Deviation = ((Current Price - MAโ‚‚โ‚€โ‚€) รท MAโ‚‚โ‚€โ‚€) ร— 100

This percentage forms the basis for our percentile analysis.

๐ŸŽฏ Statistical Significance (1-Sigma)

Our extreme thresholds correspond to statistically significant percentiles:

16th Percentile โ‰ˆ -1ฯƒ (1 standard deviation below mean)
84th Percentile โ‰ˆ +1ฯƒ (1 standard deviation above mean)

In a normal distribution, ~68% of values fall within ยฑ1ฯƒ, meaning only 32% of observations are "extreme" (16% below, 16% above).

๐Ÿ“ˆ Why These Percentiles Matter

The 16th and 84th percentiles represent statistically significant deviations:

P(X โ‰ค 16th percentile) = 0.16 (16% probability)
P(X โ‰ฅ 84th percentile) = 0.16 (16% probability)

When a stock hits these levels, it's experiencing a rare event that occurs only ~16% of the time historically.

Why 1-Sigma? One standard deviation captures meaningful but not extreme outliers. It's frequent enough to be actionable (~16% of the time) but rare enough to be statistically significant.