ZenAlgo - Coin X

A multi input Z Score framework that compares the behavior of a selected symbol against several market wide aggregates: total crypto market metrics, alternative asset baskets, stablecoin dominance, Bitcoin, and risk composites. The script processes each data stream into comparable normalized values, evaluates their relationships, and derives a set of bias states, alerts, and real time conditions.

Data Preparation and Normalization

The indicator starts by gathering multiple reference series:

• The chart ticker.
  
• A basket representing non Bitcoin crypto assets.
  
• Bitcoin market data.
  
• Several total market variations (full, without Bitcoin, and additional categories).
  
• A stablecoin dominance series.
  
• A macro risk composite.
  
• A daily anchored average used for context.
  

Each series is transformed into a normalized value using a lookback window. This produces multiple comparable Z Scores that reflect how far each series currently sits from its typical range. Smoothing is optionally applied to macro based values to reduce noise. These normalized values allow consistent comparisons across unrelated instruments.

This works because Z Score based normalization removes scale differences and makes directional deviations directly comparable across many independent metrics, which is necessary when the script later evaluates their relationships.

Cross and Momentum Detection

The script then evaluates structural interactions between the normalized series:

• Whether one group rises above or falls below another.
  
• Whether any of the series crosses over or under another.
  
• Whether each series is currently advancing or declining.
  
• Whether price is above or below the daily anchored average.
  
• Whether stablecoin dominance is rising or falling.
  
• Whether a sharp directional change occurs within a single bar.
  
• Whether a multi threshold movement happens within a defined number of bars.
  

These checks capture relative strength shifts across the market. For example, an increase in the ticker combined with a decline in dominance suggests capital rotation toward the ticker, while the opposite suggests defensive flows. Using normalized changes allows these comparisons to be scale independent.

Combined Bias Logic

The indicator then evaluates a hierarchy of conditions that combine normalized relationships, momentum, and sharp movement checks. Each condition corresponds to a specific market state. The script tests the conditions in a defined order because later conditions depend on earlier structural checks.

Examples of combined evaluations include:

• Cases where the ticker and alternative asset basket rise together while dominance declines.
  
• Cases where both the ticker and alternatives fall together under a rising dominance series.
  
• Conditions where several aggregates cross above or below dominance simultaneously.
  
• Cases where multiple aggregates show coordinated sharp rises or sharp declines.
  
• Situations where stablecoin dominance rises during weakness of other groups.
  
• Situations where stablecoins fall while the ticker strengthens.
  
• Conditions where the ticker rapidly moves through several thresholds in a short period.
  

The script assigns a bias label that corresponds to the earliest satisfied condition. This design ensures that highly distinctive and rare states take priority over broader or more common states. The reasoning behind this is that specific coordinated market moves provide clearer view than general divergence or simple momentum alone.

Crash and Pump Amplification

The script includes a section that detects extreme scenarios by combining several coordinated factors:

• Very negative or very positive normalized values across multiple aggregates.
  
• Sharp bar by bar declines or rises across key series.
  
• Simultaneous movement in the risk composite and dominance.
  

These checks amplify certain bias states when market conditions show synchronized extreme movement. This provides additional clarity when multiple parts of the market behave in the same direction beyond typical deviation. The logic relies only on the relationships of the normalized values and their changes.

Fast Movement Detection

Two additional mechanisms evaluate movements over a short multi bar window.

• A fast ticker move is detected when the current normalized ticker value differs from one several bars ago by multiple threshold increments.
  
• A fast stablecoin rise or fall is detected using a step based method. The script checks for progression through sequential levels across the window while verifying whether the ticker moves in agreement or disagreement with the direction.
  

These mechanisms are intended to identify sudden acceleration or deceleration that standard normalized changes may not fully capture.

Season Scale

The script calculates a quantitative scale from minus 100 to plus 100 by evaluating several binary conditions:

• Whether the ticker is above or below the alternative basket.
  
• Whether the alternative basket is above or below dominance.
  
• Whether the ticker and alternative basket are rising or falling.
  
• Whether dominance is rising or falling.
  
• Optionally whether price is above or below the anchored average.
  

Each condition contributes positively or negatively. The weighted combination produces the season value which is rounded. The naming of the state (Full Bull, Neutral, Full Bear etc.) is derived from where the score falls on the range.

This works because combining several directional tests across related groups provides a compressed singular measure of market structure.

Divergence Detection

The script includes divergence logic for Bitcoin, the alternative asset basket, and the chart ticker. It evaluates pivot highs and lows in price and compares them with pivot highs and lows in their respective normalized values. The script checks for pairs of pivot points where price moves in one direction while the normalized oscillator moves in the opposite. Both regular and hidden forms are evaluated.

This works because divergences highlight points where price and its normalized deviation disagree which often marks a structural imbalance.

Table Output

If enabled, the indicator displays a table showing the current normalized values of all monitored series along with color backgrounds reflecting structural relationships identified earlier. This supports interpretation without opening additional charts.

Visual Lines and Background

The script draws horizontal reference lines for several normalized levels using a fading mechanism if ghost mode is enabled. The background color changes according to the main season logic and intensifies with market wide deviations. Optional pulse effects are triggered when the bias state changes.

This works because visual context helps understand how extreme the current market state is relative to its typical historical range.

Alerts

The indicator creates alerts for all important structural states:

• Bias state changes.
  
• Fast ticker moves.
  
• Fast stablecoin rises or falls.
  
• Divergence based triggers.
  
• Cross conditions corresponding to notable structural transitions.
  

These alerts correspond exactly to the logical conditions already described.

Added Value Compared to Free Alternatives

• It evaluates many separate market wide aggregates simultaneously rather than relying on a single comparison.
  
• It uses a consistent normalized framework so unrelated metrics become comparable.
  
• It identifies multi series coordinated shifts which many simpler indicators cannot detect.
  
• It provides a full deterministic bias state hierarchy that removes interpretation ambiguity.
  
• It includes fast movement evaluation through multi level and multi bar logic.
  
• It combines multiple categories of divergences with normalized values rather than only price based oscillators.
  
• It provides a unified season value derived from several independent binary conditions.
  

Limitations and Situations Where It May Fall Short

• Normalized values depend on the chosen lookback window and may behave differently under unusual volatility regimes.
  
• If reference data feeds are incomplete or delayed the relationships may briefly reflect distorted values.
  
• Extreme single bar events can cause temporary exaggeration of normalized values before stabilization.
  
• Divergence detection depends on identifying pivots which may repaint until the pivot is confirmed.
  
• Bias states rely on hierarchical evaluation so rare but extreme conditions will override more common states by design.
  
• Sudden changes in stablecoin supply or methodology on the data source may influence stable dominance readings.
  

How to Interpret the Values

• Positive normalized values indicate movement above the typical range while negative values indicate movement below the typical range.
  
• The relationships between the ticker, the alternative asset basket, dominance, and the risk composite define the structural meaning of each bias.
  
• The season value near plus 100 means most bull related conditions are simultaneously satisfied while near minus 100 means most bear related conditions are satisfied.
  
• Sharp rise or fall conditions indicate abrupt movement beyond the usual deviation.
  
• Cross conditions indicate structural transitions such as the ticker moving above or below another aggregate.
  
• Divergences indicate inconsistency between price action and normalized deviation.
  

Best Practices for Practical Use

• Use the bias state as a structural context rather than a direct entry or exit trigger.
  
• Observe whether multiple aggregates align in the same direction since the script is designed around confirming coordinated behavior.
  
• Combine the season value with the main bias state to evaluate whether short term view agree with broader conditions.
  
• Use fast movement alerts for monitoring sudden volatility or intraday acceleration.
  
• Use divergence conditions to identify potential exhaustion points when the main bias does not align with price behavior.
  
• Reference the table and background colors for a quick visual overview of how several groups relate in the current moment.