GTA MARKET SENTIMENT

GTA Market Sentiment Indicator – Multi-Timeframe Momentum Analysis
Technical Overview

The GTA Market Sentiment indicator is a multi-timeframe momentum analysis tool that calculates trend strength and directional bias by aggregating data from higher timeframes. It applies a timeframe multiplier to derive price data from three progressively larger timeframes, providing a broader perspective on market conditions.

Key Components:

Multi-Timeframe Data Aggregation:

Uses a timeframe multiplier to fetch price data from three higher timeframes.

Computes an averaged price input to smoothen noise and enhance trend clarity.
Exponential Moving Averages (EMAs):

Two EMAs (fast and slow) are calculated on the multi-timeframe aggregated price.
A signal line is derived using an additional EMA to track momentum shifts.
Histogram Representation:

Displays the difference between the moving averages as a histogram.
Implements a gradient color fill to visually indicate trend shifts.
Histogram color intensity adapts dynamically to signal strength variations.
Slope Calculation:

Computes the slope of the aggregated momentum data to assess trend strength.
Helps detect acceleration or deceleration in trend movement.
Zero Line & Signal Levels:

Zero line acts as a baseline for trend bias determination.
Additional signal levels provide reference points for potential trend shifts.

Customization & Parameters:

Time Frame Multiplier: Adjustable multiplier for selecting higher timeframes.
Fast, Slow, and Signal Lengths: User-defined parameters to modify responsiveness.

Moving Average Display Toggle: Option to enable or disable visualization of EMAs.

Usage Considerations:

Designed for multi-timeframe confirmation and momentum-based trend assessment.

Suitable for analyzing trend consistency across different time horizons.
Can be combined with other technical tools for deeper market context.
This indicator provides a structured approach to momentum analysis by leveraging multiple timeframes, smoothing out short-term noise, and offering a clearer visualization of trend dynamics.