This indicator calculates a reduced-lag moving average by weight-averaging dual linear momentum components to identify trend reversals through color-coded directional shifts.

This indicator identifies trend shifts by calculating the derivative of weighted moving averages to detect directional changes in price momentum.

Identifies directional bias by detecting slope changes in a weighted moving average calculation derived from dual-period linear weights.

This indicator calculates a weighted moving average of the difference between two half-period and full-period linear weighted averages to minimize lag while identifying trend directional shifts.

This indicator calculates a weighted moving average of price variance to identify trend reversals by bifurcating the hull mean into independent bullish and bearish directional components.

This indicator calculates a weighted moving average hybrid that identifies price momentum shifts by separating upward and downward trends into distinct color-coded streams based on slope velocity.

This indicator calculates a smoothed trend trajectory by applying nested linear weighted averages to capture price momentum with minimal lag.

This indicator calculates a smoothed Hull Moving Average and employs a standard deviation-based percentile filter to identify distinct directional trend shifts while minimizing noise.

This indicator calculates a smoothed Hull Moving Average derivative to isolate momentum shifts and visually differentiate bullish trajectories from bearish declines.

This script calculates a weighted linear moving average by processing the difference between two half-period averages to minimize lag while maintaining high price sensitivity.

This indicator calculates a high-velocity trend line by applying a weighted moving average to the variance between two different period linear weighted averages.

This indicator calculates a smoothed directional trajectory by processing a weighted difference of dual moving averages to isolate trend momentum and flip between bullish and bearish states.

This algorithm calculates a weighted moving average by applying a linear weighted mean to the difference between two nested LWMA values, then smoothing the result with a square root period lag.

This indicator calculates a weighted moving average by applying a square-root period smoothing to the difference between two weighted averages, dynamically shifting colors and sending alerts based on directional slope changes.

This indicator, based on J. Ehlers' work, calculates and smooths the dominant cycle period of price data using quadrature components and filtering techniques.

This indicator estimates the dominant cycle period of price data using a complex homodyne discriminator algorithm derived from detrended prices and quadrature components.

This indicator visualizes the directional magnitude of price movement relative to the candle's opening price by calculating high and low extremities as distinct histograms.

This indicator calculates and displays the real-time absolute pip distance between current market prices and user-defined horizontal level markers.

This indicator scans for horizontal lines on the chart and dynamically displays the real-time pip distance between each level and the current market price.

This indicator plots three moving averages with dynamically varying time periods to visualize structural trend shifts across different temporal scales.

This indicator calculates a linear regression line over a user-defined hourly period to project three parallel price levels based on historical volatility and trend trajectory.

This indicator utilizes the Hodrick-Prescott filtering algorithm to decompose time-series data into cyclical and trend components, allowing for mathematical forecasting of future price trajectories based on historical volatility and structural momentum.

This indicator extracts the long-term cyclical component of price action by applying a structural decomposition filter to smooth out high-frequency noise.

This indicator utilizes the Hodrick-Prescott filter to decompose price series and project future trajectory trends based on historical cycle variance.

This utility parses binary .hst price files from MetaTrader 4 and exports the historical candle data into a structured CSV format for external analysis.

This indicator identifies momentum shifts by comparing price action against a calculated 50.6% retracement level derived from high and low extremes within a rolling window.

This indicator calculates a weighted moving average of the difference between two median price averages to identify trend velocity and directional shifts based on a specific slope threshold.

This indicator calculates a weighted moving average variance to identify directional momentum and highlights price extremes based on structural shifts.

This indicator utilizes the Hull Moving Average formula to calculate price momentum and identifies trend polarity by comparing weighted linear averages against their own square-root offsets.

This indicator identifies trend direction by calculating the weighted variance between a dual-layered linear weighted moving average and its square-root adjusted derivative.

This indicator identifies trend direction by calculating the weighted difference between dual linear moving averages and comparing them against a square-root smoothed Hull Moving Average output.

This indicator identifies directional shifts by calculating the variance between weighted moving average components to project trend flow and highlight price extremes.

This indicator calculates the Hull Moving Average to identify structural momentum shifts by comparing smoothed price velocity against dynamic lag-reduced averages.

This indicator calculates a dynamic trend envelope by applying a linear weighted moving average to the difference between two offset Hull Moving Averages to identify directional momentum.

This indicator calculates a weighted linear moving average of the difference between two distinct weighted periods to minimize lag and provide rapid price trend tracking.

This algorithm utilizes a nested linear weighted moving average structure to minimize phase lag while maintaining high responsiveness to price curvature.

This indicator synthesizes Hull Moving Average calculations with Heikin Ashi price logic to smooth out market noise and visualize trend momentum through high/low extremes.

This indicator synthesizes Hull Moving Average calculations with Heikin Ashi price transformations to generate smoothed trend channels and mean reversion signals.

This indicator synchronizes four nested timeframes to project directional trend shifts by comparing Hull Moving Average prices against Heikin Ashi open and close values.

This indicator synchronizes directional momentum from four nested timeframes using the Hull Moving Average and Heikin Ashi logic to visualize concurrent trend alignment.

This indicator plots synchronized trend signals from four distinct timeframes onto a single chart by calculating Hull Moving Average differences and displaying them as offset price bars.

This indicator synthesizes Hull Moving Average smoothing with Heikin-Ashi price action logic to filter market noise and visualize trend momentum.

This indicator utilizes a nested linear weighted average calculation to generate a high-responsiveness trend line that minimizes lag while smoothing price fluctuations.

This indicator synthesizes Hull Moving Average dynamics with Heikin-Ashi price smoothing to identify momentum shifts through multi-buffer trend crossovers.

This indicator synthesizes Hull Moving Average calculations with Heikin Ashi candle logic to smooth price volatility and identify trend momentum across four distinct data buffers.

This indicator synthesizes Hull Moving Average dynamics with Heikin-Ashi price action by calculating smoothed open, high, low, and close values to identify trend momentum.

This indicator applies a linear weighted moving average to a multi-period differential calculation of the Average Directional Index (ADX) and its component vectors.