Z-Score — Statistical Anomaly Parameter

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What is Z-Score in DCMM?

The Z-Score is a statistical normalization parameter that measures how far the current price move deviates from the stock’s historical norm, expressed in standard deviations. In the DCMM context, Z-Score serves as an anomaly detector — identifying when a stock’s recent behavior is statistically unusual compared to its own history.

How Z-Score is Calculated

The Z-Score is calculated using the standard statistical formula applied to price changes:

Z-Score = (Current_Move - Mean_Historical_Move) / StdDev_Historical_Move

Where the mean and standard deviation are calculated from the stock’s own historical price movements under similar conditions (same market regime, similar DD stage).

A Z-Score of 0 means the current move is exactly average. Negative Z-Scores indicate the stock is performing worse than its historical average under similar conditions.

Interpreting Z-Score Values

  • Z-Score > +2.0 — Strong positive anomaly. The stock is performing exceptionally well relative to history. Watch for potential exhaustion of the move.
  • Z-Score +0.5 to +2.0 — Mildly positive. Normal to good performance.
  • Z-Score -0.5 to +0.5 — Near historical average. Neutral signal.
  • Z-Score -0.5 to -2.0 — Below historical average. The drawdown is somewhat worse than typical, but still within the normal range for mean-reversion setups.
  • Z-Score < -2.0 — Significant negative anomaly. The stock is behaving very unusually on the downside. Exercise extreme caution — something may be fundamentally wrong with this stock or sector today.

Z-Score as a Setup Filter

Z-Score is used in DCMM primarily as a negative filter — to avoid setups where the price decline is statistically extreme:

  • A very negative Z-Score (< -2.5) often indicates a news event, earnings miss, or sector-specific shock that invalidates the mean-reversion thesis
  • In these cases, the Historical Twins may not be relevant because the current decline is driven by fundamentally different factors than historical drawdown cycles

Z-Score and Anomaly Detection

Beyond individual stock analysis, Z-Score is aggregated across the watchlist to detect broader market anomalies. When many stocks simultaneously show Z-Scores below -2.0, it often signals:

  • A market regime change (from NORMAL to CAUTION or RISK-OFF)
  • A sector rotation event
  • An exogenous shock (macro event, geopolitical news)

Practical Use

In the DCMM workflow:

  1. After identifying high Exp Score setups, review the Z-Score column
  2. Avoid setups where Z-Score < -2.0 (anomalous negative behavior)
  3. Prefer setups where Z-Score is in the -0.5 to -2.0 range (normal pullback territory)
  4. Mildly negative Z-Scores combined with high P_win and R/R are the sweet spot for mean-reversion trades

Z-Score in the Dashboard

In the DCMM Excel dashboard, the Z-Score column appears in the right portion of the main data table. Values are color-coded: neutral values appear without highlighting, while extreme negative values may be flagged for visual prominence. Cross-reference with the Cycle Drop (%) to understand whether a strongly negative Z-Score is justified by the size of the price move.

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