This indicator utilizes Ehlers' cyclicity algorithms to decompose price action into harmonic sine waves, identifying phase shifts and predictive leading signals for trend exhaustion.

This indicator extracts cyclical components from price action by applying a recursive smoothing filter and calculating the dominant phase shift to project leading sine waves.

This indicator utilizes a recursive cycle decomposition and digital signal processing to extract underlying periodicities from price action, identifying momentum phases and dynamic support-resistance pivots.

This indicator extracts cyclical components from price data using a smoothed sine wave transformation to identify phase shifts and automated support/resistance levels.

This indicator utilizes Hilbert Transform components to calculate instantaneous cycles and dominant periods, deriving a smoothed sine wave trend based on the real-time detected phase.

This indicator calculates the sine of the price differential relative to a dynamically adjusted timeframe period to visualize cyclical momentum shifts.

This indicator quantifies price velocity by calculating the sine of the normalized difference between current and historical closing prices across dynamic timeframe-adjusted periods.

This indicator calculates a sinusoidal wave based on the relative price displacement over dynamic timeframes to visualize cyclical momentum shifts.

This indicator calculates a trigonometric sine function based on the price delta between current and historical closing prices across period-specific shifts.

Identifies persistent directional trends by detecting six consecutive price openings moving in a single linear direction.

This indicator identifies bullish and bearish reversals by detecting consecutive ascending or descending trends across six consecutive typical price calculation periods.

This indicator identifies distinct bullish and bearish trend shifts by detecting consecutive six-period monotonic progression in the typical price calculation.

This indicator calculates the statistical skewness of price action by measuring the deviation between Volume Weighted Average Price (VWAP) and Point of Control (PVP) normalized by standard deviation.

This indicator identifies directional momentum by constructing a quantized price ceiling and floor based on ATR-derived volatility steps.

This indicator identifies trend momentum by constructing a quantized, step-like trajectory based on ATR-derived price fluctuations and historical range extremes.

This indicator calculates real-time trading volume by evaluating the price distance between entry and stop-loss levels against a fixed percentage of available account margin.

This indicator calculates a Hull Moving Average derivative to identify momentum shifts and visualizes trend direction through slope-based polarity changes.

This indicator identifies directional shifts by calculating the derivative of a Hull Moving Average to detect structural trend transitions and provide real-time price alerts.

This indicator calculates the directional velocity of a Hull Moving Average by processing a smoothed vector of weighted price differences to identify trend reversals.

This indicator identifies trend reversals by calculating the derivative of a dual-weighted moving average to map directional momentum changes.

This indicator calculates a smoothed trend momentum by applying an iterative moving average to the difference between dual Hull Moving Average components.

This indicator calculates the momentum of price movement by determining the direction of the Hull Moving Average slope to identify distinct trend shifts.

This indicator identifies market trajectory by calculating the differential between two moving averages and applying a secondary smoothing pass to isolate directional trend shifts.

This indicator calculates a Hull Moving Average derivative to isolate directional momentum and visually bifurcate bullish and bearish trend trajectories.

This indicator calculates a weighted moving average to determine price velocity and filters directional shifts into distinct bullish and bearish trend components.

This indicator identifies directional bias by calculating the derivative of a Hull Moving Average to isolate underlying momentum shifts.

This indicator visualizes price momentum by mapping smoothed moving average trajectories from higher temporalities onto the current chart to identify structural bias.

This indicator projects trend polarity by synchronizing higher timeframe moving average slopes onto the current chart via dynamic bar shifting.

This indicator synchronizes and plots directional momentum from higher temporal frames onto the current chart to visualize long-term price trajectory.

This indicator calculates a smoothed trend trajectory by applying a moving average to the weighted difference between dual-period WMA calculations to identify directional momentum shifts.

This indicator utilizes a double-smoothed moving average calculation to filter market noise and identify the underlying directional momentum of price action.

This indicator calculates a smoothed momentum trajectory by averaging the main and signal lines of the Stochastic oscillator over three consecutive bars to filter out high-frequency noise.

This indicator calculates a three-period moving average of both the main and signal lines of a standard stochastic oscillator to filter out market noise.

This indicator calculates a smoothed stochastic percentage based on relative price range boundaries to identify overextended trends and potential reversal zones.

The algorithm calculates a smoothed directional trajectory by applying a weighted moving average to the differential velocity between two nested moving averages.

This indicator identifies and plots discrete geometric markers at the exact coordinates where a fast Simple Moving Average pierces through a slow SMA to highlight trend shifts.

This indicator detects precise momentum shifts by identifying the instantaneous crossover points between a fast and slow simple moving average, visually marking trends and triggering real-time notifications.

This indicator identifies specific price action pivot points by detecting momentum shifts where a fast simple moving average pierces a slower timeframe baseline.

This indicator identifies precise bullish and bearish momentum shifts by detecting the exact intersection points of two distinct simple moving average periods.

This indicator identifies trend reversals by detecting precise crossover points between an exponential moving average difference histogram and its simple moving average signal line.

This indicator applies a complex multi-stage weighted smoothing algorithm to the ADX, +DI, and -DI components to filter out market noise and identify latent directional trends.

This indicator dynamically maps price extremes based on the dominance of directional indices and applies a moving average to these shifted values to identify trend-biased price levels.

Automatically terminates all open long and short positions immediately upon reaching a predefined minimum profit margin.

This script performs an exhaustive, recursive scan of all open positions to force-terminate every active buy and sell order immediately upon execution.

This indicator applies a triple-smoothed moving average filter to the Average True Range to isolate underlying market volatility trends.

Identifies and visualizes exact crossover points between two simple moving averages using dynamic price range offsets for enhanced visibility.

This indicator identifies and visualizes precise crossover points between two customizable moving averages while providing real-time alerts for momentum shifts.