Valuation Metric

12 gru 2024

Valuation Metric Indicator
The Valuation Metric Indicator provides a comprehensive tool for evaluating price dynamics in relation to a moving average and standard deviation. It combines the power of statistical analysis with clear visualizations to help traders assess market valuation levels and potential overbought or oversold conditions.

Key Features:
Z-Score Calculation:

Displays the Z-score of the price relative to the moving average, normalized by standard deviation.
Z-score is clamped within the range of -3 to +3 to focus on significant deviations.
Standard Deviation Bands:

Plots bands at 1x, 2x, and 3x standard deviations above and below the moving average.
Helps identify areas of extreme overvaluation or undervaluation.
Dynamic Valuation Table:

Displays the current Z-score and provides a textual assessment of the market's valuation:
Overvalued
Slightly Overvalued
Neutral
Slightly Undervalued
Undervalued
Background color dynamically changes based on the valuation.
Customizable Background Signals:

Optional background highlighting for "Top Signal" (overvaluation) and "Bottom Signal" (undervaluation).

Configurable Display:
Users can toggle the visibility of standard deviation bands and background signals to fit their preferences.

Color-Coded Visualization:
Uses gradient-based color coding for Z-scores and standard deviation bands, improving readability and decision-making.

3 cze

Informacje o Wersji

Complete over hall of the script

Core Features:

Multi-Dimensional Inputs: Includes RSI, ROC, price deviation from Bollinger Bands, Sharpe Ratio, Sortino Ratio, Omega Ratio, MFI, CCI, Volatility, and a custom drawdown-adjusted performance measure (Crosby Ratio).

Z-Score Normalization: Each metric is converted into a Z-score based on user-defined lookback periods, facilitating comparability across heterogeneous scales.

Aggregated Composite Signal: The average of all non-null Z-scores provides a single, composite value to gauge overbought/oversold conditions or valuation anomalies.

Gradient Visualization: A color-coded histogram and table display dynamically reflect the composite Z-score level for intuitive visual analysis.

User Customization: Adjustable lengths and parameters for each input metric allow tailored optimization to different assets or timeframes.